- android - 多次调用 OnPrimaryClipChangedListener
- android - 无法更新 RecyclerView 中的 TextView 字段
- android.database.CursorIndexOutOfBoundsException : Index 0 requested, 光标大小为 0
- android - 使用 AppCompat 时,我们是否需要明确指定其 UI 组件(Spinner、EditText)颜色
我正在学习 Spark,并坚持运行示例基本程序来进行字数统计。请帮忙解决这个问题
我使用的是 pycharm,我的操作系统是 windows
这是我正在使用的代码
import os
import sys
# Path for folder containing winutils.exe . Without it I was getting the error java.io.IOException: Could not locate executable null\bin\winutils.exe in the Hadoop binaries.
os.environ['HADOOP_HOME']="C:\\Users\\ekhaavi\\Documents\\ApacheSpark\\Hadoop"
# Path for spark source folder
os.environ['SPARK_HOME']="C:\\Users\ekhaavi\\Documents\\ApacheSpark\\spark-1.6.0-bin-hadoop2.6"
# Append to PYTHONPATH so that pyspark could be found
sys.path.append("C:\\Users\\ekhaavi\\Documents\\ApacheSpark\\spark-1.6.0-bin-hadoop2.6\\python")
#this is to overcome the py4j exception
sys.path.append("C:\\Users\\ekhaavi\\Documents\\ApacheSpark\\spark-1.6.0-bin-hadoop2.6\\python\\lib\\py4j-0.9-src.zip")
# Now we are ready to import Spark Modules
try:
from pyspark import SparkContext
from pyspark import SparkConf
except ImportError as e:
print ("Error importing Spark Modules", e)
sys.exit(1)
if __name__ == "__main__":
sc = SparkContext('local')
words = sc.parallelize(["scala","java","hadoop","spark","akka"])
print(words.count())
运行后我收到以下异常
org.apache.spark.SparkException: Python worker exited unexpectedly (crashed)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:203)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.EOFException
at java.io.DataInputStream.readInt(DataInputStream.java:392)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:139)
... 11 more
16/03/03 14:40:55 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, localhost): org.apache.spark.SparkException: Python worker exited unexpectedly (crashed)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:203)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.EOFException
at java.io.DataInputStream.readInt(DataInputStream.java:392)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:139)
... 11 more
16/03/03 14:40:55 ERROR TaskSetManager: Task 0 in stage 0.0 failed 1 times; aborting job
16/03/03 14:40:55 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool
16/03/03 14:40:55 INFO TaskSchedulerImpl: Cancelling stage 0
16/03/03 14:40:55 INFO DAGScheduler: ResultStage 0 (count at C:/Users/ekhaavi/PycharmProjects/FileProcessingStream/FileProcessingStream.py:32) failed in 0.539 s
16/03/03 14:40:55 INFO DAGScheduler: Job 0 failed: count at C:/Users/ekhaavi/PycharmProjects/FileProcessingStream/FileProcessingStream.py:32, took 0.854514 s
Traceback (most recent call last):
File "C:/Users/ekhaavi/PycharmProjects/FileProcessingStream/FileProcessingStream.py", line 32, in <module>
print(words.count())
File "C:\Users\ekhaavi\Documents\ApacheSpark\spark-1.6.0-bin-hadoop2.6\python\pyspark\rdd.py", line 1004, in count
return self.mapPartitions(lambda i: [sum(1 for _ in i)]).sum()
File "C:\Users\ekhaavi\Documents\ApacheSpark\spark-1.6.0-bin-hadoop2.6\python\pyspark\rdd.py", line 995, in sum
return self.mapPartitions(lambda x: [sum(x)]).fold(0, operator.add)
File "C:\Users\ekhaavi\Documents\ApacheSpark\spark-1.6.0-bin-hadoop2.6\python\pyspark\rdd.py", line 869, in fold
vals = self.mapPartitions(func).collect()
File "C:\Users\ekhaavi\Documents\ApacheSpark\spark-1.6.0-bin-hadoop2.6\python\pyspark\rdd.py", line 771, in collect
port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
File "C:\Users\ekhaavi\Documents\ApacheSpark\spark-1.6.0-bin-hadoop2.6\python\lib\py4j-0.9-src.zip\py4j\java_gateway.py", line 813, in __call__
