Github user budde commented on a diff in the pull request:
https://github.com/apache/spark/pull/17467#discussion_r112817123
--- Diff: docs/streaming-kinesis-integration.md ---
@@ -216,3 +216,7 @@ de-aggregate records during consumption.
- If no Kinesis checkpoint info exists when the input DStream starts, it
will start either from the oldest record available
(`InitialPositionInStream.TRIM_HORIZON`) or from the latest tip
(`InitialPositionInStream.LATEST`). This is configurable.
- `InitialPositionInStream.LATEST` could lead to missed records if data
is added to the stream while no input DStreams are running (and no checkpoint
info is being stored).
- `InitialPositionInStream.TRIM_HORIZON` may lead to duplicate
processing of records where the impact is dependent on checkpoint frequency and
processing idempotency.
+
+- Kinesis retry configurations
--- End diff --
@brkyvz or another Spark committer might have better suggestions here, but
I would suggest making this section a new heading (rather than part of
**Kinesis Checkpointing**) and adding a brief explanatory sentence, e.g.:
```
#### Kinesis retry configuration
- A Kinesis DStream will retry any failed request to the Kinesis API. The
following SparkConf properties can be set in order to customize the behavior of
the retry logic:
```
followed by the rest of your changes here.
This also reminds me that I owe @brkyvz a change to add docs for the stream
builder interface here :)
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