While generating new technical content for Oracle Solaris 11 is one of our higher priorities here at Oracle, it's always fun to have a look at some web stats to see what existing published content is popular among our audience. So here's the top ten as voted by your browsers. Interestingly it's a great mix of technologies. What's your favourite? Let us know!

Missed the recent Quarterly Customer Update Webcast? We presented the product roadmaps for WebCenter Portal, WebCenter Content and WebCenter Sites.

VIEW WEBCAST RECORDING:
Access the webcast recording and presentation by going to:
My Oracle Support Site Note: 568127.1

We'll announce the next Quarterly Customer Update Webcast here on the WebCenter Alerts blog.

Recently, I had blogged about enabling the UCM content cache invalidator for Spaces (found here).  This can also be enabled for a WebCenter Custom Portal application as well.  The much overlooked setting is done through the Content Repository connection definition in the JDeveloper Application Resources section.

Enabling the cache invalidator "sweeper" can be invaluable, where UCM content is being updated from within UCM (console) and not within the portal.

Invitation : Advisor Webcast December 2012

In December 2012 we have scheduled an Advisor Webcast, where we want to give you a closer look into the invalid objects in an E-Business Suite Environment.

E-Business Suite - Troubleshooting invalid objects

• Introduction
• Activities that generate invalid objects
• EBS Architecture
• EBS Patching Concepts
• Troubleshooting Invalid Objects
• References

Details & Registration : Doc ID 1501696.1
Direct link to register in WebEx


US Session :
Wednesday December 12th, 2012 at 18:00 UK / 19:00 CET / 10:00 AM Pacific / 11:00 AM Mountain/ 01:00 PM Eastern

Details & Registration : Doc ID 1501697.1
Direct link to register in WebEx


If you have any question about the schedules or if you have a suggestion for an Advisor Webcast to be planned in future, please send an E-Mail to Ruediger Ziegler.

One of the first questions people asked when they start using the Oracle Unified Method (OUM) is “how do I find X ?”

Well of course no one is really looking for “X”!! but typically an OUM user might know the Task ID, or part of the Task Name, or maybe they just want to find out if there is any content within OUM that is related to a couple of keys words they have in their mind.

Here are three quick tips I give people:

1. Open up one of the OUM Views, then click “Expand All”, and then use your Browser’s search function to locate a key Word.

For example, Google Chrome or Internet Explorer: <CTRL> F, then type in a key Word, i.e. Architecture

This is fast and easy option to use, but it only searches the current OUM page

2. Use the PDF view of OUM

Open up one of the OUM Views, and then click the PDF View button located at the top of the View. Depending on your Browser’s settings, the PDF file will either open up in a new Window, or be saved to your local machine. In either case, once the PDF file is open, you can use the built in PDF search commands to search for key words across a large portion of the OUM Method Pack.

This is great option for searching the entire Full Method View of OUM, including linked HTML pages, however the search will not included linked Documents, i.e. Word, Excel.

3.Use your operating systems file index to search for key words

This is my favorite option, and one I use virtually every day. I happen to use Windows Search, but you could also use Google Desktop Search, of Finder on a MAC.

All you need to do (on a Windows machine) is to make sure your local OUM folder structure is included in the Windows Index. Go to Control Panel, select Indexing Options, and ensure your OUM folder is included in the Index, i.e. C:/METHOD/OM40/OUM_5.6

Once your OUM folders are indexed, just open up Windows Search (or Google Desktop Search) and type in your key worlds, i.e. Unit Testing

The reason I use this option the most is because the Search will take place across the entire content of the Indexed folders, included linked files.

Happy searching!

As "guest" pointed out, in my file I/O test I didn't open the file with O_SYNC, so in fact the time was spent in OS code rather than in disk I/O. It's a straightforward change to add O_SYNC to the open() call, but it's also useful to reduce the iteration count - since the cost per write is much higher:

...
#define SIZE 1024

void test_write()
{
  starttime();
  int file = open("./test.dat",O_WRONLY|O_CREAT|O_SYNC,S_IWGRP|S_IWOTH|S_IWUSR);
...

