如何修复“java.lang.ClassNotFoundException:组织,apache,Spark,内部,io,云,路径输出提交协议”Pyspark

mwkjh3gx  于 2023-01-01  发布在  Java
关注(0)|答案(1)|浏览(108)

下面是pycharm中的运行时版本。

Java Home   /Library/Java/JavaVirtualMachines/jdk-11.0.16.1.jdk/Contents/Home
Java Version    11.0.16.1 (Oracle Corporation)
Scala Version   version 2.12.15
Spark Version.         spark-3.3.1
Python 3.9

我正在尝试将pyspark Dataframe 写入csv,如下所示:

df.write.csv("/Users/data/data.csv")

并得到错误:

Traceback (most recent call last):
  File "/Applications/PyCharm.app/Contents/plugins/python/helpers/pydev/_pydevd_bundle/pydevd_exec2.py", line 3, in Exec
    exec(exp, global_vars, local_vars)
  File "<input>", line 1, in <module>
  File "/Users/mambaforge-pypy3/envs/lib/python3.9/site-packages/pyspark/sql/readwriter.py", line 1240, in csv
    self._jwrite.csv(path)
  File "/Users/mambaforge-pypy3/envs/lib/python3.9/site-packages/py4j/java_gateway.py", line 1321, in __call__
    return_value = get_return_value(
  File "/Users/mambaforge-pypy3/envs/lib/python3.9/site-packages/pyspark/sql/utils.py", line 190, in deco
    return f(*a, **kw)
  File "/Users/mambaforge-pypy3/envs/lib/python3.9/site-packages/py4j/protocol.py", line 326, in get_return_value
    raise Py4JJavaError(
py4j.protocol.Py4JJavaError: An error occurred while calling o747.csv.
: java.lang.ClassNotFoundException: org.apache.spark.internal.io.cloud.PathOutputCommitProtocol

spark配置如下:

spark_conf = SparkConf()
        spark_conf.setAll(parameters.items())
        spark_conf.set('spark.jars.packages', 'org.apache.hadoop:hadoop-aws:3.3.4')
        spark_conf.set('spark.hadoop.fs.s3.aws.credentials.provider',
                       'org.apache.hadoop.fs.s3.TemporaryAWSCredentialsProvider')
        spark_conf.set('spark.hadoop.fs.s3.access.key', os.environ.get('AWS_ACCESS_KEY_ID'))
        spark_conf.set('spark.hadoop.fs.s3.secret.key', os.environ.get('AWS_SECRET_ACCESS_KEY'))
        spark_conf.set('spark.hadoop.fs.s3a.bucket.all.committer.magic.enabled', 'true')
        spark_conf.set("com.amazonaws.services.s3.enableV4", "true")
        spark_conf.set("fs.s3a.impl", "org.apache.hadoop.fs.s3a.S3AFileSystem")
        spark_conf.set("fs.s3a.aws.credentials.provider",
                       "com.amazonaws.auth.InstanceProfileCredentialsProvider,com.amazonaws.auth.DefaultAWSCredentialsProviderChain")
        spark_conf.set("fs.AbstractFileSystem.s3a.impl", "org.apache.hadoop.fs.s3a.S3A")
        spark_conf.set("hadoop.fs.s3a.path.style.access", "true")
        spark_conf.set("hadoop.fs.s3a.fast.upload", "true")
        spark_conf.set("hadoop.fs.s3a.fast.upload.buffer", "bytebuffer")
        spark_conf.set("fs.s3a.path.style.access", "true")
        spark_conf.set("fs.s3a.multipart.size", "128M")
        spark_conf.set("fs.s3a.fast.upload.active.blocks", "4")
        spark_conf.set("fs.s3a.committer.name", "partitioned")
        spark_conf.set("spark.hadoop.fs.s3a.committer.name", "directory")
        spark_conf.set("spark.sql.sources.commitProtocolClass",
                       "org.apache.spark.internal.io.cloud.PathOutputCommitProtocol")
        spark_conf.set("spark.sql.parquet.output.committer.class",
                       "org.apache.spark.internal.io.cloud.BindingParquetOutputCommitter")
        spark_conf.set("spark.hadoop.mapreduce.fileoutputcommitter.algorithm.version", "1")

任何解决这个问题的帮助都是感激的。谢谢!!

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