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A Siddhi Application is a combination of multiple Siddhi executional elements. A Siddhi executional element can be a Siddhi Query or a Siddhi Partition. When defining a Siddhi application, you can specify a number of parallel instances to be created for each executional element, and how each executional element must be isolated for an SP instance. Based on this, the initial Siddhi application is divided into multiple Siddhi applications and deployed in different SP instances.

This deployment pattern is supported so that a high volume of data can be distributed among multiple SP instances instead of having them accumulated at a single point. Therefore, it is suitable to be used in scenarios where the volume of data handled is too high to be managed in a single SP instance.

Creating a distributed Siddhi application

This section explains how to write distributed Sidhi applications by assigning executional elements to different execution groups.

Executional elements

A distributed Siddhi application can contain one or more of the following elements:

Stateless queries

Queries that only consider currently incoming events when generating an output.

e.g., Filters

Stateful queriesQueries that consider both currently incoming events as well as past events when generating an output.
e.g., windows, sequences, patterns, etc. 
PartitionsCollections of stream definitions and Siddhi queries separated from each other within a Siddhi application for the purpose of processing events in parallel and in isolation.


The following annotations are used when writing a distributed Siddhi application.

@dist(execGroup='name of the group')

All the executional elements with the same execution group are executed in the same Siddhi application. When different execution groups are mentioned within the same distributed Siddhi application, WSO2 SP initiates a separate Siddhi Application per execution group. In each separated Siddhi application, only the executional elements assigned to the relevant execution group are executed.

Executional elements that have no execution group assigned to them are executed in a separate SP instance.

@dist (parallel='number of parallel instances’)

The number of instances in which the executional element must be executed in parallel. All the executional elements assigned to a specific execution group (i.e., via the @dist(execGroup) annotation) must have the same number of parallel instances specified. If there is a mismatch in the parallel instances specified for an execution group, an exception occurs.

When the number of parallel instances to be run is not given for the executional elements assigned to an execution group, only one Siddhi application is initiated for that execution group.


The following is a sample distributed Siddhi application.

@info(name = ‘query1') @dist(execGroup='group1')
from TempStream#window.time(2 min) 
select avg(temp) as avgTemp, roomNo, deviceID insert all events into AvgTempStream;

@info(name = ‘query2') @dist(execGroup='group1')
from TempStream[temp > 30.0]#window.time(1 min) as T join 
RegulatorStream[isOn ==false]#window.length(1) as R on T.roomNo == R.roomNo
select T.roomNo, R.deviceID, 'start' as action insert into RegulatorActionStream;

@info(name = ‘query3') @dist(execGroup='group1')
from every( e1=TempStream ) -> e2=TempStream[e1.roomNo==roomNo and (e1.temp + 5) <= temp ] within 10 min select e1.roomNo, e1.temp as initialTemp, e2.temp as finalTemp
insert into AlertStream;

@info(name = ‘query4') @dist(execGroup='group2' ,parallel ='2')
from TempStream [(roomNo >= 100 and roomNo < 110) and temp > 40 ] select roomNo, temp insert into HighTempStream;

@info(name = ‘query5') @dist(execGroup='group3' , parallel=’2’)
partition with ( deviceID of TempStream )
    from TempStream#window.time(1 min)
    select roomNo, deviceID, temp, avg(temp) as avgTemp
    insert into #AvgTempStream;

    from #AvgTempStream[avgTemp > 20]#window.length(10)
    select roomNo, deviceID, max(temp) as maxTemp
    insert into deviceTempStream;

When this Siddhi application is deployed, it is executed as shown in the table below.

Execution Group

Number of Siddhi

Application Instances

Queries executed










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