Running this gave the following results:

Time per iteration   0.000065606310 MB/s
Time per iteration   2.709711563906 MB/s
Time per iteration   0.178590114758 MB/s

Yup, disk I/O is way slower than the original I/O calls. However, it's not a very fair comparison since disks get written in large blocks of data and we're deliberately sending a single byte. A fairer result would be to look at the I/O operations per second; which is about 65 - pretty much what I'd expect for this system.

It's also interesting to examine at the profiles for the two cases. When the write() was trapping into the OS the profile indicated that all the time was being spent in system. When the data was being written to disk, the time got attributed to sleep. This gives us an indication how to interpret profiles from apps doing I/O. It's the sleep time that indicates disk activity.

Fellow foodies will recognize the recent movement towards "farm-to-table" restaurants. These venues attempt to simplify their menus and source ingredients as close to the source as possible. I had the opportunity to dine at such a restaurant the other evening. I was gushing about the appetizer to my server when she described the preparation for the item and then punctuated her comments with "basic is best". I reminded my fellow enterprise architect diners there was an architecture lesson in that statement. They rolled their eyes and chuckled. But they also knew I was right.

I'm reminded of Frederick Brooks' book The Mythical Man Month and his latest The Design of Design. The former must read book talks about complexity. But he refrains from damning all complexity. The world we live in and enterprises we strive to transform with enterprise architecture are complicated organisms, much like the human body. But sometimes a simple solution is the best approach. Fewer applications (think: portfolio rationalization). Fewer components. Fewer lines of code. Whatever level of abstraction you are working at, less is more.

I'm reminded of the enterprise architecture principle "Control Technical Diversity". At one firm I created pithy catch phrases for each principles. I named this one "Less is More". But perhaps another variation is what my server said the other night, "Basic is Best".

My earlier blog posting shows how to enable, retrieve and interpret BPEL engine performance statistics to aid performance troubleshooting. The strength of BPEL engine statistics at EM is its break down per request. But there are some limitations with the BPEL performance statistics mentioned in that blog posting:

• The statistics were stored in memory instead of being persisted. To avoid memory overflow, the data are stored to a buffer with limited size. When the statistic entries exceed the limitation, old data will be flushed out to give ways to new statistics. Therefore it can only keep the last X number of entries of data. The statistics 5 hour ago may not be there anymore.

• The BPEL engine performance statistics only includes latencies. It does not provide throughputs.

Fortunately, Oracle SOA Suite runs with the SOA Infrastructure database and a lot of performance data are naturally persisted there. It is at a more coarse grain than the in-memory BPEL Statistics, but it does have its own strengths as it is persisted.

Here I would like offer examples of some basic SQL queries you can run against the infrastructure database of Oracle SOA Suite 11G to acquire the performance statistics for a given period of time. You can run it immediately after you modify the date range to match your actual system.

1. Asynchronous/one-way messages incoming rates

The following query will show number of messages sent to one-way/async BPEL processes during a given time period, organized by process names and states

select composite_name composite, state, count(*) Count from dlv_message
       where receive_date >= to_timestamp('2012-10-24 21:00:00','YYYY-MM-DD HH24:MI:SS')
         and receive_date <= to_timestamp('2012-10-24 21:59:59','YYYY-MM-DD HH24:MI:SS')
      group by composite_name, state
      order by Count;

2. Throughput of BPEL process instances

The following query shows the number of synchronous and asynchronous process instances created during a given time period. It list instances of all states, including the unfinished and faulted ones. The results will include all composites cross all SOA partitions

select state, count(*) Count, composite_name composite, component_name,componenttype from cube_instance
       where creation_date >= to_timestamp('2012-10-24 21:00:00','YYYY-MM-DD HH24:MI:SS')
          and creation_date <= to_timestamp('2012-10-24 21:59:59','YYYY-MM-DD HH24:MI:SS')
        group by composite_name, component_name, componenttype 
          order by count(*) desc;

3. Throughput and latencies of BPEL process instances

This query is augmented on the previous one, providing more comprehensive information. It gives not only throughput but also the maximum, minimum and average elapse time BPEL process instances.

