Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/3798#discussion_r23822726
--- Diff:
external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaUtils.scala
---
@@ -144,4 +149,182 @@ 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 batch Each OffsetRange in the batch corresponds to a
+ * range of offsets for a given Kafka topic/partition
+ */
+ def createRDD[
+ K: ClassTag,
+ V: ClassTag,
+ U <: Decoder[_]: ClassTag,
+ T <: Decoder[_]: ClassTag,
+ R: ClassTag] (
+ sc: SparkContext,
+ kafkaParams: Map[String, String],
+ batch: Array[OffsetRange]
+ ): RDD[(K, V)] with HasOffsetRanges = {
+ val messageHandler = (mmd: MessageAndMetadata[K, V]) => (mmd.key,
mmd.message)
+ val kc = new KafkaCluster(kafkaParams)
+ val topics = batch.map(o => TopicAndPartition(o.topic,
o.partition)).toSet
+ val leaderMap = kc.findLeaders(topics).fold(
+ errs => throw new SparkException(errs.mkString("\n")),
+ ok => ok
+ )
+ val rddParts = batch.zipWithIndex.map { case (o, i) =>
+ val tp = TopicAndPartition(o.topic, o.partition)
+ val (host, port) = leaderMap(tp)
+ new KafkaRDDPartition(i, o.topic, o.partition, o.fromOffset,
o.untilOffset, host, port)
+ }.toArray
+ new KafkaRDD[K, V, U, T, (K, V)](sc, kafkaParams, rddParts,
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 batch 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
+ */
+ def createRDD[
+ K: ClassTag,
+ V: ClassTag,
+ U <: Decoder[_]: ClassTag,
+ T <: Decoder[_]: ClassTag,
+ R: ClassTag] (
+ sc: SparkContext,
+ kafkaParams: Map[String, String],
+ batch: Array[OffsetRange],
+ leaders: Array[Leader],
+ messageHandler: MessageAndMetadata[K, V] => R
+ ): RDD[R] with HasOffsetRanges = {
+ val leaderMap = leaders.map(l => (l.topic, l.partition) -> (l.host,
l.port)).toMap
+ val rddParts = batch.zipWithIndex.map { case (o, i) =>
+ val (host, port) = leaderMap((o.topic, o.partition))
+ new KafkaRDDPartition(i, o.topic, o.partition, o.fromOffset,
o.untilOffset, host, port)
+ }.toArray
+
+ new KafkaRDD[K, V, U, T, R](sc, kafkaParams, rddParts, messageHandler)
+ }
+
+ /**
+ * Compared to `createStream`, the stream created by this can guarantee
that each message
--- End diff --
A scala doc has to start with this method does, not with a comparison with
another method. Then for understanding this method, they will have to read
another method first. That's not good. In future if we deprecate the other
method, then even worse. Its best to say what this method does independent of
anything else, and as a second para (for those who want to understand more),
compare with the other method.
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