![]() (It is recommended to define attribute names in camelCase.) The schema of an stream is defined by its attributes with uniquely identifiable attribute names. (It is recommended to define a stream name in PascalCase.) The following parameters are configured in a stream definition. The syntax for defining a new stream is as follows. This enables them to be processed via queries using their defined attributes in a streaming manner, and allow sinks and sources to map events to/from various data formats. Its schema is defined via the stream definition.Ī stream definition contains a unique name and a set of attributes with specific types and uniquely identifiable names within the stream.Īll the events that are selected to be received into a specific stream have the same schema (i.e., have the same attributes in the same order).īy defining a schema it unifies common types of events together. stream TempStream (deviceID long, roomNo int, temp = '5minAvgQuery')Ī stream is a logical series of events ordered in time. Siddhi Application named Temperature-Analytics defined with a stream named TempStream and a query Here, a separate instance of queries is generated for each partition key to achieve isolation.Ī positionable stream that connects portioned queries within their partitions, preserving isolation.Īn element of Siddhi SQL can be composed together as a script in a Siddhi application, Here each construct must be separatedīy a semicolon ( ) as shown in the below syntax. format) to a Siddhi event, and passes that to a Stream for processing.Ī contract that takes events arriving at a stream, maps them to a predefined data format (such as XML, JSON, binary, etc), and publishes them to external endpoints (such as E-mail, TCP, Kafka, HTTP, etc).Ī mechanism to programmatically inject events into streams.Ī mechanism to programmatically consume output events from streams and queries.Ī logical container that isolates the processing of queries based on partition keys. ![]() Then it processes these events in a streaming manner and publishes the output events to streams or tables for further processing or to generate notifications.Ī contract that consumes data from external sources (such as TCP, Kafka, HTTP, etc)in the form of events, then converts each event (which can be in XML, JSON, binary, etc. A query consumes one or more input streams, and zero or one table. to be accessed and manipulated at runtime.Ī logical construct that processes events in streaming manner by combining existing streams and/or tables, and generates events to an output stream or table. Stored data can be backed by In-Memory, RDBMs, MongoDB, etc. An event contains a timestamp and set of attribute values according to the schema.Ī structured representation of data stored with a defined schema. ![]() ElementsĪ logical series of events ordered in time with a uniquely identifiable name, and set of defined attributes with specific data types defining its schema.Īn event is associated with only one stream, and all events of that stream have an identical set of attributes that are assigned specific types (or the same schema). The following diagram depicts how event flows work with some of the key Siddhi Streaming SQL elementsīelow table provides brief description of a few key elements in the Siddhi Streaming SQL Language. Together as a SiddhiApp in a single file.Įach Siddhi Application is an isolated processing unit that allows you to deploy and execute queries independent of other Siddhi applications in the system. Streaming processing and Complex Event Processing rules can be written is Siddhi Streaming SQL and they can be put Siddhi Streaming SQL is designed to process event streams in a streaming manner, detect complex event occurrences,Īnd notify them in real-time. Siddhi 4.x Streaming SQL Guide ¶ Introduction ¶ Configuring and Monitoring Siddhi Applications
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