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// a function to read a text file asynchronusly let readFileAsync file = async { do print (sprintf "Beginning file %s" file) let! stream = File.AsyncOpenText(file) let! fileContents = stream.AsyncReadToEnd() do print (sprintf "Ending file %s" file) return fileContents } let filesContents = Async.RunSynchronously (Async.Parallel [ readFileAsync "text1.txt"; readFileAsync "text2.txt"; readFileAsync "text3.txt"; ]) Again, this version incorporates some debugging code, so you can see how the program executes. The biggest change is that you now use the Async.Parallel function to compose several workflows into a single workflow. This means that when the first thread finishes processing the first asynchronous call, it will be free to carry on processing the other workflows. This is probably easiest to see when you look at the results of the two programs: Synchronous results Thread Thread Thread Thread Thread Thread 1: 1: 1: 1: 1: 1: Beginning Ending Beginning Ending Beginning Ending file file file file file file text1.txt text1.txt text2.txt text2.txt text3.txt text3.txt

It is simple to then add the values recorded on every instance within the cluster and multiply them by 60 to determine the overall transaction rate per minute observed for the test. This will coincide with the transaction rate observed within the Hammerora transaction counter. The AWR report also contains a wealth of information that can be browsed at leisure after the test is complete. In 24, we present the guidelines for interpreting the RAC-related AWR report statistics. For example, if you are interested in a pseudo-tpmC-type number to obtain the number of business transactions, the "SQL Ordered by Elapsed Time" details the number of executions of each statement. Therefore, the total number of new orders processed across the entire cluster during the test period can easily be derived.

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The "Operating System Statistics" section can also prove particularly useful if you wish to observe levels of processor performance for the application running on different systems. A great deal of information can be gathered and coupled with experience to provide valuable empirical evidence for generic Oracle OLTP performance observations.

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Swingbench is a freely available tool designed for the load and stress testing of Oracle databases and can be downloaded from http: //www dominicgiles com Swingbench is used extensively for visually demonstrating RAC functionality and can also be used to demonstrate additional Oracle features such as online table rebuilds, Data Guard, and online backup and recovery Swingbench provides a comprehensive graphical toolset to observe system throughput and response times in a RAC environment By default, Swingbench includes two open source preconfigured benchmarks: Order Entry and Calling Circle It also includes PL/SQL stubs to enable the development of a bespoke benchmark Order Entry is based on a modified version of the oe sample schema included with the Oracle database so that the schema can be utilized independently.

It is designed to demonstrate RAC functionality when there is a high level of contention on a small number of tables increasing the level of activity on the interconnect and memory Calling Circle implements an example OLTP online telecommunications application Whereas Order Entry can be run continuously Calling Circle requires the generation of input data files in advance Both benchmarks induce a high level of CPU utilization, and it is recommended to use one processor per load generator for two processors per database server Swingbench also offers an API for Java developers to create their own benchmarks by defining classes and parameters to be implemented by the Swingbench framework In a single-instance environment, Swingbench can be used exclusively to conduct a benchmark test.

Asynchronous results Thread Thread Thread Thread Thread Thread 3: 4: 3: 4: 4: 4: Beginning Beginning Beginning Ending Ending Ending file file file file file file text1.txt text2.txt text3.txt text2.txt text1.txt text3.txt

However, in a RAC environment, in addition to Swingbench, it is useful to configure two additional components (the coordinator and cluster overview) to implement an integrated RAC benchmark The coordinator and cluster overview are already included with the standard Swingbench installation The following section will look in greater depth at the installation and configuration of Swingbench on two load-generation servers (loadl and load2) and the execution of an example Calling Circle benchmark..

A prerequisite for running Swingbench on a load-generation server is a Java virtual machine (JVM). The actual JVM selected will depend on the client environment, but an example JVM for a Linux x86-based load generator is the Java 2 Platform, Standard Edition (J2SE) Java Runtime Environment (JRE). This is available as a self-extracting compressed file that produces an RPM file and can be downloaded from the Sun Java software web site at http: //Java. sun. com. Once the RPM file is extracted by running the .bin file, install the RPM file on all of the loadgeneration hosts with the following command:

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