Spark Cassandra Connector配置信任库路径报NoSuchFileException异常

我在PySpark应用中使用Datastax Spark Cassandra Connector，运行模式为.master("yarn")。根据安全规则，必须通过SSL连接Cassandra：Cassandra仅校验用户名/密码，无需客户端认证，但客户端需通过SSL证书校验Cassandra。

我配置的SparkSession参数如下：

spark.cassandra.connection.ssl.enabled: true
spark.cassandra.connection.ssl.clientAuth.enabled: false
spark.cassandra.connection.ssl.trustStore.path: "/home/tech_profiling/mdp-cassandra-keystore.jks"
spark.cassandra.connection.ssl.trustStore.password: "cassandra"
spark.cassandra.auth.username: "my_super_dooper_gigachad_user"
spark.cassandra.auth.username: "my_mega_password"

已确认文件/home/tech_profiling/mdp-cassandra-keystore.jks存在于Spark集群节点上，但仍触发如下异常：

py4j.protocol.Py4JJavaError: An error occurred while calling o486.save.
: java.nio.file.NoSuchFileException: /home/tech_profiling/mdp-cassandra-keystore.jks
    at sun.nio.fs.UnixException.translateToIOException(UnixException.java:86)
    at sun.nio.fs.UnixException.rethrowAsIOException(UnixException.java:102)
    at sun.nio.fs.UnixException.rethrowAsIOException(UnixException.java:107)
    at sun.nio.fs.UnixFileSystemProvider.newByteChannel(UnixFileSystemProvider.java:214)
    at java.nio.file.Files.newByteChannel(Files.java:361)
    at java.nio.file.Files.newByteChannel(Files.java:407)
    at java.nio.file.spi.FileSystemProvider.newInputStream(FileSystemProvider.java:384)
    at java.nio.file.Files.newInputStream(Files.java:152)
    at com.datastax.spark.connector.cql.DefaultConnectionFactory$.getKeyStore(CassandraConnectionFactory.scala:78)
    at com.datastax.spark.connector.cql.DefaultConnectionFactory$.trustStore$lzycompute$1(CassandraConnectionFactory.scala:92)
    at com.datastax.spark.connector.cql.DefaultConnectionFactory$.trustStore$1(CassandraConnectionFactory.scala:91)
    at com.datastax.spark.connector.cql.DefaultConnectionFactory$.maybeCreateSSLOptions(CassandraConnectionFactory.scala:97)
    at com.datastax.spark.connector.cql.DefaultConnectionFactory$.clusterBuilder(CassandraConnectionFactory.scala:62)
    at com.datastax.spark.connector.cql.DefaultConnectionFactory$.createCluster(CassandraConnectionFactory.scala:131)
    at com.datastax.spark.connector.cql.CassandraConnector$.com$datastax$spark$connector$cql$CassandraConnector$$createSession(CassandraConnector.scala:159)
    at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$8.apply(CassandraConnector.scala:154)
    at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$8.apply(CassandraConnector.scala:154)
    at com.datastax.spark.connector.cql.RefCountedCache.createNewValueAndKeys(RefCountedCache.scala:32)
    at com.datastax.spark.connector.cql.RefCountedCache.syncAcquire(RefCountedCache.scala:69)
    at com.datastax.spark.connector.cql.RefCountedCache.acquire(RefCountedCache.scala:57)
    at com.datastax.spark.connector.cql.CassandraConnector.openSession(CassandraConnector.scala:79)
    at com.datastax.spark.connector.cql.CassandraConnector.withSessionDo(CassandraConnector.scala:111)
    at com.datastax.spark.connector.rdd.partitioner.dht.TokenFactory$.forSystemLocalPartitioner(TokenFactory.scala:98)
    at org.apache.spark.sql.cassandra.CassandraSourceRelation$.apply(CassandraSourceRelation.scala:276)
    at org.apache.spark.sql.cassandra.DefaultSource.createRelation(DefaultSource.scala:83)
    at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:45)
    at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
    at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
    at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:86)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:136)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:132)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:160)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:157)
    at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:132)
    at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:83)
    at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:81)
    at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:696)
    at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:696)
    at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:80)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:127)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:75)
    at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:696)
    at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:305)
    at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:291)
    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)

问题排查与解决方案 #

1. YARN模式下的文件路径问题 #

YARN集群中，Driver和Executor可能运行在不同节点，本地路径/home/tech_profiling/...仅对提交任务的节点可见，Executor节点或Driver所在的ApplicationMaster节点可能没有该文件。

• 方案一：将信任库文件上传到HDFS，修改配置路径为HDFS路径，例如：

  spark.cassandra.connection.ssl.trustStore.path: "hdfs:///user/tech_profiling/mdp-cassandra-keystore.jks"
  

• 方案二：提交Spark任务时通过--files参数将文件分发到所有节点的工作目录，此时配置路径使用相对路径：

  spark-submit --files /home/tech_profiling/mdp-cassandra-keystore.jks ...
  

  配置改为：

  spark.cassandra.connection.ssl.trustStore.path: "./mdp-cassandra-keystore.jks"
  

2. 配置项笔误修正 #

你的配置中重复使用了spark.cassandra.auth.username，密码项应该改为spark.cassandra.auth.password，修正后的配置：

spark.cassandra.auth.username: "my_super_dooper_gigachad_user"
spark.cassandra.auth.password: "my_mega_password"

3. 文件权限检查 #

即使文件存在，Spark运行的用户（通常是yarn用户）可能没有读取权限：

• 执行ls -l /home/tech_profiling/mdp-cassandra-keystore.jks查看权限，确保其他用户有读权限（权限位包含r--）
• 若权限不足，可修改权限：chmod o+r /home/tech_profiling/mdp-cassandra-keystore.jks，或修改文件所属组为yarn组：chgrp yarn /home/tech_profiling/mdp-cassandra-keystore.jks

内容的提问来源于stack exchange，提问作者Felix