Working with the Design View

To configure the stream, click the settings icon on the stream component you added to the grid. Then enter values as follows:

Stream Name : A unique name for the stream. This should be specified in title caps, and without spaces (e.g., ProductionDataStream).

Attributes: Attributes of streams are specified as name and type pairs in the Attributes table.

The details entered in the above form creates a stream configuration as follows:

define stream SweetProductionStream (amount double, name string);

To configure the source, click the settings icon on the source component you added to the grid. This opens a form where you can enter the following information:

• Source Type: This specifies the transport type via which the events are received. The value should be entered in lower case (e.g., tcp). The other parameters displayed for the source depends on the source type selected.
• Map Type: This specifies the format in which you want to receive the events (e.g., xml). The other parameters displayed for the map depends on the map type selected. If you want to add more configurations to the mapping, click Customized Options and set the required properties and key value pairs.
  

• Map Attribute as Key/Value Pairs: If this check box is selected, you can define custom mapping by entering key value pairs. You can add as many key value pairs as required under this check box.

The details entered in the above form creates a source configuration as follows:

@source(type = 'tcp', 
	@map(type = 'json', 
		@attributes(name = "$.sweet", amount = "$.batch.count")))

To configure the sink, click the settings icon on the sink component you added to the grid.

• Sink Type: This specifies the transport via which the sink publishes processed events. The value should be entered in lower case (e.g., log ).
  
• Map Type: This specifies the format in which you want to publish the events (e.g., passThrough). The other parameters displayed for the map depends on the map type selected. If you want to add more configurations to the mapping, click Customized Options and set the required properties and key value pairs.

• Map Attribute as Key/Value Pairs: If this check box is selected, you can define custom mapping by entering key value pairs. You can add as many key value pairs as required under this check box.
  

The details entered in the above form creates a sink configuration as follows:

@sink(type = 'log', prefix = "Sweet Totals:")

The details entered in the above form creates a table definition as follows:

@store(type = 'rdbms', datasource = "SweetProductionDB")
define table ShipmentDetails (name string, supplier string, amount double);

The details entered in the above form creates a window definition as follows:

define window FiveMinTempWindow (roomNo int, temp double) time(5 min) output all events;

To configure the trigger, click the settings icon on the trigger component you added to the grid, and update the following information.

• Name: A unique name for the trigger.
• Trigger Criteria: This specifies the criteria based on which the trigger is activated. Possible values are as follows:
  • start: Select this to trigger events when the SP server has started.
  • every: Select this to specify a time interval at which events should be triggered.
  • cron-expression: Select this to enter a cron expression based on which the events can be triggered. For more information about cron expressions, see the quartz-scheduler.

The details entered in the above orm creates a trigger definition as follows:

define trigger FiveMinTriggerStream at every 5 min;

Incremental aggregation allows you to obtain aggregates in an incremental manner for a specified set of time periods. For more information, see Siddhi Query Guide - Incremental Aggregation.

To configure the aggregation, click the settings icon on the aggregation component you added to the grid, and update the following information. 

• Aggregation Meta Information: In this section, define a unique name for the aggregation in the Name field, and specify the stream from which the input information is taken to perform the aggregations. You can also select the optional annotations you want to use in the aggregation definition by selecting the relevant check boxes. For more information about configuring the annotations once you select them, see Incremental Analysis.
• Projection: This section specifies the attributes to be included in the aggregation query. In the Select field, you can select All attributes to perform the aggregation for all the attributes of the stream specified under Input, or select User Defined Attributes to select specific attributes. If you select User Defined Attributes, you can add attributes to be selected to be inserted into the output stream. Here, you can enter the names of specific attributes in the input stream, or enter expressions to convert input stream attribute values as required to generate output events. You can also specify the attribute(s) by which you want to group the output.
• Aggregation Criteria: Here, you can specify the time values based on which the aggregates are calculated.

The details entered in the above form creates an aggregation definition as follows:

define aggregation TradeAggregation
from TradeStream
select symbol, avg(price) as avgPrice, sum(price) as total
	group by symbol
	aggregate by timestamp every seconds...years;

The details entered in the above form creates a function definition as follows:

define function concatFN[JAVASCRIPT] return string {
    var str1 = data[0];
    var str2 = data[1];
    var str3 = data[2];
    var responce = str1 + str2 + str3;
    return responce;
};

This icon represents a query to project the events in an input stream to an output stream. This invoves selectng the attributes to be included in the output, renaming attributes, introducing constant values, and using mathematical and/or logical expressions. For more information, see Siddhi Query Guide - Query Projection. 

Once you connect the query to an input stream (source) and an output stream (target), you can configure it. To configure the projection query, click the settings icon on the projection query component you added to the grid, and update the following information.

• Query Meta Information: This section specifies the stream to be considered as the input stream with the events to which the query needs to be applied. The input stream connected to the query as the source is automatically displayed.
• Projection: This section specifies the attributes to be included in the output. In the Select field, you can select All Attributes to select all the attributes of the events, or select User Defined Attributes to select specific attributes from the input stream. If you select User Defined Attributes, you can add attributes to be selected to be inserted into the output stream. Here, you can enter the names of specific attributes in the input stream, or enter expressions to convert input stream attribute values as required to generate output events. You can also specify the attribute(s) by which you want to group the output.
• Output: This section specifies the action to be performed on the output event. The fields to be configured in this section are as follows:
  • Operation: This field specifies the operation to be performed on the generated output event (e.g., Insert to insert events to a selected stream/table/window).
  • Into: This field specifies the stream/table/window in which the operation specified need to be performed.
  • Event Type This field specifies whether the operation needs to be performed for all output events, only current events or for only expired events.|

The details entered in the above form creates a query as follows:

from TradeStream
select symbol, avg(price) as averagePrice, sum(volume) as total
insert all events into OutputStream;

A filter query filters information in an input stream based on a given condition. For more information, see Siddhi Query Guide - Filters.

