Hadoop运维记录系列（二十七）

记录一个调试 pyspark2sql 访问 HDFS 透明加密的问题。

访问源码如下，使用 pyspark2.1.3，基于 CDH 5.14.0 hive 1.1.0 + parquet，其中select的部分会访问 hdfs 加密区域。

from pyspark.sql import SQLContextfrom pyspark.sql import HiveContext, Rowfrom pyspark.sql.types import *import pandas as pdimport pyspark.sql.functions as F trial_pps_order = spark.read.parquet('/tmp/exia/trial_pps_select')pps_order = spark.read.parquet('/tmp/exia/orders_pps_wc_member')member_info = spark.read.parquet('/tmp/exia/member_info')  # newHiveContext=HiveContext(sc) query_T="""   select  * from crm.masterdata_hummingbird_product_mst_banner_v1 where brand_name = 'pampers' """product_mst=spark.sql(query_T) product_mst.show()

在 zeppelin里运行后返回报错如下

Traceback (most recent call last):  File "/tmp/zeppelin_pyspark-7483288776781667654.py", line 367, in     raise Exception(traceback.format_exc())Exception: Traceback (most recent call last):  File "/tmp/zeppelin_pyspark-7483288776781667654.py", line 360, in     exec(code, _zcUserQueryNameSpace)  File "", line 14, in   File "/usr/lib/spark-2.1.3-bin-hadoop2.6/python/pyspark/sql/dataframe.py", line 318, in show    print(self._jdf.showString(n, 20))  File "/usr/lib/spark-2.1.3-bin-hadoop2.6/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__    answer, self.gateway_client, self.target_id, self.name)  File "/usr/lib/spark-2.1.3-bin-hadoop2.6/python/pyspark/sql/utils.py", line 63, in deco    return f(*a, **kw)  File "/usr/lib/spark-2.1.3-bin-hadoop2.6/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value    format(target_id, ".", name), value)Py4JJavaError: An error occurred while calling o76.showString.: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 3.0 failed 4 times, most recent failure: Lost task 0.3 in stage 3.0 (TID 6, pg-dmp-slave28.hadoop, executor 1): java.io.IOException: No KeyProvider is configured, cannot access an encrypted file        at org.apache.hadoop.hdfs.DFSClient.decryptEncryptedDataEncryptionKey(DFSClient.java:1338)        at org.apache.hadoop.hdfs.DFSClient.createWrappedInputStream(DFSClient.java:1414)        at org.apache.hadoop.hdfs.DistributedFileSystem$3.doCall(DistributedFileSystem.java:304)        at org.apache.hadoop.hdfs.DistributedFileSystem$3.doCall(DistributedFileSystem.java:298)        at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)        at org.apache.hadoop.hdfs.DistributedFileSystem.open(DistributedFileSystem.java:298)        at org.apache.hadoop.fs.FileSystem.open(FileSystem.java:766)        at org.apache.hadoop.mapred.LineRecordReader.(LineRecordReader.java:109)        at org.apache.hadoop.mapred.TextInputFormat.getRecordReader(TextInputFormat.java:67)        at org.apache.spark.rdd.HadoopRDD$$anon$1.liftedTree1$1(HadoopRDD.scala:257)        at org.apache.spark.rdd.HadoopRDD$$anon$1.(HadoopRDD.scala:256)        at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:216)        at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:102)        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)        at org.apache.spark.scheduler.Task.run(Task.scala:100)        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:325)        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)        at java.lang.Thread.run(Thread.java:748)Driver stacktrace:        at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1455)        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1443)        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1442)        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)        at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1442)        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)        at scala.Option.foreach(Option.scala:257)        at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1670)        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1625)        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1614)        at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)        at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)        at org.apache.spark.SparkContext.runJob(SparkContext.scala:1928)        at org.apache.spark.SparkContext.runJob(SparkContext.scala:1941)        at org.apache.spark.SparkContext.runJob(SparkContext.scala:1954)        at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:333)        at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)        at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2390)        at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)        at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2792)        at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2389)        at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2396)        at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2132)        at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2131)        at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2822)        at org.apache.spark.sql.Dataset.head(Dataset.scala:2131)        at org.apache.spark.sql.Dataset.take(Dataset.scala:2346)        at org.apache.spark.sql.Dataset.showString(Dataset.scala:248)        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.io.IOException: No KeyProvider is configured, cannot access an encrypted file        at org.apache.hadoop.hdfs.DFSClient.decryptEncryptedDataEncryptionKey(DFSClient.java:1338)        at org.apache.hadoop.hdfs.DFSClient.createWrappedInputStream(DFSClient.java:1414)        at org.apache.hadoop.hdfs.DistributedFileSystem$3.doCall(DistributedFileSystem.java:304)        at org.apache.hadoop.hdfs.DistributedFileSystem$3.doCall(DistributedFileSystem.java:298)        at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)        at org.apache.hadoop.hdfs.DistributedFileSystem.open(DistributedFileSystem.java:298)        at org.apache.hadoop.fs.FileSystem.open(FileSystem.java:766)        at org.apache.hadoop.mapred.LineRecordReader.(LineRecordReader.java:109)        at org.apache.hadoop.mapred.TextInputFormat.getRecordReader(TextInputFormat.java:67)        at org.apache.spark.rdd.HadoopRDD$$anon$1.liftedTree1$1(HadoopRDD.scala:257)        at org.apache.spark.rdd.HadoopRDD$$anon$1.(HadoopRDD.scala:256)        at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:216)        at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:102)        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)        at org.apache.spark.scheduler.Task.run(Task.scala:100)        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:325)        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)        ... 1 more

主要来说，日志里提示是没有提供访问加密区域的key，无法访问被加密的数据。

出现这个报错的主要原因是spark会优先使用其自身conf文件夹下的hive-site.xml配置项来访问hiveserver2服务，但是这个hive-site.xml文件里面没有配置访问加密区域所需要的配置。加上就OK了。

      hadoop.security.key.provider.path    kms://http@dmp-master2.hadoop:16000/kms        dfs.encrypt.data.transfer.algorithm    3des        dfs.encrypt.data.transfer.cipher.suites    AES/CTR/NoPadding        dfs.encrypt.data.transfer.cipher.key.bitlength    256        dfs.encryption.key.provider.uri    kms://http@dmp-master2.hadoop:16000/kms