select composite_name Composite, component_name Process, componenttype, state,
       count(*) Count,
      trunc(Max(extract(day    from (modify_date-creation_date))*24*60*60 + 
                extract(hour   from (modify_date-creation_date))*60*60 + 
                extract(minute from (modify_date-creation_date))*60 + 
                extract(second from (modify_date-creation_date))),4) MaxTime, 
      trunc(Min(extract(day    from (modify_date-creation_date))*24*60*60 + 
                extract(hour   from (modify_date-creation_date))*60*60 +  
                extract(minute from (modify_date-creation_date))*60 + 
                extract(second from (modify_date-creation_date))),4) MinTime, 
      trunc(AVG(extract(day    from (modify_date-creation_date))*24*60*60 +  
                extract(hour   from (modify_date-creation_date))*60*60 +  
                extract(minute from (modify_date-creation_date))*60 + 
                extract(second from (modify_date-creation_date))),4) AvgTime       
       from cube_instance
       where creation_date >= to_timestamp('2012-10-24 21:00:00','YYYY-MM-DD HH24:MI:SS')
          and creation_date <= to_timestamp('2012-10-24 21:59:59','YYYY-MM-DD HH24:MI:SS')
        group by composite_name, component_name, componenttype, state
          order by count(*) desc; 
 

4. Combine all together

Now let's combine all of these 3 queries together, and parameterize the start and end time stamps to make the script a bit more robust. The following script will prompt for the start and end time before querying against the database:

accept startTime prompt 'Enter start time (YYYY-MM-DD HH24:MI:SS)'
accept endTime   prompt 'Enter end time (YYYY-MM-DD HH24:MI:SS)'

Prompt "==== Rejected Messages ====";
REM 2012-10-24 21:00:00
REM 2012-10-24 21:59:59
select count(*), composite_dn from rejected_message
       where created_time >= to_timestamp('&&StartTime','YYYY-MM-DD HH24:MI:SS')
         and created_time <= to_timestamp('&&EndTime','YYYY-MM-DD HH24:MI:SS')
    group by composite_dn;
Prompt "";
Prompt "==== Throughput of one-way/asynchronous messages ====";
select state, count(*) Count, composite_name composite from dlv_message
       where receive_date >= to_timestamp('&StartTime','YYYY-MM-DD HH24:MI:SS')
         and receive_date <= to_timestamp('&EndTime','YYYY-MM-DD HH24:MI:SS')
      group by composite_name, state
      order by Count;

Prompt "";
Prompt "==== Throughput and latency of BPEL process instances ===="
select state,
       count(*) Count,
      trunc(Max(extract(day    from (modify_date-creation_date))*24*60*60 + 
                extract(hour   from (modify_date-creation_date))*60*60 + 
                extract(minute from (modify_date-creation_date))*60 + 
                extract(second from (modify_date-creation_date))),4) MaxTime, 
      trunc(Min(extract(day    from (modify_date-creation_date))*24*60*60 + 
                extract(hour   from (modify_date-creation_date))*60*60 +  
                extract(minute from (modify_date-creation_date))*60 + 
                extract(second from (modify_date-creation_date))),4) MinTime, 
      trunc(AVG(extract(day    from (modify_date-creation_date))*24*60*60 +  
                extract(hour   from (modify_date-creation_date))*60*60 +  
                extract(minute from (modify_date-creation_date))*60 + 
                extract(second from (modify_date-creation_date))),4) AvgTime,
       composite_name Composite, component_name Process, componenttype
       from cube_instance
       where creation_date >= to_timestamp('&StartTime','YYYY-MM-DD HH24:MI:SS')
          and creation_date <= to_timestamp('&EndTime','YYYY-MM-DD HH24:MI:SS')
        group by composite_name, component_name, componenttype, state
          order by count(*) desc; 

This notification describes vulnerabilities fixed in third-party components that are included in Oracle's product distributions.
Information about vulnerabilities affecting Oracle products can be found on Oracle Critical Patch Updates and Security Alerts page.

1. How to assure all of the SOA cluster members receive different messages instead of the same (duplicate) messages, even though the SOA cluster members are all subscribers to the Topic?
2. How to make sure the messages are evenly distributed (load balanced) to SOA cluster members?

