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TOP TEN WAYS TO SPEEDUP YOUR LIFERAYDEPLOYMENT

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TOP TEN WAYS TO SPEEDUP YOUR LIFERAYDEPLOYMENT Powered By Docstoc
					TOP TEN WAYS TO SPEED
   UP YOUR LIFERAY
     DEPLOYMENT
                     Copyright © 2000 ­ 2009 Liferay, Inc.
                              All Rights Reserved.
    No material may be reproduced electronically or in print, duplicated,
   copied, sold, resold, or otherwise exploited for any commercial purpose
                without express written consent of Liferay, Inc.


                                                                             Rich Sezov
                                                                             Knowledge Manager
                                                                             Liferay, Inc.
                         Liferay Portal: Open Source and
                         Tweakable
As an infrastructure portal, Liferay Portal can support over 3300 concurrent users
on a single server with mean login times under ½ a second and maximum
throughput of 79+ logins per second.
In collaboration and social networking scenarios, each physical server supports
over 1300 concurrent users at average transaction times of under 800ms.
Liferay Portal’s WCM scales to beyond 150,000 concurrent users on a single
Liferay Portal server with average transaction times under 50ms and 35% CPU
utilization.
Given sufficient database resources and efficient load balancing, Liferay Portal
can scale linearly as one adds additional servers to a cluster.
How do I get Liferay to do that?!?
Top Ten Ways to Speed Up Your Liferay Deployment
                Number 10:


Flood the data center with gamma radiation and then
 make the server angry by rebooting it over and over
                       again.
                        Number 10: Adjust the server's thread
                        pool and JDBC connection pool.
Unfortunately, there's no magic number for this: it must be tuned based on
usage.
By default, Liferay is configured for a maximum of 100 database connections.
For Tomcat, a good number is between 200 and 400 threads in the thread pool.
YMMV: use a profiler and tune to the right number.
                Number 9:


Detach Jon Stewart's mouth from the network router.
                          Number 9: Turn off unused servlet
                          filters.
Servlet filters were introduced in the servlet specification 2.3.
They dynamically intercept requests and transform them in some way.
Liferay contains 17 servlet filters.
Chances are, you don't need them all, so turn off the ones you aren't using!
                          Servlet Filters to Turn Off

SSO CAS Filter: Are you using CAS for Single Sign-On? If not, you don't need this
filter running.
SSO NTLM Filter: Are your users authenticating via NTLM (NT LAN Manager)? If not,
you don't need this filter running.
SSO OpenSSO Filter: Are you using OpenSSO for Single Sign-On? If not, you don't
need this filter running.
Virtual Host Filter: Are you mapping domain names to communities or
organizations? If not, turn this filter off.
Sharepoint Filter: Are you using Liferay's Sharepoint functionality for saving
documents directly to the portal? If not, this filter is not for you. Turn it off.
                               How do you turn off a servlet filter?

       Easy! Comment it out of the web.xml file:
<!--
<filter>
    <filter-name>SSO Ntlm Filter</filter-name>
    <filter-class>com.liferay.portal.servlet.filters.sso.ntlm.NtlmFilter</filter-class>
</filter>
-->
…
<!--
<filter-mapping>
    <filter-name>SSO Ntlm Filter</filter-name>
    <url-pattern>/c/portal/login</url-pattern>
</filter-mapping>
-->
                  Number 8:


Use EMM386 to put all the TSRs into high memory to free
        up—oh, never mind, wrong decade.
                         Number 8: Tune your JVM parameters.

