IBM WebSphere Portal software family
Your world. Your way.
IBM WebSphere Portal 6.1.X
Performance Tuning Guide
IBM WPLC Performance Team
March 2009
Document version 2.1
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Web Server Tuning ......................................................................................................................... 32
Portlet Caching .............................................................................................................................. 33
MANY PAGES TUNING................................................................................................................................ 34
DB2 Database Tuning...................................................................................................................... 34
Cache Manager Service ................................................................................................................... 35
Required Fixes .............................................................................................................................. 35
WEB CONTENT MANAGEMENT TUNING......................................................................................................... 36
Application Server Tuning ................................................................................................................. 36
WebSphere Portal Service Properties................................................................................................... 37
Cache Manager Service .............................................................................................................. 37
Navigation Service..................................................................................................................... 38
WCM Object Cache ........................................................................................................................ 38
WCM Configuration Service............................................................................................................... 39
JCR Text Search............................................................................................................................ 39
DB2 Tuning (Authoring Environment) ................................................................................................... 40
Multiplatform (LUW) ................................................................................................................... 40
Z/OS...................................................................................................................................... 41
COMPOSITE APPLICATIONS TUNING ............................................................................................................ 43
Cache Manager Service Properties...................................................................................................... 43
Composite Applications Best Practices ................................................................................................. 44
CLUSTER TUNING ..................................................................................................................................... 46
Application Server Tuning ................................................................................................................. 46
Dynacache Custom Properties ...................................................................................................... 46
z/OS Dynacache Custom Property.................................................................................................. 46
Thread Pools ........................................................................................................................... 47
Transport Buffer Size.................................................................................................................. 47
WMM Context Pooling ................................................................................................................ 47
Web Server Tuning ......................................................................................................................... 48
Session Persistence To Database Tuning.............................................................................................. 49
Vertical Cluster Tuning..................................................................................................................... 50
Required Fixes .............................................................................................................................. 51
OTHER PERFORMANCE TUNING OPTIONS..................................................................................................... 52
Improving Portal Startup Performance .................................................................................................. 52
Managing the Retrieval of User Attributes .............................................................................................. 53
Identifying a Full Fetch of User Attributes.......................................................................................... 54
Minimum Attribute Set................................................................................................................. 55
Use of Dynamic Content Features ....................................................................................................... 55
Real-World Network Considerations..................................................................................................... 56
Compress Content on the HTTP Server ........................................................................................... 56
Enabling Client-Side Caching........................................................................................................ 57
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WEBSPHERE PORTAL CACHES.................................................................................................................... 58
General Information ........................................................................................................................ 58
Cache Configuration Properties ..................................................................................................... 58
Cache Usage Patterns ..................................................................................................................... 61
Cache Instances ............................................................................................................................ 62
Access Control ......................................................................................................................... 62
Portal User Management ............................................................................................................. 67
Datastore................................................................................................................................ 68
Model .................................................................................................................................... 69
URL Mappings.......................................................................................................................... 74
Virtual Portals........................................................................................................................... 74
WSRP.................................................................................................................................... 75
Dynamic Assembly / Process Integration .......................................................................................... 77
Policy..................................................................................................................................... 78
Collaboration Services ................................................................................................................ 78
Miscellaneous .......................................................................................................................... 79
Example Scenarios ......................................................................................................................... 82
General Comments.................................................................................................................... 82
Small Number of Pages and Small Number of Users............................................................................ 83
Small Number of Pages and Large Number of Users............................................................................ 83
Portals with Long Session Timeouts................................................................................................ 84
Portals with Many Pages ............................................................................................................. 84
WEB CONTENT MANAGEMENT CACHES........................................................................................................ 86
WCM Cache Instances..................................................................................................................... 86
WCM Item caching..................................................................................................................... 86
WCM Summary ........................................................................................................................ 86
WCM Basic Caching................................................................................................................... 87
Advanced and Resources ............................................................................................................ 87
Session Cache ......................................................................................................................... 87
Menu ..................................................................................................................................... 88
Navigator ................................................................................................................................ 88
Absolute path ........................................................................................................................... 88
Missed Items............................................................................................................................ 88
Library.................................................................................................................................... 88
Library Parent........................................................................................................................... 89
Draft Summary ......................................................................................................................... 89
User cache.............................................................................................................................. 89
Appendix A. References............................................................................................................................ 90
Appendix B. Credits ................................................................................................................................. 91
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Figures
Figure 1 Portal Access Control Cache Hierarchy .................................................................................................. 63
Figure 2 Portal Model Cache Hierarchy.............................................................................................................. 70
Tables
Table 1: Additional Sun JVM Settings.................................................................................................................. 8
Table 2: WebSphere Security Attribute Propagation Settings.................................................................................... 10
Table 3: VMM Context Pool Setting .................................................................................................................. 11
Table 4: Navigation Service Settings................................................................................................................. 12
Table 5: Registry Service Settings.................................................................................................................... 13
Table 6: Cache Manager Service Settings .......................................................................................................... 14
Table 7: DB2 Database Domains..................................................................................................................... 15
Table 8: Oracle Database Tuning..................................................................................................................... 20
Table 9: IDS Tuning..................................................................................................................................... 22
Table 10: Web Server Tuning ......................................................................................................................... 23
Table 11: AIX Network Settings....................................................................................................................... 25
Table 12: Linux Network Settings..................................................................................................................... 26
Table 13: Windows Network Settings ................................................................................................................ 26
Table 14: Solaris Network Settings................................................................................................................... 27
Table 15: z/OS System Tuning........................................................................................................................ 29
Table 16: Navigation Service Settings for Web 2.0 Theme....................................................................................... 30
Table 17: Reverse Proxy Settings .................................................................................................................... 31
Table 18: DB2 Database Settings for Many Pages ................................................................................................ 34
Table 19: Cache Manager Service Settings for Many Pages .................................................................................... 35
Table 20: Cache Manager Service Settings for WCM............................................................................................. 37
Table 21: Navigation Service Settings for WCM ................................................................................................... 38
Table 22: WCM Object Cache Settings.............................................................................................................. 38
Table 23: DB2 z/OS Bufferpool Settings............................................................................................................. 41
Table 24: DB2 z/OS Default Bufferpool Settings ................................................................................................... 42
Table 25: Cache Manager Serivce Properties for Application Infrastructure .................................................................. 43
Table 26: Web Server Tuning for Clusters .......................................................................................................... 48
Table 27: WebSphere Session Persistence Tuning ............................................................................................... 49
Table 28: IDS Tuning in Vertical Cluster............................................................................................................. 51
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ABOUT THIS DOCUMENT
This white paper provides a basis for parameter and application tuning for IBM WebSphere
Portal for Multiplatform V6.1. Remember that both tuning and capacity are affected by many
factors, including the workload scenario and the performance measurement environment.
For tuning, the objective of this paper is not to recommend that you use the values we used
when measuring our scenarios, but to make you aware of those parameters used in our
configuration. When tuning your individual systems, it is important to begin with a baseline,
monitor the performance metrics to determine if any parameters should be changed and,
when a change is made, monitor the performance metrics to determine the effectiveness of
the change.
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1
PERFORMANCETUNINGOVERVIEW
Tuning a WebSphere Portal environment involves tuning and configuring the various
systems and components of the environment. This chapter discusses some general
concepts and details the specifics of the configuration used in our measurement
environments. These specifics entail:
ꢀ Configuring the application server and the resources defined for that application
server
ꢀ Tuning the database(s) and database server
ꢀ Tuning the directory server and its database
ꢀ Tuning the web server and/or proxy server
ꢀ Tuning the operating system and network
ꢀ Tuning the WebSphere Portal services
When tuning your individual systems, it is important to begin with a baseline, monitor the
performance metrics to determine if any parameters should be changed and, when a
change is made, monitor the performance metrics to determine the effectiveness of the
change.
In addition to the tuning changes we made in our measurement environments, there are
some additional tuning options available which can improve performance in certain
circumstances; these will be discussed in a separate section.
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Environment Considerations
Before beginning your install of WebSphere Portal you should consider how to use the
environment in order to achieve ideal performance. Topics to consider include:
• Choosing between 32-bit and 64-bit JVMs
• Use of hardware multithreading, also known as Simultaneous Multithreading or
Hyper-Threading.
3 2 - B I T A N D 6 4 - B I T C O N S I D E R A T I O N S
The choice of a 32-bit or 64-bit JVM involves some trade-offs. The key advantage of a 64-bit
JVM is its vastly larger address space. Heap sizes of 2.5GB or larger can be practical on
modern server systems. This can be a significant benefit for applications with high memory
demands.
A 64-bit JVM does have disadvantages as well. Machine instructions and memory
references in a 64-bit JVM are larger than in a 32-bit JVM. This means that Java objects,
which typically contain multiple memory references, are larger in a 64-bit JVM than
compared to a 32-bit JVM. Therefore a 64-bit JVM will need a larger heap than a 32-bit JVM
for the same population of objects.
The increased size of instructions and memory references imposes a second performance
penalty. They increase the demand on the memory subsystem of the system, causing more
cache misses and a higher demand for memory bandwidth. As a result, executing a set of
operations in a 64-bit JVM can be slower than executing the same operations in a 32-bit
JVM.
When considering a deployment of WebSphere Portal 6.1, consider the memory demands
your applications will have. If you expect a high demand for memory, the best performance
will probably come from a 64-bit JVM. On the other hand, if the memory demand is lower, a
32-bit JVM is likely to give superior performance.
H A R D W A R E M U L T I T H R E A D I N G ( H Y P E R - T H R E A D I N G )
Many modern processor architectures support hardware multithreading. For example, this is
known as Hyper-Threading (HT) on Intel processors and Simultaneous Multithreading
(SMT) on Power-series processors. Our experience is that using hardware multithreading
provides an improvement in capacity in all of the scenarios and platforms reported in this
report, so we would recommend its use on platforms where this is an option.
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2
BASEPORTALTUNING
The Base Portal Scenario covers user login, page navigation, and interaction with simple
portlets. Users can see a small set of pages, some of which are visible to all authenticated
users, with access to others based on their group membership.
We have also benchmarked a number of other scenarios, which focus on different functions
or use cases for WebSphere Portal. For example, there are scenarios which make use of
Web Content Management (WCM), and a scenario where users have access to thousands
of pages. While we have used different tuning to optimize performance for some of those
scenarios, the tuning is all based on the tuning done in the Base Portal Scenario.
In all of our measurement environments, we use a separate database server and directory
server, in addition to the WebSphere Portal server. We run these servers on separate
systems to avoid resource contention on the system running the WebSphere Portal server.
This helps improve the maximum capacity achievable.
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Application Server Tuning
There are many aspects to configuring and tuning an application server in WebSphere
Application Server. We found that those aspects presented here were critical to a correctly
functioning and optimally performing WebSphere Portal in our laboratory environment.
For more details on tuning a WebSphere Application Server, see the Tuning Section of the
information center located at:
How to get to Admin Console
There are two methods to get to WebSphere Administrative Console.
• Start Server1 and use port 10001
1. In <WAS_root>/profiles/wp_profile/bin
2. ./startServer.sh server1
• Start Portal and use port 10027
1. In <WAS_Root>/profile/wp_profile/bin
2. ./startServer.sh WebSphere_Portal
Customer ports can differ from the ports 10001 or 10027 mentioned on this page. To find out the
ports in use for your installation, look for ‘adminhost’ in <wp_profile
root>/config/cells/<cell_name>/nodes/<node_name>/serverindex.xml.
The following are settings based on our experience with the Base Portal workloads
described above:
J V M I N I T I A L A N D M A X I M U M H E A P S I Z E
Java Virtual Machine heap size: The value of the JVM Heap size is directly related to the
amount of physical memory on the system. Never set the JVM heap size larger than the
physical memory on the system.
How-To Set: In the WebSphere Administrative Console: Servers
ꢁ
Application Servers
ꢁ
WebSphere Portal Server Infrastructure: Java and Process Management
ꢁ
ꢁProcess Definition
ꢁ
Java Virtual Machine
- Initial Heap Size
- Maximum Heap Size
See JVM Max Heap Size Limits for further discussion.
See instruction on How to get to Admin Console
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JVM M AXI MUM HE AP SI ZE LI MI TS
When setting the heap size for an application server, keep the following in mind:
ꢀ Make sure that the system has enough physical memory for all of the processes to fit
into physical memory, plus enough for the operating system. When more memory is
allocated than the physical memory in the system, paging will occur, and this can
result in very poor performance.
ꢀ We set the minimum and maximum heap sizes to the same values since we’re using
the gencon garbage collection policy available in 1.5 IBM JDK which avoids heap
fragmentation, this may not be the best choice if you plan to use a different garbage
collection. In our measurement runs, the system is under load for a relatively short
time (around 3 hours), and it is running with portlets which do not have large memory
requirements. When using portlets which have larger memory requirements, or for
continuous operation, it may be possible to reduce heap fragmentation by setting the
initial heap size to 320 megabytes.
ꢀ After doing any tuning of heap sizes, monitor the system to make sure that paging is
not occurring. As mentioned above, paging can cause poor performance.
ꢀ 32-bit operating systems have an address space limit of 4GBytes, regardless of the
amount of physical memory in the system. This space limits the maximum size of
each individual process in the system. In addition, some operating systems restrict
the size of processes to be even less than this limit. Many versions of Windows limit
processes to 2GBytes in size; you can find more information at
ꢀ The address space limit further restricts the size of the JVM process. If the process
grows larger than the limit imposed by the operating system, it may terminate
unexpectedly.
Due to the demands on native memory by WebSphere Portal V6.1 and its underlying
components, we chose a maximum heap size of 1408MB in our Windows environments.
There is a balance between JVM heap and native memory, all of which must fit within the
2GB restriction in 32-bit Windows. 1408MB was the largest value we could use to
successfully measure all of our Windows configurations and workloads. If your application
has additional native memory requirements then you may need to choose a smaller
maximum heap size. For more information, see the WebSphere Application Server
information center.
On Solaris and zLinux, we use 3.5GB heap size in 64-bit environment.
AIX
POWER5
Windows
2003
Parameter
Linux
2048
Solaris
z/Linux
3584
z/OS
2048
Initial and
Maximum
heap size
(Mbytes)
1792
3584
1408
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J V M H E A P L A R G E P A G E
Large pages can reduce the CPU overhead needed to keep track of heap. With this setting
we have seen 10% throughput improvement in our measurements.
This setting does improve performance on Windows, we did not set it for our measurements because
Portal doesn’t start reliably when –Xlp is set, sometimes it requires a system reboot to get the jvm to
start.
How-to Set: In the WebSphere Administrative Console: Servers -> Application Servers ->
WebSphere Portal -> Server Infrastructure: Java and Process Management -> Process Definition ->
Java Virtual Machine -> Generic JVM Argument. Add –Xlp.
Large pages are supported by systems running Linux kernels V2.6 or higher. See JVM
Large Page Tuning for AIX Operation System.
JVM L ARGE PAGE TUNI NG ON AI X OPER ATI NG SYSTEM
To use JVM Large Page, AIX operating system must be configured to support large pages.
How-To Set:
1. We use the following steps to allocate 4GB of RAM as large pages (16MB) . We chose
this amount based on having 8GB of physical memory in these systems. These values
may need to be adjusted on systems with different amounts of physical memory.
vmo -r -o lgpg_regions=256 -o lgpg_size=16777216
bosboot -ad /dev/ipldevice
reboot -q
vmo -p -o v_pinshm=1
chuser capabilities=CAP_BYPASS_RAC_VMM,CAP_PROPAGATE $USER
2. Add: -Xlp command-line option as described above.
3. In the WebSphere Administrative Console: Servers ꢁ Application Servers ꢁ
WebSphere Portal ꢁ Server Infrastructure: Java and Process ManagementꢁProcess
Definition-> Environment Entries ꢁ New ꢁ EXTSHM=OFF (note: When EXTSHM is
on it prevents use of large page).
4. Restart Portal Server. To verify if large pages are being used, run the AIX command
vmstat -l 1 5 and check the "alp" column which is the active large page used. It should
be a non-zero value if large pages are being used.
Parameter
AIX
POWER5
Windows
2003
Linux
Solaris
Not
z/Linux
z/OS
JVM Heap
Large page
-Xlp
-Xlp
Not
Applicable
Not
Not
Applicable
Applicable Applicable
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J V M H E A P N E W A R E A S I Z E
The Generational Garbage Collector introduced in Java 5.0 is efficient to Portal application JVM
memory management, and it is set as default by installation with the –Xgcpolicy:gencon command-
line option. Use –Xmn to further fine tune the Java heap new area (Nursery).
The –Xgcpolicy:gencon option does not apply to Solaris.
How To Set: In the WebSphere Administrative Console: Servers
WebSphere Portal
ꢁ
Application Servers
ꢁ
ꢁ
Server Infrastructure: Java and Process Management
ꢁProcess Definition
ꢁ
Java Virtual Machine -> Generic JVM Arguments:–Xmn256m
AIX
POWER5
Windows
2003
Parameter
Linux
Solaris
z/Linux
z/OS
New Area Size -Xmn320m -Xmn256m -Xmn768m -Xmn256m -Xmn1024m -Xmn320m
A D D I T I O N A L S U N J V M A R G U M E N T S
On the Solaris platform, we use the following Java HotSpot parameters to achieve optimum
performance.
Table 1: Additional Sun JVM Settings
Parameter
Value
Additional Information
-server
Offers higher throughput than the "client" mode.
-XX:MaxPermSize
-XX:+UseConcMarkSweepGC
768m
Use concurrent mark-sweep collection for the tenured
generation. The application is paused for short periods
during the collection; we found this collector works best
in Portal.
-XX:SurvivorRatio
6
5
-XX:+UseParNewGC
By default concurrent low pause collector uses the
default, single threaded young generation copying
collector. Set this parameter to use parallel young
generation collector for new area.
-XX:ParallelGCThreads
Reduces the number of garbage threads. On the Chip
multithreading processor based system, we set the
threads no higher than one quarter of the hardware
threads. We also distribute the threads for 6 JVMs. Our
system has 128 virtual processors, we set a total of
(128/4)=32 GC threads across all the JVMs. So 5 or 6
GC threads per JVM.
-XX:+PrintGCDetails
Print more details at garbage collection. This does not
improve performance, but it provides additional
information related to garbage collection activity, which
is useful in tuning garbage collection.
-XX:+PrintGCTimeStamps
Print timestamps at garbage collection. See above.
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S E S S I O N T I M E O U T
Session timeout: The default value of Session Timeout is 30 minutes. Reducing this
value to a lower number can help reduce memory consumption requirements, allowing a
higher user load to be sustained for longer periods of time. Reducing the value too low can
interfere with the user experience.
