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API Docs - v5.0.18

Tested Siddhi Core version: 5.1.21

It could also support other Siddhi Core minor versions.

Sink

kafka (Sink)

A Kafka sink publishes events processed by WSO2 SP to a topic with a partition for a Kafka cluster. The events can be published in the TEXT XML JSON or Binary format.
If the topic is not already created in the Kafka cluster, the Kafka sink creates the default partition for the given topic. The publishing topic and partition can be a dynamic value taken from the Siddhi event.
To configure a sink to use the Kafka transport, the type parameter should have kafka as its value.

Syntax

@sink(type="kafka", bootstrap.servers="<STRING>", topic="<STRING>", partition.no="<INT>", sequence.id="<STRING>", key="<STRING>", is.binary.message="<BOOL>", optional.configuration="<STRING>", is.synchronous="<BOOL>", @map(...)))

QUERY PARAMETERS

Name	Description	Default Value	Possible Data Types	Optional	Dynamic
bootstrap.servers	This parameter specifies the list of Kafka servers to which the Kafka sink must publish events. This list should be provided as a set of comma separated values. e.g., `localhost:9092,localhost:9093`.		STRING	No	No
topic	The topic to which the Kafka sink needs to publish events. Only one topic must be specified.		STRING	No	No
partition.no	The partition number for the given topic. Only one partition ID can be defined. If no value is specified for this parameter, the Kafka sink publishes to the default partition of the topic (i.e., 0)	0	INT	Yes	No
sequence.id	A unique identifier to identify the messages published by this sink. This ID allows receivers to identify the sink that published a specific message.	null	STRING	Yes	No
key	The key contains the values that are used to maintain ordering in a Kafka partition.	null	STRING	Yes	No
is.binary.message	In order to send the binary events via kafka sink, this parameter is set to 'True'.	null	BOOL	No	No
optional.configuration	This parameter contains all the other possible configurations that the producer is created with. e.g., `producer.type:async,batch.size:200`	null	STRING	Yes	No
is.synchronous	The Kafka sink will publish the events to the server synchronously when thevalue is set to `true`, and asynchronously if otherwise	false	BOOL	Yes	No

Examples EXAMPLE 1

@App:name('TestExecutionPlan') 
define stream FooStream (symbol string, price float, volume long); 
@info(name = 'query1') 
@sink(
type='kafka',
topic='topic_with_partitions',
partition.no='0',
bootstrap.servers='localhost:9092',
@map(type='xml'))
Define stream BarStream (symbol string, price float, volume long);
from FooStream select symbol, price, volume insert into BarStream;

This Kafka sink configuration publishes to 0th partition of the topic named topic_with_partitions.

EXAMPLE 2

@App:name('TestExecutionPlan') 
define stream FooStream (symbol string, price float, volume long); 
@info(name = 'query1') 
@sink(
type='kafka',
topic='{{symbol}}',
partition.no='{{volume}}',
bootstrap.servers='localhost:9092',
@map(type='xml'))
Define stream BarStream (symbol string, price float, volume long); 
from FooStream select symbol, price, volume insert into BarStream;

This query publishes dynamic topic and partitions that are taken from the Siddhi event. The value for partition.no is taken from the volume attribute, and the topic value is taken from the symbol attribute.

kafka-replay-request (Sink)

This sink is used to request replay of specific range of events on a specified partition of a topic.

Syntax

@sink(type="kafka-replay-request", sink.id="<STRING>", @map(...)))

QUERY PARAMETERS

Name	Description	Default Value	Possible Data Types	Optional	Dynamic
sink.id	a unique SINK_ID should be set. This sink id will be used to match with the appropriate kafka-replay-response source		STRING	No	No

Examples EXAMPLE 1

@App:name('TestKafkaReplay')

@sink(type='kafka-replay-request', sink.id='1')
define stream BarStream (topicForReplay string, partitionForReplay string, startOffset string, endOffset string);

@info(name = 'query1')
@source(type='kafka-replay-response',  group.id='group', threading.option='single.thread', bootstrap.servers='localhost:9092', sink.id='1',
@map(type='json'))
Define stream FooStream (symbol string, amount double);

@sink(type='log')
Define stream logStream(symbol string, amount double);

from FooStream select * insert into logStream;

In this app we can send replay request events into BarStream and observe the replayed events in the logStream

kafkaMultiDC (Sink)

A Kafka sink publishes events processed by WSO2 SP to a topic with a partition for a Kafka cluster. The events can be published in the TEXT XML JSON or Binary format.
If the topic is not already created in the Kafka cluster, the Kafka sink creates the default partition for the given topic. The publishing topic and partition can be a dynamic value taken from the Siddhi event.
To configure a sink to publish events via the Kafka transport, and using two Kafka brokers to publish events to the same topic, the type parameter must have kafkaMultiDC as its value.