Again, there is nothing set in stone for this: you will have to go through the
cycle of tune and profile, tune and profile until you get the parameters right.
Java memory looks something like this:
                                Young Generation

                         Eden                       From       To


                                                                          Java Heap
                                Old Generation



                            Permanent Generation
                        Garbage Collection

When Garbage Collection occurs, here's what happens:
                            Young Generation
                                                  X
         X     X               X      X                      To




                            Old Generation



                           Permanent Generation


When all of this is done, the space is compacted, so the memory is contiguous.
                         Serial vs. Parallel Garbage Collection

By default, the JDK uses a serial garbage collector.
When it runs, the garbage collector stops all application execution in order to do
its job.
This works really well for desktop-based, client applications which are running
on one processor.
For server-based, multi processor systems, you will perhaps want to switch to
the parallel garbage collector known as the Concurrent Mark-Sweep collector
(CMS).
This collector makes one short pause in application execution to mark objects
directly reachable from the application code.
Then it allows the application to run while it marks all objects which are
reachable from the set it marked.
Finally, it adds another phase called the remark phase which finalizes marking
by revisiting any objects modified while the application was running.
It then sweeps through and garbage collects.
                         JVM Options
NewSize, MaxNewSize: The initial size and the maximum size of the New or
Young Generation.
+UseParNewGC: Causes garbage collection to happen in parallel, using multiple
CPUs. This decreases garbage collection overhead and increases application
throughput.
+UseConcMarkSweepGC: Use the Concurrent Mark-Sweep Garbage Collector. This
uses shorter garbage collection pauses, and is good for applications that have a
relatively large set of long-lived data, and that run on machines with two or
more processors, such as web servers.
+CMSParallelRemarkEnabled: For the CMS GC, enables the garbage collector to
use multiple threads during the CMS remark phase. This decreases the pauses
during this phase.
ServivorRatio: Controls the size of the two survivor spaces. It's a ratio between
the survivor space size and Eden. The default is 25. There's not much bang for
the buck here, but it may need to be adjusted.
ParallelGCThreads: The number of threads to use for parallel garbage collection.
Should be equal to the number of CPU cores in your server.
                Example Java Options String

JAVA_OPTS="$JAVA_OPTS -XX:NewSize=700m
-XX:MaxNewSize=700m -Xms2048m -Xmx2048m
-XX:MaxPermSize=128m -XX:+UseParNewGC -XX:
+UseConcMarkSweepGC -XX:+CMSParallelRemarkEnabled
-XX:SurvivorRatio=20 -XX:ParallelGCThreads=8"
                 Number 7:

Tell the OS it's been featured on America's Most Wanted
  and—hey look, you better run: I see some FBI agents
                     coming this way!
                        Number 7: Tune ehcache.

Liferay uses ehcache, which is a cluster-aware, tunable cache.
Caching greatly speeds up performance by reducing the number of times the
application has to go grab something from the database.
Liferay's cache comes tuned to default settings, but you may want to modify it
to suit your web site.
If you have a heavily trafficked message board, you may want to consider
adjusting the cache for the message board.
                                 Caching the Message Board

<cache
    name="com.liferay.portlet.messageboards.model.impl.MBMessageImpl"
    maxElementsInMemory="10000"
    eternal="false"
    timeToIdleSeconds="600"
    overflowToDisk="true"
>
    <cacheEventListenerFactory
         class="net.sf.ehcache.distribution.RMICacheReplicatorFactory"
         properties="replicatePuts=false,replicateUpdatesViaCopy=false"
         propertySeparator=","
    />
    <bootstrapCacheLoaderFactory
           class="net.sf.ehcache.distribution.RMIBootstrapCacheLoaderFactory"
    />
</cache>
                        Tuning the Cache

MaxElementsInMemory: Monitor the cache using a JMX Console, as you cannot
guess at the right amount here. You can adjust the setting if you find the cache
is full.
TimeToIdleSeconds: This sets the time to idle for an element before it expires
from the cache.
Eternal: If eternal, timeouts are ignored and the element is never expired.
                        Other Cache Settings

There are many, many other settings which can be used to tune the cache.
You can, as an example, change the cache algorithm if it seems to be caching
the wrong things.
If we were to go over them all, we'd never get through to the rest of the top ten;
speaking of which....
                 Number 6:


 Take a queue from Speed: configure the server so that
any time the pages per second drops below your defined
      threshold, it'll blow up. That'll get it moving.
                         Number 6: Lucene Index Writer Interval