For Solaris, on a T5240 hardware, we used a much lower think time, 5 seconds, than was
used for other platform hardware measurement of 12 seconds. With a lower thinktime, fewer
vusers will result in a heavier load on the system. The reason we lowered the thinktime was
specifically to decrease the number of vusers required for this measurement. Our pool of
LoadRunner vuser licenses was inadequate to generate enough load with the higher think
time. With a shorter think time than is used in the other measurements, the duration of each
virtual user's interaction with the site is shorter by approximately 2 minutes. To compensate
for this, and keep the sessions live on the server for the same period of time, we increased
the session timeout by 2 minutes, to 12 minutes.
How To Set: In the WebSphere Administrative Console: Servers ꢁ Application Servers ꢁ
WebSphere Portal ꢁ Container Settings: Web Container Settings ꢁ Session Management
ꢁ Session Timeout -> Set Timeout
AIX
POWER5
Windows
2003
Parameter
Linux
Solaris
z/Linux
z/OS
Session
timeout
10 minutes
10 minutes 12 minutes 10 minutes
10 minutes 10 minutes
W E B C O N T A I N E R T H R E A D P O O L S I Z E
Servlet engine thread pool size: Set this value and monitor the results. Increase this value if
all the servlet threads are busy most of the time.
How To Set: In the WebSphere Administrative Console: Servers ꢁ Application Servers ꢁ
WebSphere Portalꢁ Additional Properties: Thread Poolsꢁ Web Container ꢁ Thread Pool
- Minimum size threads - Maximum size threads
AIX
POWER5
Windows
2003
Parameter
Linux
Solaris
z/Linux
50
z/OS
Web Container 50
Thread pool
size
50
50
50
50
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S E C U R I T Y A T T R I B U T E P R O P A G A T I O N
To reduce the Security Attribute Propagation (SAP) overhead, please use a custom property
'disable Callerlist'. If SAP is not used, you can disable that, to remove the extra overhead to
improve the login performance.
If Subject has not been customized, then there is no need to enable Security Attribute
Propagation. Security Attribute Propagation can add extra overhead due to some extra
processing that is required. However, there are certain configurations where performance
might be better with security propagation enabled due to reduction of remote registry calls.
See the WebSphere 6.1 InfoCenter (search for 'security attribute propagation') for a
discussion of when propagating security attributes is desirable. If you want to enable SAP
for functional reasons, you can improve the performance with CallerList tuning mentioned
below.
These settings apply to all platforms.
How to Set: In the WebSphere Administrative Console: Security->Secure Administration,
Applications, and Infrastructure -> Custom properties ->
Table 2: WebSphere Security Attribute Propagation Settings
Security
Attribute
Name
Value
Propagation
com.ibm.CSI.disablePropagationCallerList
true
com.ibm.CSI.rmiOutboundPropagationEnabled
com.ibm.CSI.rmiInboundPropagationEnabled
com.ibm.ws.security.webInboundPropagationEnabled
false
false
false
For com.ibm.CSI.disablePropagationCallerList create a new property, for the other 3
properties, modify their value to “false”.
Note to WAS 7:
In our WAS 7 environment, we add com.ibm.CSI.disablePropagationCallerList = true, and
use the other 3 default true attributes. For was7, this field is accessed through:
Security->Global Security ->CustomProperties->New.
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V M M C O N T E X T P O O L I N G
Tune VMM Context Pooling to improve the performance of concurrent access to an LDAP
server.
We changed the following Context Pooling settings line in:
<wp_profile_root>/config/cells/<cellname>/wim/config/wimconfig.xml
<config:contextPool enabled="true" initPoolSize="10" maxPoolSize="0"
poolTimeOut="0" poolWaitTime="3000" prefPoolSize="30"/>
You can also set them via the administrative console as described in
ere.base.doc/info/aes/ae/uwim_ldapperfsettings.html
Table 3: VMM Context Pool Setting
Context Pool Setting
initPoolSize
Default Value
Value
1
10
30
prefPoolSize
3
Number of open connections to maintain to
LDAP server.
maxPoolSize
20
0.
A value of 0 allows the pool to grow as large
as needed. If access to the LDAP server is
shared by many systems, this setting may
allow an excessive number of connections to
the LDAP server; in such a case, set the
maximum pool size to a value appropriate to
your environment.
O R B S E R V I C E T U N I N G F O R Z / O S
In the WAS Admin Console, set the ORB Service to be "pass by reference" instead of
"pass by value" (default) for both server1 and WebSphere_Portal
How to Set:
- Serversꢁ Application Serversꢁ server1ꢁ Orb Service
- check box for "Pass by Reference"
- Serversꢁ Application Servers ꢁWebSphere_Portal ꢁ Orb Service
- check box for "Pass by Reference"
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WebSphere Portal Services
WebSphere Portal has a number of configurable “services”; each service has several
parameters available to it. This section describes which services we tuned, the tuning values
used, and the rationale for those changes.
How to Set:
1. Edit <wp_profile_root>/PortalServer/config/properties/xxxService.properties
2. uncomment the line, then change the size.
3. run <wp_profile_root>/ConfigEngine/ConfigEngine.sh update-properties
The changes should appear on WAS Console -> Resource Environment Providers ->
WP_xxxService -> Custom properties
N A V I G A T O R S E R V I C E
The navigator service manages the content model for unauthenticated users, which controls
the pages those users are able to see. This content model is periodically reloaded by
WebSphere Portal; new pages which are visible to unauthenticated users will not be
available until the next reload occurs. Our environment assumes a low rate of change for
pages, so we set this reload to only occur once per hour. In a production environment where
new pages for unauthenticated users are rarely created, setting this reload time to an hour
or more will give better performance. In a test or staging environment where updates to
unauthenticated pages need to be seen more often, a lower reload time is more appropriate.
This service also controls the HTTP cache-control headers which will be sent on
unauthenticated pages. While our environment did not exploit HTTP page caching,
increasing these cache lifetimes in a production environment can reduce load on the portal.
For more discussion of the use of HTTP cache-control headers with WebSphere Portal,
refer to the “Caching” section of the “Tuning” topic in the WebSphere Portal V6.1 InfoCenter.
Table 4: Navigation Service Settings
NavigatorService.properties
Default
Value
Value
Used
Definition
Parameter
public.expires (seconds) 60
3600
Determines cache expiration time for caches
outside of WebSphere Portal and for
unauthenticated portal pages only. If the setting
remote.cache.expiration is also set to a value
greater than or equal to 0, the smaller one of the
two values is used.
public.reload (seconds)
60
3600
Determines cache expiration time for the portal
internal cache for unauthenticated pages
remote.cache.expiration 60
(seconds)
28800
Determines cache expiration for caches outside
of portal server for authenticated as well as for
unauthenticated pages
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R E G I S T R Y S E R V I C E
WebSphere Portal maintains information about many resource types in its databases. Some
of these resources are replicated into memory for faster access; this is provided by the
registry service. This replicated information will be periodically reloaded from the database,
thus picking up any changes which may have been made on a peer node in a clustered
environment.
The registry service allows configuring a reload time, in seconds, for each type of data which
it is managing. In a production environment, we expect this type of information changes very
infrequently, so we used very long reload times for the registry service. A full list of the types
of information managed by the registry service is in table 4.
Table 5: Registry Service Settings
RegistryService.properties
Default
Value
Value
Used
Definition
Parameter
default.interval
1800
28800
Reload frequency for any object types not
explicitly specified in the file.
bucket.application.interval
bucket.portlet.interval
bucket.theme.interval
bucket.skin.interval
600
28800
28800
28800
28800
28800
28800
28800
Reload frequency for application definitions
Reload frequency for portlet definitions
Reload frequency for theme definitions
Reload frequency for skin definitions
Reload frequency for client definitions
Reload frequency for markup definitions
600
3000
3500
19000
20000
600
bucket.client.interval
bucket.markup.interval
bucket.transformation
application.interval
Reload frequency for transformation
application definitions
bucket.transformation.interval
600
28800
Reload frequency for transformation
definitions
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C A C H E M A N A G E R S E R V I C E
The cache manager service in WebSphere Portal is used to cache a wide variety of types of
information in memory. These caches are somewhat similar to the registries maintained by
the registry service, as each type of information gets its own cache. The key differences are:
ꢀ The information stored in the cache manager service’s caches tends to be more
dynamic than the information stored in the registry service’s registries.
ꢀ The caches used by the cache manager service are limited in size, and entries will
be discarded when the caches become full. The registries used by the registry
service are not size-limited; they contain all entries of the specific data type.
ꢀ Expiry times are managed individually for each entry in the cache, managed by the
cache manager service. In contrast, when the reload time is reached for a registry,
the entire contents of that registry are reloaded.
Each cache has several configurable options. A full discussion of these options, along with a
list of the caches in WebSphere Portal V6.1, is given in chapter 2. Table 5 lists the changes
which we made to the cache manager service configuration file. Size values are specified in
“number of objects” and lifetime values are specified in “seconds”.
Table 6: Cache Manager Service Settings
CacheManagerService.properties
Default Value Value Used
Cache Name
com.ibm.wps.model.factory.ContentModelCache.live.size
com.ibm.wps.ac.ExplicitEntitlements Cache.USER_GROUP.size
1000
1000
1000
2500
2000
2500
com.ibm.wps.model.factory.Navigation
SelectionModelCache.live.size
com.ibm.wps.ac.OwnedResourcesCache.enabled
com.ibm.wps.ac.ProtectedResourceCache.lifetime
true
false
5000
2500
14400
5000
com.ibm.wps.datastore.services.Identification.SerializedOidString
Cache.size
com.ibm.wps.puma.DN_OID_Cache.size
500
5000
3000
1500
3000
3000
5000
False
False
28800
43200
com.ibm.wps.puma.DN_User_Cache.size
500
com.ibm.wps.puma.DN_Group_Cache.size
com.ibm.wps.puma.OID_DN_Cache.size
500
1500
1500
1500
true
com.ibm.wps.puma.OID_User_Cache.size
com.ibm.wps.puma.OID_Group_Cache.size
com.ibm.wps.ac.groupmanagement.NestedGroupCache.enabled
com.ibm.wps.ac.RolesCache.enabled
true
com.ibm.wps.ac.ChildResourcesCache.lifetime
com.ibm.wps.policy.services.PolicyCacheManager.lifetime
7200
7780
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Database Tuning
D A T A S O U R C E T U N I N G F O R D B 2
Multiple databases are used to hold information in WebSphere Portal V6.1. We used six
separate DB2 databases, each representing a separate database domain and having their
own datasources. These are:
Table 7: DB2 Database Domains
Database
Release
Database name
release
community
custom
fdbkdb
Lmdb
Datasource name
reldbDS
commdbDS
cusdbDS
fdbkdbDS
lmdbDS
jcrdbDS
Community
Customization
Feedback
Likeminds
JCR
jcrdb
All datasources are configured in a similar manner by logging on to the WebSphere
Application Server administrative console. For the prepared statement cache size, the path
is Resources → JDBC Providers → provider name → Data Sources → datasource name.
The provider name and datasource name are based on the names selected for that
database during the database transfer step. Look for the parameter Statement cache size.
For the connection pool settings, the path in the WebSphere Application Server
administrative console is Resources → JDBC Providers → Provider name → Data Sources
→ Datasource name → Connection Pools. The settings are Minimum connections and
Maximum connections.
The default settings were used for the prepared statement cache size, and connection pool
minimum and maximum sizes.
D B 2 D A T A B A S E S E R V E R T U N I N G
WebSphere Portal V6.1 uses database servers for core functionality. In our measurement
environment, we used DB2 database server for the Portal application. The LDAP server,
IBM Tivoli Directory Server also included a DB2 database as a repository, but it is largely
unseen and was operated as an out of box configuration.
We recommend using a remote database server for the largest capacity. For our
measurements we used IBM DB2 Enterprise Edition V9.1 fixpack 5 as our database server.
WebSphere Portal V6.1 uses the concept of Database domains to designate either groups
of tables belonging to one domain, or even entirely separate databases to store the data
specific to each domain.
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We built six separate databases within one database server to house the tables and data
needed to support each domain. For the Base Portal and Many Pages measurements, the
Release domain is the primary database being exercised.
The databases and related domains supported by Portal V6.1 are:
1. Release (release domain). This is the primary database domain used by the Base
Portal and Many Pages Scenarios.
2. Customization (customization domain). This database receives some light traffic in
our scenarios.
3. Community (community domain). This database receives some light traffic in our
scenarios.
4. JCR (JCR domain). JCR database is used heavily in WCM (Web Content
Management) Scenario. This database receives light traffic in all other scenarios
measured in our Benchmark report.
5. Likeminds database, used for Likeminds enabled systems. This database is not used
in the scenarios measured in our Benchmark report.
6. Feedback database, used by the feedback subsystem. This database is not used in
the scenarios measured in this report.
DB2 ON AI X SETUP
We configure our DB2 database on AIX using the following setup,
• Set the filesystem which will hold the Portal databases to be a Enhanced
Journal File System (JFS2) because a large file system is limited to 64GB.
• Turn on concurrent I/O (CIO) for Enhanced Journal File System as this improves
performance.
To enable CIO, use the following command to mount the database fileset.
Mount –o cio /portaldb
• Increase AIX maximum number of processes per user to 4096.
The default 500 processes per user is too low for database server, we increase
it to 4096 in our AIX environment. To increase it,
chdev –l sys0 –a maxuproc=’4096’
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While the Portal databases are configured for high capacity performance, various tuning
adjustments may be necessary from time to time. Typically these tuning needs are based
on the volume of database traffic and the size of table populations.
Our database tuning settings is documented in the Portal Info Center under ‘Creating
Remote Database’ section.
DB2 ON Z/OS SETUP
After transferring the database tables, first Identify what tables need to be reorganized.
Perform a re-org check to improve performance.
• Run the EJPSDBTC job after database transfer. This job contains the DB2
check and RUNSTATS utility for the JCR, Likemind and Feedback database.
• For details on re-org DB2 database, visit WebSphere Portal Info Center.
Create a Re-org job to re-org all table spaces in WPSDBJCR database.
RECOMMENDED D ATAB ASE MAI N TEN ANCE FOR DB2 LUW
Two of the database attributes, which DB2 relies upon to perform optimally, are the
database catalog statistics and the physical organization of the data in the tables.
Catalog statistics should be recomputed periodically during the life of the database,
particularly after periods of heavy data modifications (inserts, updates, and deletes)
such as a population phase. Due to the heavy contention of computing these statistics,
we recommend performing this maintenance during off hours, periods of low demand,
or when the portal is off-line. The DB2 runstats command is used to count and record
the statistical details about tables, indexes and columns. We have used two techniques
in our environment to recompute these statistics. The form we recommend is:
db2 runstats on table tableschema.tablename on all columns with
distribution on all columns and sampled detailed indexes all
allow write access
These options allow the optimizer to determine optimal access plans for complex SQL.
A simpler, more convenient technique for recomputing catalog statistics is:
db2 reorgchk update statistics on table all
Not only does this command count and record some of the same catalog statistics, it
also produces a report that can be reviewed to identify table organization issues.
However, we have found instances where this produces insufficient information for the
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optimizer to select an efficient access plan for complex SQL, particularly for queries of
the JCR database.
We have determined a technique that has the same convenience of the reorgchk
command and provides the detailed statistics preferred by the optimizer.
db2 -x -r "runstats.db2" "select rtrim(concat('runstats on table
',concat(rtrim(tabSchema),concat('.',concat(rtrim(tabname),' on all
columns with distribution on all columns and sampled detailed indexes
all allow write access'))))) from syscat.tables where type='T'"
db2 -v -f "runstats.db2"
The first command is used to create a file, runstats.db2, which contains all of the
runstats commands for all of the tables. The second command uses the db2 command
processor to run these commands.
To determine which tables might benefit from reorganization, we use the command:
db2 reorgchk current statistics on table all > "reorgchk.txt"
For those tables which require reorganization, we use the command:
db2 reorg table tableschema.tablename
to reorganize the table based upon its primary key.
You should also ensure that your database servers have adequate numbers of disks.
Multiple disks allow for better throughput by the database engine. Throughput is also
improved by separating the database logs onto separate physical devices from the
database.
You should ensure that the database parameter MaxAppls is greater than the total
number of connections for both the datasource and the session manager for each
WebSphere Portal application server instance. If MaxAppls is not large enough, you will
see exceptions in your connection pools.
You should use System Managed Storage (SMS) for temporary table spaces to benefit
complex SQL which require temporary tables to compute their result sets. This saves
time in buffer writes and improves disk utilization.
Database performance is very important for obtaining good performance from
WebSphere Portal. The maintenance tasks and practices mentioned here were found
to be critical to the performance and correct operation of WebSphere Portal in our lab
environment. Additional database maintenance and tuning may be needed in your
production environments. For further information on DB2 administration and tuning,
refer to the DB2 Information Center.
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O R A C L E D A T A B A S E S E R V E R T U N I N G
WebSphere Portal V6.1 uses database servers for core functionality. In this measurement
environment, we used Oracle database server for the Portal application. The LDAP server,
IBM Tivoli Directory Server included a DB2 database as a repository.
PL ANNI NG FOR ORAC LE ENTERPRI SE EDI TI ON D AT AB ASE
For our Solaris platform measurements we also used Oracle 10g R2 as our database
server. WebSphere Portal V6.1 uses the concept of Database domains to designate either
groups of tables belonging to one domain, or even entirely separate databases to store the
data specific to each domain.
On Oracle, we built a single database and create Oracle users to own the tables and data
needed to support each domain. The domains are listed in PortalDatabaseDomain, above.
For the Base Portal measurements, the Release domain is the primary database being
exercised.
A well designed database can save a lot of trouble later down the road, and improve
database performance. We recommend that you refer to the Oracle Administrator’s
Guide to help you make informed database design decisions. Here are the key choices
we have implemented in our Oracle database.
• To avoid I/O contention and allow for better throughput, you should ensure your
database server have adequate number of disks. Our database is on seven stripped
disks.
• For better management and performance of storage structures, Oracle-Managed
Files are used for database, as well as redo logs, and control files.
• Database block size: 8k
• The following tablespace sizing was required to support roughly a medium sized
Portal, with 100,000 authenticated users, approximately 180 installed portlets and
220 pages, which the load generally consisting of database read operations. We
recommend monitoring your tablespace sizing and growth on a regular basis. We
used DBCA to create database with the following Tablespace size:
o SYSAUX: 800MB
o SYSTEM: 800MB
o TEMP: 800MB
o UNDOTBS: 1024MB
o USERS: 2048MB
• Redo log groups: 500MB each.
