/*
 * 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.
 */

// scalastyle:off println
package org.apache.spark.examples.streaming

import org.apache.spark.SparkConf
import org.apache.spark.storage.StorageLevel
import org.apache.spark.streaming._
import org.apache.spark.util.IntParam

/**
 * Receives text from multiple rawNetworkStreams and counts how many '\n' delimited
 * lines have the word 'the' in them. This is useful for benchmarking purposes. This
 * will only work with spark.streaming.util.RawTextSender running on all worker nodes
 * and with Spark using Kryo serialization (set Java property "spark.serializer" to
 * "org.apache.spark.serializer.KryoSerializer").
 * Usage: RawNetworkGrep <numStreams> <host> <port> <batchMillis>
 *   <numStream> is the number rawNetworkStreams, which should be same as number
 *               of work nodes in the cluster
 *   <host> is "localhost".
 *   <port> is the port on which RawTextSender is running in the worker nodes.
 *   <batchMillise> is the Spark Streaming batch duration in milliseconds.
 */
object RawNetworkGrep {
  def main(args: Array[String]) {
    if (args.length != 4) {
      System.err.println("Usage: RawNetworkGrep <numStreams> <host> <port> <batchMillis>")
      System.exit(1)
    }

    StreamingExamples.setStreamingLogLevels()

    val Array(IntParam(numStreams), host, IntParam(port), IntParam(batchMillis)) = args
    val sparkConf = new SparkConf().setAppName("RawNetworkGrep")
    // Create the context
    val ssc = new StreamingContext(sparkConf, Duration(batchMillis))

    val rawStreams = (1 to numStreams).map(_ =>
      ssc.rawSocketStream[String](host, port, StorageLevel.MEMORY_ONLY_SER_2)).toArray
    val union = ssc.union(rawStreams)
    union.filter(_.contains("the")).count().foreachRDD(r =>
      println("Grep count: " + r.collect().mkString))
    ssc.start()
    ssc.awaitTermination()
  }
}
// scalastyle:on println
