Converting to a Distributed Streaming Application

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:

Annotations

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

Example

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 )
begin
    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;
end;

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