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OR ACLE ON AI X SETUP
We configure our Oracle database on AIX using the following setup,
• Set the filesystem which will hold the Portal databases to be a Enhanced
Journal File System (JFS2).
• Turn on concurrent I/O (CIO) for database filesystem as this improves
performance. Do not enable CIO for Oracle product filesystem, ie, /u01, as
Oracle could fail to start.
To enable CIO, use the following command to mount the database fileset.
Mount –o cio /u02
• Increase AIX maximum number of processes per user to 4096.
The default 500 processes per user is too low for database server, we increase
it to 4096 in our AIX environment. To increase it,
chdev –l sys0 –a maxuproc=’4096’
• Enable AIX async I/O, and increase MinServer to 5.
smitty aio
ꢁ
Change/Show Characteristics of Async I/O
ꢁ
MinServers = 5
• We also set in oracle user’s profile as Oracle Installation Guide for AIX
recommends,
AIXTHREAD_SCOPE=S
OR ACLE ENTERPRISE EDI TION DATAB ASE PAR AMETER TUNI NG
Database performance is very important for obtaining good performance from WebSphere
Portal. Below is a list of tuning applied on our Oracle database server with the alter system
command. Additional database tuning maybe needed in your production environments. For
further information on Oracle database tuning, refer to Oracle Performance Tuning Guide at
Command used:
Alter system set <parameter> scope=spfile;
Table 8: Oracle Database Tuning
Parameter
Value
sessions
900
sga_target
1813M
604M
750
pga_aggregate_target
processes
open_cursors
db_files
1500
1024
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RECOMMENDED ORAC LE D AT AB ASE MAI NT EN ANCE
Optimizer statistics are a collection of data about the database and the objects in the
database, these statistics are used by the query optimizer to choose the best execution
plan for each SQL statement. Because the objects in a database can be constantly
changing, statistics must be regularly updated so that they accurately describe these
database objects, particularly after periods of heavy data modifications (inserts,
updates, and deletes) such as a population phase. We have used the following
commands in our environment to recompute these statistics:
execute
dbms_stats.gather_database_stats(dbms_stats.auto_sample_size,
method_opt=>'FOR ALL INDEXED COLUMNS SIZE AUTO',cascade=>TRUE);
O T H E R D A T A B A S E C O N S I D E R A T I O N S
WebSphere Portal maintains some information about users in its database tables, which
grow when a user first logs in. We were interested in the steady-state performance of
WebSphere Portal, not the performance of a user’s first login to the site. Therefore our
performance evaluates after all users logged in at least one time.
One of the most important database tuning factors is bufferpool sizing. It is important to
evaluate the database's physical versus logical reads and size the bufferpools to achieve as
much as a 95% logical read rate if possible.
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Directory Server Tuning
Our measurements used IBM Tivoli Directory Server versions 6.0 as the directory server.
These products use a database for storing user information; DB2 Enterprise Server was
used for this database in our environment. This database is typically located on the same
system as the directory server. If your workload involves creating, updating, or deleting
users, then database maintenance described above may be needed on this database.
The following table shows the tuning values used for the directory servers in our Solaris
Base Portal Scenario measurements
How-to-Set: These values are in the file /opt/IBM/ldap/V6.0/etc/SchemaV6.0/ibmslapd.conf. You
must restart the LDAP server after changing these values.
Table 9: IDS Tuning
Parameter
Value
Ibm-slapdACLCacheSize
Ibm-slapdEntryCacheSize
Ibm-slapdFilterCacheSize
Ibm-slapdFilterCacheBypassLimit
250000
250000
250000
7500
The IBM Tivoli Directory Server uses IBM DB2 as the database server. The database
instance and alias are named IDSLDAP. We applied the following tuning to this database:
db2 “update db config for idsldap using dbheap 4800”
db2 “update db config for idsldap using num_ioservers 10”
db2 “update db config for idsldap using num_iocleaners 5”
db2 alter bufferpool LDAPBP size 3690
db2 alter bufferpool IBMDEFAULTBP size 88500
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Web Server Tuning
We used IBM HTTP Server 6.1 in our measurement environment. The cluster configuration
and the Solaris configuration has a remote web server, find the tuning in Web Server Tuning
in Cluster Tuning section. All other configurations have the web server running on the same
system as the WebSphere Portal application server. If, during your monitoring, you notice
insufficient processor capacity on the system when running the web server and the portal
application server on a single system, consider separating the servers onto different
systems. We used the following tuning on our web servers:
Table 10: Web Server Tuning
Parameter
AIX
POWER5
Windows
2003
Linux
z/Linux
Additional Information
KeepAliveTimeout
5
5
5
5
This value is less than the think
time defined in our scripts to
ensure that testing is
conservative. Each user is
assumed to open a new TCP
connection for each page view.
However, in a live environment, it
can be helpful to increase the
KeepAlive Timeout. A higher
timeout value can increase
contention for HTTP server
processes, if you are running out
of HTTP processes, decrease
this value.
ThreadsPerChild
25
25
0
2000
0
25
0
The higher number of threads per
child on Windows is due to a
different process model for IHS
on Windows.
MaxKeepAliveRequests 0
Selecting 0 lets an unlimited
number of requests on a single
TCP connection.
MaxRequestsPerChild
StartServers
0
0
0
0
2
2
N/A
off
2
Access logging
off
off
off
This was turned off by
commenting out the following
configuration line:
CustomLog
/usr/HTTPServer/logs/access_log
common
ThreadLimit
ServerLimit
25
25
2000
N/A
25
150
120
180
Set it
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MaxClient/ThreadsPerChild.
Set it same as MaxClients.
MinSpareThreads
MaxSpareThreads
MaxClients
25
25
N/A
25
3750
3750
4500 N/A
4500 N/A
4500
4500
We also enabled the server-status module so that we could monitor the number of
running and available Web server processes. This enables appropriate tuning of the
MaxClientsand ThreadsPerChildparameters.
We did additional Web Server tuning in Web 2.0 Scenario. See Web 2.0 section for details.
Note: For z/OS, no Web Server was configured.
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Operating System Tuning
In any high-load environment, the network must be closely monitored to ensure that its
performance is acceptable and consistent. Note that, the following is not to suggest that all
network parameters are set to these values, but merely make the reader aware that the
network is also an entity in the performance environment and bottleneck resolution process.
A I X
NETWORK TUNI NG
Use smitty->Performance and Resource Scheduling->Tuning Kernel and Network
Parameters->Tuning Network Option Parameters->Change/Show Current Parameters to
change. These will take effect immediately, improving the network layer performance in high
volume environments.
Then remember to ‘Save current parameters for Next Boot’.
Table 11: AIX Network Settings
Parameter
Value
tcp_sendspace
tcp_recvspace
udp_sendspace
udp_recvspace
somaxconn
131072
131072
65536
655360
10000
1
tcp_nodelayack
rfc1323
1
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L I N U X
NETWORK TUNI NG
For Red Hat Linux and z/Linux (Suse Linux on zOS), we add the following settings to file
/etc/sysctl.conf, then run the command: sysctl -p
To inspect current TCP parameters, run the command: sysctl -a | fgrep tcp
Table 12: Linux Network Settings
Parameter
Value
net.ipv4.ip_forward
0
net.ipv4.conf.default.rp_filter
net.ipv4.conf.default.accept_source_route
net.core.rmem_max
1
0
16777216
16777216
net.core.wmem_max
net.ipv4.tcp_rmem
4096 87380 16777216
net.ipv4.tcp_wmem
4096 65536 16777216
net.ipv4.tcp_fin_timeout
net.core.netdev_max_backlog
net.core.somaxconn
30
3000
10000
15
net.ipv4.tcp_keepalive_intvl
net.ipv4.tcp_keepalive_probes
5
W I N D O W S 2 0 0 3
NETWORK TUNI NG
Use the regedit command, the following registry settings were made in the section
HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Services\
Tcpip\Parameters. Create a new REG_DWORD named below.
Table 13: Windows Network Settings
Parameter
Value
MaxFreeTcbs
dword:00011940
dword:0000ffff
MaxHashTableSize
MaxUserPort
dword:0000fffe
TcpTimedWaitDelay
TcpWindowSize
dword:0000001e
dword:0000ffff (65535)
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S O L A R I S
NETWORK TUNI NG
For Solaris, use the nddcommand to set the following TCP layer parameters. These will
take effect immediately, improving the network layer performance in high-volume
environments. We use the following settings in Portal server running Solaris 10:
How-to-Set: ndd -set /dev/tcp <PARAMETER> <VALUE>
Table 14: Solaris Network Settings
Parameter
Value
tcp_time_wait_interval
tcp_keepalive_interval
tcp_fin_wait_2_flush_interval
tcp_conn_req_max_q
tcp_conn_req_max_q0
tcp_xmit_hiwat
60000
15000
67500
16384
16384
400000
400000
2097152
60000
4000
tcp_recv_hiwat
tcp_cwnd_max
tcp_ip_abort_interval
tcp_rexmit_interval_initial
tcp_rexmit_interval_max
tcp_rexmit_interval_min
tcp_max_buf
10000
3000
4194304
KERNEL TUNING
Our Portal Server is running on Solaris 10. In Solaris 10, we use the following ‘projmod’
commands to set system parameters. After making the changes, we must logout then login
to take these changes into effect. To examine your current settings, do ‘cat /etc/project’.
projmod -s -K 'project.max-shm-memory=(privileged,4294967296,deny)' user.root
projmod -s -K 'project.max-shm-ids=(privileged,1024,deny)' user.root
projmod -s -K 'project.max-sem-ids=(privileged,1024,deny)' user.root
projmod -s -K 'process.max-sem-nsems=(privileged,4098,deny)' user.root
projmod -s -K 'process.max-sem-ops=(privileged,16384,deny)' user.root
projmod -s -K 'process.max-file-descriptor=(privileged,16384,deny)' user.root
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SOLARI S CONTAI NER
Use Solaris Containers to better utilize your modern, powerful T2 server with hundreds of
virtual processors. In our lab, we use Processor Sets to partition virtual processors. We
create a vertical cluster with six Portal members, then bind each member to a Solaris
Processor Set, this configuration gives the optimum performance result.
The commands we use to setup,
1.”pooladm –e” to enable pool facility
2.”pooladm –s” to create a static configuration file that matches the current dynamic
configuration
3.”poolcfg –c ‘create wp_pset1 (unit pset.min=20; unit pset.amx =21)’”
Create a processor set, named wp_pset1 or your choice, with between 20 and 21
processors. Create one per processor set.
4.”poolcfg –c ‘create pool wp_pool1’”
Create resource pool named wp_pool1 or your choice.
Create one per pool.
5.”poolcfg –c ‘associate pool wp_pool1(pset wp_pset1)’”
Join the pool and the processor set with an association.
Do this for each Processor set.
6.”pooladm –c”
Commit the configuration at /etc/pooladm.conf.
7.”poolbind –p wp_pool1 <PortalPID>”
Bind the resource pool to a Portal process.
Refer to IBM Redbook “IBM WebSphere Application Server V6.1 on the Solaris 10
Operating System”, sg247584.
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Z / O S
SYS TEM TUNING
In the PARMLIB member BPXPRMxx check the values of the following parameters:
Table 15: z/OS System Tuning
Parameter
Value
15000
Additional Information
MAXPROCSYS
System will allow at most 15000 processes to be
active concurrently.
MAXPROCUSER
MAXUIDS
15000
200
Allow each user (same UID) to have at most 15000
concurrent processes active.
Allow at most 200 z/OS UNIX users to be active
concurrently.
MAXFILEPROC
MAXPTYS
65535
800
Allow at 65535 open files per user.
Allow up to 800 pseudo-terminal sessions
MAXTHREADTASKS
5000
System will allow at most 5000 threads tasks to be
active concurrently in a single process
MAXTHREADS
10000
40960
System will allow at most 10000 threads to be active
concurrently in a single process.
MAXMMAPAREA
System will allow at most 40960 pages to be used for
memory mapping.
MAXFILESIZE
MAXCORESIZE
MAXASSIZE
NOLIMIT
Unlimited file size.
4194304
2147483647
This size is same as the region size for TSO. By
default USS ids get some pre-defined minimum
which is usually not enough for WPS kind of stuff. To
avoid problems instantiating java processes this size
should be set to 214783647.
MAXCPUTIME
2147483647
32768000
To improve the CPU process time.
MAXSHAREPAGES
System will allow at most 32768000 pages of shared
storage to be concurrently in use.
Required Fixes
The following fix is required to apply in WebSphere Portal Version 6.1 Solaris environment.
PK73368: Cache synchronization issue, deadlocks can occur in the CacheOnRequest
class. This fix is included in WebSphere Portal 6.1.0.1 and later.
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WEB2.0THEMETUNING
In the Web 2.0 theme environment a reverse proxy was used to cache content outboard of
WebSphere Portal. The reverse proxy was set up to take advantage of the fact that portlet
fragments are fetchable and cacheable. This avoids having to refetch the entire portal page
in many cases. This allowed some content to be fetched without going to the web server or
the portal server. Performance can be further improved by having the reverse proxy set up
to gzip much of the content.
In general, the same tuning that was used for the Base Portal Scenario described in
previous section was used for the Web 2.0 Scenario. The differences in tuning are
mentioned below.
JVM Initial and Maximum Heap Size
JVM’s Initial and Maximum heap size (ms and mx) were set to 1280. With higher values the
system ran out of native memory under high Vuser load. This can be alleviated by using the
– Xalwaysclassgc jvm parameter along with setting -Xmx=1408. However the throughput
was better with -Xmx=1280 than when using – Xalwaysclassgc and –Xmx=1408.
Navigator Service Properties
The following values were specified in NavigatorService.properties in addition to the
parameters changed in the Base Portal tuning.
Table 16: Navigation Service Settings for Web 2.0 Theme
Parameter
Setting Used
remote.cache.expiration.feed.cm
remote.cache.expiration.feed.nm
remote.cache.expiration.feed.lm
remote.cache.expiration.feed.pm
600
600
600
600
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Internet Explorer Support of Vary Header
When Internet Explorer 7 is sent a ‘vary’ http header, it is unable to cache that reply
effectively. To configure WebSphere portal to not send the vary header to IE 7, log in as
portal administrator and navigate to Administration -> Portal Settings -> Supported Clients.
Then select IE 7 as the browser and remove support for the ‘vary’ header.
Caching Proxy Tuning
The following are the settings and tunings specified in the reverse proxy’s ibmproxy.conf file
for the Web 2.0 performance test.
Table 17: Reverse Proxy Settings
Parameter
Setting Used
Additional Information
Proxy /wps/* http://{server-name}/wps/*
Proxy for /wps
name}/wps_semanticTag* :80
Proxy for /wps_semanticTag
ConnThreads
15
on
ServerConnPool
MaxSocketPerServer
CacheTimeMargin
CacheFileSizeLimit
flexibleSocks
20
5 seconds
2 M
off
LimitRequestFieldSize
16384
CompressionFilterEnable C:\PROGRA~1\IBM\edge\
cp\Bin\mod_z.dll
CompressionFilter
AddContentType
Image/bitmap,text/css,text/ Compresses everything except text/html,
xml,application/xml
application/atom+xml, text/plain,
application/x-javascript. Portal
compresses those types. Experiments
were done where reverse proxy gzipped
those files as well which caused the
reverse proxy CPU to become a
bottleneck. If a more powerful reverse
proxy server was available, it might make
sense to do all gzipping on the reverse
proxy. Note that fixes for PMR 43866,499
were applied to Edge Server v6.02 to get
proper gzipping behavior.
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Web Server Tuning
Http server tuning for cacheability:
# uncommented these to enable statics to be cached
LoadModule expires_module modules/mod_expires.so
LoadModule headers_module modules/mod_headers.so
BrowserMatch ^Mozilla/4\.[0678] no-gzip
BrowserMatch \bMSIE\s7 !no-gzip !gzip-only-text/html
# added this for caching of dojo javascript and the theme’s xsl files, max-age = 1 day
<Location /wps/themes/dojo>
Header set Cache-Control public;max-age=86400
</Location>
<Location /wps/themes/html/PortalWeb2/xsl>
Header set Cache-Control public;max-age=86400
</Location>
# set cache-control public for various static content
<FilesMatch "\.(gif|jpeg|jpg|png|ico|css|js|swf)$">
Header set cache-control "public"
</FilesMatch>
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# expire images after a month in the client's cache. Note that one month expiration
worked fine for a performance evaluation in a test lab. It should be set appropriately
for your environment where images might be updated more frequently than once a
month.
ExpiresActive On
ExpiresByType image/gif A2592000
ExpiresByType image/jpg A2592000
ExpiresByType image/jpeg A2592000
ExpiresByType image/png A2592000
ExpiresByType application/x-javascript "access plus 1 week"
ExpiresByType text/javascript "access plus 1 week"
ExpiresByType text/css "access plus 1 week"
ExpiresByType application/xml "access plus 1 week"
ExpiresByType application/vnd.mozilla.xul+xml "access plus 1 week"
ExpiresByType application/x-www-form-urlencoded "access plus 1 week"
ExpiresByType text/html "access plus 1 week"
ExpiresByType text/xml "access plus 1 week"
Portlet Caching
portlet.xml is part of a portlet’s war file. It is located in the portlet’s WEB-INF directory. To
make portlet fragments publicly cacheable set:
a.<expiration-cache>28800</expiration-cache>
b.<cache-scope>public</cache-scope>
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4
MANYPAGESTUNING
The “Many Pages Scenario”, derived from the Base Portal Scenario, measures the effects of
having larger numbers of pages visible to the users.
Since it is derived from the Base Portal Scenario, the same tuning that was used for the
Base Portal Scenario applied for the Many Pages Scenario. The differences in tuning are
mentioned below.
DB2 Database Tuning
We applied the following tunings to our Release database.
Table 18: DB2 Database Settings for Many Pages
Release DB
Parameter
Setting Used
dbheap
4800
4096
256
8
applheapsz
logbufsz
num_IOServers
num_IOCleaners
8
How-To Set: In the DB2 server run the following commands:
db2 “update db cfg for release using dbheap 4800”
db2 “update db cfg for release using applheapsz 4096”
db2 “update db cfg for release using logbufsz 256”
db2 “update db cfg for release using app_ctl_heap_sz 4096”
db2 “update db cfg for release using num_IOServers 8”
db2 “update db cfg for release using num_IOCleaners 8”
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Cache Manager Service
Table 19: Cache Manager Service Settings for Many Pages
Parameter
Setting Used
com.ibm.wps.datastore.pageinstance.OIDCache.size
com.ibm.wps.datastore.pageinstance.OIDCache.lifetime
com.ibm.wps.datastore.pageinstance.DerivationCache.size
com.ibm.wps.datastore.pageinstance.DerivationCache.lifetime
10000
28800
10000
28800
Required Fixes
On WebSphere Portal 6.1, PK70946 is required in Many Pages Scenario. This fix is
included in WebSphere Portal 6.1.0.1 and later.
