日韩性视频-久久久蜜桃-www中文字幕-在线中文字幕av-亚洲欧美一区二区三区四区-撸久久-香蕉视频一区-久久无码精品丰满人妻-国产高潮av-激情福利社-日韩av网址大全-国产精品久久999-日本五十路在线-性欧美在线-久久99精品波多结衣一区-男女午夜免费视频-黑人极品ⅴideos精品欧美棵-人人妻人人澡人人爽精品欧美一区-日韩一区在线看-欧美a级在线免费观看

歡迎訪問 生活随笔!

生活随笔

當前位置: 首頁 > 编程语言 > python >内容正文

python

Python in worker has different version 3.7 than that in driver 3.6

發布時間:2023/12/31 python 41 豆豆
生活随笔 收集整理的這篇文章主要介紹了 Python in worker has different version 3.7 than that in driver 3.6 小編覺得挺不錯的,現在分享給大家,幫大家做個參考.

環境:

組件版本
Ubuntu20.04
Spark3.0.0-preview2-bin-hadoop3.2

完整報錯如下 :

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 1 in stage 0.0 failed 4 times, most recent failure: Lost task 1.3 in stage 0.0 (TID 43, 192.168.0.103, executor 1): org.apache.spark.api.python.PythonException: Traceback (most recent call last):File "/home/appleyuchi/bigdata/spark-3.0.0-preview2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 469, in main("%d.%d" % sys.version_info[:2], version)) Exception: Python in worker has different version 3.7 than that in driver 3.6, PySpark cannot run with different minor versions.Please check environment variables PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON are correctly set.at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:484)at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:619)at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:602)at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:437)at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)at scala.collection.Iterator.foreach(Iterator.scala:941)at scala.collection.Iterator.foreach$(Iterator.scala:941)at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)at scala.collection.generic.Growable.$plus$plus$eq(Growable.scala:62)at scala.collection.generic.Growable.$plus$plus$eq$(Growable.scala:53)at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:105)at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:49)at scala.collection.TraversableOnce.to(TraversableOnce.scala:315)at scala.collection.TraversableOnce.to$(TraversableOnce.scala:313)at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)at scala.collection.TraversableOnce.toBuffer(TraversableOnce.scala:307)at scala.collection.TraversableOnce.toBuffer$(TraversableOnce.scala:307)at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)at scala.collection.TraversableOnce.toArray(TraversableOnce.scala:294)at scala.collection.TraversableOnce.toArray$(TraversableOnce.scala:288)at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)at org.apache.spark.rdd.RDD.$anonfun$collect$2(RDD.scala:1004)at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2156)at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)at org.apache.spark.scheduler.Task.run(Task.scala:127)at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:441)at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:444)at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)at java.lang.Thread.run(Thread.java:748)Driver stacktrace:at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:1989)at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:1977)at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:1976)at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1976)at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:956)at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:956)at scala.Option.foreach(Option.scala:407)at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:956)at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2206)at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2155)at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2144)at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:758)at org.apache.spark.SparkContext.runJob(SparkContext.scala:2116)at org.apache.spark.SparkContext.runJob(SparkContext.scala:2137)at org.apache.spark.SparkContext.runJob(SparkContext.scala:2156)at org.apache.spark.SparkContext.runJob(SparkContext.scala:2181)at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1004)at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)at org.apache.spark.rdd.RDD.withScope(RDD.scala:388)at org.apache.spark.rdd.RDD.collect(RDD.scala:1003)at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:168)at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)at java.lang.reflect.Method.invoke(Method.java:498)at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)at py4j.Gateway.invoke(Gateway.java:282)at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)at py4j.commands.CallCommand.execute(CallCommand.java:79)at py4j.GatewayConnection.run(GatewayConnection.java:238)at java.lang.Thread.run(Thread.java:748) Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):File "/home/appleyuchi/bigdata/spark-3.0.0-preview2-bin-hadoop3.2/python/lib/pyspark.zip/pyspark/worker.py", line 469, in main("%d.%d" % sys.version_info[:2], version)) Exception: Python in worker has different version 3.7 than that in driver 3.6, PySpark cannot run with different minor versions.Please check environment variables PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON are correctly set.at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:484)at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:619)at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:602)at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:437)at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)at scala.collection.Iterator.foreach(Iterator.scala:941)at scala.collection.Iterator.foreach$(Iterator.scala:941)at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)at scala.collection.generic.Growable.$plus$plus$eq(Growable.scala:62)at scala.collection.generic.Growable.$plus$plus$eq$(Growable.scala:53)at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:105)at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:49)at scala.collection.TraversableOnce.to(TraversableOnce.scala:315)at scala.collection.TraversableOnce.to$(TraversableOnce.scala:313)at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28)at scala.collection.TraversableOnce.toBuffer(TraversableOnce.scala:307)at scala.collection.TraversableOnce.toBuffer$(TraversableOnce.scala:307)at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28)at scala.collection.TraversableOnce.toArray(TraversableOnce.scala:294)at scala.collection.TraversableOnce.toArray$(TraversableOnce.scala:288)at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)at org.apache.spark.rdd.RDD.$anonfun$collect$2(RDD.scala:1004)at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2156)at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)at org.apache.spark.scheduler.Task.run(Task.scala:127)at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:441)at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:444)at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)... 1 more

這個事情比較復雜,我們有三種python

root自帶的系統python

anaconda的python

Spark自帶的python

所以上面的log中的python到底來自哪里。。。。。。。

?

這個問題據我觀察,Pyspark是這么使用的,

master上用的是虛擬環境anaconda里面的默認python版本

slave上用的是系統python版本。。。。

?

恢復成shell的設置如下:

export PYSPARK_PYTHON=~/anaconda3/envs/Python3.6/bin/python3
export PYSPARK_DRIVER_PYTHON=~/anaconda3/envs/Python3.6/bin/python3

這樣設置jupyter notebook就無法使用了。

?

?

總結

以上是生活随笔為你收集整理的Python in worker has different version 3.7 than that in driver 3.6的全部內容,希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網站內容還不錯,歡迎將生活随笔推薦給好友。