Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/3798#discussion_r24028967
--- Diff:
external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaUtils.scala
---
@@ -144,4 +150,174 @@ object KafkaUtils {
createStream[K, V, U, T](
jssc.ssc, kafkaParams.toMap,
Map(topics.mapValues(_.intValue()).toSeq: _*), storageLevel)
}
+
+ /** A batch-oriented interface for consuming from Kafka.
+ * Starting and ending offsets are specified in advance,
+ * so that you can control exactly-once semantics.
+ * @param sc SparkContext object
+ * @param kafkaParams Kafka <a
href="http://kafka.apache.org/documentation.html#configuration";>
+ * configuration parameters</a>.
+ * Requires "metadata.broker.list" or "bootstrap.servers" to be set
with Kafka broker(s),
+ * NOT zookeeper servers, specified in host1:port1,host2:port2 form.
+ * @param offsetRanges Each OffsetRange in the batch corresponds to a
+ * range of offsets for a given Kafka topic/partition
+ */
+ @Experimental
+ def createRDD[
+ K: ClassTag,
+ V: ClassTag,
+ U <: Decoder[_]: ClassTag,
+ T <: Decoder[_]: ClassTag] (
+ sc: SparkContext,
+ kafkaParams: Map[String, String],
+ offsetRanges: Array[OffsetRange]
+ ): RDD[(K, V)] with HasOffsetRanges = {
+ val messageHandler = (mmd: MessageAndMetadata[K, V]) => (mmd.key,
mmd.message)
+ val kc = new KafkaCluster(kafkaParams)
+ val topics = offsetRanges.map(o => TopicAndPartition(o.topic,
o.partition)).toSet
+ val leaders = kc.findLeaders(topics).fold(
+ errs => throw new SparkException(errs.mkString("\n")),
+ ok => ok
+ )
+ new KafkaRDD[K, V, U, T, (K, V)](sc, kafkaParams, offsetRanges,
leaders, messageHandler)
+ }
+
+ /** A batch-oriented interface for consuming from Kafka.
+ * Starting and ending offsets are specified in advance,
+ * so that you can control exactly-once semantics.
+ * @param sc SparkContext object
+ * @param kafkaParams Kafka <a
href="http://kafka.apache.org/documentation.html#configuration";>
+ * configuration parameters</a>.
+ * Requires "metadata.broker.list" or "bootstrap.servers" to be set
with Kafka broker(s),
+ * NOT zookeeper servers, specified in host1:port1,host2:port2 form.
+ * @param offsetRanges Each OffsetRange in the batch corresponds to a
+ * range of offsets for a given Kafka topic/partition
+ * @param leaders Kafka leaders for each offset range in batch
+ * @param messageHandler function for translating each message into the
desired type
+ */
+ @Experimental
+ def createRDD[
+ K: ClassTag,
+ V: ClassTag,
+ U <: Decoder[_]: ClassTag,
+ T <: Decoder[_]: ClassTag,
+ R: ClassTag] (
+ sc: SparkContext,
+ kafkaParams: Map[String, String],
+ offsetRanges: Array[OffsetRange],
+ leaders: Array[Leader],
+ messageHandler: MessageAndMetadata[K, V] => R
+ ): RDD[R] with HasOffsetRanges = {
+
+ val leaderMap = leaders
+ .map(l => TopicAndPartition(l.topic, l.partition) -> (l.host,
l.port))
+ .toMap
+ new KafkaRDD[K, V, U, T, R](sc, kafkaParams, offsetRanges, leaderMap,
messageHandler)
+ }
+
+ /**
+ * This stream can guarantee that each message from Kafka is included in
transformations
--- End diff --
That applies to people who already know what "createStream" does. But think
about the people who is looking at KafkaUtilsl forthe first time, and happens
to look upon this method first. Unless the first sentence conveys what this
does, they will get extremely confused.
As a developer I think the question i need answering first is "what does
this do". "what does this do different from the other one" comes second, and
only after I know what this one does.
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