Frederick Reiss created SPARK-16963:
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Summary: Change Source API so that sources do not need to keep
unbounded state
Key: SPARK-16963
URL: https://issues.apache.org/jira/browse/SPARK-16963
Project: Spark
Issue Type: Improvement
Components: Streaming
Affects Versions: 2.0.0
Reporter: Frederick Reiss
The version of the Source API in Spark 2.0.0 defines a single getBatch() method
for fetching records from the source, with the following Scaladoc comments
defining the semantics:
{noformat}
/**
* Returns the data that is between the offsets (`start`, `end`]. When `start`
is `None` then
* the batch should begin with the first available record. This method must
always return the
* same data for a particular `start` and `end` pair.
*/
def getBatch(start: Option[Offset], end: Offset): DataFrame
{noformat}
These semantics mean that a Source must retain all past history for the stream
that it backs. Further, a Source is also required to retain this data across
restarts of the process where the Source is instantiated, even when the Source
is restarted on a different machine.
These restrictions make it difficult to implement the Source API, as any
implementation requires potentially unbounded amounts of distributed storage.
See the mailing list thread at
[http://apache-spark-developers-list.1001551.n3.nabble.com/Source-API-requires-unbounded-distributed-storage-td18551.html]
for more information.
This JIRA will cover augmenting the Source API with an additional callback that
will allow Structured Streaming scheduler to notify the source when it is safe
to discard buffered data.
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