Author: buildbot
Date: Sat Feb 27 16:20:05 2016
New Revision: 981287
Log:
Production update by buildbot for tapestry
Modified:
websites/production/tapestry/content/cache/main.pageCache
websites/production/tapestry/content/page-life-cycle.html
Modified: websites/production/tapestry/content/cache/main.pageCache
==============================================================================
Binary files - no diff available.
Modified: websites/production/tapestry/content/page-life-cycle.html
==============================================================================
--- websites/production/tapestry/content/page-life-cycle.html (original)
+++ websites/production/tapestry/content/page-life-cycle.html Sat Feb 27
16:20:05 2016
@@ -125,7 +125,7 @@
</div>
</li></ul>
-</div><p>In Tapestry, you are free to develop your presentation objects, page
and components classes, as ordinary objects, complete with instance variables
and so forth.</p><p>This is somewhat revolutionary in terms of web development
in Java. Using traditional servlets, or Struts, your presentation objects
(Servlets, or Struts Actions, or the equivalent in other frameworks) are
<em>stateless singletons</em>. That is, a <em>single</em> instance is created,
and all incoming requests are threaded through that single
instance.</p><p>Because multiple requests are handled by many different
threads, this means that the single instance's variable are useless ... any
value written into an instance variable would immediately be overwritten by a
different thread. Thus, it is necessary to use the Servlet API's
HttpServletRequest object to store per-request data, and the HttpSession object
to store data between requests.</p><p>Tapestry takes a very different
approach.</p><p>In Tapestry, each pa
ge is a singleton, but with a <em>per thread</em> map of field names &
values that Tapestry invisibly manages for you.</p><p>With this approach, all
the difficult, ugly issues related to multi-threading go by the wayside.
Instead, familiar, simple coding practices (using ordinary methods and fields)
can be used.</p><div class="confluence-information-macro
confluence-information-macro-information"><span class="aui-icon aui-icon-small
aui-iconfont-info confluence-information-macro-icon"></span><div
class="confluence-information-macro-body"><p>Tapestry 5.0 and 5.1 used page
pooling, rather than a singleton page with a per-thread map, to achieve the
same effect.</p></div></div><h2 id="PageLifeCycle-PageLifeCycleMethods">Page
Life Cycle Methods</h2><p>There are a few situations where it is useful for a
component to perform some operations, usually some kind of initialization or
caching, based on the life cycle of the page.</p><p>The page life cycle is
quite simple. When first needed,
a page is loaded. Loading a page involves instantiating the components of the
page and connecting them together.</p><p>Once a page is loaded, it is
<em>attached</em> to the current request. Remember that there will be many
threads, each handling its own request to the same page.</p><p>At the end of a
request, after a response has been sent to the client, the page is
<em>detached</em> from the request. This is a chance to perform any cleanup
needed for the page.</p><p>As with <a
href="component-rendering.html">component rendering</a>, you have the ability
to make your components "aware" of these events by identifying methods to be
invoked.</p><p>Page life cycle methods should take no parameters and return
void.</p><p>You have the choice of attaching an annotation to a method, or
simply using the method naming conventions:</p><div class="table-wrap"><table
class="confluenceTable"><tbody><tr><th colspan="1" rowspan="1"
class="confluenceTh"><p>Annotation</p></th><th colspan="1" rowspa
n="1" class="confluenceTh"><p>Method Name</p></th><th colspan="1" rowspan="1"
class="confluenceTh"><p>When Called</p></th></tr><tr><td colspan="1"
rowspan="1" class="confluenceTd"><p>@<a class="external-link"
href="http://tapestry.apache.org/current/apidocs/org/apache/tapestry5/annotations/PageLoaded.html";>PageLoaded</a></p></td><td
colspan="1" rowspan="1" class="confluenceTd"><p>pageLoaded()</p></td><td
colspan="1" rowspan="1" class="confluenceTd"><p>After the page is fully
loaded</p></td></tr><tr><td colspan="1" rowspan="1" class="confluenceTd"><p>@<a
class="external-link"
href="http://tapestry.apache.org/current/apidocs/org/apache/tapestry5/annotations/PageAttached.html";>PageAttached</a></p></td><td
colspan="1" rowspan="1" class="confluenceTd"><p>pageAttached()</p></td><td
colspan="1" rowspan="1" class="confluenceTd"><p>After the page is attached to
the request.</p></td></tr><tr><td colspan="1" rowspan="1"
class="confluenceTd"><p>@<a class="external-link" href="http://tapestry
.apache.org/current/apidocs/org/apache/tapestry5/annotations/PageDetached.html">PageDetached</a></p></td><td
colspan="1" rowspan="1" class="confluenceTd"><p>pageDetached()</p></td><td
colspan="1" rowspan="1" class="confluenceTd"><p>AFter the page is detached from
the request.</p></td></tr></tbody></table></div><h2
id="PageLifeCycle-ComparisontoJavaServerPages">Comparison to JavaServer
Pages</h2><p>JSPs also act as singletons. However, the individual JSP tags are