Once you connect the query to an input stream (source) and an output stream (target), you can configure it. To configure the filter query, click the settings icon on the filter query component you added to the grid, and update the following information.

• By default, the Stream Handler check box is selected, and a stream handler of the filter type is available under it to indicate that the query is a filter. Expand this stream handler, and enter the condition based on which the information needs to be filtered.

  A Siddhi application can have multiple stream handlers. To add another stream handler, click the + Stream Handler. Multiple functions, filters and windows can be defined within the same form as stream handlers.

• Projection: This section specifies the attributes to be included in the output. In the Select field, you can select All Attributes to select all the attributes of the events, or select User Defined Attributes to select specific attributes from the input stream. If you select User Defined Attributes, you can add attributes to be selected to be inserted into the output stream. Here, you can enter the names of specific attributes in the input stream, or enter expressions to convert input stream attribute values as required to generate output events. You can also specify the attribute(s) by which you want to group the output.
• Output: This section specifies the action to be performed on the output event. The fields to be configured in this section are as follows:
  • Operation: This field specifies the operation to be performed on the generated output event (e.g., Insert to insert events to a selected stream/table/window).
  • Into: This field specifies the stream/table/window in which the operation specified need to be performed.
  • Event Type This field specifies whether the operation needs to be performed for all output events, only current events or for only expired events.

The details entered in the above form creates a query with a filter as follows:

from TradeStream[sum(amount) > 10000]
select symbol, avg(price) as averagePrice, sum(amount) as total
insert all events into OutputStream;

Window queries include a window to select a subset of events to be processed based on a specific criterion. For more information, see Siddhi Query Guide - (Defined) Window.

Once you connect the query to an input stream (source) and an output stream (target), you can configure it. To configure the window query, click the settings icon on the window query component you added to the grid, and update the following information.

• By default, the Stream Handler check box is selected, and a stream handler of the window type is available under it to indicate that the query is a filter. Expand this stream handler, and enter details to determine the window including the window type and the basis on which the subset of events considered by the window is determined (i.e., based on the window type selected).

  A Siddhi application can have multiple stream handlers. To add another stream handler, click the + Stream Handler. Multiple functions, filters and windows can be defined within the same form as stream handlers.

• Projection: This section specifies the attributes to be included in the output. In the Select field, you can select All Attributes to select all the attributes of the events, or select User Defined Attributes to select specific attributes from the input stream. If you select User Defined Attributes, you can add attributes to be selected to be inserted into the output stream. Here, you can enter the names of specific attributes in the input stream, or enter expressions to convert input stream attribute values as required to generate output events. You can also specify the attribute(s) by which you want to group the output.
• Output: This section specifies the action to be performed on the output event. The fields to be configured in this section are as follows:
  • Operation: This field specifies the operation to be performed on the generated output event (e.g., Insert to insert events to a selected stream/table/window).
  • Into: This field specifies the stream/table/window in which the operation specified need to be performed.
  • Event Type This field specifies whether the operation needs to be performed for all output events, only current events or for only expired events.

The details entered in the above Query Configuration form creates a query with a window as follows:

from TradeStream#window.time(1 month)
select symbol, avg(price) as averagePrice, sum(amount) as total
insert all events into OutputStream;

• Streams
• Tables
• Triggers
• Windows

Once you connect two Siddhi components to the join query as sources and another Siddhi component as the target, you can configure the join query. To configure the join query, click the settings icon on the join query component you added to the grid and update the following information.

• Query Meta Information: In this section, enter a unique name for the query and any annotations that you want to include in the query. The @dist annotation is supported by default to use the query in a fully distributed deployment if required (for more information, see Converting to a Distributed Streaming Application). You can also add customized annotations.
  
• Input: Here, you can specify the input sources, the references, the join type, join condition, and stream handlers for the left source and right source of the join. For a detailed explanation of the join concept, see Siddhi Query Guide - Joins.
• Projection: This section specifies the attributes to be included in the output. In the Select field, you can select All Attributes to select all the attributes of the events, or select User Defined Attributes to select specific attributes from the input stream. If you select User Defined Attributes , you can add attributes to be selected to be inserted into the output stream. Here, you can enter the names of specific attributes in the input stream, or enter expressions to convert input stream attribute values as required to generate output events. You can also specify the attribute(s) by which you want to group the output.
• Output: This section specifies the action to be performed on the output event. The fields to be configured in this section are as follows:
  • Operation: This field specifies the operation to be performed on the generated output event (e.g., Insert to insert events to a selected stream/table/window).
  • Into: This field specifies the stream/table/window in which the operation specified need to be performed.
  • Event Type This field specifies whether the operation needs to be performed for all output events, only current events or for only expired events.

A join query is configured as follows:

 The above configurations result in creating the following join query.

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;

• Streams
• Tables
• Aggregations
• Windows

• Streams
• Tables
• Windows