Syntax

@sink(type="kafkaMultiDC", bootstrap.servers="<STRING>", topic="<STRING>", sequence.id="<STRING>", key="<STRING>", partition.no="<INT>", is.binary.message="<BOOL>", optional.configuration="<STRING>", @map(...)))

QUERY PARAMETERS

Name	Description	Default Value	Possible Data Types	Optional	Dynamic
bootstrap.servers	This parameter specifies the list of Kafka servers to which the Kafka sink must publish events. This list should be provided as a set of comma -separated values. There must be at least two servers in this list. e.g., `localhost:9092,localhost:9093`.		STRING	No	No
topic	The topic to which the Kafka sink needs to publish events. Only one topic must be specified.		STRING	No	No
sequence.id	A unique identifier to identify the messages published by this sink. This ID allows receivers to identify the sink that published a specific message.	null	STRING	Yes	No
key	The key contains the values that are used to maintain ordering in a Kafka partition.	null	STRING	Yes	No
partition.no	The partition number for the given topic. Only one partition ID can be defined. If no value is specified for this parameter, the Kafka sink publishes to the default partition of the topic (i.e., 0)	0	INT	Yes	No
is.binary.message	In order to send the binary events via kafkaMultiDCSink, it is required to set this parameter to `true`.	null	BOOL	No	No
optional.configuration	This parameter contains all the other possible configurations that the producer is created with. e.g., `producer.type:async,batch.size:200`	null	STRING	Yes	No

Examples EXAMPLE 1

@App:name('TestExecutionPlan') 
define stream FooStream (symbol string, price float, volume long); 
@info(name = 'query1') 
@sink(type='kafkaMultiDC', topic='myTopic', partition.no='0',bootstrap.servers='host1:9092, host2:9092', @map(type='xml'))Define stream BarStream (symbol string, price float, volume long);
from FooStream select symbol, price, volume insert into BarStream;

This query publishes to the default (i.e., 0th) partition of the brokers in two data centers

Source

kafka (Source)

A Kafka source receives events to be processed by WSO2 SP from a topic with a partition for a Kafka cluster. The events received can be in the TEXT XML JSON or Binary format.
If the topic is not already created in the Kafka cluster, the Kafka sink creates the default partition for the given topic.

Syntax

@source(type="kafka", bootstrap.servers="<STRING>", topic.list="<STRING>", group.id="<STRING>", threading.option="<STRING>", partition.no.list="<STRING>", seq.enabled="<BOOL>", is.binary.message="<BOOL>", topic.offsets.map="<STRING>", enable.offsets.commit="<BOOL>", enable.async.commit="<BOOL>", optional.configuration="<STRING>", @map(...)))