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5
WEBCONTENTMANAGEMENTTUNING
In general, the same tuning that was used for the Base Portal Scenario was used for the
WCM authoring, rendering and API Scenario. The main differences are to the cache
tuning settings: WCM increases demands on the portal access control component
which requires a different set of cache tunings to accommodate and WCM has an
internal set of object caches that can be tuned as well. On top of cache tunings, WCM
can require more Web Container threads and JCR data source connections than the
Base Portal Scenario, especially for heavy authoring workloads. The differences in
tuning are mentioned below.
Application Server Tuning
•
Web Container Thread Pool – we used 60 threads for both the minimum
and maximum value
•
Data Source Connection Pool – We used the following values:
Data Source
Rendering Value
(min/max)
Authoring/API
Value (min/max)
JCRDB
10/150
10/150
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WebSphere Portal Service Properties
C A C H E M A N A G E R S E R V I C E
Portal Caches sizes – Ignore the Base Portal values and set the following in
CacheManagerService.properties:
Table 20: Cache Manager Service Settings for WCM
CacheManagerService.properties File
Value Used
Cache Name
5000
cacheinstance.com.ibm.workplace.searchmenu.helper.SearchMenuCacheHelper.size
cacheinstance.com.ibm.wps.ac.ContainedRolesCache.size
500
5000
12500
10800
500
cacheinstance.com.ibm.wps.ac.AccessControlUserContextCache.size
cacheinstance.com.ibm.wps.ac.ApplicationRolesForPrincipalCache.size
cacheinstance.com.ibm.wps.ac.AccessControlUserContextCache.lifetime
cacheinstance.com.ibm.wps.ac.ExplicitEntitlementsCache.size
cacheinstance.com.ibm.wps.ac.ExplicitEntitlementsCache.ICM_CONTENT.size
cacheinstance.com.ibm.wps.ac.ExplicitEntitlementsCache.VIRTUAL.size
cacheinstance.com.ibm.wps.ac.ProtectedResourceCache.size
cacheinstance.com.ibm.wps.ac.ExternalOIDCache.size
12000
500
12500
12000
10800
7500
1200
250
cacheinstance.com.ibm.wps.ac.AccessControlUserContextCache.lifetime
cacheinstance.com.ibm.wps.ac.RolesCache.size
cacheinstance.com.ibm.wps.ac.groupmanagement.NestedGroupCache.size
cacheinstance.com.ibm.wps.datastore.pageinstance.DerivationCache.size
cacheinstance.com.ibm.wps.datastore.pageinstance.OIDCache.size
cacheinstance.com.ibm.wps.datastore.services.Identification.SerializedOidString.cache.size
cacheinstance.com.ibm.wps.model.content.impl.ResourceCache.size
cacheinstance.com.ibm.wps.model.content.impl.TopologyCache.size
cacheinstance.com.ibm.wps.pe.portletentity.size
250
500
500
500
250
cacheinstance.com.ibm.wps.services.cache.cachedstate.CachedStateServiceSession
Bound.cache.size
250
cacheinstance.com.ibm.wps.ac.ApplicationRoleChildrenCache.size
cacheinstance.com.ibm.wps.ac.ApplicationRoleDescriptorCache.size
cacheinstance.com.ibm.wps.ac.ApplicationRoleOIDCache.size
cacheinstance.com.ibm.wps.ac.ChildEntitlementsCache.size
cacheinstance.com.ibm.wps.ac.ExplicitEntitlementsCache.APPLICATION_ROLE.size
cacheinstance.com.ibm.wps.policy.services.PolicyCacheManager.lifetime
cacheinstance.com.ibm.wps.model.content.impl.ResourceCache.lifetime
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500
500
500
500
500
28800
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N A V I G A T I O N S E R V I C E
Portal Navigator Service – In addition to the settings mentioned for Base Portal we set
the following property to allow public sessions required for rendering portlets on
anonymous pages:
Table 21: Navigation Service Settings for WCM
NavigatorService.properties File
Default Value
Parameter
Definition
Value
Used
Controls whether anonymous users have
sessions
public.session
false
true
WCM Object Cache
Table 22: WCM Object Cache Settings
WCM Object Caches
Cache Name
abspath
Value Used
8000
8000
abspathreverse
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processing
session
menu
10000
6000
500
nav
500
strategy
global
8000
100
module
100
How-To Set: Login to the WAS Administration Console → Resources → Cache instances →
Object cache instances.
WCM Configuration Service
Enable the user cache
Find the WCMConfigService.properties file under:
<wp_profile>/PortalServer/wcm/shared/app/config/wcmservices
Set user.cache=true
JCR Text Search
icm.properties – Disable jcr textsearch
During our measurements, we have disabled text indexing. Text indexing is done
periodically, adding new content to the text index. However, the indexing interval is not
synchronized with our load plateaus. As a result, if we let text indexing run during our
performance measurements, it would likely reduce the reliability and repeatability of our
measurements.
We do not recommend disabling text indexing in production environments, as doing so
would mean that new content will not be added to the text index, and therefore would
not appear in search results.
If you wish to disable text indexing, this can be done in the file icm.properties, by
setting the property jcr.textsearchto the value false. This file is found in the directory
<wp_profile>/PortalServer/jcr/lib/com/ibm/icm
.
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DB2 Tuning (Authoring Environment)
M U L T I P L A T F O R M ( L U W )
On top of the DB2 tunings for the base portal scenario, during our testing we found that the
following tunings to the JCR database below significantly decreased load on the CPU and
disk i/o of the DB2 server in our environment.
In our authoring scenario we found that it was necessary to initially size the IBMDEFAULTP
and ICMLSMAINBP32 bufferpools. This was because DB2 was unable to autosize them
fast enough during our user ramp ups and it was therefore causing inconsistent results
during the early stages of the scenario. We also noticed a large amount of database file
handles being opened and closed during our runs stressing the disk i/o prompting us to
increase the maximum number of file handles that can be opened for the JCR database.
Finally, three indexes were added to eliminate some troublesome queries that were table
scanning.
db2 connect to jcrdb
db2 alter bufferpool IBMDEFAULTBP IMMEDIATE size 26000
db2 alter bufferpool ICMLSMAINBP32 IMMEDIATE size 24000
db2set DB2_ASYNC_IO_MAXFILOP=512
db2 update db cfg for jcrdb using MAXFILOP 512
db2 create index taw_ut01590_idx6 on jcr.icmut01590001
(attr0000001334, itemid, versionid )
db2 reorgchk update statistics on table jcr.icmut01590001
db2 create index taw_entry_idx2 on jcr.ev_entry (parentid)
db2 reorgchk update statistics on table jcr.ev_entry
db2 create index taw_ICMSTJCRWSX_2 on jcr.icmstjcrws (basewsid,
wstype)
db2 reorgchk update statistics on table jcr.icmstjcrws
db2stop force
db2start
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Z / O S
The following section details the tunings that we made in our DB2 9 for z/OS backend
database during our testing. To start here are a few general recommendations:
• When the DB2 z/OS server is on a different server to the Portal/WCM installation, the
use of the Universal Driver type 4 database driver is recommended
• For data sharing groups, we additionally recommend enabling Sysplex Distributor to
enhance high availability and exploit workload balancing.
In our environment we created nine databases to support WCM on Portal. The release,
customization, community, likeminds, and feedback are required for Portal. For WCM, a
minimum of two JCR databases are required for scalability and in our environment we used
four.
TABLESP ACES
Following DB2 best practices, it is recommended to create all tables into individual
tablespaces. This will avoid device contention and provides better monitoring possibilities.
Furthermore, most DB2 utilities such as REORG operate with tablespaces rather than
tables.
BUFFERPOOLS
It is also beneficial to create separate bufferpools for use by Portal to avoid contention.
When creating your database, ensure that each tablespace/indexspace has a specific
bufferpool specified by the BUFFERPOOL/INDEXBP attributes rather than using the DB2
system defaults. It is recommended that a set of bufferpools separate from the Portal
databases gets created for the JCR databases. The following table shows the settings for
our configuration.
Table 23: DB2 z/OS Bufferpool Settings
Bufferpool settings
BP
Pagesize
DB2
BP
BP
Size
Database Domain
wkplc_comp.properties
(KB)
<domain>.Db4KBufferPoolName
BP2
4
40000
5000
RELEASE
CUSTOMIZATION
COMMUNITY
LIKEMINDS
<domain>.DbIndex4KBufferPoolName
BP3
4
<domain>.Db32KBufferPoolName
BP32K
32
1000
FEEDBACK
jcr.Db4KBufferPoolName
jcr.DbIndex4KBufferPoolName
jcr.Db32KBufferPoolName
BP4
4
80000
40000
20000
JCR
BP5
4
BP32K1
32
Note: When running Portal, DB2 objects like tablespaces will be created dynamically. It is
important to keep your default bufferpools well defined to avoid causing contention due to an
overloaded bufferpool. This is especially true for LOB and 4-KB tablespaces as they default
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to BP0. In DB2 9 for z/OS, ZPARM’s can be set to specifiy default bufferpools. In our
environment we used the following values.
Table 24: DB2 z/OS Default Bufferpool Settings
Default Bufferpool Settings
ZPARM
Value Used BP Size
Description
Specifies the default buffer pool to use for LOB table spaces that
are created implicitly and for LOB table spaces that are created
explicitly without the BUFFERPOOL clause.
Specifies the default buffer pool to use for 4-KB page size table
spaces that are created implicitly and for 4-KB page size table
spaces that are created explicitly without the BUFFERPOOL
clause.
TBSBPLOB BP16K0
TBSBPOOL BP4
10000
80000
Specifies the default buffer pool to use for 8-KB page size table
spaces that are created implicitly and for 8-KB page size table
spaces that are created explicitly without the BUFFERPOOL
clause.
Specifies the default buffer pool to use for 16-KB page size table
spaces that are created implicitly and for 16-KB page size table
spaces that are created explicitly without the BUFFERPOOL
clause.
Specifies the default buffer pool to use for 32-KB page size table
spaces that are created implicitly and for 32-KB page size table
spaces that are created explicitly without the BUFFERPOOL
clause.
TBSBP8K
BP8K0
35000
10000
1000
TBSBP16K BP16K0
TBSBP32K BP32K
DB2 uses the IDXBPOOL value if you do not specify a value for
INDEXBP on the CREATE DATABASE statement. DB2 does not
use this value for a CREATE INDEX statement without the
BUFFERPOOL option. In that case, DB2 uses the default index
buffer pool for the database.
IDXBPOOL BP5
40000
DB2 FOR Z/OS V8 FI XES
The following fixes are required for running WCM on WPS 610x on DB2 for z/OS v8.
• PK62728 - DB2 improves the performance of selected queries (UK36555)
• PK67292 - DB2 was fixed to transform the subquery into a join (UK37970)
• PK68259 - Addresses CORRELATED SUBQUERY TO JOIN TRANSFORMATION
ENHANCEMENT FOR MULTI-TABLE JOINS IN ANY QUERY BLOCK (UK37971)
ADDI TIONAL RESOUR CES FOR DB2 Z/OS
•
•
•
WCM/JCR database table usage information for WebSphere Portal v6
Performance Improvement Possible For Remote TCP Access to z/OS
DB2 9 for z/OS Performance Topics
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COMPOSITEAPPLICATIONSTUNING
For the Composite Application Infrastructure scenario, we started with the tuning given in the
Base Portal Scenario above. However, the Composite Application Infrastructure scenario
accesses a large number of applications, and therefore a large number of pages and
portlets. Therefore there is higher demand on some of the caches in WebSphere Portal; to
improve performance in this scenario, we modified the sizes of some of the caches in
WebSphere Portal.
Cache Manager Service Properties
The following values were specified in CacheManagerService.properties in addition to the
parameters changed in the Base Portal tuning. We recommend that you monitor the caches
in your environment to determine which caches might need tuning.
Table 25: Cache Manager Serivce Properties for Application Infrastructure
Parameter
Value
8000
cacheinstance.com.ibm.wps.resolver.friendly.cache.size
cacheinstance.com.ibm.wps.ac.ProtectedResourceCache.size
cacheinstance.com.ibm.wps.ac.PermissionCollectionCache.lifetime
cacheinstance.com.ibm.wps.ac.AccessControlUserContextCache.lifetime
cacheinstance.com.ibm.wps.ac.ProtectedResourceCache.lifetime
cacheinstance.com.ibm.wps.ac.OwnedResourcesCache.lifetime
cacheinstance.com.ibm.wps.ac.RolesCache.lifetime
10000
28800
28800
28800
28800
28800
28800
28800
28800
28800
cacheinstance.com.ibm.wps.ac.ParentResourceRoleMappingCache.lifetime
cacheinstance.com.ibm.wps.ac.ResourceRoleMappingCache.lifetime
cacheinstance.com.ibm.wps.ac.ExplicitEntitlementsCache.lifetime
cacheinstance.com.ibm.wps.ac.ChildEntitlementsCache.lifetime
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cacheinstance.com.ibm.wps.ac.SingleEntitlementsCache.lifetime
28800
28800
cacheinstance.com.ibm.wps.ac.ExplicitEntitlementsCache.CONTENT_NODE.
lifetime
cacheinstance.com.ibm.wps.ac.ExplicitEntitlementsCache.WEB_MODULE.lifetime
28800
28800
cacheinstance.com.ibm.wps.ac.ExplicitEntitlementsCache.APPLICATION_ROLE.
lifetime
cacheinstance.com.ibm.wps.ac.ExplicitEntitlementsCache.PORTLET_APPLICATIO 28800
N_DEFINITION!PORTLET_DEFINITION.lifetime
cacheinstance.com.ibm.wps.ac.ExplicitEntitlementsCache.USER_GROUP.lifetime
cacheinstance.com.ibm.wps.ac.ExplicitEntitlementsCache.VIRTUAL.lifetime
28800
28800
28800
cacheinstance.com.ibm.wps.ac.ExplicitEntitlementsCache.WSRP_PRODUCER.
lifetime
cacheinstance.com.ibm.wps.ac.ExplicitEntitlementsCache.ICM_CONTENT.lifetime
cacheinstance.com.ibm.wps.ac.ExternalOIDCache.lifetime
28800
28800
28800
28800
28800
28800
28800
28800
28800
cacheinstance.com.ibm.wps.ac.ApplicationRoleOIDCache.lifetime
cacheinstance.com.ibm.wps.ac.ApplicationRoleDescriptorCache.lifetime
cacheinstance.com.ibm.wps.ac.ApplicationRolesForPrincipalCache.lifetime
cacheinstance.com.ibm.wps.ac.ApplicationRoleChildrenCache.lifetime
cacheinstance.com.ibm.wps.ac.ContainedRolesCache.lifetime
cacheinstance.com.ibm.wps.ac.AuthLevelConfigurationCache.lifetime
cacheinstance.com.ibm.wps.ai.rt.impl.service.ActiveApplicationOIDCache.lifetime
Composite Applications Best Practices
As with other components of WebSphere Portal, the way in which teamspaces are used will
influence the performance of the site. Based on our experience and analysis, the following
tips can help you achieve better performance with teamspaces:
•
As the measurements above show, the number of teamspaces on the system
influences the capacity of the system. However, the key determining factor is not the
total number of teamspaces, but rather the number of teamspaces visible to each
user. For example, a site with 1,000 teamspaces visible to all users could have a
capacity lower than a site with 5,000 teamspaces where the typical user can see no
more than 50 of those.
•
One way to exploit the observation above is to not make teamspaces public by
default. Public teamspaces are visible to all users, so a large number of public
teamspaces will increase the average number of teamspaces visible to each user.
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•
To paraphrase Albert Einstein, “keep teamspaces as simple as possible, but no
simpler”. In implementing this, consider both the number of pages as well as the
number of portlets on each page. Adding additional pages or portlets to a teamspace
increases the overhead associated with that teamspace. While this is not a great
overhead when considering an individual teamspace, when aggregated across
thousands of teamspaces, the overhead can become significant. In addition, the
more portlets are on each page, the more work will required to render that page.
•
•
Another area to consider regarding teamspace complexity is the number of
application roles. For many teamspaces, two roles (manager and user) are
adequate. Don’t create additional roles unless they are really needed.
When assigning membership to a teamspace, the best performance will be seen
when membership is assigned by groups rather than by individual users. For
example, WebSphere Portal will cache permissions based on the way permissions
are assigned, giving the chance for more cache hits if permissions are assigned by
groups.
•
Memory demand increases with the number of teamspaces on the system.
Therefore, if you expect to use large numbers of teamspaces, a 64-bit JVM will
probably provide better capacity than a 32-bit JVM.
See also the section regarding “Use of Dynamic Content Features”. Experiments in our lab
showed a reduced demand for memory, and thus an improvement in capacity, in the
application infrastructure scenario when disabling dynamic content support.
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CLUSTERTUNING
The Base Portal Scenario is measured in a three-node horizontal cluster environment,
with or without session persistence, and six-members vertical cluster environment.
In general, the same tuning that was used for the Base Portal Scenario was used for
cluster. The additional settings are mentioned below:
Application Server Tuning
D Y N A C A C H E C U S T O M P R O P E R T I E S
There are several properties which can be set to reduce the number and size of
Dynacache messages sent between nodes. This will improve scalability and reduce
resource consumption in a clustered Portal environment. To set these properties, do the
following:
1) Open and log in to the Administrative Console.
2) Click Application servers -> WebSphere_Portal -> Java and Process
Management -> Process Definition -> Java Virtual Machine -> Custom
properties -> New
3) Under General Properties, add the following information:
Name: com.ibm.ws.cache.CacheConfig.ignoreValueInInvalidationEvent
Value: true
Name: com.ibm.ws.cache.CacheConfig.filterTimeOutInvalidation
Value: true
Name: com.ibm.ws.cache.CacheConfig.filterLRUInvalidation
Value: true
Z / O S D Y N A C A C H E C U S T O M P R O P E R T Y
A custom property has been defined: com.ibm.ws.cache.CacheConfig.
propogateInvalidationsNotShared, which when set to true leads to invalidations
being sent for cache entry insertions and updates for a NOT_SHARED cache instance.
This property should be removed on z/OS configurations as it has a major impact on
performance.
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T H R E A D P O O L S
Increase Default Thread Pool size to help DRS traffic.
