pegasas commented on code in PR #23135:
URL: https://github.com/apache/flink/pull/23135#discussion_r1285223853
##########
docs/content/docs/concepts/stateful-stream-processing.md:
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@@ -342,26 +342,3 @@ give *exactly once* guarantees even in *at least once*
mode.
{{< /hint >}}
{{< top >}}
-
-## State and Fault Tolerance in Batch Programs
-
-Flink executes [batch programs]({{< ref "docs/dev/dataset/overview" >}}) as a
special case of
-streaming programs, where the streams are bounded (finite number of elements).
-A *DataSet* is treated internally as a stream of data. The concepts above thus
-apply to batch programs in the same way as well as they apply to streaming
-programs, with minor exceptions:
-
- - [Fault tolerance for batch programs]({{< ref
"docs/ops/state/task_failure_recovery" >}})
- does not use checkpointing. Recovery happens by fully replaying the
- streams. That is possible, because inputs are bounded. This pushes the
- cost more towards the recovery, but makes the regular processing cheaper,
- because it avoids checkpoints.
-
- - Stateful operations in the DataSet API use simplified in-memory/out-of-core
- data structures, rather than key/value indexes.
-
- - The DataSet API introduces special synchronized (superstep-based)
- iterations, which are only possible on bounded streams. For details, check
- out the [iteration docs]({{< ref "docs/dev/dataset/iterations" >}}).
Review Comment:
sure.
This is a good point.
I will search the others to see if any other same pattern, which could be
executed in BATCH mode.
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