QUERY PARAMETERS

Name	Description	Default Value	Possible Data Types	Optional	Dynamic
bootstrap.servers	This specifies the list of Kafka servers to which the Kafka source must listen. This list can be provided as a set of comma-separated values. e.g., `localhost:9092,localhost:9093`		STRING	No	No
topic.list	This specifies the list of topics to which the source must listen. This list can be provided as a set of comma-separated values. e.g., `topic_one,topic_two`		STRING	No	No
group.id	This is an ID to identify the Kafka source group. The group ID ensures that sources with the same topic and partition that are in the same group do not receive the same event.		STRING	No	No
threading.option	This specifies whether the Kafka source is to be run on a single thread, or in multiple threads based on a condition. Possible values are as follows: `single.thread`: To run the Kafka source on a single thread. `topic.wise`: To use a separate thread per topic. `partition.wise`: To use a separate thread per partition.		STRING	No	No
partition.no.list	The partition number list for the given topic. This is provided as a list of comma-separated values. e.g., `0,1,2,`.	0	STRING	Yes	No
seq.enabled	If this parameter is set to `true`, the sequence of the events received via the source is taken into account. Therefore, each event should contain a sequence number as an attribute value to indicate the sequence.	false	BOOL	Yes	No
is.binary.message	In order to receive binary events via the Kafka source,it is required to setthis parameter to 'True'.	false	BOOL	Yes	No
topic.offsets.map	This parameter specifies reading offsets for each topic and partition. The value for this parameter is specified in the following format: `<topic>=<offset>,<topic>=<offset>,` When an offset is defined for a topic, the Kafka source skips reading the message with the number specified as the offset as well as all the messages sent previous to that message. If the offset is not defined for a specific topic it reads messages from the beginning. e.g., `stocks=100,trades=50` reads from the 101th message of the `stocks` topic, and from the 51st message of the `trades` topic.	null	STRING	Yes	No
enable.offsets.commit	This parameter specifies whether to commit offsets. If the manual asynchronous offset committing is needed, `enable.offsets.commit` should be `true` and `enable.auto.commit` should be `false`. If periodical committing is needed `enable.offsets.commit` should be `true` and `enable.auto.commit` should be `true`. If committing is not needed, `enable.offsets.commit` should be `false`. Note: `enable.auto.commit` is an `optional.configuration` property. If it is set to `true`, Source will periodically(default: 1000ms. Configurable with `auto.commit.interval.ms` property as an `optional.configuration`) commit its current offset (defined as the offset of the next message to be read) for the partitions it is reading from back to Kafka. To guarantee at-least-once processing, we recommend you to enable Siddhi Periodic State Persistence when `enable.auto.commit` property is set to `true`. During manual committing, it might introduce a latency during consumption.	true	BOOL	Yes	No
enable.async.commit	This parameter will changes the type of the committing offsets returned on the last poll for the subscribed list of topics and partitions. When `enable.async.commit` is set to true, committing will be an asynchronous call.	true	BOOL	Yes	No
optional.configuration	This parameter contains all the other possible configurations that the consumer is created with. e.g., `ssl.keystore.type:JKS,batch.size:200`.	null	STRING	Yes	No

Examples EXAMPLE 1

@App:name('TestExecutionPlan') 
define stream BarStream (symbol string, price float, volume long); 
@info(name = 'query1') 
@source(
type='kafka', 
topic.list='kafka_topic,kafka_topic2', 
group.id='test', 
threading.option='partition.wise', 
bootstrap.servers='localhost:9092', 
partition.no.list='0,1', 
@map(type='xml'))
Define stream FooStream (symbol string, price float, volume long);
from FooStream select symbol, price, volume insert into BarStream;

This kafka source configuration listens to the kafka_topic and kafka_topic2 topics with 0 and 1 partitions. A thread is created for each topic and partition combination. The events are received in the XML format, mapped to a Siddhi event, and sent to a stream named FooStream.

EXAMPLE 2

@App:name('TestExecutionPlan') 
define stream BarStream (symbol string, price float, volume long); 
@info(name = 'query1') 
@source(
type='kafka', 
topic.list='kafka_topic',
group.id='test', 
threading.option='single.thread',
bootstrap.servers='localhost:9092',
@map(type='xml'))
Define stream FooStream (symbol string, price float, volume long);
from FooStream select symbol, price, volume insert into BarStream;

This Kafka source configuration listens to the kafka_topic topic for the default partition because no partition.no.list is defined. Only one thread is created for the topic. The events are received in the XML format, mapped to a Siddhi event, and sent to a stream named FooStream.

