Github user lw-lin commented on a diff in the pull request:
https://github.com/apache/spark/pull/15679#discussion_r85641731
--- Diff: docs/streaming-kafka-0-10-integration.md ---
@@ -120,15 +184,24 @@ Kafka has an offset commit API that stores offsets in
a special Kafka topic. By
<div class="codetabs">
<div data-lang="scala" markdown="1">
stream.foreachRDD { rdd =>
- val offsets = rdd.asInstanceOf[HasOffsetRanges].offsetRanges
+ val offsetRanges = rdd.asInstanceOf[HasOffsetRanges].offsetRanges
// some time later, after outputs have completed
- stream.asInstanceOf[CanCommitOffsets].commitAsync(offsets)
+ stream.asInstanceOf[CanCommitOffsets].commitAsync(offsetRanges)
}
As with HasOffsetRanges, the cast to CanCommitOffsets will only succeed if
called on the result of createDirectStream, not after transformations. The
commitAsync call is threadsafe, but must occur after outputs if you want
meaningful semantics.
</div>
<div data-lang="java" markdown="1">
+ stream.foreachRDD(new VoidFunction<JavaRDD<ConsumerRecord<String,
String>>>() {
+ @Override
+ public void call(JavaRDD<ConsumerRecord<String, String>> rdd) {
+ OffsetRange[] offsetRanges = ((HasOffsetRanges)
rdd.rdd()).offsetRanges();
+
+ // some time later, after outputs have completed
+ ((CanCommitOffsets)
stream.inputDStream()).commitAsync(offsetRanges);
--- End diff --
thanks Cody. sorry for not being clear, but my point was that the Java
kafka input stream does not implements `CanCommitOffsets`, thus it has to
delegate `commitAsync(...)` explicitly to `stream.inputDStream()`, which is a
scala input stream which implements `CanCommitOffsets`.
should we return a java kafka inputdstream that also implements
`CanCommitOffsets` when we `createDirectStream()` in java?
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