Java server faces

ZK Performance Monitors

Given Ajax applications' event driven nature, it would be beneficial if developers could
identify the time consuming event handlers and make the necessary performance tuning
accordingly. With ZK, a server-driven Ajax framework, developers could choose to handle all
Ajax events at the server-side. Previous efforts on ZK performance monitors have been
made in the area of identifying the network latency, process time at server, and rendering
time at client. In this article, we'll explore how "ZK Gazer", an implementation of a ZK
performance monitor, may reveal Ajax applications' bottlenecks at the event handling level
in real-time.

Technical Background

In ZK, all Ajax events can be forwarded to the server for management and processing. ZK's
org.zkoss.zk.ui.util.PerformanceMeter interface provides developers the utility to retrieve
information with respect to each stage of an Ajax request-response cycle, including

The PerformanceMeter Method Summary

• T1: requestStartAtClient (java.lang.String requestId, Execution exec, long time)
• T2: requestStartAtServer(java.lang.String requestId, Execution exec, long time)
• T3: requestCompleteAtServer(java.lang.String requestId, Execution exec, long time)
• T4: requestReceiveAtClient(java.lang.String requestId, Execution exec, long time)
• T5: requestCompleteAtClient(java.lang.String requestId, Execution exec, long time)

Developers could then work out the processing time at server, rendering time at client, and
the network latency:

• Server processing time = T3 - T2
• Client rendering time = T5 - T4
• Network latency = T4 - T1 - T3 + T2

However, to satisfy our need in obtaining the process time for each individual event handler,
we need to implement ZK's org.zkoss.zk.ui.util.EventInterceptor interface. With this
convenient interface, we could insert instructions before and after each event, which is
queued for processing at the server.

For our purposes, we'll need to implement the below methods:

• afterProcessEvent (Event event)
• beforeProcessEvent (Event event)

We'll set the current time at before, and after each event is processed and subtract the
latter by the former to obtain the event handling time for the particular event:

• Ta = timestamp at afterProcessEvent
• Tb = timestamp at beforeProcessEvent
• Event handling time = Ta - Tb

Performance Monitor Design

We can approach the design of our performance monitor in two ways:

• a performance monitor that is deployed for testers (beta testing) or the public,
which collects a great amount of data that is then processed as statistics for
• a performance monitor that is deployed for the web app developer (alpha testing) to
learn, in real time, the performance of specific event handlers

For ZK Gazer, we'll focus on the latter for now.

The UI elements are:

Enter URL to Monitor button + textbox: Users enter the ZUL file path here,
enter the text either by pressing "Enter" key, or pressing the button.
Clear Data button: Clears all performance data in memory
Reload URL button: Refreshes the iframe in Browser Panel
Real-Time Monitoring Tab: Contains the Target Monitor, Request Monitor, and
Browser Panel.
Browser Panel: Houses an iframe which acts as a browser for users to interact
with a ZK application under monitoring. The benefit of this is getting rid of the need
to switch between different browsers (one for the performance monitor interface,
others for the Ajax apps being monitored)
Target Monitor: Shows information on events and their target component in realtime
as the application under monitoring is being tested
Request Monitor: Shows information on each ZK asynchronous update request in
real-time as the application under monitoring is being tested
Request Path explorer: Click on a request path shown to switch to the iframe and
data associated with that request path

Statistics Tab: Contains the Data Record grid, Analytics grid, and Plot
Data Record Panel: Shows a log of all data collected
Sort Menu:Click and select a sorting function to display the data record in a more
meaningful format
Analytics Panel: Shows the event handling time with respect to each target
Plot Panel: Shows the average event handling time for each target component in a
pie chart

Performance Monitor Implementation

• Register listeners for org.zkoss.zk.ui.util.PerformanceMeter and
org.zkoss.zk.ui.util.EventInterceptor interfaces

<?xml version="1.0" encoding="UTF-8"?>
 <description>Monitor the statistic</description>
  <description>ZK performance monitor</description>
  <description>ZK AuInfoInterceptor</description>  

• Write a class that implements the org.zkoss.zk.ui.util.PerformanceMeter interface
• Get the request ID, Execution, and time from each stage of a ZK AU request cycle
◦ request ID = an automatically assigned string to identify a ZK AU request
◦ Execution = org.zkoss.zk.ui.Execution, a wrapper for the AU request. The
request is served through this wrapper
◦ time = epoch time in milliseconds

public void requestStartAtServer(String requestId, Execution exec, long time) {
  ReqDataCarrier carrier = ...;
 carrier.setTime(1, time);

• Write an implementation for the org.zkoss.zk.ui.util.EventInterceptor interface
• Set timestamps before and after processing the incoming event, for example:

public Event beforeProcessEvent(Event event) {
 EventInfo eventInfo = createEventInfoInst( event);
public void afterProcessEvent(Event event) {
 EventInfo eventInfo = getEventInfoInst();

*Note the last line getDataCarrier().addEventInfo(eventInfo) appends EventInfo to its
corresponding asynchronous request data object

A Proof of Concept Walkthrough

In this section, we'll look at how ZK Gazer reveals the bottleneck of a small demo
application that accesses database(HSQLDB) and renders data in grid.

Set Up

• Download ZK Gazer on Google Code; the necessary Java source code is included in
org.zkoss.poc.gazer.demo and the ZUL file life.zul is contained in the WebContent
• Find the hsqldb folder on Google Code, copy and paste it to your local C:

Demo Program Implementation

The demo app displays the average life expectancy of citizens around the world upon the
click of the "Display" button.

For illustration purposes, this simple action is divided into 3 events:

onClick$display -- the "Display" button's onClick event
onReadData -- the event in which the database is accessed and read
onRenderGrid -- the event in which data is rendered in a grid

Operating and Analyzing Results on ZK Gazer

• Enter "life.zul" in the URL text box and click on the "Display" butto
• Notice the event handling time for the events we engineered into this demo. As
expected, onReadData took significantly more time (388ms), followed by
onRenderGrid (5ms), and lastly, the simple onClick event (<1 ms) that triggers
the other events.
• Select on the "Statistics Tab" and view the "Data Record" and "Analytics" grids to
view the statistics. 

We could use the click and choose a sort function to display the
data record in a better format. The Flash plot gives an overview of the average
event handling time for each event; however the cursor over the chart to get the
percentage associated with each event.


In this article, we explored how in addition to determining the server processing time, client
rendering time, and network latency of the Ajax request-response cycle, we could better
pinpoint the performance bottlenecks by learning the handling time for each Ajax event
forwarded to the server. The embedded iframe along with real-time data feedback allows
developers to test, monitor, and analyze a ZK application all at once on a single active

Download zkGazer.war from Google Code

13 May 2010

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