我遇到了在EMR集群上运行pyspark作业的问题,所以我登录主节点并直接在那里运行spark-submit
我有一个我提交给pyspark的python文件,在这个文件中我有:
import subprocess
from pyspark import SparkContext, SparkConf
import boto3
from boto3.s3.transfer import S3Transfer
import os, re
import tarfile
import time
...
当我尝试在群集模式下运行时,我得到: (来自纱线原木,为简洁而修剪)
16/01/31 21:45:57 INFO spark.CacheManager: Partition rdd_2_0 not found, computing it
16/01/31 21:45:57 INFO spark.CacheManager: Partition rdd_1_0 not found, computing it
16/01/31 21:45:57 ERROR executor.Executor: Exception in task 0.0 in stage 0.0 (TID 0)
org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/mnt1/yarn/usercache/hadoop/appcache/application_1454273602144_0005/container_1454273602144_0005_01_000002/pyspark.zip/pyspark/worker.py", line 98, in main
command = pickleSer._read_with_length(infile)
File "/mnt1/yarn/usercache/hadoop/appcache/application_1454273602144_0005/container_1454273602144_0005_01_000002/pyspark.zip/pyspark/serializers.py", line 164, in _read_with_length
return self.loads(obj)
File "/mnt1/yarn/usercache/hadoop/appcache/application_1454273602144_0005/container_1454273602144_0005_01_000002/pyspark.zip/pyspark/serializers.py", line 422, in loads
return pickle.loads(obj)
ImportError: No module named boto3.s3.transfer
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:69)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:268)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:69)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:268)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$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)
稍后我收到有关无法导入boto3的错误。
如果我在客户端模式下运行,我只会获得有关boto3.s3.transfer的ImportError。
Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3, ip-172-31-39-79.us-west-2.compute.internal): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/mnt1/yarn/usercache/hadoop/appcache/application_1454273602144_0005/container_1454273602144_0005_01_000002/pyspark.zip/pyspark/worker.py", line 98, in main
command = pickleSer._read_with_length(infile)
File "/mnt1/yarn/usercache/hadoop/appcache/application_1454273602144_0005/container_1454273602144_0005_01_000002/pyspark.zip/pyspark/serializers.py", line 164, in _read_with_length
return self.loads(obj)
File "/mnt1/yarn/usercache/hadoop/appcache/application_1454273602144_0005/container_1454273602144_0005_01_000002/pyspark.zip/pyspark/serializers.py", line 422, in loads
return pickle.loads(obj)
ImportError: No module named boto3.s3.transfer
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:69)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:268)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:69)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:268)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$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)
但是,如果我检查pip冻结:
boto3==1.2.3
botocore==1.3.23
如果我在主服务器上打开Spark Shell并执行此操作:
import boto3
client = boto3.client("s3")
工作正常。
这里有某种虚拟环境吗?我完全糊涂了。
修改 忘记提到我使用Spark 1.6.0的最新EMR版本。
此外,这在我自己的机器上以本地模式正常工作。
答案 0 :(得分:3)
嗯,derp,我发现了这个问题。
原来我必须pip install boto3
,默认情况下EMR节点没有安装。
这是错误具有描述性的一种情况。