EXAMPLE 3

@App:name('TestExecutionPlan')
@source(type='kafka',
        topic.list='trp_topic',
        partition.no.list='0',
        threading.option='single.thread',
        group.id='group',
        bootstrap.servers='localhost:9092',
        @map(type='xml', enclosing.element='//events',             @attributes(symbol ='symbol', price = 'price', volume = 'volume',                         partition = 'trp:partition',                         topic = 'trp:topic', key = 'trp:key',                         recordTimestamp = 'trp:record.timestamp',                          eventTimestamp = 'trp:event.timestamp',                         checkSum = 'trp:check.sum', topicOffset = 'trp:offset')))
define stream FooStream (symbol string, price float, volume long,                                      partition string,                                      topic string, key string,                                      recordTimestamp string,                                      eventTimestamp string, checkSum string,                                      topicOffset string);
from FooStream select * insert into BarStream;

This Kafka source configuration listens to the trp_topic topic for the default partition because no partition.no.list is defined.
Since the custom attribute mapping is enabled with TRP values, the siddhi event will be populated with the relevant trp values as well

kafka-replay-response (Source)

This source is used to listen to replayed events requested from kafka-replay-request sink

Syntax

@source(type="kafka-replay-response", bootstrap.servers="<STRING>", group.id="<STRING>", threading.option="<STRING>", sink.id="<INT>", @map(...)))

QUERY PARAMETERS

Name	Description	Possible Data Types	Optional	Dynamic
bootstrap.servers	This specifies the list of Kafka servers to which the Kafka source must listen. This list can be provided as a set of comma-separated values. e.g., `localhost:9092,localhost:9093`	STRING	No	No
group.id	This is an ID to identify the Kafka source group. The group ID ensures that sources with the same topic and partition that are in the same group do not receive the same event.	STRING	No	No
threading.option	This specifies whether the Kafka source is to be run on a single thread, or in multiple threads based on a condition. Possible values are as follows: `single.thread`: To run the Kafka source on a single thread. `topic.wise`: To use a separate thread per topic. `partition.wise`: To use a separate thread per partition.	STRING	No	No
sink.id	a unique SINK_ID .	INT	No	No

Examples EXAMPLE 1

@App:name('TestKafkaReplay')

@sink(type='kafka-replay-request', sink.id='1')
define stream BarStream (topicForReplay string, partitionForReplay string, startOffset string, endOffset string);

@info(name = 'query1')
@source(type='kafka-replay-response',  group.id='group', threading.option='single.thread', bootstrap.servers='localhost:9092', sink.id='1',
@map(type='json'))
Define stream FooStream (symbol string, amount double);

@sink(type='log')
Define stream logStream(symbol string, amount double);

from FooStream select * insert into logStream;

In this app we can send replay request events into BarStream and observe the replayed events in the logStream

kafkaMultiDC (Source)

The Kafka Multi-Datacenter(DC) source receives records from the same topic in brokers deployed in two different kafka clusters. It filters out all the duplicate messages and ensuresthat the events are received in the correct order using sequential numbering. It receives events in formats such as TEXT, XML JSON and Binary`.The Kafka Source creates the default partition '0' for a given topic, if the topic has not yet been created in the Kafka cluster.

Syntax

@source(type="kafkaMultiDC", bootstrap.servers="<STRING>", topic="<STRING>", partition.no="<INT>", is.binary.message="<BOOL>", optional.configuration="<STRING>", @map(...)))

QUERY PARAMETERS

Name	Description	Default Value	Possible Data Types	Optional	Dynamic
bootstrap.servers	This contains the kafka server list which the kafka source listens to. This is given using comma-separated values. eg: 'localhost:9092,localhost:9093'		STRING	No	No
topic	This is the topic that the source listens to. eg: 'topic_one'		STRING	No	No
partition.no	This is the partition number of the given topic.	0	INT	Yes	No
is.binary.message	In order to receive the binary events via the Kafka Multi-DC source, the value of this parameter needs to be set to 'True'.	false	BOOL	Yes	No
optional.configuration	This contains all the other possible configurations with which the consumer can be created.eg: producer.type:async,batch.size:200	null	STRING	Yes	No

Examples EXAMPLE 1

@App:name('TestExecutionPlan') 
define stream BarStream (symbol string, price float, volume long); 
@info(name = 'query1') 
@source(type='kafkaMultiDC', topic='kafka_topic', bootstrap.servers='host1:9092,host1:9093', partition.no='1', @map(type='xml'))
Define stream FooStream (symbol string, price float, volume long);
from FooStream select symbol, price, volume insert into BarStream;

The following query listens to 'kafka_topic' topic, deployed in the broker host1:9092 and host1:9093, with partition 1. A thread is created for each broker. The receiving xml events are mapped to a siddhi event and sent to the FooStream.