Whenever Liferay calls Lucene to index some content, it may create any number
of files to do so.
Depending on the content, these files can be large files or lots of small files.
Every now and then, Liferay optimizes the index for reading by combining
smaller files into larger files.
You can change this behavior based on your use case.
The property is lucene.optimize.interval
If you are doing a lot of publishing and loading of data, make the number very
high, like 1000.
If you are doing mostly reads, make it low, like the default value of 100.
Of course, the best thing is to move search out to a separate environment, such
as Solr.
                   Number 5:


That's it, we have no other choice: go to Ludicrous Speed!
                         Number 5: Optimize Counter Increment

One of the ways Liferay is able to support so many databases is that it does not
use any single database's method of determining sequences for primary keys.
Instead, Liferay includes its own counter utility which can be optimized.
The default value: counter.increment=100 will cause Liferay to go to the database
to update the counter only once for every 100 primary keys it needs to create.
Each time the counter increments itself, it keeps track of the current set of
available keys in an in-memory, cluster aware object.
You could set this to a higher number to reduce the number of database calls for
primary keys within Liferay.
               Number 4:

Use a Redundant Array of Impelling Rodents (RAIR).
                        Number 4: Use a Content Delivery
                        Network
A Content Delivery Network serves up static content from a location that is
geographically close to the end user.
This goes one step better than simply using a web server to serve up your static
content, and is very simple to set up.
cdn.host=[your CDN host here]
The value should include the full protocol and port number if the CDN does not
use the standard HTTP and HTTPS ports.
Liferay.com is configured this way.
                 Number 3:


Put some of that Comcast Speed Boost into the server.
                         Number 3: CSS/JS Sprites

You heard it here: programmers are not lazy.
When anybody is under a tight deadline, it's faster to get the project done if you
implement it using experience already under your belt.
If, however, you take the time to learn to use some of Liferay's built-in tag
libraries, the performance benefits will pay off.
<liferay-ui:icon src='<%= themeDisplay.getPathThemeImages() + "/arrows/02_down.png"
%>' message="down" url="<%= taglibDownURL %>" />

Instead of standard <img src> tags, use the <liferay-ui:icon> tag as shown above.
                           What does this do?

What's faster, transferring 100KB over 1 HTTP connection or opening up 10
connections for 10KB each?
This is the reason developers have moved to CSS sprites for graphics.
If you use the Liferay tag libraries, we will do all the packing and imaging for
you.
Upon deployment, Liferay, using the StripFilter and MinifierFilter, will
automatically create a .sprite.png and .sprite.gif (for any IE 6 users out there),
and generate code in the pages that looks like this:
<img class="icon" src="/html/themes/classic/images/spacer.png"
     alt="Configuration"
     style="background-image: url('/html/themes/classic/images/portlet/.sprite.png');
     background-position: 50% -131px;
     background-repeat: no-repeat;
     height: 16px;
     width: 16px;" />
                        Less work, same performance benefit

We don't force you to cut up images.
If you have 50 icons on one page, we consolidate that into one file automatically.
The filters understand CSS too.
            Number 2:


Buy another server from the planet Krypton.
                                    Number 2: Stupid Database tricks.
    Trick 1: Read-writer Database
      This allows you to direct write operations and read operations to separate data
      sources.
      You must configure your database for replication in order to do this. All major
      databases support this.


jdbc.read.driverClassName=com.mysql.jdbc.Driver
jdbc.read.url=jdbc:mysql://dbread.com/lportal?useUnicode=true&characterEncoding=UTF-8&useFastDateParsing=false
jdbc.read.username=
jdbc.read.password=

jdbc.write.driverClassName=com.mysql.jdbc.Driver
jdbc.write.url=jdbc:mysql://dbwrite.com/lportal?useUnicode=true&characterEncoding=UTF-8&useFastDateParsing=fal
jdbc.write.username=
jdbc.write.password=




