Github user Maple-Wang commented on the issue:
https://github.com/apache/spark/pull/20027
use SparkR in the R shell, the master parameter too old,connot run
"spark-submit --master yarn --deploy-mode client" . I install R on all node.
when use in this way:
if (nchar(Sys.getenv("SPARK_HOME")) < 1) {
Sys.setenv(SPARK_HOME = "/usr/hdp/2.6.1.0-129/spark2")
}
library(SparkR, lib.loc = c(file.path(Sys.getenv("SPARK_HOME"), "R",
"lib")))
sparkR.session(master = "yarn", sparkConfig = list(spark.driver.memory =
"10g"))
it comes out:
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0
in stage 1.0 failed 4 times, most recent failure: Lost task 0.3 in stage 1.0
(TID 4, node23.nuctech.com, executor 1): java.net.SocketTimeoutException:
Accept timed out
at java.net.PlainSocketImpl.socketAccept(Native Method)
at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:409)
at java.net.ServerSocket.implAccept(ServerSocket.java:545)
at java.net.ServerSocket.accept(ServerSocket.java:513)
at org.apache.spark.api.r.RRunner$.createRWorker(RRunner.scala:372)
at org.apache.spark.api.r.RRunner.compute(RRunner.scala:69)
at org.apache.spark.api.r.BaseRRDD.compute(RRDD.scala:51)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.
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