Github user pwendell commented on a diff in the pull request:

    https://github.com/apache/spark/pull/3798#discussion_r23990370
  
    --- 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
    +   * (as opposed to output actions) exactly once, even in most failure 
situations.
    +   *
    +   * Points to note:
    +   *
    +   * Failure Recovery - You must checkpoint this stream, or save offsets 
yourself and provide them
    +   * as the fromOffsets parameter on restart.
    +   * Kafka must have sufficient log retention to obtain messages after 
failure.
    +   *
    +   * Getting offsets from the stream - see programming guide
    +   *
    +.  * Zookeeper - This does not use Zookeeper to store offsets.  For 
interop with Kafka monitors
    +   * that depend on Zookeeper, you must store offsets in ZK yourself.
    +   *
    +   * End-to-end semantics - This does not guarantee that any output 
operation will push each record
    +   * exactly once. To ensure end-to-end exactly-once semantics (that is, 
receiving exactly once and
    +   * outputting exactly once), you have to either ensure that the output 
operation is
    +   * idempotent, or transactionally store offsets with the output. See the 
programming guide for
    +   * more details.
    +   *
    +   * @param ssc StreamingContext 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 messageHandler function for translating each message into the 
desired type
    +   * @param fromOffsets per-topic/partition Kafka offsets defining the 
(inclusive)
    +   *  starting point of the stream
    +   */
    +  @Experimental
    +  def createNewStream[
    --- End diff --
    
    What about `createDirectStream` or something that conveys we are reading 
directly from Kafka rather than going through receivers. The issue with "new" 
is that in short time this won't be new anymore, in fact it will be the main 
one we ask people to use, most likely.


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