spark streaming 2 streaming on RDD
作者:互联网
package com.shujia.spark.streaming import org.apache.spark.{SparkConf, SparkContext} import org.apache.spark.sql.{DataFrame, SparkSession} import org.apache.spark.streaming.dstream.ReceiverInputDStream import org.apache.spark.streaming.{Durations, StreamingContext} object Demo2StreamOnRDD { def main(args: Array[String]): Unit = { val spark: SparkSession = SparkSession.builder() .appName("streaming") .master("local[2]") .config("spark.sql.shuffle.partitions", 1) .getOrCreate() import spark.implicits._ import org.apache.spark.sql.functions._ val sc: SparkContext = spark.sparkContext /** * 创建streaming 上下文对象,指定batch的间隔时间,多久计算一次 * */ val ssc = new StreamingContext(sc, Durations.seconds(5)) val linesDS: ReceiverInputDStream[String] = ssc.socketTextStream("master", 8888) /** * foreachRDD:将DS转换成RDD使用,可以使用 rdd 的 api * */ linesDS.foreachRDD(rdd => { /** * 每个batch计算一次,不能做全局的计算 * */ //使用rdd api rdd.flatMap(_.split(",")) .map((_, 1)) .reduceByKey(_ + _) // .foreach(println) val lineDF: DataFrame = rdd.toDF("lines") lineDF .select(explode(split($"lines", ",")) as "word") .groupBy($"word") .agg(count($"word") as "C") // .show() lineDF.createOrReplaceTempView("words") spark.sql( """ | |select word,count(1) from ( |select explode(split(lines,',')) as word from words |) as a |group by word | """.stripMargin) .show() }) //启动streaming ssc.start() ssc.awaitTermination() //等待关闭 这三行代码必须要写 ssc.stop() } }
标签:word,RDD,streaming,apache,import,spark,ssc 来源: https://www.cnblogs.com/lipinbigdata/p/15058225.html