2. The typical configuration

• StepA. Configure JMS Topic to be UDD and PDT, at the WebLogic cluster that house the JMS Topic
• Step B. Configure JCA Connection Factory with proper ServerProperties at the SOA cluster
• Step C. Reference the JCA Connection Factory and define a durable subscriber name, at composite's JmsAdapter (or the *.jca file)

ClientID=myClient;ClientIDPolicy=UNRESTRICTED;SubscriptionSharingPolicy=SHARABLE;TopicMessageDistributionAll=false

• Except for ClientID, other properties such as the ClientIDPolicy=UNRESTRICTED, SubscriptionSharingPolicy=SHARABLE and TopicMessageDistributionAll=false are all default settings for the JmsAdapter's connection factory. Therefore you do NOT have to explicitly specify them explicitly. All you need to do is the specify the ClientID.
• The ClientID is different from the subscriber ID that we are to discuss in the later steps. To make it simple, you just need to remember you need to specify the client ID and make it unique per connection factory.

<adapter-config name="subscribe" adapter="JMS Adapter" wsdlLocation="subscribe.wsdl" xmlns="http://platform.integration.oracle/blocks/adapter/fw/metadata"><connection-factory location="eis/wls/MyTestUDDTopic" UIJmsProvider="WLSJMS" UIConnectionName="ateam-hq24b"/><endpoint-activation portType="Consume_Message_ptt" operation="Consume_Message"><activation-spec className="oracle.tip.adapter.jms.inbound.JmsConsumeActivationSpec"><property name="DurableSubscriber" value="MySubscriberID-1"/><property name="PayloadType" value="TextMessage"/><property name="UseMessageListener" value="false"/><property name="DestinationName" value="jms/MyTestUDDTopic"/></activation-spec></endpoint-activation></adapter-config>

2.The "atypical" configurations:

References:

• Managing Durable Subscription
• WebLogic JMS Partitioned Distributed Topics and Shared Subscriptions
• JMS Troubleshooting:
• Configuring JMS Message Logging:
• Advanced Programming with Distributed Destinations Using the JMS Destination Availability Helper API

Tuning performance of Oracle SOA 11G applications could be challenging. Because SOA is a platform for you to build composite applications that connect many applications and "services", when the overall performance is slow, the bottlenecks could be anywhere in the system: the applications/services that SOA connects to, the infrastructure database, or the SOA server itself.How to quickly identify the bottleneck becomes crucial in tuning the overall performance.

Fortunately, the BPEL engine in Oracle SOA 11G (and 10G, for that matter) collects BPEL Engine Performance Statistics, which show the latencies of low level BPEL engine activities. The BPEL engine performance statistics can make it a bit easier for you to identify the performance bottleneck.

Although the BPEL engine performance statistics are always available, the access to and interpretation of them are somewhat obscure in the early and current (PS5) 11G versions.

This blog attempts to offer instructions that help you to enable, retrieve and interpret the performance statistics, before the future versions provides a more pleasant user experience.

Overview of BPEL Engine Performance Statistics 

Step1: Enable BPEL Engine Statistics for Each SOA Servers via Enterprise Manager

• EM Console -> soa-infra(Server Name) -> SOA Infrastructure -> SOA Administration -> BPEL Properties
• Click on "More BPEL Configuration Properties"
• Click on attribute "StatLastN", set its value to some integer number. Typically you want to set it 1000 or more.

Step 2: Download and Deploy bpelstat.war File to Admin Server,

• Download the bpelstat.war to your local PC
• At WebLogic Console, Go to Deployments -> Install
• Click on the "upload your file(s)"
• Click the "Browse" button to upload the deployment to Admin Server
• Accept the uploaded file as the path, click next
• Check the default option "Install this deployment as an application"
• Check "AdminServer" as the target server
• Finish the rest of the deployment with default settings

• Console -> Deployments
• Check the box next to "bpelstat" application
• Click on the "Start" button. It will change the state of the app from "prepared" to "active"

Step 3: Invoke the BPEL Statistic Tool

• The BPELStat tool merely call the MBean of BPEL server and collects and display the in-memory performance statics. You usually want to do that after some peak loads.
• Go tohttp://<admin-server-host>:<admin-server-port>/bpelstat
• Enter the correct admin hostname, port, username and password
• Enter the SOA Server Name from which you want to collect the performance statistics. For example, SOA_MS1, etc.
• Click Submit
• Keep doing the same for all SOA servers.

