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spark streaming的入門案例

1, spark streaming: tcp 源

maven依賴:

<dependency>
    <groupId>org.apache.spark</groupId>
    <artifactId>spark-streaming_2.11</artifactId>
    <version>2.1.0</version>
</dependency>
<dependency>
    <groupId>org.apache.spark</groupId>
    <artifactId>spark-streaming-kafka-0-10_2.11</artifactId>
    <version>2.1.0</version>
</dependency>

<dependency>
    <groupId>org.apache.spark</groupId>
    <artifactId>spark-core_2.11</artifactId>
    <version>2.1.0</version>
</dependency>

程式:


import org.apache.spark.SparkConf
import org.apache.spark.streaming.{Seconds, StreamingContext}

object wc {
  def main(args: Array[String]): Unit = {
    //配置:spark
    val conf = new SparkConf().setMaster("local[3]").setAppName("wc")
    //流的上下文
    val ssc = new StreamingContext(conf,Seconds(2))
    //獲取輸入源
    val dstream1 = ssc.socketTextStream("localhost",9999)
    val dstream2 = dstream1.map((_, 1)).reduceByKey(_+_)
    
    //開啟上下文
    dstream2.print()
    ssc.start()
    ssc.awaitTermination()
  }
}

2, spark streaming : kafka資料來源

1.5.2版本

<dependency>
   <groupId>org.apache.spark</groupId>
   <artifactId>spark-core_2.10</artifactId>
   <version>1.5.2</version>
</dependency>
<dependency>
   <groupId>org.apache.spark</groupId>
   <artifactId>spark-streaming_2.10</artifactId>
   <version>1.5.2</version>
</dependency>
<dependency>
   <groupId>org.apache.spark</groupId>
   <artifactId>spark-streaming-kafka_2.10</artifactId>
   <version>1.5.2</version>
</dependency>

程式碼如下:

import org.apache.kafka.common.serialization.StringDeserializer
import org.apache.spark._
import org.apache.spark.streaming._
import org.apache.spark.streaming.kafka010.{ConsumerStrategies, LocationStrategies, KafkaUtils}


object wc_kafka {
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf()
    conf.setAppName("kafka")
    conf.setMaster("local[*]")

    val ssc = new StreamingContext(conf, Seconds(2))

    //kafka引數
    val kafkaParams = Map[String, Object](
      "bootstrap.servers" -> "localhost:9092",
      "key.deserializer" -> classOf[StringDeserializer],
      "value.deserializer" -> classOf[StringDeserializer],
      "group.id" -> "g1",
      "auto.offset.reset" -> "latest",
      "enable.auto.commit" -> (false: java.lang.Boolean)
    )
    //建立streaming輸入源
    val topics = Array("t1")
    val stream = KafkaUtils.createDirectStream[String, String](
      ssc,
      LocationStrategies.PreferConsistent,
      ConsumerStrategies.Subscribe[String, String](topics, kafkaParams)
    )

    //列印結果
    val ds2 = stream.map(record => (record.key, record.value))
    ds2.print()

    //啟動
    ssc.start()
    ssc.awaitTermination()
  }
}