scala - “User did not initialize spark context”在SPARK YARN集群模式下使用Scala代码时出错

为了缩小问题的范围，我删除了其他类依赖关系，并使用了以下干净的代码:

object LoaderProcessor extends App {

val logger = LoggerFactory.getLogger(this.getClass())
execute()

def execute(): Unit = {

val spark = get_spark()
import spark.implicits._

var df = spark.read
  .format("csv")
  .option("delimiter", ",")
  .option("header", true)
  .option("inferSchema", "true")
  .option("timestampFormat", "yyyy/MM/dd HH:mm:ss")
  .load(args(2))

df = df.withColumn("zs_source", lit(1)) //the only operation on dataframe

val o_file = Config().getString("myapp.dataFolder") + "/8/1/data.csv"
logger.info("Writing output to: {}", o_file)

df.write.mode("overwrite")
.option("header", "true").csv(o_file)

}

def get_spark(): SparkSession = {
val env = System.getenv("MYAPP_ENV")
var spark:SparkSession = null
if (env == null || env == "dev_local") {
  spark = org.apache.spark.sql.SparkSession.builder
    .master("local")
    .appName("MyApp")
    .getOrCreate;
}else{
  spark = org.apache.spark.sql.SparkSession.builder
    .appName("MyApp")
    //.enableHiveSupport()
    .getOrCreate;
}
spark.sparkContext.setCheckpointDir(Config().getString("myapp.rddcp"))
return spark
}
}

它在客户端模式中可以很好地工作。无法解决问题。我的集群位于HDInsight上。

同样，也注意到“写”操作一直在输出文件夹上进行写操作，如下所示:

part-00000-3e9566ae-c13c-468a-8732-e7b8a8df5335-c000.csv

然后几秒钟:

部分00000-4f4979a0-d9f9-481b-aac4-115e63b9f59c-c000.csv

8/12/01 15:08:53 INFO ApplicationMaster:在单独的线程中启动用户应用程序
18/12/01 15:08:53 INFO ApplicationMaster:WAITINGSpark上下文初始化...
18/12/01 15:08:55 INFO Config $:环境:dev
18/12/01 15:08:55错误ApplicationMaster:未捕获的异常:
java.lang.IllegalStateException:用户未初始化spark上下文!
在org.apache.spark.deploy.yarn.ApplicationMaster.runDriver(ApplicationMaster.scala:510)
在org.apache.spark.deploy.yarn.ApplicationMaster.org $ apache $ spark $ deploy $ yarn $ ApplicationMaster $$ runImpl(ApplicationMaster.scala:345)
在org.apache.spark.deploy.yarn.ApplicationMaster $$ anonfun $ run $ 2.apply $ mcV $ sp(ApplicationMaster.scala:260)
在org.apache.spark.deploy.yarn.ApplicationMaster $$ anonfun $ run $ 2.apply(ApplicationMaster.scala:260)
在org.apache.spark.deploy.yarn.ApplicationMaster $$ anonfun $ run $ 2.apply(ApplicationMaster.scala:260)
在org.apache.spark.deploy.yarn.ApplicationMaster $$ anon $ 5.run(ApplicationMaster.scala:815)
在java.security.AccessController.doPrivileged(本机方法)
在javax.security.auth.Subject.doAs(Subject.java:422)
在org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1869)
在org.apache.spark.deploy.yarn.ApplicationMaster.doAsUser(ApplicationMaster.scala:814)
在org.apache.spark.deploy.yarn.ApplicationMaster.run(ApplicationMaster.scala:259)
在org.apache.spark.deploy.yarn.ApplicationMaster $ .main(ApplicationMaster.scala:839)
在org.apache.spark.deploy.yarn.ApplicationMaster.main(ApplicationMaster.scala)
spark-submit --master yarn --deploy-mode cluster --jars "wasb://xx@yy/zs/jars/config-1.3.1.jar" --class myapp.LoaderProcessor "wasb://xx@yy/zs/jars/myapp.jar" l 8 /data/8_data.csv 1 , true false-> 问题
spark-submit --deploy-mode client --jars "wasb://xx@yy/zs/jars/config-1.3.1.jar" --class myapp.LoaderProcessor "wasb://xx@yy/zs/jars/myapp.jar" l 8 /data/8_data.csv 1 , true false-> 工作!!!

最佳答案

编辑:根据我们的评论更新

问题是您总是使用if (env == null || env == "dev_local")创建本地上下文(在分布式环境中MYAPP_ENV为null)