Step 3: Interpret the BPEL Engine Statistics

Overview

Solutions

• A single URL. For example: opmn:ormi://host1:6003:oc4j_instance1/appName1
• A comma separated list of multiple URLs. For examples:  opmn:ormi://host1:6003:oc4j_instanc1/appName, opmn:ormi://host2:6003:oc4j_instance1/appName, opmn:ormi://host3:6003:oc4j_instance1/appName

• appName on oc4j_instance1 on host1
• appName on oc4j_instance1 on host2,
• appName on oc4j_instance1 on host3, 

• One OPMN will be sufficient to find the list of all contexts from the entire cluster that satisfy the JNDI lookup query. You can do an experiment by shutting down appName on host1, and observe that OPMN on host1 will still be able to return you appname on host2 and appName on host3.

As a follow on to yesterday's blog entry, here's the equivalent starter application for GeoToolkit (also known as Geotk) on the NetBeans Platform, which ends up looking like this:

The above is a border.shp file I found on-line, while here's a USA states shape file rendered in the application:

Note that the navigation bar is also included, though that could later be migrated into the menu bar of the NetBeans Platform. 

Download the Maven based NetBeans Platform application with GeoToolkit integration here:

http://java.net/projects/nb-api-samples/sources/api-samples/show/versions/7.3/tutorials/geospatial/geotoolkit/MyGeospatialSystem

It was quite tricky getting this sample together, parts of it, especially the installer, which creates the database, comes from the Puzzle GIS project, while the files come from on-line locations, with the JAI-related dependencies providing problems of their own. I was able to solve the vendorName==null problem by downloading the jai_imageio.jar JAR found here and replacing the equivalent JAR in my POM with that one. But it's definitely a starting point and you now have the basic Maven structure needed for getting started with GeoToolkit in the context of all the services and components provided by the NetBeans Platform. 

Many thanks to Johann Sorel for his patience and help. 

In this edition of the ADF Mobile blog we'll tackle part 3 of our Web Service examples.  In this posting we'll take a look at firing the web service asynchronously and then filling in the UI when it completes.  This can be useful when you have data on the device in a local store and want to show that to the user while the application uses lazy loading from a web service to load more data.

Getting the sample code:

Just click here to download a zip of the entire project.  You can unzip it and load it into JDeveloper and deploy it either to iOS or Android.  Please follow the previous blog posts if you need help getting JDeveloper or ADF Mobile installed.  Note: This is a different workspace than WS-Part2

What's different?

In this example, when you click the Search button on the Forecast By Zip option, now it takes you directly to the results page, which is initially blank.  When the web service returns a second or two later the data pops into the UI.  If you go back to the search page and hit Search it will again clear the results and invoke the web service asynchronously.  This isn't really that useful for this particular example but it shows an important technique that can be used for other use cases.

How it was done

1)  First we created a new class, ForecastWorker, that implements the Runnable interface.  This is used as our worker class that we create an instance of and pass to a new thread that we create when the Search button is pressed inside the retrieveForecast actionListener handler.  Once the thread is started, the retrieveForecast returns immediately. 

2)  The rest of the code that we had previously in the retrieveForecast method has now been moved to the retrieveForecastAsync.  Note that we've also added synchronized specifiers on both these methods so they are protected from re-entrancy.

3)  The run method of the ForecastWorker class then calls the retrieveForecastAsync method.  This executes the web service code that we had previously, but now on a separate thread so the UI is not locked.  If we had already shown data on the screen it would have appeared before this was invoked.  Note that you do not see a loading indicator either because this is on a separate thread and nothing is blocked.