pooled.</p><p>This is one of the areas where Tapestry can significantly
outperform JSPs. Much of the code inside a compiled JSP class concerns getting
tags from a tag pool, configuring the properties of the tag instance, using the
tag instance, then cleaning up the tag instance and putting it back in the
pool.</p><p>The operations Tapestry does once per request are instead executed
dozens or potentially hundreds of times (depending the complexity of the page,
and if any nested loops occur).</p><p>Pooling JSP tags is simply t
he wrong granularity.</p><p>Tapestry can also take advantage of its more
coarse grained caching to optimize how data moves, via parameters, between
components. This means that Tapestry pages will actually speed up after they
render the first time.</p><h2 id="PageLifeCycle-PagePoolConfiguration">Page
Pool Configuration</h2><div class="confluence-information-macro
confluence-information-macro-note"><span class="aui-icon aui-icon-small
aui-iconfont-warning confluence-information-macro-icon"></span><div
class="confluence-information-macro-body"><p>This related to versions of
Tapestry prior to 5.2. Modern Tapestry uses an alternate approach that allows a
single page instance to be shared across many request processing
threads.</p></div></div><p>In Tapestry 5.0 and 5.1, a page pool is used to
store page instances. The pool is "keyed" on the name of the page (such as
"start") and the <em>locale</em> for the page (such as "en" or
"fr").</p><p>Within each key, Tapestry tracks the number of p
age instances that have been created, as well as the number that are in use
(currently attached to a request).</p><p>When a page is first accessed in a
request, it is taken from the pool. Tapestry has some <a
href="configuration.html">configuration values</a> that control the details of
how and when page instances are created.</p><ul><li>If a free page instance is
available, the page is marked in use and attached to the request.</li><li>If
there are fewer page instances than the <em>soft limit</em>, then a new page
instance is simply created and attached to the request.</li><li>If the soft
limit has been reached, Tapestry will wait for a short period of time for a
page instance to become available before creating a new page
instance.</li><li>If the hard limit has been reached, Tapestry will throw an
exception rather than create a new page instance.</li><li>Otherwise, Tapestry
will create a new page instance.<br clear="none"> Thus a busy application will
initially create pages up-to
the soft limit (which defaults to five page instances). If the application
continues to be pounded with requests, it will slow its request processing,
using the soft wait time in an attempt to reuse an existing page
instance.</li></ul><p>A truly busy application will continue to create new page
instances as needed until the hard limit is reached.</p><p>Remember that all
these configuration values are per key: the combination of page name and
locale. Thus even with a hard limit of 20, you may eventually find that
Tapestry has created 20 start page instances for locale "en" <em>and</em> 20
start page instances for locale "fr" (if your application is configured to
support both English and French). Likewise, you may have 20 instances for the
start page, and 20 instances for the newaccount page.</p><p>Tapestry
periodically checks its cache for page instances that have not been used
recently (within a configurable window). Unused page instances are release to
the garbage collector.</p><p
>The end result is that you have quite a degree of tuning control over the
>process. If memory is a limitation and throughput can be sacrificed, try
>lowering the soft and hard limit and increasing the soft wait.</p><p>If
>performance is absolute and you have lots of memory, then increase the soft
>and hard limit and reduce the soft wait. This encourages Tapestry to create
>more page instances and not wait as long to re-use existing
>instances.</p></div>
+</div><p>In Tapestry, you are free to develop your presentation objects, page
and components classes, as ordinary objects, complete with instance variables
and so forth.</p><p>This is somewhat revolutionary in terms of web development
in Java. Using traditional servlets, or Struts, your presentation objects
(Servlets, or Struts Actions, or the equivalent in other frameworks) are
<em>stateless singletons</em>. That is, a <em>single</em> instance is created,
and all incoming requests are threaded through that single
instance.</p><p>Because multiple requests are handled by many different
threads, this means that the single instance's variable are useless ... any
value written into an instance variable would immediately be overwritten by a
different thread. Thus, it is necessary to use the Servlet API's
HttpServletRequest object to store per-request data, and the HttpSession object
to store data between requests.</p><p>Tapestry takes a very different
approach.</p><p>In Tapestry, each pa
ge is a singleton, but with a <em>per thread</em> map of field names &
values that Tapestry invisibly manages for you.</p><p>With this approach, all
the difficult, ugly issues related to multi-threading go by the wayside.