How-To Set: Portal Server->Thread Pools ->DefaultPool=150/150 (default=5/20)
T R A N S P O R T B U F F E R S I Z E
Default Transport Buffer size is insufficient. We increase to 200MB.
How-To Set:
Portal Server-> Core Group Service ->Transport buffer=200mb (default=10MB)
Must also configure the same size for Node Agent & DM.
System Administration -> Deployment Manager-> Core Group Service ->Transport
buffer size=200
System Administration -> Node agents-> node_agent_name ->under Additional
properties->Core Group Service ->Transport buffer size=200
W M M C O N T E X T P O O L I N G
Tuning Cluster for WMM Context Pooling must be done in Deployment Manager, then do
full resync to each node from Administrative Console. See VMM Context Pooling on how to
set.
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Web Server Tuning
Table 26: Web Server Tuning for Clusters
Parameter
Setting Used
25
ThreadLimit
180
2
ServerLimit
StartServers
4500
25
MaxClients
MinSpareThreads
MaxSpareThreads
ThreadsPerChild
MaxRequestsPerChild
4500
25
0
Sample configuration:
<IfModule worker.c>
ThreadLimit
ServerLimit
StartServers
MaxClients
25
180
2
4500
MinSpareThreads 25
MaxSpareThreads 4500
ThreadsPerChild 25
MaxRequestsPerChild 0
</IfModule>
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Session Persistence To Database Tuning
To enable Session Persistence to Database, a data source with non-XA JDBC driver must
be created. We also configured DB2 Session Database with 32K page size to optimize
performance for writing large amounts of data to the database. For details on configuring
tablespace and page size for DB2 session database visit WebSphere Application Server
Info Center. Additional tunings are applied below:
Table 27: WebSphere Session Persistence Tuning
Parameter
Setting
2000
Additional Details
The default value of Session in memory count is 1000.
For Session database persistence enabled load, we set
session in memory count to 2000.
Session in
memory count
How-To Set Parameter:
In the WebSphere Administrative Console: Servers ꢁ
Application Servers ꢁ WebSphere Portal ꢁ Container
Settings: Session Management ꢁ Max in memory
- Set Max in memory
The default value of session allow overflow is checked.
For Session database persistence enabled load, we
unchecked it.
Allow overflow
disable
How-To Set Parameter:
In the WebSphere Administrative Console: Servers ꢁ
Application Servers ꢁ WebSphere Portal ꢁ Container
Settings: Session Management -> Allow overflow ->
uncheck it.
How-To Set Parameter:
Session
Enable with
In the WebSphere Administrative Console: Servers ꢁ
Application Servers ꢁ WebSphere Portal ꢁ Container
Settings: ꢁ Session Management
Distributed
Environment
database 32K page
tablespace
DistributedEnvironment Settings ->database
Jndi name: jdbc/sessions (set it according to your
Session datasource)
Userid/password: set it according to your session db
DB2 Row size: ROW_SIZE_32KB
Tablespace name=sess_user32k (set it according to
your db tablespace)
Multiple row schema: uncheck it
Refer to Datasource Tuning For DB2 on how-to set
parameter.
ConnectionPool
size for Session
Data Source
Min=10
Max=33
15
Refer to Datasource Tuning For DB2 on how-to set
parameter.
Prepared
Statement Cache
size for Session
Data Source
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SESSION D AT AB AS E TUNING
In addition to creating bufferpool and tablespace to support 32K page size for Session
database, we applied the following tunings to our dedicated session database server,
db2set DB2_USE_ALTERNATE_PAGE_CLEANING=ON
db2set DB2_RR_TO_RS=YES
db2set DB2_PARALLEL_IO=*
# disable session tablespace FILE SYSTEM CACHING
db2 alter tablespace sess_user32k NO FILE SYSTEM CACHING
db2 alter tablespace sess_temp32k NO FILE SYSTEM CACHING
db2 “update db cfg for <sess61> using locklist 5120”
db2 “update db cfg for <sess61> using maxlocks 80”
db2 “update db cfg for <sess61> using dbheap 4800”
db2 “update db cfg for <sess61> using num_iocleaners 20”
db2 “update db cfg for <sess61> using num_ioservers 20”
db2 “update db cfg for <sess61> using logbufsz 256”
db2 “update db cfg for <sess61> using logfilsiz 12288”
db2 “update db cfg for <sess61> using logprimary 40”
Vertical Cluster Tuning
We set the following in our vertical cluster environment,
• See Dynacache Custom Properties in Cluster Tuning section to reduce the number
and size of Dynacache messages sent between JVMs. Additional DynaCache
properties for Vertical Cluster:
Name: com.ibm.ws.cache.CacheConfig.cacheEntryWindow Value: 10
Name: com.ibm.ws.cache.CacheConfig.cacheInvalidateEntryWindow Value: 10
Name:com.ibm.ws.cache.CacheConfig.propogateInvalidationNotSharedValue: false
Name: com.ibm.ws.cache.CacheConfig.useServerClassLoader Value: true
• See Transport Buffer Size in Cluster Tuning section to increase transfer buffer size.
• Increase Dynamic cache size to 3500.
How to set: Portal Server -> Container Services -> Dynamic Cache Service -> Cache size =
3500
• See WMM Context Pooling on how to improve the performance of concurrent access
to an LDAP server.
• Use the following command to increase DBHEAP for Release database.
db2 “update db cfg for <release> using dbheap 4800”
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IBM Tivoli Directory Server Tuning
The following table shows the tuning values used for the directory servers.
How-to-Set: These values are in the file /opt/IBM/ldap/V6.0/etc/SchemaV6.0/ibmslapd.conf. You
must restart the LDAP server after changing these values.
Table 28: IDS Tuning in Vertical Cluster
Parameter
Setting Used
Ibm-slapdACLCacheSize
Ibm-slapdEntryCacheSize
Ibm-slapdFilterCacheSize
Ibm-slapdFilterCacheBypassLimit
250000
250000
250000
7500
The IBM Tivoli Directory Server uses IBM DB2 as the database server. The database
instance and alias are named IDSLDAP. We applied the following tuning to this database:
db2 “update db config for idsldap using dbheap 4800”
db2 “update db config for idsldap using num_iocleaners 5”
db2 “update db config for idsldap using num_ioservers 10”
db2 alter bufferpool IBMDEFAULTBP size 88500
db2 alter bufferpool LDAPBP size 3690
Required Fixes
• The following fixes are required to apply in 6.1 Cluster environment,
• PK67324 (for Windows is PK67800)
• WAS DynaCache PK67942
• WAS DynaCache PK59026 (include PK62850 and prereq PK67942), to
eliminate renounce messages
• PK70944: to eliminate GroupCache invalidation
• PK70890: Friendly URL fix
• The following fix is required to apply in 6.1.0.1 Cluster environment
PK76988: Cluster performance Degradation by large amount of DRS invalidation
messages
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8
OTHERPERFORMANCETUNINGOPTIONS
In addition to the scenarios discussed above, WebSphere Portal has some other tuning
options which may be useful in specific scenarios. These options include:
• Improving portal startup performance
• Managing the retrieval of user attributes
• Use of dynamic content features
Improving Portal Startup Performance
WebSphere Portal 6.1 introduced a “development mode” that greatly improves startup
performance, so that WebSphere Portal will start more quickly. This can be very useful for
development environments where WebSphere Portal must be stopped and started
frequently.
However, it’s important to note that this mode is only meant to be used for development or
test environments, not production or performance benchmark environments. Development
mode turns on lazy-start for almost all applications in WebSphere Portal, and this can cause
a performance impact the first time an application is accessed under load. Development
mode also changes the way the JVM is started to give better startup speed at the cost of
reducing capacity under load.
To switch to development mode, run the enable-develop-mode-startup-
performanceconfiguration task to complete the configuration and optimize the portal
startup. The changes can be reverted to the original values using the disable-develop-
mode-startup-performanceconfiguration task.
For more information, please visit the following URL:
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Managing the Retrieval of User Attributes
A user directory doesn’t just contain a user’s ID and password; it also contains a number of
other pieces of information – attributes – about the user. A directory server can contain a lot
of attributes for each user, so if every reference to a user required retrieving all of these
attributes, this would impose a performance penalty on both the Portal server node(s) and
the directory server node(s).
Therefore WebSphere Portal attempts to optimize the loading of these attributes. Two sets
of user attributes are defined: the base set of attributes, and the minimum set of attributes.
Depending on what action caused the user to be retrieved from the directory, either the base
or the minimum set of attributes will be retrieved. Typically, the base set of attributes will be
loaded when the user is retrieved; for example, this is what occurs when a user logs in. If the
user was looked up when searching for users, then the minimum set of attributes will be
loaded. For example, this can occur when searching for users to assign access to a page.
By default, WebSphere Portal defines the user attribute sets as follows:
•
Base set: the following attributes are in the base set:
o uid
o cn
o sn
o preferredLanguage
o ibm-primaryEmail
o givenName
o displayName
Minimum set:
o uid
•
o cn
What happens if additional attributes are needed? For example, consider a portlet which
requires the user attribute countryName. Assume that the user in question was looked up on
login, so the base set of attributes was retrieved. The attribute countryNameisn’t in the base
set, so the full user record – with all of its attributes – will be retrieved from the directory
server at that point. This will require a second request to the directory server. Also, since all
user attributes are retrieved on the second request, this can end up consuming more
memory on the WebSphere Portal server.
This provides an important performance tuning point to both improve response times and
reduce load on the directory server. If a user attribute will commonly be needed, then it
should be included in the base set of attributes so that it’s retrieved on the initial lookup,
eliminating the need for a second request. However, if an attribute is only needed
infrequently, consider leaving it out of the base set of attributes, so that it’s not retrieved for
all users.
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I D E N T I F Y I N G
A
F U L L F E T C H O F U S E R A T T R I B U T E S
How can you identify a second request is made to the directory server to retrieve the full set
of user attributes? This is best done in a test or staging environment, rather than a live
production environment, as it requires turning on tracing in the portal server, and this can
impose a significant performance overhead. There are two traces to enable to look for this
condition. The first one will show if the all the needed user attributes have been retrieved. If
this is false, then a full fetch of the user information will occur. The second trace shows
which attributes are being requested, so you can tell which ones should be added to the
base set.
The two trace strings are:
com.ibm.wps.um.PrincipalImpl=all=enabled
com.ibm.wps.um.PumaProfileImpl=all=enabled
Enable those traces, and then execute the use case you wish to test. Then, look for this
message in the trace.log:
PrincipalImpl 3 com.ibm.wps.um.PrincipalImpl isCompletelyLoaded false
This message may be output multiple times for the same user, so check all occurrences of
it. If the value after isCompletelyLoadedis always true, then all the needed attributes have
already been loaded, and no changes are needed. In this example, the value after
isCompletelyLoadedis false, showing that the needed user attributes haven’t all been
loaded. This will result in reloading all the user information from the user directory.
In that case, the trace will then typically show a call to reload the information for that user;
this will tell the full distinguished name of the user whose information is being loaded from
the user directory:
PrincipalImpl > com.ibm.wps.um.PrincipalImpl reload ENTRY id: cn=Yin Yin_000_992,
cn=users,l=SharedLDAP,c=US,ou=Lotus,o=Software Group,dc=ibm,dc=com
Next, search above that in the trace for the getAttributes call, which will show the attributes
the user has requested. It will look like this:
PumaProfileIm > com.ibm.wps.um.PumaProfileImpl getAttributes ENTRY id: cn=Yin
Yin_000_992, cn=users,l=SharedLDAP,c=US,ou=Lotus,o=Software Group,dc=ibm,dc=com
…more user details follow…
isExternal: false[preferredLanguage, ibm-primaryEmail, countryName,
displayName, givenName, cn, sn, uid]
The last line of the log entry shows the attributes being requested. In this case, the attributes
being requested are [preferredLanguage, ibm-primaryEmail, countryName, displayName,
givenName, cn, sn, uid]. Comparing this against the list of base user attributes, we can
see that countryNameis not in the base user attributes. Depending on whether the action
being executed is a common one or not, consider adding this to the base set of attributes.
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M I N I M U M A T T R I B U T E S E T
Generally, the minimum set of attributes does not need to be modified from the default
provided by WebSphere Portal, as that attribute set is satisfactory for the user management
applications provided with WebSphere Portal. However, if your site contains a custom
application for managing users and groups, and it uses attributes other than those in the
minimum set, then you should consider expanding the minimum attribute set.
Use of Dynamic Content Features
WebSphere Portal contains dynamic content support infrastructure which supports two
dynamic content features: dynamic user interfaces and attribute based administration. If
neither of these features is being used, the dynamic content support can be disabled. Note
that attribute based administration is only one use of the Personalization capabilities in
WebSphere Portal; other uses of Personalization, such as placing content spots within a
portlet, do not require the dynamic content features.
Disabling the dynamic content features will provide a modest performance benefit. It will
provide a reduction in the memory needed for each user, and also reduce the processing
time for generating pages in WebSphere Portal. For example, in one measurement with our
Base Portal scenario, capacity improved about 5% when disabling the dynamic content
support.
Disabling dynamic content support is done by adding a custom property to the
ConfigService.propertiesresource provider. The property is:
content.topology.dynamic=false
See “Overview of configuration services” in the WebSphere Portal information center for
more information on how to update configuration properties.
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Real-World Network Considerations
In our lab environment, we had the luxury of our clients and servers being on the same LAN
segment, so that they could take advantage of a high-bandwidth, low-latency network
connection. However, this is typically not the case for real clients. Over a wide-area network,
latencies can be significant, and bandwidth limited. In this case, the time to transfer the page
content from the server to the client can become a significant contributor to overall page
response time.
Here are some steps which can help alleviate this situation:
•
•
Compress content on the HTTP server
Allow client-side caching of images, Javascript files, and stylesheets,
Details on these steps will be given below.
C O M P R E S S C O N T E N T O N T H E H T T P S E R V E R
Much of the content served by a WebSphere Portal site can be compressed to reduce
transmission time and save network bandwidth. Typically, images should not be
compressed (as they are usually stored in a compressed format), but other types of content
can show a significant size reduction from compression.
IBM HTTP Server supports Deflate compression through the mod_deflatemodule. When
it is enabled, the HTTP server checks the Accept-Encoding:header sent by the browser
to see if it can accept a compressed version of the content. If so, the HTTP server will
compress the content before sending it to the browser.
In one measurement, we observed an average of 65% network traffic reduction when
Deflate compression is enabled. However, the compression operation does not come free
as we also observed approximately a 10% processor utilization increase on the HTTP
server.
To enable deflate compression in IBM HTTP Server, add the following lines in
httpd.conf:
# compress everything but images
LoadModule deflate_module modules/mod_deflate.so
DeflateFilterNote Input instream
DeflateFilterNote Output outstream
DeflateFilterNote Ratio ratio
# Insert filter
SetOutputFilter DEFLATE
# Netscape 4.x has some problems...
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BrowserMatch ^Mozilla/4 gzip-only-text/html
# Netscape 4.06-4.08 have some more problems
BrowserMatch ^Mozilla/4\.0[678] no-gzip
# MSIE masquerades as Netscape, but it is fine
BrowserMatch \bMSIE !no-gzip !gzip-only-text/html
# Don't compress images
SetEnvIfNoCase Request_URI \
\.(?:gif|jpe?g|png|exe)$ no-gzip dont-vary
E N A B L I N G C L I E N T - S I D E C A C H I N G
The HTTP protocol allows the server to tell clients how long they can cache responses.
When the client has the content in their cache, they do not need to request it again, saving
the round-trip time to the server to retrieve the content.
This is done by adding Cache-Control: headers to the content which we wish to make
cacheable. By default, WebSphere Portal will include these headers in the stylesheets it
uses, making that content cacheable at a client for 5 days (432,000 seconds). It is possible
to use mod_headers in IBM HTTP Server to add the same headers to images and
JavaScript files by adding the following lines to httpd.conf:
LoadModule headers_module modules/mod_headers.so
<Location ~ "\.(js|gif|jpg|jpeg|png)$">
Header add Cache-Control "public, max-age=432000, post-
check=172000"
</Location>
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9
ꢀ
WEBSPHEREPORTALCACHES
In the preceding chapter we described the specific values we modified for the WebSphere
Portal caches in our environments. This chapter describes the WebSphere Portal caches,
the general parameters for those caches, which cache instances WebSphere Portal v6.1
provides, and, finally, some sample portal usage patterns along with suggestions on portal
cache properties.
General Information
With WebSphere Portal V6.1, portal configuration properties, including cache configuration
properties, are managed via the WebSphere Application Server administrative console. In
previous WebSphere Portal releases these configuration properties were maintained in
properties files. More information on how to modify portal configuration properties can be
found in the Setting configuration properties section of the WebSphere Portal Version 6.1
information center.
C A C H E C O N F I G U R A T I O N P R O P E R T I E S
The cache configuration properties are organized in two groups: global configuration
properties and cache instance specific properties. Global properties have the prefix
cacheglobaland apply to all caches unless they are specifically overridden with a cache
instance specific property.
Cache instance specific properties have the prefix
cacheinstance and then contain the name of the cache instance and the name of the
property, for example:
cacheinstance.com.ibm.wps.ac.ExplicitEntitlementsCache.USER_GROUP.size
All entries of a cache are governed by a single set of properties.
The cache configuration properties that are safe to modify are: enabled, lifetime,
size, shared, replacement, and admit-threshold. The replacement and
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admit-thresholdproperties do not apply to all cache implementations. In general, only
caches that are not shared will use these properties. There are other properties that should
not be modified unless specifically instructed to do so by IBM WebSphere Portal support.
enabled: The enabledproperty determines whether a cache is used or not. If a cache is
not enabled, the property has a value of false, then no values are held by the
cache and every cache lookup will return a null value. This property should only be
modified for testing purposes, never in a production environment. The supported
values are trueand falseand the global default value is true.
lifetime:The lifetimeproperty determines the number of seconds an entry will exist
in a cache. A cache no longer returns an entry once the entry has existed longer
than the lifetimeproperty. Cache entries can also be invalidated prior to reaching
their lifetime due to explicit invalidation of the entry or Least Recently Used (LRU)
eviction from the cache.
A value of -1indicates an infinite lifetime. This value should be used with caution
since cache entries will only be invalidated programmatically. Infinite lifetimes are
particularly discouraged with access control caches because:
ꢀ In a cluster there can be rare occurrences when not all cache invalidation
messages are processed on every node due to race conditions in the
application server’s dynacache code. While the probability of this occurring is
low, it can not be completely avoided with the current code base. Finite
lifetimes allow these entries to be invalidated.
ꢀ Finite lifetimes allow modifications made to roles, which have been
externalized to an External Security Manager, to be reflected in role caches.