4)  The last but very important aspect of this method is that once we update data in the collections from the data we retrieve from the web service, we call AdfmfJavaUtilities.flushDataChangeEvents().   We need this because as data is updated in the background thread, those data change events are not propagated to the main thread until you explicitly flush them.  As soon as you do this, the UI will get updated if any changes have been queued.

Summary of Fundamental Changes In This Application

The most fundamental change is that we are invoking and handling our web services in a background thread and updating the UI when the data returns.  This allows an application to provide a better user experience in many cases because data that is already available locally is displayed while lengthy queries or web service calls can be done in the background and the UI updated when they return.  There are many different use cases for background threads and this is just one example of optimizing the user experience and generating a better mobile application. 

【Oracle Application Testing Suiteを実機で体験】
テストツールを活用してWebシステムの機能テストや負荷テストを効率的・効果的に実践しよう! 

Oracle Functional Testing および Oracle Load Testing を実際に操作していただき、いかにテストを効率良く行えるか体感していただけます。

日時: 2012年12月19日(水) 13:30～18:00
会場: 日本オラクル株式会社本社

詳しくはこちら
http://www.oracle.com/goto/jpm121219_2

Welcome to another post in the series of blogs which demonstrates how to use JMS queues in a SOA context. The previous posts were:

1. JMS Step 1 - How to Create a Simple JMS Queue in Weblogic Server 11g
2. JMS Step 2 - Using the QueueSend.java Sample Program to Send a Message to a JMS Queue
3. JMS Step 3 - Using the QueueReceive.java Sample Program to Read a Message from a JMS Queue
4. JMS Step 4 - How to Create an 11g BPEL Process Which Writes a Message Based on an XML Schema to a JMS Queue

Today we will create a BPEL process which will read (dequeue) the message from the JMS queue, which we enqueued in the last example. The JMS adapter will dequeue the full XML payload from the queue.

1. Recap and Prerequisites

In the previous examples, we created a JMS Queue, a Connection Factory and a Connection Pool in the WebLogic Server Console. Then we designed and deployed a BPEL composite, which took a simple XML payload and enqueued it to the JMS queue. In this example, we will read that same message from the queue, using a JMS adapter and a BPEL process. As many of the configuration steps required to read from that queue were done in the previous samples, this one will concentrate on the new steps. A summary of the required objects is listed below. To find out how to create them please see the previous samples. They also include instructions on how to verify the objects are set up correctly.

WebLogic Server Objects

Schema XSD File

The following XSD file is used for the message format. It was created in the previous example and will be copied to the new process.

stringPayload.xsd

JMS Message

After executing the previous samples, the following XML message should be in the JMS queue located at jms/TestJMSQueue:

JDeveloper Connection

You will need a valid Application Server Connection in JDeveloper pointing to the SOA server which the process will be deployed to.

2. Create a BPEL Composite with a JMS Adapter Partner Link

In the previous example, we created a composite in JDeveloper called JmsAdapterWriteSchema. In this one, we will create a new composite called JmsAdapterReadSchema.

There are probably many ways of incorporating a JMS adapter into a SOA composite for incoming messages. One way is design the process in such a way that the adapter polls for new messages and when it dequeues one, initiates a SOA or BPEL instance. This is possibly the most common use case. Other use cases include mid-flow adapters, which are activated from within the BPEL process. In this example we will use a polling adapter, because it is the most simple to set up and demonstrate. But it has one disadvantage as a demonstrative model. When a polling adapter is active, it will dequeue all messages as soon as they reach the queue. This makes it difficult to monitor messages we are writing to the queue, because they will disappear from the queue as soon as they have been enqueued. To work around this, we will shut down the composite after deploying it and restart it as required. (Another solution for this would be to pause the consumption for the queue and resume consumption again if needed. This can be done in the WLS console JMS-Modules -> queue -> Control -> Consumption -> Pause/Resume.)

We will model the composite as a one-way incoming process. Usually, a BPEL process will do something useful with the message after receiving it, such as passing it to a database or file adapter, a human workflow or external web service. But we only want to demonstrate how to dequeue a JMS message using BPEL and a JMS adapter, so we won’t complicate the design with further activities. However, we do want to be able to verify that we have read the message correctly, so the BPEL process will include a small piece of embedded java code, which will print the message to standard output, so we can view it in the SOA server’s log file. Alternatively, you can view the instance in the Enterprise Manager and verify the message.