Instead, familiar, simple coding practices (using ordinary methods and fields)
can be used.</p><div class="confluence-information-macro
confluence-information-macro-information"><span class="aui-icon aui-icon-small
aui-iconfont-info confluence-information-macro-icon"></span><div
class="confluence-information-macro-body"><p>Tapestry 5.0 and 5.1 used page
pooling, rather than a singleton page with a per-thread map, to achieve the
same effect.</p></div></div><h2 id="PageLifeCycle-PageLifeCycleMethods">Page
Life Cycle Methods</h2><p>There are a few situations where it is useful for a
component to perform some operations, usually some kind of initialization or
caching, based on the life cycle of the page.</p><p>The page life cycle is
quite simple. When first needed,
a page is loaded. Loading a page involves instantiating the components of the
page and connecting them together.</p><p>Once a page is loaded, it is
<em>attached</em> to the current request. Remember that there will be many
threads, each handling its own request to the same page.</p><p>At the end of a
request, after a response has been sent to the client, the page is
<em>detached</em> from the request. This is a chance to perform any cleanup
needed for the page.</p><p>As with <a
href="component-rendering.html">component rendering</a>, you have the ability
to make your components "aware" of these events by identifying methods to be
invoked.</p><p>Page life cycle methods should take no parameters and return
void.</p><p>You have the choice of attaching an annotation to a method, or
simply using the method naming conventions:</p><div class="table-wrap"><table
class="confluenceTable"><tbody><tr><th colspan="1" rowspan="1"
class="confluenceTh"><p>Annotation</p></th><th colspan="1" rowspa
n="1" class="confluenceTh"><p>Method Name</p></th><th colspan="1" rowspan="1"
class="confluenceTh"><p>When Called</p></th></tr><tr><td colspan="1"
rowspan="1" class="confluenceTd"><p>@<a class="external-link"
href="http://tapestry.apache.org/current/apidocs/org/apache/tapestry5/annotations/PageLoaded.html";>PageLoaded</a></p></td><td
colspan="1" rowspan="1" class="confluenceTd"><p>pageLoaded()</p></td><td
colspan="1" rowspan="1" class="confluenceTd"><p>After the page is fully
loaded</p></td></tr><tr><td colspan="1" rowspan="1" class="confluenceTd"><p>@<a
class="external-link"
href="http://tapestry.apache.org/current/apidocs/org/apache/tapestry5/annotations/PageAttached.html";>PageAttached</a></p></td><td
colspan="1" rowspan="1" class="confluenceTd"><p>pageAttached()</p></td><td
colspan="1" rowspan="1" class="confluenceTd"><p>After the page is attached to
the request.</p></td></tr><tr><td colspan="1" rowspan="1"
class="confluenceTd">@<a class="external-link" href="http://tapestry.ap
ache.org/current/apidocs/org/apache/tapestry5/annotations/PageReset.html">PageReset</a></td><td
colspan="1" rowspan="1" class="confluenceTd">pageReset()</td><td colspan="1"
rowspan="1" class="confluenceTd">After the page is <em>activated</em>, except
when requesting the same page</td></tr><tr><td colspan="1" rowspan="1"
class="confluenceTd"><p>@<a class="external-link"
href="http://tapestry.apache.org/current/apidocs/org/apache/tapestry5/annotations/PageDetached.html";>PageDetached</a></p></td><td
colspan="1" rowspan="1" class="confluenceTd"><p>pageDetached()</p></td><td
colspan="1" rowspan="1" class="confluenceTd"><p>AFter the page is detached from
the request.</p></td></tr></tbody></table></div><p>The @PageReset life cycle is
new in Tapestry 5.2. It is invoked on a page render request when linked to from
some <em>other</em> page of the application (but <em>not</em> on a link to the
same page). This is to allow the page to reset its state, if any, when a user
returns to the page fr
om some other part of the application.</p><h2
id="PageLifeCycle-ComparisontoJavaServerPages">Comparison to JavaServer
Pages</h2><p>JSPs also act as singletons. However, the individual JSP tags are
