我有下面简单的 SparkR 程序，即创建 SparkR DataFrame 并从中检索/收集数据。

Sys.setenv(HADOOP_CONF_DIR = "/etc/hadoop/conf.cloudera.yarn")
Sys.setenv(SPARK_HOME = "/home/user/Downloads/spark-1.6.1-bin-hadoop2.6")
.libPaths(c(file.path(Sys.getenv("SPARK_HOME"), "R", "lib"), .libPaths()))
library(SparkR)
sc <- sparkR.init(master="yarn-client",sparkEnvir = list(spark.shuffle.service.enabled=TRUE,spark.dynamicAllocation.enabled=TRUE,spark.dynamicAllocation.initialExecutors="40"))
hiveContext <- sparkRHive.init(sc)

n = 1000
x = data.frame(id = 1:n, val = rnorm(n))
xs <- createDataFrame(hiveContext, x)

xs

head(xs)
collect(xs)

我能够成功地创建它并查看信息，但是任何与获取数据相关的操作都会抛出以下错误。
16/07/25 16:33:59警告tasksetmanager:在阶段17.0中丢失任务0.3（tid 86，wlos06.nrm.minn.seagate.com）：java.net.sockettimeoutexception:accept在java.net.plainsocketimpl.socketaccept（本机方法）处超时，位于java.net.abstractplainsocketimpl.accept（abstractplainsocketimpl）。java:398)在java.net.serversocket.implacept（serversocket。java:530)在java.net.serversocket.accept（serversocket。java:498)在org.apache.spark.api.r.rrdd$.createrworker（rrdd。scala:432)在org.apache.spark.api.r.baserrdd.compute（rrdd。scala:63)在org.apache.spark.rdd.rdd.computeorreadcheckpoint（rdd。scala:306)在org.apache.spark.rdd.rdd.iterator（rdd。scala:270)在org.apache.spark.rdd.mappartitionsrdd.compute（mappartitionsrdd。scala:38)在org.apache.spark.rdd.rdd.computeorreadcheckpoint（rdd。scala:306)在org.apache.spark.rdd.rdd.iterator（rdd。scala:270)在org.apache.spark.rdd.mappartitionsrdd.compute（mappartitionsrdd。scala:38)在org.apache.spark.rdd.rdd.computeorreadcheckpoint（rdd。scala:306)在org.apache.spark.rdd.rdd.iterator（rdd。scala:270)在org.apache.spark.rdd.mappartitionsrdd.compute（mappartitionsrdd。scala:38)在org.apache.spark.rdd.rdd.computeorreadcheckpoint（rdd。scala:306)在org.apache.spark.rdd.rdd.iterator（rdd。scala:270)在org.apache.spark.scheduler.resulttask.runtask（resulttask。scala:66)在org.apache.spark.scheduler.task.run（task。scala:89)在org.apache.spark.executor.executor$taskrunner.run（executor。scala:214)位于java.util.concurrent.threadpoolexecutor.runworker（threadpoolexecutor。java:1145)在java.util.concurrent.threadpoolexecutor$worker.run（threadpoolexecutor。java:615)在java.lang.thread.run（线程。java:745)
16/07/25 16:33:59错误tasksetmanager:阶段17.0中的任务0失败4次；中止作业16/07/25 16:33:59错误rbackendhandler:org.apache.spark.sql.api.r.sqlutils失败invokejava中的错误（isstatic=true，classname，methodname，…）：org.apache.spark.sparkeexception:由于阶段失败而中止作业：阶段17.0中的任务0失败了4次，最近的失败：阶段17.0中的任务0.3丢失（tid 86，wlos06.nrm.minn.seagate.com）：java.net.sockettimeoutexception:accept在java.net.plainsocketimpl.socketaccept（本机方法）处超时，位于java.net.abstractplainsocketimpl.accept（abstractplainsocketimpl）。java:398)在java.net.serversocket.implacept（serversocket。java:530)在java.net.serversocket.accept（serversocket。java:498)在org.apache.spark.api.r.rrdd$.createrworker（rrdd。scala:432)在org.apache.spark.api.r.baserrdd.compute（rrdd。scala:63)在org.apache.spark.rdd.rdd.computeorreadcheckpoint（rdd。scala:306)在org.apache.spark.rdd.rdd.iterator（rdd。scala:270)在org.apache.spark.rdd.mappartitionsrdd.compute（mappartitionsrdd。scala:38)在org.apache.spark.rdd.rdd.computeorreadcheckpoint（rdd。scala:306)在org.apache.spark.rdd.rdd.iterator（rdd。scala:270)位于org.apache.spark.rdd.mappartitionsrdd.compute（mappar
如果我用下面的sparkr命令行执行它，它就会被执行。

~/Downloads/spark-1.6.1-bin-hadoop2.6/bin/sparkR --master yarn-client

但是当我通过r和sparkr.init（（master=“yarn client”）执行它时，它会抛出错误。
有人能帮忙解决这些错误吗？