spark提交抛纱pyspark脚本超过最大递归深度

Question

我可以在spark submit yarn-cluster模式下提交org.apache.spark.examples.sparkpi示例jar，它成功了，但是pyspark中的下面的代码片段失败了，最大递归深度超过了错误。

spark-submit --master yarn --deploy-mode cluster --executor-memory 1G --num-executors 4 --conf spark.yarn.appMasterEnv.PYSPARK_PYTHON="/usr/bin/python2.7" test.py --verbose

在纱线集群模式下，我根据Pyspark的建议添加了pyspark_python env

test.py

from pyspark import SparkContext
from pyspark.sql import HiveContext

sc_new = SparkContext()
SQLContext = HiveContext(sc_new)
SQLContext.setConf("spark.sql.hive.convertMetastoreOrc", "false")
txt = SQLContext.sql( "SELECT 1")
txt.show(2000000, False)

怎么解决这个？

File "/hdfs/data_06/yarn/nm/usercache/<alias>/appcache/application_1583989737267_1123855/container_e59_1583989737267_1123855_01_000001/py4j-0.9-src.zip/py4j/java_gateway.py", line 746, in send_command
                   raise Py4JError("Answer from Java side is empty")
               Py4JError: Answer from Java side is empty
               ERROR:py4j.java_gateway:Error while sending or receiving.
               Traceback (most recent call last):File "/hdfs/data_10/yarn/nm/usercache/<alias>/appcache/application_1583989737267_1123601/container_e59_1583989737267_1123601_01_000001/py4j-0.9-src.zip/py4j/java_gateway.py", line 626, in send_command
File "/hdfs/data_10/yarn/nm/usercache/<alias>/appcache/application_1583989737267_1123601/container_e59_1583989737267_1123601_01_000001/py4j-0.9-src.zip/py4j/java_gateway.py", line 749, in send_command
File "/usr/lib64/python2.7/logging/__init__.py", line 1182, in exception
  self.error(msg, *args, **kwargs)
File "/usr/lib64/python2.7/logging/__init__.py", line 1175, in error
  self._log(ERROR, msg, args, **kwargs)
File "/usr/lib64/python2.7/logging/__init__.py", line 1268, in _log
  self.handle(record)
File "/usr/lib64/python2.7/logging/__init__.py", line 1278, in handle
  self.callHandlers(record)
File "/usr/lib64/python2.7/logging/__init__.py", line 1318, in callHandlers
  hdlr.handle(record)
File "/usr/lib64/python2.7/logging/__init__.py", line 749, in handle
  self.emit(record)
File "/usr/lib64/python2.7/logging/__init__.py", line 879, in emit
  self.handleError(record)
File "/usr/lib64/python2.7/logging/__init__.py", line 802, in handleError
  None, sys.stderr)
File "/usr/lib64/python2.7/traceback.py", line 125, in print_exception
  print_tb(tb, limit, file)
File "/usr/lib64/python2.7/traceback.py", line 69, in print_tb
  line = linecache.getline(filename, lineno, f.f_globals)
File "/usr/lib64/python2.7/linecache.py", line 14, in getline
  lines = getlines(filename, module_globals)
File "/usr/lib64/python2.7/linecache.py", line 40, in getlines
  return updatecache(filename, module_globals)
File "/usr/lib64/python2.7/linecache.py", line 128, in updatecache
  lines = fp.readlines()
RuntimeError: maximum recursion depth exceeded while calling a Python object

• 运行Spark 1.6.0版
• 配置单元，版本1.1.0
• Hadoop版本:2.6.0-CDH5.13.0

Answer 1

通过调用txt.show(2000000,False），您正在执行py4j，以便在结果中没有那么多行的地方执行to-and-frojvm-python-object-jvm调用。我相信您可以在show()中调用的最大值是2000-ish。当您所做的只是选择1时，为什么需要显示2000000条记录？