Repository: spark Updated Branches: refs/heads/master b374a2583 -> 93db50d1c
[SPARK-12487][STREAMING][DOCUMENT] Add docs for Kafka message handler Author: Shixiong Zhu <shixi...@databricks.com> Closes #10439 from zsxwing/kafka-message-handler-doc. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/93db50d1 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/93db50d1 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/93db50d1 Branch: refs/heads/master Commit: 93db50d1c2ff97e6eb9200a995e4601f752968ae Parents: b374a25 Author: Shixiong Zhu <shixi...@databricks.com> Authored: Tue Dec 22 15:33:30 2015 -0800 Committer: Tathagata Das <tathagata.das1...@gmail.com> Committed: Tue Dec 22 15:33:30 2015 -0800 ---------------------------------------------------------------------- docs/streaming-kafka-integration.md | 3 +++ 1 file changed, 3 insertions(+) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/93db50d1/docs/streaming-kafka-integration.md ---------------------------------------------------------------------- diff --git a/docs/streaming-kafka-integration.md b/docs/streaming-kafka-integration.md index 5be73c4..9454714 100644 --- a/docs/streaming-kafka-integration.md +++ b/docs/streaming-kafka-integration.md @@ -104,6 +104,7 @@ Next, we discuss how to use this approach in your streaming application. [key class], [value class], [key decoder class], [value decoder class] ]( streamingContext, [map of Kafka parameters], [set of topics to consume]) + You can also pass a `messageHandler` to `createDirectStream` to access `MessageAndMetadata` that contains metadata about the current message and transform it to any desired type. See the [API docs](api/scala/index.html#org.apache.spark.streaming.kafka.KafkaUtils$) and the [example]({{site.SPARK_GITHUB_URL}}/blob/master/examples/src/main/scala/org/apache/spark/examples/streaming/DirectKafkaWordCount.scala). </div> @@ -115,6 +116,7 @@ Next, we discuss how to use this approach in your streaming application. [key class], [value class], [key decoder class], [value decoder class], [map of Kafka parameters], [set of topics to consume]); + You can also pass a `messageHandler` to `createDirectStream` to access `MessageAndMetadata` that contains metadata about the current message and transform it to any desired type. See the [API docs](api/java/index.html?org/apache/spark/streaming/kafka/KafkaUtils.html) and the [example]({{site.SPARK_GITHUB_URL}}/blob/master/examples/src/main/java/org/apache/spark/examples/streaming/JavaDirectKafkaWordCount.java). @@ -123,6 +125,7 @@ Next, we discuss how to use this approach in your streaming application. from pyspark.streaming.kafka import KafkaUtils directKafkaStream = KafkaUtils.createDirectStream(ssc, [topic], {"metadata.broker.list": brokers}) + You can also pass a `messageHandler` to `createDirectStream` to access `KafkaMessageAndMetadata` that contains metadata about the current message and transform it to any desired type. By default, the Python API will decode Kafka data as UTF8 encoded strings. You can specify your custom decoding function to decode the byte arrays in Kafka records to any arbitrary data type. See the [API docs](api/python/pyspark.streaming.html#pyspark.streaming.kafka.KafkaUtils) and the [example]({{site.SPARK_GITHUB_URL}}/blob/master/examples/src/main/python/streaming/direct_kafka_wordcount.py). </div> --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org
