Github user koeninger commented on a diff in the pull request:
https://github.com/apache/spark/pull/3798#discussion_r24019904
--- 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 --
I think we want the first sentence of the doc to convey why someone would
choose this method.
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