      Make sure the spring config is included in your portal-ext.properties file (see
      next slide)
                               Read Writer Database

spring.configs=\
        META-INF/base-spring.xml,\                  You will now have a dedicated data
        \
        META-INF/hibernate-spring.xml,\             source where write requests will go.
        META-INF/infrastructure-spring.xml,\
        META-INF/management-spring.xml,\            With replication enabled, updates to
        \
        META-INF/util-spring.xml,\                  all nodes can be done much faster
        \
        META-INF/editor-spring.xml,\                by your database software.
        META-INF/jcr-spring.xml,\
        META-INF/messaging-spring.xml,\             You can have one configuration of
        META-INF/scheduler-spring.xml,\
        META-INF/search-spring.xml,\                your database optimized for reads.
        \
        META-INF/counter-spring.xml,\
        META-INF/document-library-spring.xml,\
                                                    You can have one configuration of
        META-INF/lock-spring.xml,\                  your database optimized for writes.
        META-INF/mail-spring.xml,\
        META-INF/portal-spring.xml,\
        META-INF/portlet-container-spring.xml,\
        META-INF/wsrp-spring.xml,\
        \
        META-INF/mirage-spring.xml,\
        \
        META-INF/dynamic-data-source-spring.xml,\
        #META-INF/shard-data-source-spring.xml,\
        \
        META-INF/ext-spring.xml
                         Trick #2: Database Sharding

Sharding is splitting up your
database by various types of data
that may be in it.
It is a technique used for high
scalability scenarios.
One algorithm might be to split up
your users:
 –   A-D: Database 1
 –   E-H: Database 2
 –   (etc)
When users log in, they are directed
to the instance of the app that has
their data in it.
                            Liferay Sharding

Liferay supports sharding through portal instances.
You can create separate portal instances with your application in them, enable
sharding, and Liferay will use its round robin shard selector to determine where
users should go.
To enable sharding, use your portal-ext.properties file:
       shard.selector=com.liferay.portal.dao.shard.RoundRobinShardSelector
                                More Sharding

spring.configs=\
        META-INF/base-spring.xml,\                   And, of course, enable it in your
        \
        META-INF/hibernate-spring.xml,\              spring configs.
        META-INF/infrastructure-spring.xml,\
        META-INF/management-spring.xml,\
        \
        META-INF/util-spring.xml,\
        \
        META-INF/editor-spring.xml,\
        META-INF/jcr-spring.xml,\
        META-INF/messaging-spring.xml,\
        META-INF/scheduler-spring.xml,\
        META-INF/search-spring.xml,\
        \
        META-INF/counter-spring.xml,\
        META-INF/document-library-spring.xml,\
        META-INF/lock-spring.xml,\
        META-INF/mail-spring.xml,\
        META-INF/portal-spring.xml,\
        META-INF/portlet-container-spring.xml,\
        META-INF/wsrp-spring.xml,\
        \
        META-INF/mirage-spring.xml,\
        \
        #META-INF/dynamic-data-source-spring.xml,\
        META-INF/shard-data-source-spring.xml,\
        \
Number 1:


Red Bull anyone?
                                  Number 1: HTML Positioning of Elements

   Here's a code snippet from Yahoo.com. Anybody notice anything strange?

</script>
</html>
<script language=javascript>
if(window.yzq_p==null)
document.write("<scr"+"ipt language=javascript src=http://l.yimg.com/d/lib/bc/bc_2.0.4.js></scr"+"ipt>");
</script>
                                  Positioning Changes Things

   Bingo!
</script>
</html>
<script language=javascript>
if(window.yzq_p==null)
document.write("<scr"+"ipt language=javascript src=http://l.yimg.com/d/lib/bc/bc_2.0.4.js></scr"+"ipt>");
</script>

   They have JavaScript after the HTML tag. That's not according to spec, but all the
   browsers support it, and it improves performance.
                               JavaScript in Portlets

 If you have JavaScript in your portlets, you can control where Liferay positions it
 via the liferay-portlet.xml file.
<footer-portlet-javascript>/html/portlet/message_boards/javascript.js</footer-portlet-javascript>


 Here's your algorithm: try it in the footer first.
 If you have errors, put it back in the header.
 This is just as simple:
 <header-portlet-javascript>/html/portlet/message_boards/javascript.js</header-portlet-javascript>
And there you have it!

				
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