Spark Stuctured Streaming 读取文件夹数据

package com.atguigu.structure.streaming


import org.apache.spark.sql.streaming.Trigger
import org.apache.spark.sql.{DataFrame, SparkSession}
import org.apache.spark.sql.types.{IntegerType, StringType, StructField, StructType}

object filesource {

  def main(args: Array[String]): Unit = {
    val spark: SparkSession = SparkSession.builder()
      .master("local[*]")
      .appName("FileSource")
      .getOrCreate()


    val struct = StructType(
        StructField("id", IntegerType) ::
        StructField("name", StringType, false) ::
        StructField("age", IntegerType, false) :: Nil)

    val df: DataFrame = spark.readStream.format("csv")
      .schema(struct)
      .load("G://spark")
    df.writeStream.format("console").outputMode("update")
      .trigger(Trigger.ProcessingTime(1000))
      .start()
      .awaitTermination()

    spark.stop()

  }

}

spark 目录下数据文件格式:

运行结果:

标签：Stuctured,val,SparkSession,StructField,Streaming,IntegerType,import,Spark,spark
来源： https://www.cnblogs.com/kpwong/p/13953426.html