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From helena <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-4964] [Streaming] Exactly-once semantic...
Date Thu, 08 Jan 2015 12:04:47 GMT
Github user helena commented on a diff in the pull request:

    https://github.com/apache/spark/pull/3798#discussion_r22648091
  
    --- Diff: external/kafka/src/main/scala/org/apache/spark/streaming/kafka/DeterministicKafkaInputDStream.scala
---
    @@ -0,0 +1,119 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one or more
    + * contributor license agreements.  See the NOTICE file distributed with
    + * this work for additional information regarding copyright ownership.
    + * The ASF licenses this file to You under the Apache License, Version 2.0
    + * (the "License"); you may not use this file except in compliance with
    + * the License.  You may obtain a copy of the License at
    + *
    + *    http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.spark.streaming.kafka
    +
    +import scala.annotation.tailrec
    +import scala.reflect.{classTag, ClassTag}
    +
    +import kafka.common.TopicAndPartition
    +import kafka.message.MessageAndMetadata
    +import kafka.serializer.Decoder
    +
    +import org.apache.spark.Logging
    +import org.apache.spark.rdd.RDD
    +import org.apache.spark.rdd.kafka.{KafkaCluster, KafkaRDD}
    +import org.apache.spark.streaming.{StreamingContext, Time}
    +import org.apache.spark.streaming.dstream._
    +
    +/** A stream of {@link org.apache.spark.rdd.kafka.KafkaRDD} where
    +  * each given Kafka topic/partition corresponds to an RDD partition.
    +  * The spark configuration spark.streaming.receiver.maxRate gives the maximum number
of messages
    +  * per second that each '''partition''' will accept.
    +  * Starting offsets are specified in advance,
    +  * and this DStream is not responsible for committing offsets,
    +  * so that you can control exactly-once semantics.
    +  * For an easy interface to Kafka-managed offsets,
    +  *  see {@link org.apache.spark.rdd.kafka.KafkaCluster}
    +  * @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 fromOffsets per-topic/partition Kafka offsets defining the (inclusive)
    +  *  starting point of the stream
    +  * @param messageHandler function for translating each message into the desired type
    +  * @param maxRetries maximum number of times in a row to retry getting leaders' offsets
    +  */
    +class DeterministicKafkaInputDStream[
    +  K: ClassTag,
    +  V: ClassTag,
    +  U <: Decoder[_]: ClassTag,
    +  T <: Decoder[_]: ClassTag,
    +  R: ClassTag](
    +    @transient ssc_ : StreamingContext,
    +    val kafkaParams: Map[String, String],
    +    val fromOffsets: Map[TopicAndPartition, Long],
    +    messageHandler: MessageAndMetadata[K, V] => R,
    +    maxRetries: Int = 1
    +) extends InputDStream[R](ssc_) with Logging {
    +
    +  private val kc = new KafkaCluster(kafkaParams)
    +
    +  private val maxMessagesPerPartition: Option[Long] = {
    +    val ratePerSec = context.sparkContext.getConf.getInt("spark.streaming.receiver.maxRate",
0)
    +    if (ratePerSec > 0) {
    +      val secsPerBatch = context.graph.batchDuration.milliseconds.toDouble / 1000
    +      Some((secsPerBatch * ratePerSec).toLong)
    +    } else {
    +      None
    +    }
    +  }
    +
    +  private var currentOffsets = fromOffsets
    +
    +  @tailrec
    +  private def latestLeaderOffsets(retries: Int): Map[TopicAndPartition, Long] = {
    +    val o = kc.getLatestLeaderOffsets(currentOffsets.keys.toSet)
    --- End diff --
    
    currentOffsets.keySet


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