File "C:\Users\ekhaavi\Documents\ApacheSpark\spark-1.6.0-bin-hadoop2.6\python\lib\py4j-0.9-src.zip\py4j\protocol.py", line 308, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost): org.apache.spark.SparkException: Python worker exited unexpectedly (crashed)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:203)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.EOFException
at java.io.DataInputStream.readInt(DataInputStream.java:392)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:139)
... 11 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1929)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:927)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.RDD.collect(RDD.scala:926)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:405)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
at py4j.Gateway.invoke(Gateway.java:259)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:209)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.SparkException: Python worker exited unexpectedly (crashed)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:203)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
... 1 more
Caused by: java.io.EOFException
at java.io.DataInputStream.readInt(DataInputStream.java:392)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:139)
... 11 more
最佳答案
为了克服这个问题,我们必须从“
下载“winutils.exe”https://social.msdn.microsoft.com/forums/azure/en-US/28a57efb- 082b-424b-8d9e-
731b1fe135de/请阅读- if-experiencing- job-failures?forum=hdinsight”
下载文件后,将其放入 Directory/bin 中,并将该目录定义到 HADOOP_HOME 下
Windows环境变量
关于python - 在pycharm中运行pyspark程序,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/35766053/
我在数据框中有一列月份数字,想将其更改为月份名称,所以我使用了这个: df['monthName'] = df['monthNumber'].apply(lambda x: calendar.mont
Pyspark 中是否有一个 input() 函数,我可以通过它获取控制台输入。如果是,请详细说明一下。 如何在 PySpark 中编写以下代码: directory_change = input("
我们正在 pyspark 中构建数据摄取框架,并想知道处理数据类型异常的最佳方法是什么。基本上,我们希望有一个拒绝表来捕获所有未与架构确认的数据。 stringDf = sparkSession.cr
我正在开发基于一组 ORC 文件的 spark 数据框的 sql 查询。程序是这样的: from pyspark.sql import SparkSession spark_session = Spa
我有一个 Pyspark 数据框( 原始数据框 )具有以下数据(所有列都有 字符串 数据类型): id Value 1 103 2
我有一台配置了Redis和Maven的服务器 然后我执行以下sparkSession spark = pyspark .sql .SparkSession .builder .master('loca
从一些简短的测试来看,pyspark 数据帧的列删除功能似乎不区分大小写,例如。 from pyspark.sql import SparkSession from pyspark.sql.funct
我有: +---+-------+-------+ | id| var1| var2| +---+-------+-------+ | a|[1,2,3]|[1,2,3]| | b|[2,
从一些简短的测试来看,pyspark 数据帧的列删除功能似乎不区分大小写,例如。 from pyspark.sql import SparkSession from pyspark.sql.funct
我有一个带有多个数字列的 pyspark DF,我想为每一列根据每个变量计算该行的十分位数或其他分位数等级。 这对 Pandas 来说很简单,因为我们可以使用 qcut 函数为每个变量创建一个新列,如
我有以下使用 pyspark.ml 包进行线性回归的代码。但是,当模型适合时,我在最后一行收到此错误消息: IllegalArgumentException: u'requirement failed
我有一个由 | 分隔的平面文件(管道),没有引号字符。示例数据如下所示: SOME_NUMBER|SOME_MULTILINE_STRING|SOME_STRING 23|multiline text
给定如下模式: root |-- first_name: string |-- last_name: string |-- degrees: array | |-- element: struc
我有一个 pyspark 数据框如下(这只是一个简化的例子,我的实际数据框有数百列): col1,col2,......,col_with_fix_header 1,2,.......,3 4,5,.
我有一个数据框 +------+--------------------+-----------------+---- | id| titulo |tipo | formac
我从 Spark 数组“df_spark”开始: from pyspark.sql import SparkSession import pandas as pd import numpy as np
如何根据行号/行索引值删除 Pyspark 中的行值? 我是 Pyspark(和编码)的新手——我尝试编码一些东西,但它不起作用。 最佳答案 您不能删除特定的列,但您可以使用 filter 或其别名
我有一个循环生成多个因子表的输出并将列名存储在列表中: | id | f_1a | f_2a | |:---|:----:|:-----| |1 |1.2 |0.95 | |2 |0.7
我正在尝试将 hql 脚本转换为 pyspark。我正在努力如何在 groupby 子句之后的聚合中实现 case when 语句的总和。例如。 dataframe1 = dataframe0.gro
我想添加新的 2 列值服务 arr 第一个和第二个值 但我收到错误: Field name should be String Literal, but it's 0; production_targe
我是一名优秀的程序员,十分优秀!