If updates to production environments are restricted to a well-defined staging
process using XML Access, it is usually safe to use infinite lifetimes.
size:The maximum number of entries in a cache is limited by the size property. If this size
limit is reached, entries are removed from the cache by an algorithm which usually
includes 1) remove invalidated entries and entries which have exceeded their lifetime
and 2) apply a LRU algorithm to the valid entries.
Any positive integer is allowed. Cache sizes have a direct impact on the memory
requirements of your portal, specifically the demands on the Java heap. You should
monitor and record the Java heap metrics and any performance impact when
modifying the size of a cache.
shared: Cluster-aware caches are shared across the nodes of a cluster. These caches
propagate invalidations of cache entries by using the WebSphere Application Server
DistributedMap interface.
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Supported values are trueand false. The default values shipped in WebSphere
Portal V6.1 should apply to most configurations. If you do not have a cluster there
may be a small performance benefit to setting this property to false since a different
cache implementation is used. We did not modify the defaults in our single node
measurement environments.
If this parameter is false in a cluster, it can ultimately lead to data inconsistencies
between the cluster members.
replacement: The cache replacement algorithm used by these caches works on the
frequency of recent access to cache entries; entries that have been used
frequently are less likely to be discarded than entries that have not been used
frequently. This parameter controls how long the access history will be kept. A
setting of aggressivemeans those only recently accessed entries will be
considered, which causes stale entries to be discarded more quickly. The
opposite setting, conservative, will consider a longer access history. The
intermediate setting of moderateis appropriate for most caches.
admit-threshold: Caches that have a very high insert rate may cause useful entries to
be discarded prematurely. An admittance threshold restricts the rate at which entries
are allowed into the cache by only allowing them to enter after an attempt has been
made to insert the same entry into the cache multiple times. The default value of 0
means “no admittance threshold”, which will allow entries into the cache on the first
insert attempt. This is appropriate for most caches. A higher value indicates that a
cache entry will not be allowed into the cache until that many attempts have been
made to insert the same key. For example, a value of 2 means that the first two
attempts to insert a cache entry will be ignored, and the third attempt will insert the
value into the cache. We did not modify the admit-thresholdfor any cache in
our measurement environments.
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Cache Usage Patterns
Most WebSphere Portal caches follow the simple paradigm: if an entry already exists use it,
otherwise add the entry. However, there are caches that behave differently. Each cache
follows one of the following four patterns:
ꢀ Pattern: regular
The regular pattern, described earlier, is the most common cache pattern:
value = cache.get(key);
if (value == null) {
value = calculateNewValue();
cache.put(key, value);
}
ꢀ Pattern: invalidation checking
Invalidating cache entries in a clustered environment is rather expensive. Therefore, portal caches often check whether the entry to be
invalidated actually exists in the local cache.
test = cache.get(key);
if (test != null) {
cache.invalidate(key);
}
Caches following this pattern follow the regular pattern for all but invalidation
actions.
ꢀ Pattern: multiple object types
Most caches hold only a single object type. When caches can hold multiple types,
they follow the regular pattern for each of those types.
ꢀ Pattern: cascading object types
This pattern is a special case of the ‘multiple object types’ pattern in that two or more object types that are queried in a certain order are
stored in a single cache. There may be one cache hit along with a cache miss on a regular basis.
value = cache.get(keyA);
if (value == null) {
value = cache.get(keyB);
if (value == null) {
value = calculateNewValue();
cache.put(keyA || keyB, value); // either key could be used
}
}
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Cache Instances
This section describes the caches in WebSphere Portal V6.1 along with hints to best
configure those caches. As you saw in the modifications we made in our measurement
environments, the size and lifetime properties are the most commonly modified
properties when tuning portal caches. You may wish to increase the size of a cache if many
values are used on a regular basis and there is sufficient space available in the Java heap.
You may wish to increase the lifetime of the entries of a cache if the cached data rarely, if
ever, changes and it is not critical to your business to reflect changes immediately in your
portal.
Each cache description includes the following attributes:
ꢀ Default size, default lifetimeand cache usage pattern
ꢀ Cache content and scaling factor (i.e. what causes the cache to grow)
ꢀ Information on the read and write access to the cache
ꢀ Approximate costs for re-creating cache entries and relative size of cached objects.
Small objects range from 16 to 300 bytes and the largest cache entries are not larger
than a few thousand bytes. One known exception are access control caches in
systems with many resources per user can hold entries that are very large, beyond
50,000 bytes, to reflect all the resources which a user can access.
ꢀ Some cache descriptions include a sample scenario with suggested property values.
1
A C C E S S C O N T R O L
This section describes each of the access control caches. It is critical for proper operation of
a portal that the access control information be current. Hence it is vital that these caches be
shared within a cluster so that the information is propagated to all members of the cluster.
Different lifetime values should be chosen to avoid concurrent reload of information from
multiple caches. This pattern of rather random lifetime and invalidation intervals could also
be applied to other caches.
The access control caches are divided into two groups: those caches (the first caches in the
list) used during all access control operations in all portal setups and those caches (starting
with the cache com.ibm.wps.ac.ApplicationRoleOIDCache) used for the
WebSphere Portal Composite Application Infrastructure.
1 This section is partially taken from another whitepaper: Portal Access Control Performance Tuning: http://www-
128.ibm.com/developerworks/websphere/library/techarticles/0508_buehler/0508_buehler.html
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Figure 1 shows the relationships among the various caches. The small cylinders represent
cache instances. The green caches are caches of the portal user management (PUMA)
component that are closely related to the caches of the portal access control component.
The PUMA caches contain information originating from the user registry. Portal access
control uses these caches for user identification and group membership retrieval.
The vertical axis represents the cache aggregation direction. The cache instances in layer N
leverage cache instances of lower layers to compute their values. For example, when
computing effective permissions (entitlements) for
a
user (cached in the
ExplicitEntitlementsCache), the portal access control component leverages existing cache
values from the ChildResourcesCache and RoleMappingCache.
Figure 1 Portal Access Control Cache Hierarchy
com.ibm.wps.ac.PermissionCollectionCache
Default size: 2000, default lifetime: 10240, usage pattern: regular (admit-threshold).
This cache contains permission collections that can be used for permission checks. It
scales with the number of permissions in the system, i.e. the number of portal resources
and permissions assigned on those. Entries in the cache typically are requested very
frequently during permission checks. An admit-threshold is used to avoid caching rarely
used permissions. You may wish to try different admit-threshold settings to tune this
cache. Entries are never invalidated from the cache. Creating a cache entry is very fast
since all required information is in-memory. A cache entry is small.
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com.ibm.wps.ac.AccessControlUserContextCache
Default size: 8000, default lifetime: 1200, usage pattern: regular.
This cache contains the access control user context objects, a local cache for
permissions assigned to a specific user. If possible all requests against access control
are answered using this information so that access control methods can return very
quickly. This cache scales with the number of active users. For fast portal operation, you
should make sure that the entries for all actively working users fit into the cache,
especially if a user has access to many portal resources. Entries are invalidated from the
cache upon any portal administrative action. Creating a cache entry typically is rather
cheap because most information is in-memory, but can take a while if the required
information cannot be found in other caches. An entry in the cache can be become very
large, depending on the number of resources the user can access.
com.ibm.wps.ac.ProtectedResourceCache
Default size: 5000, default lifetime: 10143, usage pattern: regular.
This cache contains the resources protected by portal access control. The size of this
cache scales with the number of protected resources accessed by the active users in the
system. Entries are read from the cache during every permission call or entitlements call
against access control. Entries are invalidated from this cache during resource deletion,
resource relocation, modification of the resource state (private/shared), modification of
the resource owner, externalization, internalization, and role block change. Creating a
cache entry requires a single-row lookup in the portal database. An entry in the cache is
relatively small.
com.ibm.wps.ac.OwnedResourcesCache
Default size: 5000, default lifetime: 10043, usage pattern: invalidation checking.
This cache maps resource owners (user groups or individual users) to the resources
they own. This cache scales with the number of active users/groups multiplied with the
different ResourceTypes they access. There is one entry in the cache per principal per
resource type per WebSphere Portal domain. Data is read from this cache during many
portal access control requests, if the corresponding entitlements are not already cached
in an entitlements cache. Entries are invalidated from this cache during resource
deletion, modification of the resource owner, externalization, and logout of the user.
Creating a cache entry means executing a multi-row query against the portal database.
An entry in the cache is relatively small.
com.ibm.wps.ac.RolesCache
Default size: 10000, default lifetime: 3630, usage pattern: invalidation checking.
This cache contains the role instances. The size of this cache scales with the number of
active users/groups multiplied by the different ResourceTypes they access. There is one
entry per role instance per principal per resource type per WebSphere Portal domain.
Data is read from the cache during many portal access control requests, if the
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corresponding entitlements are not already cached. Entries are invalidated from this
cache during role mapping creation, role mapping deletion, resource deletion,
externalization, internalization, and logout of the user. Creating a cache entry means
executing at least one, but potentially multiple database queries. An entry in the cache is
relatively small.
com.ibm.wps.ac.ExplicitEntitlementsCache.* and
com.ibm.wps.ac.ChildEntitlementsCache
Default size: 10000, default lifetime: varying (around 10000), usage pattern: invalidation
checking.
These caches contain the permissions of a user or group on a number of resources of
the same ResourceType. There are dedicated caches for the different ResourceTypes.
For
example,
the
cache
for
pages
is
called com.ibm.wps.ac.
ExplicitEntitlementsCache.CONTENT_NODE. All ResourceTypes that are not
specified explicitly will be cached in the default cache. The size of this cache scales with
the number of active users/groups multiplied by the different ResourceTypes valid for
this cache and accessed by the users and groups, either by ‘using’ the resource during
navigating the portal or by portal administration. There is one entry per set of
permissions per WebSphere Portal domain. Entries are read during ‘regular’ access
control requests, during page rendering and, especially, during portal administration. If a
certain resource type is not used, you will see only misses and no other activity on the
corresponding cache. Entries are invalidated from this cache during all access control
modifications and logins. Creating an entry in one of these caches typically can be done
from in-memory information in the lower-level caches. If the required information is not
available multiple database requests might be required to create a cache entry. An entry
into the cache is rather small, but built of multiple objects typically stored in other caches.
com.ibm.wps.ac.ExternalOIDCache
Default size: 10000, default lifetime: 8640, usage pattern: regular.
This cache contains the mapping between the external ObjectIDs of individual protected
resources, for example page or portlet IDs, and the portal access control specific
ObjectIDs stored in the database table PROT_RES. Entries are read from the cache
during many portal access control requests. The size of this cache scales with the
number of protected resources accessed by the active users in the system. Since this
mapping is immutable, this cache is never explicitly invalidated. Creating a cache entry
requires a single row database query. An entry in the cache is fairly small.
com.ibm.wps.ac.groupmanagement.NestedGroupCache /
com.ibm.wps.ac.groupmanagement.GroupCache
Default size: 1000, default lifetime: 3600, usage pattern: regular.
Only one of these two caches is used in a WebSphere Portal installation depending on
your ‘nested groups’ setting. If nested groups are supported, the NestedGroupCache
cache will be used, otherwise the GroupCache is used. The caches contain the nested
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or direct groups to which a user belongs. The size of this cache scales with the number
of active users and the number of virtual portals they access. The cache is accessed
during login into portal, but typically not during regular portal navigation. Its main use
case is during administration of users and user groups. Entries are invalidated from this
cache during login of the user and after user and group administrative changes. Creating
a new cache entry requires queries against the WMM component and then typically
against the user repository. An entry in the cache is medium-sized.
com.ibm.wps.ac.ChildResourcesCache
Default size: 1000, default lifetime: 7200, usage pattern: regular.
This cache contains the resource hierarchy within portal access control. The size of this
cache scales with the number of protected resources accessed by the active users in the
system, like the protected resources cache. This cache does not contain leaf objects in
the access control tree, so the number of entries typically is smaller. The cache is
accessed during most portal access control requests. Entries are invalidated from this
cache during resource deletion, parent change of the resource, modification of the
resource owner, externalization, internalization, and role block change. Creating a cache
entry includes a multi-row query against the portal database. An entry in the cache is
fairly small.
com.ibm.wps.ac.ApplicationRoleOIDCache
Default size: 5000, default lifetime: 7650, usage pattern: regular.
This cache maps application role names to the corresponding object IDs. It scales with
the number of application roles defined in the system. Data is read from the cache
frequently when accessing or administering composite applications. In all other situations
the cache is basically not used at all. Entries are invalidated when application roles are
deleted. There is one entry in the cache per application role per WebSphere Portal
domain, except for the customization domain. Creating a cache entry means reading a
single row of data from the portal database. A cache entry is fairly small.
com.ibm.wps.ac.ApplicationRoleDescriptorCache
Default size: 5000, default lifetime: 8450, usage pattern: regular.
This cache maps the object ID of an application role to its corresponding descriptor
object, which contains the application name, parent application and other information.
The cache scales with the number of application roles defined in the system. Data is
read from the cache frequently when accessing or administering composite applications.
In all other situations the cache is basically not used at all. Creating a cache entry means
reading a single row of data from the portal database. A cache entry is medium-sized.
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com.ibm.wps.ac.ApplicationRolesForPrincipalCache
Default size: 5000, default lifetime: 8760, usage pattern: regular.
This cache maps the available application roles to a portal user. It scales with the
number of active users in the system. Data is read from the cache frequently when
accessing or administering composite applications. In addition this cache is also used as
a lookup for application role information even if no application roles are used. Hence you
will see frequent read access on this cache under all circumstances. Creating a cache
entry is rather expensive. It involves three multi-row queries against three WebSphere
Portal domains. A cache entry is medium-sized.
com.ibm.wps.ac.ContainedRolesCache
Default size: 5000, default lifetime: 8650, usage pattern: regular.
This cache contains the mappings between application roles and the ‘regular’ roles
defined in them. The cache scales with the number of application roles in the system.
There is one entry for every WebSphere Portal domain. Data is read from the cache
frequently when accessing or administering composite applications. In all other situations
the cache is basically not used at all. Creating a cache entry is rather expensive. It
involves two multi-row queries. A cache entry is medium-sized.
com.ibm.wps.ac.ApplicationRoleChildrenCache
Default size: 5000, default lifetime: 8760, usage pattern: regular.
This cache is not used in WebSphere Portal V6.0.
com.ibm.wps.ac.ParentResourceRoleMappingCache and
com.ibm.wps.ac.ResourceRoleMappingCache
Default size: 1000, default lifetime: infinite, usage pattern: regular.
These two caches are used for special access control scenarios and typically are not
accessed during portal processing. Settings of these caches should not be modified
P O R T A L U S E R M A N A G E M E N T
The following caches are used by the portal user management component (PUMA). In so
far they are closely related to the access control caches and caching within WMM.
com.ibm.wps.puma.DN_OID_Cache / com.ibm.wps.puma.OID_DN_Cache
Default size: 1500, default lifetime: infinite, usage pattern: regular.
These two caches contain the mapping between the distinguished name of users and
groups and their internal ObjectID identifier. The size of these caches scales with the
number of active users and groups or users and groups that are used for delegation.
Entries are invalidated from this cache during deletion of a user or group. Creating an
entry requires one database lookup. An entry into the caches is fairly small.
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D A T A S T O R E
The datastore caches contain data read from the portal database. It is not the goal of these
caches to be a complete image of the DB content, but to have frequently-accessed but raw
information available for all other portal components to use.
com.ibm.wps.datastore.services.Identification.OidAndUniqueName.cache
Default size: 5000, default lifetime: infinite, usage pattern: regular.
This cache stores unique names. It is used quite frequently during page rendering and
especially administration of unique names. Page and portlet unique names make up the
biggest part of the cache content. The cache should be large enough to hold entries for
the most frequently used pages and portlets having a unique name associated with
them. Note that not all resources have a unique name associated with them. To
eliminate database lookups the cache size could correspond to the database table
UNIQUE_NAME multiplied by two, to allow for mapping in two directions. Creating a
cache entry involves reading one entry from the portal database. An entry object into the
cache is fairly small.
com.ibm.wps.datastore.PortalIdCache.vpPerLpid.cache
Default size: 1000, default lifetime: infinite, usage pattern: regular.
This cache maps long Virtual Portal object IDs to the corresponding portal internal short
ID. It scales with the number of virtual portals in the system, plus one additional entry. It
is used heavily only if more than one virtual portal exists in the system. Data is read from
the cache during every rendering request then. For optimal caching the size should be
set to the number of Virtual Portals defined in the system. Creating a cache entry
involves one single-row database lookup. An entry object into the cache is fairly small.
com.ibm.wps.datastore.PortalIdCache.explicitLpidPerVP
Default size: 100, default lifetime: infinite, usage pattern: regular.
This cache maps the short object ID for a virtual portal to the corresponding long ID. In
comparison to cache com.ibm.wps.datastore.PortalIdCache.vpPerLpid.cache it stores
the reverse mappings. Hence all other descriptions given above also apply here.
com.ibm.wps.datastore.pageinstance.OIDCache
Default size: 3000, default lifetime: infinite, usage pattern: regular.
This cache stores information on portal pages for fast retrieval during login or page
navigation. It scales with the number of page instances in the system. It is one of the
most frequently used caches and should be large enough to hold all pages that are
frequently accessed by users. Pages are loaded and put into the cache by direct
navigation, creating a link to another page or by working with the page during portal
administration (always including all higher derivation levels). Creating a cache entry
includes one single-row database lookup. An entry to the cache is medium sized. To
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achieve best performance, in terms of cache hit rate, the size should be set to a value so
that all pages defined in the system fit into the cache. This corresponds to the row count
of the database table PAGE_INST.
com.ibm.wps.datastore.pageinstance.DerivationCache
Default size: 3000, default lifetime: infinite, usage pattern: regular.
This cache stores the mappings between pages and their derivation children, or empty
mappings if no such children exist. Like the pageinstance.OIDCache cache this one also
is accessed very frequently during page rendering and administration. Creating a cache
entry involves one multi-row database query. This cache also scales with the number of
pages in the system. Hence, you can use the same sizes for the previous cache and this
one. In most portal usage scenarios the actual size of this cache will be somewhat lower
than with the page instance cache. An average entry in the cache is rather small. Only if
all your pages have long lists of derivation children will the entries become larger. To
achieve best performance, in terms of cache hit rate, the size should be set to a value so
that all pages defined in the system fit into the cache. This corresponds to the row count
of the database table PAGE_INST.
com.ibm.wps.datastore.pageinstance.DynamicNodeCache
Default size: 5, default lifetime: infinite, usage pattern: regular.
