docker - 使用 docker compose 将 spark 连接到 localstack s3

标签 docker apache-spark pyspark docker-compose localstack

我一直在尝试使用 docker-compose 连接到本地 S3 存储桶 (localstack)。 这样:

  • 其中一个容器是 spark driver
  • 其中一个容器是 S3 存储桶
  • 其中一个容器是 spark master
  • 另外两个容器是 spark worker

不过,我无法让 spark 到达 localstack(S3 容器)。

我已经尝试将“spark.hadoop.fs.s3a.endpoint”配置到我的网络 ip“http://172.x.x.x”,并且工作正常。

但是当我使用“http://localstack:4572”(作为“localstack”我在 docker-compose 文件中的别名)时,我收到“名称或服务未知”错误消息:

19/10/30 20:39:49 WARN FileStreamSink: Error while looking for metadata directory.
Traceback (most recent call last):
  File "etl_job.py", line 103, in <module>
    etl_method(conf)
  File "etl_job.py", line 68, in etl_method
    df = spark.read.csv('s3a://test/data/RAW_DATA_Metro_Interstate_Traffic_Volume.csv.gz', header=True, inferSchema=True)
  File "/usr/local/lib/python3.7/site-packages/pyspark/sql/readwriter.py", line 476, in csv
    return self._df(self._jreader.csv(self._spark._sc._jvm.PythonUtils.toSeq(path)))
  File "/usr/local/lib/python3.7/site-packages/py4j/java_gateway.py", line 1257, in __call__
    answer, self.gateway_client, self.target_id, self.name)
  File "/usr/local/lib/python3.7/site-packages/pyspark/sql/utils.py", line 63, in deco
    return f(*a, **kw)
  File "/usr/local/lib/python3.7/site-packages/py4j/protocol.py", line 328, in get_return_value
    format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling o69.csv.
: com.amazonaws.AmazonClientException: Unable to execute HTTP request: test.localstack: Name or service not known
    at com.amazonaws.http.AmazonHttpClient.executeHelper(AmazonHttpClient.java:454)
    at com.amazonaws.http.AmazonHttpClient.execute(AmazonHttpClient.java:232)
    at com.amazonaws.services.s3.AmazonS3Client.invoke(AmazonS3Client.java:3528)
    at com.amazonaws.services.s3.AmazonS3Client.headBucket(AmazonS3Client.java:1031)
    at com.amazonaws.services.s3.AmazonS3Client.doesBucketExist(AmazonS3Client.java:994)
    at org.apache.hadoop.fs.s3a.S3AFileSystem.initialize(S3AFileSystem.java:297)
    at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2669)
    at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:94)
    at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2703)
    at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2685)
    at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:373)
    at org.apache.hadoop.fs.Path.getFileSystem(Path.java:295)
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$org$apache$spark$sql$execution$datasources$DataSource$$checkAndGlobPathIfNecessary$1.apply(DataSource.scala:547)
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$org$apache$spark$sql$execution$datasources$DataSource$$checkAndGlobPathIfNecessary$1.apply(DataSource.scala:545)
    at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
    at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
    at scala.collection.immutable.List.foreach(List.scala:392)
    at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
    at scala.collection.immutable.List.flatMap(List.scala:355)
    at org.apache.spark.sql.execution.datasources.DataSource.org$apache$spark$sql$execution$datasources$DataSource$$checkAndGlobPathIfNecessary(DataSource.scala:545)
    at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:359)
    at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:223)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:211)
    at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:618)
    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: java.net.UnknownHostException: test.localstack: Name or service not known
    at java.net.Inet4AddressImpl.lookupAllHostAddr(Native Method)
    at java.net.InetAddress$2.lookupAllHostAddr(InetAddress.java:929)
    at java.net.InetAddress.getAddressesFromNameService(InetAddress.java:1324)
    at java.net.InetAddress.getAllByName0(InetAddress.java:1277)
    at java.net.InetAddress.getAllByName(InetAddress.java:1193)
    at java.net.InetAddress.getAllByName(InetAddress.java:1127)
    at org.apache.http.impl.conn.SystemDefaultDnsResolver.resolve(SystemDefaultDnsResolver.java:45)
    at org.apache.http.impl.conn.DefaultClientConnectionOperator.resolveHostname(DefaultClientConnectionOperator.java:263)
    at org.apache.http.impl.conn.DefaultClientConnectionOperator.openConnection(DefaultClientConnectionOperator.java:162)
    at org.apache.http.impl.conn.ManagedClientConnectionImpl.open(ManagedClientConnectionImpl.java:326)
    at org.apache.http.impl.client.DefaultRequestDirector.tryConnect(DefaultRequestDirector.java:610)
    at org.apache.http.impl.client.DefaultRequestDirector.execute(DefaultRequestDirector.java:445)
    at org.apache.http.impl.client.AbstractHttpClient.doExecute(AbstractHttpClient.java:835)
    at org.apache.http.impl.client.CloseableHttpClient.execute(CloseableHttpClient.java:83)
    at org.apache.http.impl.client.CloseableHttpClient.execute(CloseableHttpClient.java:56)
    at com.amazonaws.http.AmazonHttpClient.executeHelper(AmazonHttpClient.java:384)
    ... 34 more


有人知道如何让 spark 以任何方式从 docker 容器连接到 localstack S3 bucket 吗?提前致谢。

最佳答案

一段时间后,我想通了。

事实证明,您需要将"spark.hadoop.fs.s3a.path.style.access" 参数设置为true,这样spark 才能找到您的容器按名字。

请记住,此参数仅适用于 hadoop 版本 2.8.0 及更高版本。

进行此更改并升级 hadoop 后,一切正常。

关于docker - 使用 docker compose 将 spark 连接到 localstack s3,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/58634166/

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