Read Structured Streaming state information

  • Article

Important

This feature is in Public Preview.

In Databricks Runtime 14.3 LTS and above, you can use DataFrame operations or SQL table-value functions to query Structured Streaming state data and metadata. You can use these functions to observe state information for Structured Streaming stateful queries, which can be useful for monitoring and debugging.

You must have read access to the checkpoint path for a streaming query in order to query state data or metadata. The functions described in this article provide read-only access to state data and metadata. You can only use batch read semantics to query state information.

Note

You cannot query state information for Delta Live Tables pipelines, streaming tables, or materialized views.

Read Structured Streaming state store

You can read state store information for Structured Streaming queries executed in any supported Databricks Runtime. Use the following syntax:

Python

df = (spark.read
  .format("statestore")
  .load("/checkpoint/path"))

SQL

SELECT * FROM read_statestore('/checkpoint/path')

The following optional configurations are supported:

Option Type Default value
batchId Long latest batch ID
operatorId Long 0
storeName String "DEFAULT"
joinSide String ("left" or "right") Represents the target side to read from. This option is used when users want to read the state from stream-stream join.

The returned data has the following schema:

Column Type Description
key Struct (further type derived from the state key) The key for a stateful operator record in the state checkpoint.
value Struct (further type derived from the state value) The value for a stateful operator record in the state checkpoint.
partition_id Integer The partition of the state checkpoint that contains the stateful operator record.

Read Structured Streaming state metadata

Important

You must run streaming queries on Databricks Runtime 14.2 or above to record state metadata. State metadata files do not break backward compatibility. If you choose to run a streaming query on Databricks Runtime 14.1 or below, existing state metadata files are ignored and no new state metadata files are written.

You can read state metadata information for Structured Streaming queries run on Databricks Runtime 14.2 or above. Use the following syntax:

Python

df = (spark.read
  .format("state-metadata")
  .load("<checkpointLocation>"))

SQL

SELECT * FROM read_state_metadata('/checkpoint/path')

The returned data has the following schema:

Column Type Description
operatorId Integer The integer ID of the stateful streaming operator.
operatorName Integer Name of the stateful streaming operator.
stateStoreName String Name of the state store of the operator.
numPartitions Integer Number of partitions of the state store.
minBatchId Long The minimum batch ID available for querying state.
maxBatchId Long The maximum batch ID available for querying state.

Note

The batch ID values provided by minBatchId and maxBatchId reflect the state at the time the checkpoint was written. Old batches are cleaned up automatically with micro-batch execution, so the value provided here is not guaranteed to still be available.