This cache stores one list per domain. These lists contain all pages in the corresponding
domain that are flagged as dynamic nodes, i.e. dynamic assembly content nodes can be
added below these pages. Since the number of domains does not grow, the size as well
as other properties of this cache should not be modified. The size of one entry into the
cache ranges from small in a portal with very few dynamic nodes up to medium with
many dynamic nodes in the system.
com.ibm.wps.datastore.services.Identification.SerializedOidString.cache
Default size: 2500, default lifetime: infinite, usage pattern: cascading object types.
This cache stores serialized ObjectIDs used in request parameters or XML Access files.
It contains a subset of all the loaded ObjectIDs in memory. In so far it scales with the
number of ObjectIDs in the system, but not for all of these IDs the serialized version is
requested, hence the actual size is impossible to predict. The cache is used during every
request. Creating a cache entry is rather cheap. Typically all information can be retrieved
in memory, database lookups are scarcely necessary. A cache entry is fairly small.
M O D E L
The model caches can be categorized into two groups: One group of caches is accessed
during every portal request during page rendering. The second group of caches is especially
important for administrative actions. Hence those caches are especially important in those
environments where content and portal administration is done. Most run-time caches have
the name suffix live; the administrative caches have the suffix isolated.
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Figure 29 describes the hierarchy of caches in the model component and depending portal
components. The structure of the picture is identical to figure 28: The vertical axis shows
caches with increasing aggregation of data. The model component only caches data at a
rather high aggregation level. All data cached here hence is rather valuable, reloads can be
expensive if the corresponding data is not available in the lower-level caches. Model caches
are dependent upon the datastore and portal access control caches. The figure only
features the most important caches.
Figure 2 Portal Model Cache Hierarchy
com.ibm.wps.model.factory.SimpleCacheKey
Default size: 2500, default lifetime: infinite, usage pattern: regular.
This cache is a helper cache for other model caches used by the portal model factory. It
contains a small number of entries based on the model types available in portal. In
addition there can be one entry per active user session. The size of this cache might be
adapted to the number of active sessions in one portal JVM. Re-creating a cache entry is
a rather cheap operation since it usually can be accomplished in memory. A cache entry
is a small object.
com.ibm.wps.model.content.impl.ResourceCache
Default size: 5000, default lifetime: 5600, usage pattern: regular.
This cache contains aggregated pages. In contrast to the data store page instance
cache this cache contains the complete models of pages and their content, i.e. the
portlets and containers on them. The page instance cache rather holds the raw page
data. This cache scales with the number of pages defined in your portal and the different
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sets of access control rights on these pages. This cache contains very ‘valuable’
information; it utilizes several other caches, for example, page instance and access
control caches, to build its data. Hence creating a cache entry usually only requires in-
memory information, but can also lead to many database queries. The size of an entry in
the cache depends on the complexity of the pages, but typically the objects are medium-
sized, since they are usually made of references to other cached data. The cache should
be large enough to hold the most frequently accessed pages multiplied with the number
of different access control settings on these pages. Increasing the cache lifetime can be
useful if page definitions do not change often in your environment.
Example: A portal has 500 pages and all users have the same permissions on these. In
addition there are another 50 pages; two groups of users have different access rights on
these pages. In this case a maximum of 600 entries would be in the cache.
com.ibm.wsp.mode.content.impl.TopologyCache
Default size: 10000, default lifetime: 5700, usage pattern: regular.
This cache contains portal topology information, i.e. portal navigation elements being
composed of navigation nodes and their sorted, access control-filtered children.
Topology elements undergo several processing steps from first loading from the
database until finally being added to the cache. This cache only contains the completely
processed topology entities. This cache is explicitly used during login and whenever a
user navigates to a part of the portal where he has not been before during the same
session. If a cache entry is not found, a private copy is created that is then further
processed. Once the private copy is completely processed -that does not happen for all
navigation nodes- it is added to the cache. If a user finds an entry in the cache a
reference is copied into his private topology model and additional cache accesses are no
longer necessary. Hence there is only one cache hit (or miss) per user and navigation
node. The cache scales with the number of navigation nodes and the number of different
sets of permissions on these and, possibly, the derivation chain (children and parents) a
page belongs to. Entries in this cache are expensive to create; they rely on other cached
information, like the access control caches and the page instance cache. The entries in
the cache are medium-sized, being mainly some lists of references to other cached data.
The cache should be sized in a way such the most important pages multiplied with all the
different sets of permissions that exist on theses page can be stored.
com.ibm.wps.model.factory.ContentModelCache.live
Default size: 1000, default lifetime: infinite, usage pattern: regular.
This run-time cache contains the content models for portal users. There is one entry per
active portal user. The cache should be large enough to hold all models for these users.
An entry in the cache has the maximum lifetime of the corresponding user session, i.e.
entries are removed at the end of the session. Creating a cache entry can be very
expensive. Typically all required information is in memory, but accessing the database,
also many times, might be necessary if underlying information is also no longer cached.
Furthermore the number of pages summarized in the model can be very large which
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also adds to the time it takes to rebuild a cache entry. Building the content model is done
incrementally as required for the current request; the model is not built at once.
Depending on the size of the model also the memory requirements vary. The more
pages a user can access and has accessed already during the current session the larger
the cache entry, ranging from medium to very large. A cache entry typically is composed
of references to other cached and shared objects. Hence an entry size is not made up by
the number of page and all subordinate objects but only contains references to these.
com.ibm.wps.model.factory.ContentModelCache.isolated
Default size: 1000, default lifetime: infinite, usage pattern: regular.
This cache contains the administrative content models. There is one entry for every user
doing administrative work at a certain point in time. In so far the number of entries in this
cache typically is much lower than in the other cache. But for this cache you should
make sure that no cache entries of active users are evicted. Compare with the content
model run-time cache for all other information.
com.ibm.wps.model.factory.NavigationSelectionModelCache.live
Default size: 1000, default lifetime: infinite, usage pattern: regular.
This run-time cache contains the navigation selection models used by portal users.
There is one entry per user session. The cache should be large enough to hold all these
models for the active users. An entry in the cache has the maximum lifetime of the
corresponding user session, i.e. entries are removed at the end of the session. Creating
a cache entry is less expensive than creating a content model cache entry. Typically all
required information is in memory, but accessing the database might be necessary. In
comparison to the content model cache creating an entry for the navigation selection
model cache is much cheaper. In addition also the in-memory size of elements in this
cache is much smaller since this type of model references fewer objects.
com.ibm.wps.model.factory.NavigationSelectionModelCache.isolated
Default size: 1000, default lifetime: infinite, usage pattern: regular.
This cache contains navigation selection models used by administrative users. The
details given for the administrative content model cache also apply here.
com.ibm.wps.model.factory.URLMappingCache.live
Default size: 50, default lifetime: infinite, usage pattern: regular.
This cache is the run-time model cache for the URL mappings defined in your portal
installation. It should be large enough to hold all URL mappings defined in your system.
Creating an entry to the cache involves reading one entry from the portal database. A
cache entry is fairly small in size.
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com.ibm.wps.model.factory.URLMappingCache.isolated
Default size: 50, default lifetime: infinite, usage pattern: regular.
This cache is the administration cache for URL mappings. The details given for the other
isolated caches also apply here.
com.ibm.wps.model.factory.MultiModelCache.live
Default size: 50, default lifetime: infinite, usage pattern: regular.
This cache contains run-time models for several different resource types in WebSphere
Portal, for example clients, supported markups and languages. One entry, for example,
is a list containing all supported markups. Those resources typically remain stable for a
long time, hence you should mostly experience read accesses to this cache. Creating a
cache entry involves reading the corresponding data from the database. An entry can be
fairly large, but the number is very low so that the total size of this cache is negligible.
com.ibm.wps.model.factory.MultiModelCache.isolated
Default size: 1000, default lifetime: infinite, usage pattern: regular.
This cache contains the administrative models for several portal resource types.
Typically this cache is empty and not used, because administration on those resource
types is a rare event. There is one entry for every user doing administration on any of the
resource types that are stored in the cache. The creation behavior and size are similar to
the run-time cache.
com.ibm.wps.model.factory.NavigationModelCache.live
Default size: 2, default lifetime: infinite.
This cache is not used in WebSphere Portal V6.0 and hence disabled. Changing any of
its properties does not have any effect.
com.ibm.wps.model.factory.NavigationModelCache.isolated
Default size: 2, default lifetime: infinite.
This cache is not used WebSphere Portal V6.0 and hence disabled. Changing any of its
properties does not have any effect.
com.ibm.wps.model.content.impl.DynamicLoadCache
Default size: 4, default lifetime: 600.
This cache is not used WebSphere Portal V6.0 and hence disabled. Changing any of its
properties does not have any effect.
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com.ibm.wps.model.impl.RuntimeClientMap.userAgent2client
Default size: 1000, default lifetime: infinite, usage pattern: regular.
This cache maps user agent strings, i.e. the identification strings sent by browsers in the
HTTP header, to client profiles. These profiles basically correspond to CC/PP profiles.
Hence the cache scales with the number of browser identification strings. Data from this
cache is accessed during every request. Creating a cache entry is very cheap since the
profile information is in memory already. An entry in the cache hence is fairly small since
already existing data is referenced.
U R L M A P P I N G S
The following caches contain data on portal URL mappings. Be sure to size the caches in a
way such that these are large enough to hold all defined URL mappings in your system.
wps.mappingurl.ContextsCache
Default size: 500, default lifetime: infinite, usage pattern: regular.
This cache contains URL mapping contexts. It scales with the number of mapping
contexts defined in the system. This cache is used if a URL mapping cannot be resolved
using the lookup cache. Creating an entry involves reading a mapping entry from the
database. An entry in the cache is medium-sized.
wps.mappingurl.LookupCache
Default size: 600, default lifetime: infinite, usage pattern: regular.
This cache is used as a final lookup cache for the computed mappings between (a
hierarchy of) URL mappings and a WebSphere Portal resource. It is accessed during
every request when analyzing the incoming URL for being a URL mapping. The size of
this cache should be the number of all mappings. Creating a cache entry typically is
cheap because the information often s in memory. An entry in the cache is rather small.
V I R T U A L P O R T A L S
The following group of caches is only relevant if you have defined additional virtual portals in
your system. In all other situations it is safe to set the size of these caches to one and the
lifetime to infinite.
com.ibm.wps.services.vpmapping.VirtualPortalIDToRealmCache
Default size: 120, default lifetime: 3600, usage pattern: regular.
This cache stores the realm information for virtual portals. One realm can contain several
virtual portals, but one virtual portal can only be part of a single realm. As a
consequence, the optimum size of this cache is the number of virtual portals defined in
your environment. You may increase the lifetime for better performance if your setup of
virtual portals changes infrequently. If you only use the default portal and no additional
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virtual portal, you will see one entry in the cache and only little traffic on the cache.
Creating a new cache entry requires one database query. An entry into the cache is
fairly small.
com.ibm.wps.services.vpmapping.VirtualPortalIDToURLCache
Default size: 120, default lifetime: 3600, usage pattern: regular.
This cache maps virtual portal IDs to their respective LPID. The LPID usually is used to
create URLs for a specific virtual portal. Since the number of LPIDs is equal to the
number of virtual portal IDs, the optimum size of this cache is the number of Virtual
Portals defined in your environment. You may increase the life time for better
performance if your setup of virtual portals changes infrequently. If you only use the
default portal and no additional virtual portal, you will see one entry in the cache and only
little traffic on the cache.
com.ibm.wps.services.vpmapping.URLToVirtualPortalIDCache
Default size: 120, default lifetime: 3600, usage pattern: regular.
This cache maps LPID values to virtual portal IDs. LPIDs are encoded in a URL that
points to a certain virtual portal. Therefore the number of LPIDs is equal to the number of
virtual portal IDs. Accordingly the optimum size of this cache is the number of virtual
portals defined in your environment. You may increase the lifetime for better
performance if your setup of virtual portals changes infrequently. If you only use the
default portal and no additional virtual portal, you will see one entry in the cache and only
little traffic on the cache.
W S R P
All WSRP caches are only accessed if the portal is used as either a WSRP consumer or
producer. Each of the caches is used on either side of the WSRP communication, but not on
both sides. Most of the WSRP caches are used and read during every WSRP request,
either displaying a page with a provided portlet on it, or administering WSRP properties.
Exceptions to this general rule are noted below.
wsrp.cache.portletdescription
Default size: 500, default lifetime: 3600, usage pattern: regular.
This cache contains the portlet descriptions delivered by producers. These descriptions
could be considered meta information on the provided portlets, like languages and
descriptions. It is used on the producer side. The cache scales with the number of
remote portlets provided by the producer. Increasing the default lifetime can improve
performance if portlet descriptions of the provided portlets change infrequently.
Rebuilding cache entries is rather expensive. It includes loading data from the database
with several calls. The cached entries are rather expensive in terms of memory usage.
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wsrp.cache.servicedescription
Default size: 150, default lifetime: infinite, usage pattern: regular
This cache contains service descriptions of WSRP producers. It is used on the
consumer side. It scales with the number of WSRP producers integrated into the
consuming portals; there is exactly one description per producer. The service description
is generated using all the portlet descriptions from the producer portal plus some
additional data. Hence a service description can be large in terms of memory
requirements. Rebuilding the description requires several roundtrips and is an expensive
operation. Cache entries are rebuilt if a user clicks the ‘Browse’ button in the WSRP
administration portlets. This leads to a refresh of all service descriptions of all producers.
This cache is only used during WSRP administration.
wsrp.cache.portlet.instance
Default size: 2500, default lifetime: 3600, usage pattern: regular.
This cache contains the proxy portlet instances on the WSRP consumer side and is only
used there. It scales with the number of integrated remote portlets multiplied with the
number of users having their own customizations of portlet preferences for these remote
portlets (portlet settings for legacy portlets respectively). Creating an entry for the cache
involves one multi-line database query. The size of a cached entry depends on the
number of parameters associated with the portlet. Hence the size ranges from small to
fairly large.
wsrp.cache.producer.user
Default size: 5000, default lifetime: 3600, usage pattern: multiple object types.
This cache contains the descriptor of the producer and context information between
users and producers. It is used on the consumer side. It scales with the total number of
active users accessing remote portlets of these producers, i.e. as a maximum the
number of producers multiplied with the number of active users accessing them plus the
number of producers. Recreating cache entry is fairly expensive. It involves some DB
queries and in-memory operations. Therefore the session timeout should not be higher
than the lifetime of entries in the cache. Cache entries are explicitly invalidated during
user session destruction.
wsrp.cache.portlet.window
Default size: 2500, default lifetime: infinite, usage pattern: regular.
This cache contains a WSRP specific wrapper on a WebSphere Portal portlet entity
object. It is used on the producer side. It scales with the number of provided portlets and
the number of occurrences of these portlets on consumer pages. Recreating cache
entries is rather cheap and typically only includes in-memory operations. An entry into
this cache is fairly small. This cache is accessed very during a request.
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wsrp.producer.portletpool.pops
Default size: 1000, default lifetime: infinite, usage pattern: cascading object types.
This cache stores the Producer Offered Portlets and hence scales with their number.
The number of entries in this cache is identical to the number of entries in the
portletdescription cache. The WSRP object model data is stored in here, though. Offered
portlets are first looked up in this cache and, if the lookup is not successful, the in the
ccps cache (see below). Reloading cache entries involves one query against the
database. Cached entries are rather small.
wsrp.producer.portletpool.ccps
Default size: 1000, default lifetime: infinite, usage pattern: regular.
This cache stores the client configure portlets. It is used on the producer side. It scales
with the number of provided portlets and the number of remote users having
personalized those (Consumer Configured Portlets); hence the maximum would be the
number of provided portlets multiplied by the number of remote users accessing the
producer. Reloading cache entries involves one query against the database. Cached
entries are rather small.
D Y N A M I C A S S E M B L Y
/
P R O C E S S I N T E G R A T I O N
The following caches are used when dynamic UI functionality, often together with
WebSphere Process Server integration are used.
processintegration.PendingTasksCache
Default size: 2500, default lifetime: infinite, usage pattern: regular.
This cache contains the pending process tasks in the scope of a user. The size of this
cache scales with the number of users concurrently using process integration
functionality. Each cache entry consists of a complete set of pending process tasks for a
given user and therefore can be fairly large in memory. Reloading a cache entry involves
accessing the Human Task Manager via an EJB call. The cache is always accessed
when the PendingTasksTag is used in a portlet JSP.
You should also configure the setting processintegration.pendingtasks.lifetime in
ConfigServices.properties which defaults to a value of 30 seconds. This setting
describes the interval at which a process engine is queried for pending tasks of a user
and the cache entries are updated.
wp.te.transformationAssociationCache
Default size: 500, default lifetime: infinite, usage pattern: regular.
This cache contains transformation extension nodes. So typically there are only few
entries in the cache. There is typically one access to the cache per request. Building an
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entry to the cache involves one database query. One entry is fairly small. Typically there
is no need to modify the settings for this cache.
P O L I C Y
The WebSphere Portal policy manager uses the following caches.
com.ibm.wps.policy.services.PolicyCacheManager
Default size: 1000, default lifetime: 7780, usage pattern: regular.
This cache stores the policies. Out of the box portal comes with twelve theme policies
and one mail policy, each of them being one entry into the cache. Hence the maximum
number of cache entries depends on your system and the number of custom policies.
This cache is accessed fairly often, if you use policies at all. The WebSphere Portal V6.0
default theme uses policies and query this cache during every request, but it is possible
to create themes that do not use policies at all. Furthermore when opening mails the
cache is accessed. Creating a cache entry involves reading data from a database. An
entry into the cache is fairly small.
com.ibm.wps.policy.services.UserPolicyNodeCacheManager
Default size: 2500, default lifetime: 600, usage pattern: regular.
This cache stores connections between a policy and a policy target, for example a user
distinguished name. Theme policies do not use targets, hence there is no cache entry
based on these policies. The out-of-the-box mail policy uses the user as target. Hence
there is at least one entry for every user accessing the CPP mail portlet. The size of a
cache entry depends on the size of the target object. For a distinguished name a cache
entry is fairly small.
C O L L A B O R A T I O N S E R V I C E S
All of the following caches are used by the DEPP portlets and some services around these
portlets. In so far the caches are not used if the DEPP portlets are not utilized in the portal
system. These caches store credential information needed for the backend servers, server
information for these servers and user information that would otherwise require LDAP
lookups.
com.lotus.cs.services.directory.ldap.BasicLDAPDirectoryService.server
Default size: 50, default lifetime: infinite, usage pattern: regular.
This cache stores mail server information. In so far it scales with the number of different
mail servers used in the environment. It is accessed whenever a mail server is
accessed. Creating a cache entry requires one LDAP search. An entry in the cache is
fairly small.
