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From zsxwing <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-2629][STREAMING] Basic implementation o...
Date Tue, 10 Nov 2015 21:52:30 GMT
Github user zsxwing commented on a diff in the pull request:

    https://github.com/apache/spark/pull/9256#discussion_r44470724
  
    --- Diff: streaming/src/main/scala/org/apache/spark/streaming/StateSpec.scala ---
    @@ -0,0 +1,212 @@
    +/*
    + * 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
    +
    +import scala.reflect.ClassTag
    +
    +import org.apache.spark.annotation.Experimental
    +import org.apache.spark.api.java.JavaPairRDD
    +import org.apache.spark.rdd.RDD
    +import org.apache.spark.util.ClosureCleaner
    +import org.apache.spark.{HashPartitioner, Partitioner}
    +
    +
    +/**
    + * :: Experimental ::
    + * Abstract class representing all the specifications of the DStream transformation
    + * `trackStateByKey` operation of a
    + * [[org.apache.spark.streaming.dstream.PairDStreamFunctions pair DStream]] (Scala) or
a
    + * [[org.apache.spark.streaming.api.java.JavaPairDStream JavaPairDStream]] (Java).
    + * Use the [[org.apache.spark.streaming.StateSpec StateSpec.apply()]] or
    + * [[org.apache.spark.streaming.StateSpec StateSpec.create()]] to create instances of
    + * this class.
    + *
    + * Example in Scala:
    + * {{{
    + *    def trackingFunction(data: Option[ValueType], wrappedState: State[StateType]):
EmittedType = {
    + *      ...
    + *    }
    + *
    + *    val spec = StateSpec.function(trackingFunction).numPartitions(10)
    + *
    + *    val emittedRecordDStream = keyValueDStream.trackStateByKey[StateType, EmittedDataType](spec)
    + * }}}
    + *
    + * Example in Java:
    + * {{{
    + *    StateStateSpec[KeyType, ValueType, StateType, EmittedDataType] spec =
    + *      StateStateSpec.function[KeyType, ValueType, StateType, EmittedDataType](trackingFunction)
    + *                    .numPartition(10);
    + *
    + *    JavaDStream[EmittedDataType] emittedRecordDStream =
    + *      javaPairDStream.trackStateByKey[StateType, EmittedDataType](spec);
    + * }}}
    + */
    +@Experimental
    +sealed abstract class StateSpec[KeyType, ValueType, StateType, EmittedType] extends Serializable
{
    +
    +  /** Set the RDD containing the initial states that will be used by `trackStateByKey`
*/
    +  def initialState(rdd: RDD[(KeyType, StateType)]): this.type
    +
    +  /** Set the RDD containing the initial states that will be used by `trackStateByKey`
*/
    +  def initialState(javaPairRDD: JavaPairRDD[KeyType, StateType]): this.type
    +
    +  /**
    +   * Set the number of partitions by which the state RDDs generated by `trackStateByKey`
    +   * will be partitioned. Hash partitioning will be used.
    +   */
    +  def numPartitions(numPartitions: Int): this.type
    +
    +  /**
    +   * Set the partitioner by which the state RDDs generated by `trackStateByKey` will
be
    +   * be partitioned.
    +   */
    +  def partitioner(partitioner: Partitioner): this.type
    +
    +  /**
    +   * Set the duration after which the state of an idle key will be removed. A key and
its state is
    +   * considered idle if it has not received any data for at least the given duration.
The state
    +   * tracking function will be called one final time on the idle states that are going
to be
    +   * removed; [[org.apache.spark.streaming.State State.isTimingOut()]] set
    +   * to `true` in that call.
    +   */
    +  def timeout(idleDuration: Duration): this.type
    +}
    +
    +
    +/**
    + * :: Experimental ::
    + * Builder object for creating instances of [[org.apache.spark.streaming.StateSpec StateSpec]]
    + * that is used for specifying the parameters of the DStream transformation
    + * `trackStateByKey` operation of a
    + * [[org.apache.spark.streaming.dstream.PairDStreamFunctions pair DStream]] (Scala) or
a
    + * [[org.apache.spark.streaming.api.java.JavaPairDStream JavaPairDStream]] (Java).
    + *
    + * Example in Scala:
    + * {{{
    + *    def trackingFunction(data: Option[ValueType], wrappedState: State[StateType]):
EmittedType = {
    + *      ...
    + *    }
    + *
    + *    val spec = StateSpec.function(trackingFunction).numPartitions(10)
    + *
    + *    val emittedRecordDStream = keyValueDStream.trackStateByKey[StateType, EmittedDataType](spec)
    + * }}}
    + *
    + * Example in Java:
    + * {{{
    + *    StateStateSpec[KeyType, ValueType, StateType, EmittedDataType] spec =
    + *      StateStateSpec.function[KeyType, ValueType, StateType, EmittedDataType](trackingFunction)
    + *                    .numPartition(10);
    + *
    + *    JavaDStream[EmittedDataType] emittedRecordDStream =
    + *      javaPairDStream.trackStateByKey[StateType, EmittedDataType](spec);
    + * }}}
    + */
    +@Experimental
    +object StateSpec {
    +  /**
    +   * Create a [[org.apache.spark.streaming.StateSpec StateSpec]] for setting all the
specifications
    +   * `trackStateByKey` operation on a
    +   * [[org.apache.spark.streaming.dstream.PairDStreamFunctions pair DStream]] (Scala)
or a
    +   * [[org.apache.spark.streaming.api.java.JavaPairDStream JavaPairDStream]] (Java).
    +   * @param trackingFunction The function applied on every data item to manage the associated
state
    +   *                         and generate the emitted data
    +   * @tparam KeyType      Class of the keys
    +   * @tparam ValueType    Class of the values
    +   * @tparam StateType    Class of the states data
    +   * @tparam EmittedType  Class of the emitted data
    +   */
    +  def function[KeyType, ValueType, StateType, EmittedType](
    +      trackingFunction: (Time, KeyType, Option[ValueType], State[StateType]) => Option[EmittedType]
    +    ): StateSpec[KeyType, ValueType, StateType, EmittedType] = {
    +    ClosureCleaner.clean(trackingFunction, checkSerializable = true)
    +    new StateSpecImpl(trackingFunction)
    +  }
    +
    +  /**
    +   * Create a [[org.apache.spark.streaming.StateSpec StateSpec]] for setting all the
specifications
    +   * `trackStateByKey` operation on a
    +   * [[org.apache.spark.streaming.dstream.PairDStreamFunctions pair DStream]] (Scala)
or a
    +   * [[org.apache.spark.streaming.api.java.JavaPairDStream JavaPairDStream]] (Java).
    +   * @param trackingFunction The function applied on every data item to manage the associated
state
    +   *                         and generate the emitted data
    +   * @tparam ValueType    Class of the values
    +   * @tparam StateType    Class of the states data
    +   * @tparam EmittedType  Class of the emitted data
    +   */
    +  def function[ValueType, StateType, EmittedType](
    +      trackingFunction: (Option[ValueType], State[StateType]) => EmittedType
    +    ): StateSpec[Any, ValueType, StateType, EmittedType] = {
    --- End diff --
    
    `StateSpec[Any, ValueType, StateType, EmittedType]` will require the user to cast the
type if he wants to use the key type. Right?


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