The following steps are all executed in JDeveloper. Create the project in the same JDeveloper application used for the previous examples or create a new one.

Create a SOA Project

Create a new project and choose SOA Tier > SOA Project as its type. Name it JmsAdapterReadSchema. When prompted for the composite type, choose Empty Composite.

Create a JMS Adapter Partner Link

In the composite editor, drag a JMS adapter over from the Component Palette to the left-hand swim lane, under Exposed Services.

This will start the JMS Adapter Configuration Wizard. Use the following entries:

Service Name: JmsAdapterRead

Oracle Enterprise Messaging Service (OEMS): Oracle WebLogic JMS

AppServer Connection: Use an application server connection pointing to the WebLogic server on which the JMS queue and connection factory mentioned under Prerequisites above are located.

Adapter Interface > Interface: Define from operation and schema (specified later)

Operation Type: Consume Message
Operation Name: Consume_message

Consume Operation Parameters

Destination Name: Press the Browse button, select Destination Type: Queues, then press Search. Wait for the list to populate, then select the entry for TestJMSQueue, which is the queue created in a previous example.

JNDI Name: The JNDI name to use for the JMS connection. As in the previous example, this is probably the most common source of error. This is the JNDI name of the JMS adapter’s connection pool created in the WebLogic Server and which points to the connection factory. JDeveloper does not verify the value entered here. If you enter a wrong value, the JMS adapter won’t find the queue and you will get an error message at runtime, which is very difficult to trace. In our example, this is the value eis/wls/TestQueue. (See the earlier step on how to create a JMS Adapter Connection Pool in WebLogic Server for details.)

Messages/Message Schema
URL: We will use the XSD file created during the previous example, in the JmsAdapterWriteSchema project to define the format for the incoming message payload and, at the same time, demonstrate how to import an existing XSD file into a JDeveloper project.

Press the magnifying glass icon to search for schema files. In the Type Chooser, press the Import Schema File button.

Select the magnifying glass next to URL to search for schema files. Navigate to the location of the JmsAdapterWriteSchema project > xsd and select the stringPayload.xsd file.

Check the “Copy to Project” checkbox, press OK and confirm the following Localize Files popup.

Now that the XSD file has been copied to the local project, it can be selected from the project’s schema files. Expand Project Schema Files > stringPayload.xsd and select exampleElement: string.

Press Next and Finish, which will complete the JMS Adapter configuration.
Save the project.

Create a BPEL Component

Drag a BPEL Process from the Component Palette (Service Components) to the Components section of the composite designer. Name it JmsAdapterReadSchema and select Template: Define Service Later and press OK.

Wire the JMS Adapter to the BPEL Component

Now wire the JMS adapter to the BPEL process, by dragging the arrow from the adapter to the BPEL process. A Transaction Properties popup will be displayed. Set the delivery mode to async.persist.

This completes the steps at the composite level.

3. Complete the BPEL Process Design

Invoke the BPEL Flow via the JMS Adapter

Open the BPEL component by double-clicking it in the design view of the composite.xml, or open it from the project navigator by selecting the JmsAdapterReadSchema.bpel file. This will display the BPEL process in the design view. You should see the JmsAdapterRead partner link in the left-hand swim lane.

Drag a Receive activity onto the BPEL flow diagram, then drag a wire (left-hand yellow arrow) from it to the JMS adapter. This will open the Receive activity editor. Auto-generate the variable by pressing the green “+” button and check the “Create Instance” checkbox. This will result in a BPEL instance being created when a new JMS message is received.

At this point it would actually be OK to compile and deploy the composite and it would pick up any messages from the JMS queue. In fact, you can do that to test it, if you like. But it is very rudimentary and would not be doing anything useful with the message. Also, you could only verify the actual message payload by looking at the instance’s flow in the Enterprise Manager.

There are various other possibilities; we could pass the message to another web service, write it to a file using a file adapter or to a database via a database adapter etc. But these will all introduce unnecessary complications to our sample. So, to keep it simple, we will add a small piece of Java code to the BPEL process which will write the payload to standard output. This will be written to the server’s log file, which will be easy to monitor.

