spark-states

Custom state store providers for Apache Spark

View the Project on GitHub chermenin/spark-states

Custom state store providers for Apache Spark

Build Status

Custom State Stores for Apache Spark to keep data between micro-batches for stateful stream processing.

Motivation

Out of the box, Apache Spark has only one implementation of state store providers. It’s HDFSBackedStateStoreProvider which stores all of the data in memory, what is a very memory consuming approach. To avoid OutOfMemory errors, this repository and custom state store providers were created.

Usage

To use the custom state store provider for your pipelines use the following additional configuration for the submit script:

--conf spark.sql.streaming.stateStore.providerClass="ru.chermenin.spark.sql.execution.streaming.state.RocksDbStateStoreProvider"

Here is some more information about it: https://docs.databricks.com/spark/latest/structured-streaming/production.html

State Timeout

With semantics similar to those of GroupState/ FlatMapGroupWithState, state timeout features have been built directly into the custom state store.

Important points to note when using State Timeouts,

To configure state timeout, additional configuration can be added,

--conf spark.sql.streaming.stateStore.stateExpirySecs=5
--conf spark.sql.streaming.stateStore.strictExpire=true

Other state timeout related points,

Contributing

You’re welcome to submit pull requests with any changes for this repository at any time. I’ll be very glad to see any contributions.

License

The standard Apache 2.0 license is used for this project.