使用Spark SQL合并小文件的一个例子

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本文链接： https://blog.csdn.net/weixin_42411818/article/details/100583088

小文件的危害完我就不在多说,请见:https://blog.csdn.net/qq_34341930/article/details/89031661

直接上代码,可以做个定时任务结合自己的业务去定时调度

import org.apache.spark.sql.{SaveMode, SparkSession}

/**
  * 使用Spark SQL合并小文件
  */
object SmallFileMerger {
  def main(args: Array[String]): Unit = {
    val spark = SparkSession.builder()
      .appName("SmallFileMerger")
      .master("local")
      .getOrCreate()

    val inputPath = spark.conf.get("spark.small.file.merge.inputPath",
      "hdfs://mycluster/user/hadoop-jrq/dw-course/streaming-etl/user-action-parquet/year=2019/month=201909/day=20190906")

    val numberPartition = spark.conf.get("spark.small.file.merge.numberPartition", "2").toInt

    val outputPath = spark.conf.get("spark.small.file.merge.outputPath",
      "hdfs://mycluster/user/hadoop-jrq/dw-course/streaming-etl/user-action-merged/year=2019/month=201909/day=20190906")

    spark.read.parquet(inputPath)
      .repartition(numberPartition)
      //.coalesce(numberPartition)
      .write
      .mode(SaveMode.Overwrite)
      .parquet(outputPath)

    spark.stop()
  }
}