Add a Java Embedding Activity

First get the full name of the process’s input variable, as this will be needed for the Java code. Go to the Structure pane and expand Variables > Process > Variables. Then expand the input variable, for example, "Receive1_Consume_Message_InputVariable> body > ns2:exampleElement”, and note variable’s name and path, if they are different from this one.

Drag a Java Embedding activity from the Component Palette (Oracle Extensions) to the BPEL flow, after the Receive activity, then open it to edit.

Delete the example code and replace it with the following, replacing the variable parts with those in your sample, if necessary.:

Tip. If you are not sure of the exact syntax of the input variable, create an Assign activity in the BPEL process and copy the variable to another, temporary one. Then check the syntax created by the BPEL designer.

This completes the BPEL process design in JDeveloper. Save, compile and deploy the process to the SOA server.

3. Test the Composite

Shut Down the JmsAdapterReadSchema Composite

After deploying the JmsAdapterReadSchema composite to the SOA server it is automatically activated. If there are already any messages in the queue, the adapter will begin polling them. To ease the testing process, we will deactivate the process first

Log in to the Enterprise Manager (Fusion Middleware Control) and navigate to SOA > soa-infra (soa_server1) > default (or wherever you deployed your composite to) and click on JmsAdapterReadSchema [1.0]. Press the Shut Down button to disable the composite and confirm the following popup.

Monitor Messages in the JMS Queue

In a separate browser window, log in to the WebLogic Server Console and navigate to Services > Messaging > JMS Modules > TestJMSModule > TestJMSQueue > Monitoring. This is the location of the JMS queue we created in an earlier sample (see the prerequisites section of this sample). Check whether there are any messages already in the queue. If so, you can dequeue them using the QueueReceive Java program created in an earlier sample. This will ensure that the queue is empty and doesn’t contain any messages in the wrong format, which would cause the JmsAdapterReadSchema to fail.

Send a Test Message

In the Enterprise Manager, navigate to the JmsAdapterWriteSchema created earlier, press Test and send a test message, for example“Message from JmsAdapterWriteSchema”.

Confirm that the message was written correctly to the queue by verifying it via the queue monitor in the WLS Console.

Monitor the SOA Server’s Output

A program deployed on the SOA server will write its standard output to the terminal window in which the server was started, unless this has been redirected to somewhere else, for example to a file. If it has not been redirected, go to the terminal session in which the server was started, otherwise open and monitor the file to which it was redirected.

Re-Enable the JmsAdapterReadSchema Composite

In the Enterprise Manager, navigate to the JmsAdapterReadSchema composite again and press Start Up to re-enable it. This should cause the JMS adapter to dequeue the test message and the following output should be written to the server’s standard output:

JmsAdapterReadSchema process picked up a message.

Input String is Message from JmsAdapterWriteSchema

Note that you can also monitor the payload received by the process, by navigating to the the JmsAdapterReadSchema’s Instances tab in the Enterprise Manager. Then select the latest instance and view the flow of the BPEL component. The Receive activity will contain and display the dequeued message too.

4. Troubleshooting

This sample demonstrates how to dequeue an XML JMS message using a BPEL process and no additional functionality. For example, it doesn’t contain any error handling. Therefore, any errors in the payload will result in exceptions being written to the log file or standard output. If you get any errors related to the payload, such as

Message handle error
...
ORABPEL-09500
...
XPath expression failed to execute.
An error occurs while processing the XPath expression; the expression is 
     /ns2:exampleElement.
...
etc.

check that the variable used in the Java embedding part of the process was entered correctly. Possibly follow the tip mentioned in previous section. If this doesn’t help, you can delete the Java embedding part and simply verify the message via the flow diagram in the Enterprise Manager. Or use a different method, such as writing it to a file via a file adapter.

This concludes this example. In the next post, we will begin with an AQ JMS example, which uses JMS to write to an Advanced Queue stored in the database.

Best regards
John-Brown Evans
Oracle Technology Proactive Support Delivery

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