pooled.</p><p>This is one of the areas where Tapestry can significantly
outperform JSPs. Much of the code inside a compiled JSP class concerns getting
tags from a tag pool, configuring the properties of the tag instance, using the
tag instance, then cleaning up the tag instance and putting it back in the
pool.</p><p>The operations Tapestry does once per request are instead executed
dozens or potentially hundreds of times (depending the complexity of the page,
and if any nested loops occur).</p><p>Pooling JSP tags is simply the wrong
granularity.</p><p>Tapestry can also take advantage of its more coarse grained
caching to optimize how data moves, via parameters, between components. This
means that Tapestry pages will actually speed up after they render the first
time.</p><h2 id="PageLifeCyc
le-PagePoolConfiguration">Page Pool Configuration</h2><div
class="confluence-information-macro confluence-information-macro-note"><span
class="aui-icon aui-icon-small aui-iconfont-warning
confluence-information-macro-icon"></span><div
class="confluence-information-macro-body"><p>This related to versions of
Tapestry prior to 5.2. Modern Tapestry uses an alternate approach that allows a
single page instance to be shared across many request processing
threads.</p></div></div><p>In Tapestry 5.0 and 5.1, a page pool is used to
store page instances. The pool is "keyed" on the name of the page (such as
"start") and the <em>locale</em> for the page (such as "en" or
"fr").</p><p>Within each key, Tapestry tracks the number of page instances that
have been created, as well as the number that are in use (currently attached to
a request).</p><p>When a page is first accessed in a request, it is taken from
the pool. Tapestry has some <a href="configuration.html">configuration
values</a> that cont
rol the details of how and when page instances are created.</p><ul><li>If a
free page instance is available, the page is marked in use and attached to the
request.</li><li>If there are fewer page instances than the <em>soft
limit</em>, then a new page instance is simply created and attached to the
request.</li><li>If the soft limit has been reached, Tapestry will wait for a
short period of time for a page instance to become available before creating a
new page instance.</li><li>If the hard limit has been reached, Tapestry will
throw an exception rather than create a new page instance.</li><li>Otherwise,
Tapestry will create a new page instance.<br clear="none"> Thus a busy
application will initially create pages up-to the soft limit (which defaults to
five page instances). If the application continues to be pounded with requests,
it will slow its request processing, using the soft wait time in an attempt to
reuse an existing page instance.</li></ul><p>A truly busy application will c
ontinue to create new page instances as needed until the hard limit is
reached.</p><p>Remember that all these configuration values are per key: the
combination of page name and locale. Thus even with a hard limit of 20, you may
eventually find that Tapestry has created 20 start page instances for locale
"en" <em>and</em> 20 start page instances for locale "fr" (if your application
is configured to support both English and French). Likewise, you may have 20
instances for the start page, and 20 instances for the newaccount
page.</p><p>Tapestry periodically checks its cache for page instances that have
not been used recently (within a configurable window). Unused page instances
are release to the garbage collector.</p><p>The end result is that you have
quite a degree of tuning control over the process. If memory is a limitation
and throughput can be sacrificed, try lowering the soft and hard limit and
increasing the soft wait.</p><p>If performance is absolute and you have lots of
memor
y, then increase the soft and hard limit and reduce the soft wait. This
encourages Tapestry to create more page instances and not wait as long to
re-use existing instances.</p></div>
</div>
<div class="clearer"></div>