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com.lotus.cs.services.directory.ldap.BasicLDAPDirectoryService.user
Default size: 2000, default lifetime: 10780, usage pattern: regular.
This cache stores user-specific information read from the LDAP. It scales with the
number of users working with DEPP portlets. The cache is accessed during rendering a
DEPP portlet, whenever those need user information. This could be multiple times per
page reload. In addition the cache is accessed whenever a mail server is accessed.
Creating a cache entry is fairly expensive and can involve multiple LDAP lookups. An
entry into the cache is medium-sized.
com.lotus.cs.services.directory.wmm.WMMDirectoryService
Default size: 4000, default lifetime: 10980, usage pattern: regular.
This cache stores user-specific information read from the LDAP and WMM. Entries in
this cache represent a more complete set of data stored in the LDAP than is available in
other parts of WebSphere Portal. The cache scales with the number of users working
with DEPP portlets. The cache is accessed during rendering a DEPP portlet, whenever
those need user information. This could be multiple times per page reload. In addition
the cache is accessed whenever a mail server is accessed. Creating a cache entry is
fairly expensive and can involve multiple LDAP lookups. An entry into the cache is
medium-sized.
com.lotus.cs.services.UserEnvironment
Default size: 2000, default lifetime: 10880, usage pattern: regular.
This cache stores user-specific information. Entries represent a compilation of credential
information for one user to different LDAP directories and details which data on the given
user can be found in which directory. For example, the general info may be stored in one
directory, but the mail server and file may be in another. The cache scales with the
number of users working with DEPP portlets. The cache is accessed whenever a DEPP
portlet is accessed. Creating a cache entry can be fairly expensive since multiple
resources might be queried. An entry to the cache is medium-sized.
com.lotus.cs.services.domino.DominoService
Default size: 2000, default lifetime: 11080, usage pattern: regular.
This cache stores user-specific Domino information. It is used for awareness functions. It
scales with the number of users working with the corresponding function. The cache is
accessed whenever awareness functions are requested during page rendering. Creating
a cache entry is cheap and simply involves creating a new Domino session. An entry to
the cache is medium-sized.
M I S C E L L A N E O U S
This group of caches does not fit in any of the other categories.
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com.ibm.wps.pe.portletentity
Default size: 10000, default lifetime: 5800, usage pattern: regular.
This cache contains configuration for portlets on pages (portlet instances, shared and
per-user). It scales with the number of pages defined in your portal, the number of
portlets on the pages and the number of portlet instances that have been personalized
by users. The cache is accessed many times during portal page rendering. In so far it is
important that the most relevant portlet entities are cached. Creating a cache entry
involves a single database lookup. An entry into the cache is fairly small.
Example: In a portal with 500 pages and on average three portlets per page, the optimal
cache size would be 1500 to store all possible portlet entity data in the cache, if users
are not allowed to personalize the portlets. If the portal has 100 users that are logged in
concurrently and these users have personalized 50 portlets on average, the required
cache size to cache all data would be 6500. These numbers give the maximum number
of entries to the cache. Typically for this cache it is not required to have all portlet entities
in memory, because most users will not view all pages so that not all personalized data
must be loaded. The most frequently accessed un-personalized portlet entities should fit
into the cache, though.
com.ibm.wps.services.cache.cachedstate.CachedStateServiceCache.cache
Default size: 50000, default lifetime: 7200, usage pattern: typically regular.
This cache stores session-scoped data in the portal context and is used by various
portal components. This cache scales linearly with the number of active sessions in the
system and the number of portal components using this cache for data retrieval. The
usage pattern, access times, entry creation costs and entry memory sizes depend on
the portal component using this cache and cannot be stated in general.
wp.xml.configitems
Default size: 1000, default lifetime: infinite, usage pattern: regular.
This cache stores XML Access configuration items. It is used only during XML Access
processing. The entries resemble references between nodes in the XML Access
document. Especially when working with complex XML files, usually used for imports or
Release Builder processes, it can be beneficial to increase the cache size. The cache
will be cleared after XML processing is completed. Reloading a cache entry involves one
database query. Entries in the cache are medium-sized.
PortletMenuCache
Default size: 200, default lifetime: infinite, usage pattern: regular.
This cache contains portlet menu trees for all portlets that define their portal menu as
global, meaning identical for all users. The portal functionality that utilizes this cache is
deprecated with WebSphere Portal Version V6.0.
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RegistryService
Default size: 32, default lifetime: infinite, usage pattern: regular.
This cache is used in a cluster for portals to notify the other cluster members when one
of the registries needs to be reloaded due to administrative action. It should never be
disabled or set to shared=false.
com.ibm.workplace.searchmenu.helper.SearchMenuCacheHelper
Default size: 2500, default lifetime: 3730, usage pattern: regular.
This cache stores a variety of information having to do with the search scopes menu,
located at the top of the theme, left to the search box. There are six rather small cache
entries per user. Hence the cache scales directly with the number of users. There are no
invalidations from the cache, but after login a user will always get fresh data from the
cache via a coupling between the cache and the user session. The cache will be
accessed on every subsequent user request for building the search bar. If the search bar
is not used, the cache will not be used, either. Rebuilding the cache is fairly inexpensive,
but it does require some calls to the search engine backend to get the required data.
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Example Scenarios
This section describes some example usage scenarios along with descriptions of possible
cache settings and suggested cache sizes. This discussion may be useful as starting point
for the caches in your environment.
G E N E R A L C O M M E N T S
Most portal caches fall into one of four groups:
1. Caches where the number of entries scales with the number of active users. For
example, the access control user context cache (com.ibm.wps.ac.
AccessControlUserContextCache) falls into this category.
2. Caches where the number of entries scales with the number of users using a
specific function. For example, the cache com.lotus.cs.services.
directory.ldap.BasicLDAPDirectoryService.user falls into this
category.
3. Caches which scale with the number of pages being visited. The resource cache
(com.ibm.wps.model.content.impl.ResourceCache) is an example of
this type.
4. Caches which scale based on the growth of some other resource, such as URL
mappings, which are stored in the cache com.ibm.wps.model.factory.
URLMappingCache.live.
Those that scale on portal resources should have lifetimes and sizes based on the number
of portal resources in the system and how frequently users access these resources. The
other caches depend upon usage scenarios such as those described in this section.
Most caches have a lifetime associated with them because the cached content might
change over time. For example, access control information could be changed via user
administration in the administrative portlets, XML Access or the WebSphere Portal scripting
interface. All code that uses caches within WebSphere Portal is implemented in a way such
that cache entries that are no longer valid are removed from the cache if the corresponding
information has been changed or deleted. The lifetime therefore is used for three reasons:
ꢀ Expired cache entries can be removed to free up memory.
ꢀ There are rare race conditions in cluster setups so that invalidation events are
processed correctly but the cache still reflects wrong data.
ꢀ Updates within external systems, like an external access control system, will never
become visible.
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If there is no or very little administration on your system and you have free memory in the
Java heap available, it is safe to increase the lifetime of cache content to save the additional
workload for reloading cached data.
Now we shall consider some recommendations for specific scenarios.
S M A L L N U M B E R O F P A G E S A N D S M A L L N U M B E R O F U S E R S
In this scenario a portal only has a limited number of pages and users accessing them. For
example, there might be 200 pages in the system and up to a few hundred users working
with the portal simultaneously. You will find portals of this kind often during development and
testing or in smaller portal production systems.
For portals of this size and usage the default cache values typically are good. Hence only
small modifications to the defaults given above should be required. Nevertheless you should
be careful not to translate those cache settings directly into production for larger user
communities.
S M A L L N U M B E R O F P A G E S A N D L A R G E N U M B E R O F U S E R S
In this scenario a portal only offers a rather small number of pages to the user. Overall there
might be again only a few hundred pages, maybe with different access rights on them so
that users might see only subsets of the pages. But in this scenario there are thousands of
users accessing the system at the same time. In other words, thousands of users have
active sessions.
Properties of caches that store information on pages typically do not need to be modified in
this scenario. But all caches that store user-dependant information might be a problem.
Assume you have 2000 active users in your system. Per-user caches being sized to only
1000 entries will operate at their upper limit nearly all of the time and constant re-calculating
or re-loading of data from the portal database will the consequence. You should size the
user-dependent caches in a way such that enough entries for the number of currently active
users can remain in memory. We define the number of ‘currently active users’ as those who
have a session and still issue requests against WebSphere Portal. By contrast there are
passive users who still have a session, but no longer issue requests and have forgotten to
log out or simply went away from the screen and let the session time out.
We increased the sizes of the following nine caches in our measurement environments in
such a way that the data of all concurrent users fits into the caches.
ꢀ com.ibm.wps.model.factory.ContentModelCache.live
ꢀ com.ibm.wps.ac.ExplicitEntitlements Cache.USER_GROUP
ꢀ com.ibm.wps.model.factory.NavigationSelectionModelCache.live
ꢀ com.ibm.wps.datastore.services.Identification.
SerializedOidString.cache
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ꢀ com.ibm.wps.puma.OID_User_Cache
ꢀ com.ibm.wps.puma.DN_User_Cache
ꢀ com.ibm.wps.puma.OID_DN_Cache
ꢀ com.ibm.wps.puma.DN_Group_Cache
ꢀ com.ibm.wps.puma.OID_Group_Cache
We increased the lifetimes of all caches to at least one hour.
P O R T A L S W I T H L O N G S E S S I O N T I M E O U T S
If the session timeout has a high value, it is likely that there will be a large number of users
who still have sessions with the portal, but who have not interacted with the site for a
significant period of time. These users are known as passive users, and they can cause
some special performance challenges.
In this situation the number of sessions can be much larger. But typically many of these
sessions are ‘passive’. It is typically not necessary to have all information in memory for all
these users when they leave their desk but not the portal, for example during lunch. To find
proper sizes for the portal caches you need a good understanding on the behavior of your
users. Users who have not worked with the portal for more than an hour typically will accept
response times of two or three seconds for their first request after such a long break,
whereas users who work with the portal rather constantly do not want to see their data being
evicted from caches.
For this scenario it is hard to give precise cache size recommendations. The values simply
depend too much on your portal usage scenario. You have to monitor your system and
users closely to determine good values.
P O R T A L S W I T H M A N Y P A G E S
Portals in this group have several thousand pages that are available for larger groups of
users and therefore are potentially accessed quite frequently. We do not count installations
with many customized pages (sometimes known as ‘implicit derivations’) to this group
because these are private resources and are loaded for the current user only. Private data is
not added to the shared portal caches.
For example, your portal could have 5000 pages in total. Half of those are available to all
users; on the other half there are several user groups who have view rights, other have
manage right on those pages. In this case you typically do not want to have all pages and all
corresponding information in memory at all times. But you want to make sure that all
frequently accessed data is in memory. Typically not all portal pages are accessed equally
frequently. The better your page view statistics are, the easier it is for you to tune the portal
caches.
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We increased the sizes of the following caches in our measurement environments so that all
frequently-accessed pages, which depend on our scenario, can be cached.
ꢀ com.ibm.wps.datastore.pageinstance.OIDCache
ꢀ com.ibm.wps.datastore.pageinstance.DerivationCache
ꢀ com.ibm.wps.model.factory.ContentModelCache
ꢀ com.ibm.wps.model.factory.NavigationSelectionModelCache
ꢀ com.ibm.wps.ac.PermissionCollectionCache
ꢀ com.ibm.wps.ac.ProtectedResourceCache
ꢀ com.ibm.wps.ac.ExplicitEntitlementsCache.USER_GROUP
ꢀ com.ibm.wps.datastore.services.Identification.
SerializedOidString
We increased the lifetimes of all caches to at least one hour.
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10
WEBCONTENTMANAGEMENTCACHES
In the preceding chapter we described the specific values we modified for the Web Content
Management (WCM) caches in our environments. This chapter describes the Web Content
Management caches and the general parameters for those caches.
WCM Cache Instances
With WebSphere Portal V6.1, the WCM caches are managed via the WebSphere
Application Server administrative console under Resources > Cache instances > Object
cache instances.
W C M I T E M C A C H I N G
services/cache/iwk/strategy – WCM Item caching
Default size: 2000, default lifetime: infinite, usage pattern: regular.
This cache stores internal WCM items. Any WCM item read from the database will first
check this cache. WCM items cover Content, Workflow, Workflow Stages, Workflow
actions, Taxonomies, Categories, Authoring Templates, Presentation Templates, Sites,
Siteareas, and all Library Components. The cache entry will be updated or cleared when
its corresponding WCM Item is updated or deleted.
W C M S U M M A R Y
services/cache/iwk/objectsummary – WCM Summary
Default size: 2000, default lifetime: infinite, usage pattern: regular.
This cache stores summaries of WCM Items. The summaries are used to display in lists
in the authoring portlet or used internally in the WCM API to calculate WCM Item
Document IDs used for Iterators. The cache entry will be cleared when a WCM Item is
updated that will affect this summary.
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W C M B A S I C C A C H I N G
services/cache/iwk/module
Default size: 2000, default lifetime: infinite, usage pattern: regular.
This cache is used for WCM Basic caching. See the InfoCenter on setting up Basic
caching. The Basic cache stores the entire response. The key is based only on the URL
so all users will see the same response.
A D V A N C E D A N D R E S O U R C E S
services/cache/iwk/processing – Advanced and Resources
Default size: 2000, default lifetime: 1 month (configurable), usage pattern: regular.
This cache stores the binary MIME for file and image resources in WCM. The maximum
size of resources to store is set in the WCMConfigService.properties file as the property
resourceserver.maxCacheObjectSize (in kb). Resources over this size are not cached
and are streamed directly to the response. The expiry is set in the same file as:
resourceserver.cacheExpiryDate. The cache entry will be cleared when that resource is
updated.
This cache also stores page data if WCM Advanced caching is enabled. See the
InfoCenter for enabling WCM Advanced caching. The processing cache stores
advanced caches for the following types:
•
•
•
•
Site: Similar to “Basic” Caching except that “Connect Tags” are processed each time.
User: Stores a copy of an item in the cache for each user
Secured: Users that belong to the same groups will access the same cached items
Personalized: Users who have selected the same personalization categories and
keywords, and who belong to the same Group, will access the same cached items
NOTE that the ‘session’ option for Advanced caching is not stored in the processing
cache, but the ‘session’ cache.
S E S S I O N C A C H E
services/cache/iwk/session - Session
Default size: 2000, default lifetime: infinite, usage pattern: regular.
This cache stores the page data for when session advanced caching is enabled. See the
InfoCenter for enabling WCM Advanced caching.
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M E N U
services/cache/iwk/menu - Menu
Default size: 2000, default lifetime: infinite, usage pattern: regular.
This cache stores WCM Menu entries. An entry comprises of the Content IDs associated
with a particular menu. The entries are retrieved and cached without applying security.
Whenever a user needs that menu’s results, their specific security will then be applied to
the cached results. A dynamic menu, which is one that is affected by the current user’s
context (e.g. based on categories in a users profile) will store a separate cache entry for
each different context. The cache entry will be cleared when a WCM Item is updated that
will affect this menu.
N A V I G A T O R
services/cache/iwk/nav Navigator
Default size: 2000, default lifetime: infinite, usage pattern: regular.
This cache stores parent to child relationships that comprise a WCM navigator. A
complex navigator might have multiple parent to child relationships (e.g. if siblings are
included). The navigator entry is made up of the IDs of the parent and children. This
cache will be cleared upon any WCM Item update in the system.
A B S O L U T E P A T H
services/cache/iwk/abspath – Absolute path
Default size: 5000, default lifetime: infinite, usage pattern: regular.
This cache stores JCR path to id relationships. The cache entry will be cleared when a
WCM Item is updated that will affect it.
M I S S E D I T E M S
services/cache/iwk/missed – Missed Items
Default size: 5000, default lifetime: infinite, usage pattern: regular.
This cache stores JCR paths that does not exist. This is used primarily for multi locale
solutions to determine if items of other locales exist or not. The cache entry will be
cleared when a WCM Item is updated that will affect it.
L I B R A R Y
services/cache/iwk/global - Library
Default size: 2000, default lifetime: infinite, usage pattern: regular.
This cache contains a lookup for library id, name and path to the library object. This is
pre-populated up to the cache size at Portal startup.
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L I B R A R Y P A R E N T
services/cache/iwk/libparent – Library Parent
Default size: 2000, default lifetime: infinite, usage pattern: regular.
This cache stores a list of all children library ids to a given parent id. Introduced for
Quickr to group libraries within a teamspace together.
D R A F T S U M M A R Y
Services/cache/iwk/draftSummary – Draft Summary
Default size: 2000, default lifetime: infinite, usage pattern: regular.
This cache stores the identity of the draft summary to the identity of the draft WCM Item.
U S E R C A C H E
User cache
Size is fixed to 2000. default is disabled.
This cache operates using a Least Recently Used algorithm. It is not shared across
nodes in the cluster and it does not use dynacache. It does not update when LDAP
changes. It is disabled by default but can be enabled through setting:
user.cache.enabled=true
in WCMConfigService.properties. Need to run a module called MemberCacheManager
or restart server. To enable the module, add to WCMConfigService.properties
connect.businesslogic.module.template.class=com.presence.connect.wmmcomms
connect.businesslogic.module.template.remoteaccess=true
connect.businesslogic.module.template.autoload=false
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Appendix A. References
WebSphere Portal Information Center:
The Tuning section of the WebSphere Application Server Information Center located at:
Redbook “WebSphere Application Server V6.1 on the Solaris 10 Operation System” located at:
WebSphere Portal Benchmark Results:
Contact WPLC Performance team.
DB2 Information Center:
Oracle Information Center:
The ROLTP factors for IBM pSeries Servers™ can be found at
For additional performance-related information, consult the following resources:
ꢀ WebSphere Application Server Performance information:
ꢀ Recommended reading list: J2EE and WebSphere Application Server
ꢀ WebSphere Application Server Development Best Practices for Performance and
Scalability:
ꢀ Diagnosing Performance Problems for WebSphere Portal 5.1 (though this document
was written for WebSphere Portal 5.1, the lessons apply to WebSphere Portal 6.1 as
well):
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Appendix B. Credits
Thanks to the following team members of the WebSphere Portal Performance Team for
contributing to this document.
Mark Alkins, Manager
Lee Backstrom, Document Coordinator
Andrew Citron
Nathan Cook
Sabine Forkel
Uwe Haller
Shibi John
Klaus Nossek
Kyung Lee
Denny Pichardo, Technical Lead
Martin Presler-Marshall
Terence Walker
Laura Yen, Document Coordinator
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