Skip to content

siddhi-execution-approximate

The siddhi-execution-approximate is an extension to Siddhi that performs approximate computing on event streams.

Find some useful links below: Source code Releases * Issue tracker

Latest API Docs

Latest API Docs is 2.0.0.

How to use

Using the extension in WSO2 Stream Processor

  • You can use this extension in the latest WSO2 Stream Processor that is a part of WSO2 Analytics offering, with editor, debugger and simulation support.

  • This extension is shipped by default with WSO2 Stream Processor, if you wish to use an alternative version of this extension you can replace the component jar that can be found in the <STREAM_PROCESSOR_HOME>/lib directory.

Using the extension as a java library

  • This extension can be added as a maven dependency along with other Siddhi dependencies to your project.
     <dependency>
        <groupId>org.wso2.extension.siddhi.execution.approximate</groupId>
        <artifactId>siddhi-execution-approximate</artifactId>
        <version>x.x.x</version>
     </dependency>

Jenkins Build Status

Branch Build Status
master Build Status

Features

  • count (Stream Processor)

    This extension applies the count-min sketch algorithm to a Siddhi window. The algorithm calculates the approximate count i.e., the frequency of events that arrive, based on the given values for the 'relative error' and 'confidence value'. Note that, using this extension without a window may cause an 'out of memory' error.

  • distinctCount (Stream Processor)

    This applies the 'HyperLogLog' algorithm to a Siddhi window. The algorithm is set with a relative error and a confidence value on the basis of which the number of distinct events with an accepted level of accuracy is calculated. Note that if this extension is used without a window, it may cause an 'out of memory' error. If you need to perform these calculations without windows, use the approximate:distinctCountEver extension.

  • distinctCountEver (Stream Processor)

    This extension applies the HyperLogLog algorithm to a Siddhi window in order to calculate the number of distinct events on a streaming data set based on a specific relative error and a confidence value given. Note that this extension returns erroneous values if it is used with a Siddhi window. If you want to perform these calculations with a window, you need to use the approximate:distinctCount extension.

How to Contribute

Contact us

Support

  • We are committed to ensuring support for this extension in production. Our unique approach ensures that all support leverages our open development methodology and is provided by the very same engineers who build the technology.

  • For more details and to take advantage of this unique opportunity contact us via http://wso2.com/support/.