问题现象

CDH版本：6.3.2
1）使用hive-cli on spark运行的时候，出现如下错误：

FAILED: Execution Error, return code 3 from org.apache.hadoop.hive.ql.exec.spark.SparkTask. Spark job failed due to: Job aborted due to stage failure: 
Aborting TaskSet 0.0 because task 0 (partition 0)
cannot run anywhere due to node and executor blacklist.
Most recent failure:
Lost task 0.1 in stage 0.0 (TID 1, syx-prod-bigdata-cdh-79-163, executor 2): java.io.IOException: java.lang.reflect.InvocationTargetException
        at org.apache.hadoop.hive.io.HiveIOExceptionHandlerChain.handleRecordReaderCreationException(HiveIOExceptionHandlerChain.java:97)
        at org.apache.hadoop.hive.io.HiveIOExceptionHandlerUtil.handleRecordReaderCreationException(HiveIOExceptionHandlerUtil.java:57)
        at org.apache.hadoop.hive.shims.HadoopShimsSecure$CombineFileRecordReader.initNextRecordReader(HadoopShimsSecure.java:271)
        at org.apache.hadoop.hive.shims.HadoopShimsSecure$CombineFileRecordReader.<init>(HadoopShimsSecure.java:217)
        at org.apache.hadoop.hive.shims.HadoopShimsSecure$CombineFileInputFormatShim.getRecordReader(HadoopShimsSecure.java:345)
        at org.apache.hadoop.hive.ql.io.CombineHiveInputFormat.getRecordReader(CombineHiveInputFormat.java:702)
        at org.apache.spark.rdd.HadoopRDD$$anon$1.liftedTree1$1(HadoopRDD.scala:272)
        at org.apache.spark.rdd.HadoopRDD$$anon$1.<init>(HadoopRDD.scala:271)
        at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:225)
        at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:96)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
        at org.apache.spark.scheduler.Task.run(Task.scala:121)
        at org.apache.spark.executor.Executor$TaskRunner$$anonfun$11.apply(Executor.scala:407)
        at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1408)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:413)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.reflect.InvocationTargetException
        at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
        at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
        at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
        at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
        at org.apache.hadoop.hive.shims.HadoopShimsSecure$CombineFileRecordReader.initNextRecordReader(HadoopShimsSecure.java:257)
        ... 21 more
Caused by: java.lang.UnsatisfiedLinkError: org.apache.hadoop.util.NativeCodeLoader.buildSupportsSnappy()Z
        at org.apache.hadoop.util.NativeCodeLoader.buildSupportsSnappy(Native Method)
        at org.apache.hadoop.io.compress.SnappyCodec.checkNativeCodeLoaded(SnappyCodec.java:63)
        at org.apache.hadoop.io.compress.SnappyCodec.getDecompressorType(SnappyCodec.java:195)
        at org.apache.hadoop.io.compress.CodecPool.getDecompressor(CodecPool.java:181)
        at org.apache.hadoop.mapred.LineRecordReader.<init>(LineRecordReader.java:111)
        at org.apache.hadoop.mapred.TextInputFormat.getRecordReader(TextInputFormat.java:67)
        at org.apache.hadoop.hive.ql.io.CombineHiveRecordReader.<init>(CombineHiveRecordReader.java:68)
        ... 26 more

这块是由于hive的表最终是采用的snappy压缩，在使用spark读取数据的时候，发现不能正常解压snappy格式的数据，从上面的错误也可以看出来。初步怀疑是本地的native库没有正常加载。
2）采用beeline客户端进行提交
采用这种方式提交没问题。

由于某些客观原因，一些脚本任务还是采用的hive-cli的方式运行。

问题排查

1）这块出现问题的时候，也在网上找到了一些资料，说是修改spark-env.sh文件的如下配置：

export JAVA_LIBRARY_PATH=$JAVA_LIBRARY_PATH:$HADOOP_HOME/lib/native
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$HADOOP_HOME/lib/native
export SPARK_YARN_USER_ENV="JAVA_LIBRARY_PATH=$JAVA_LI:BRARY_PATH,LD_LIBRARY_PATH=$LD_LIBRARY_PATH"

通过这种方式并未能解决问题。
2）问题思考
在spark里面，对于配置，一般来说主要是spark-env.sh合spark-defaults.conf文件，除了可以定义环境变量以为，还可以在spark.defaults.conf文件定义spark.driver.extraLibraryPath 等类路径信息。按着这个思路。查看对应的spark.defaults.conf文件

cat /opt/cloudera/parcels/CDH/lib/spark/conf/spark-defaults.conf
spark.driver.extraLibraryPath=/opt/cloudera/parcels/CDH-6.3.2-1.cdh6.3.2.p0.1605554/lib/hadoop/lib/native
spark.executor.extraLibraryPath=/opt/cloudera/parcels/CDH-6.3.2-1.cdh6.3.2.p0.1605554/lib/hadoop/lib/native
spark.yarn.am.extraLibraryPath=/opt/cloudera/parcels/CDH-6.3.2-1.cdh6.3.2.p0.1605554/lib/hadoop/lib/native

注：上述的参数是本人已经修改过后的值。
按照这种方式修改以后，接着在hive-cli里面在运行hive sql，发现还是不行，依然出现最开始的错误。
3）会不会hive-cli 根本就没有读取到spark.defaults.conf和spark-env.sh信息？？？
按着这个思路，执行了下述操作：

cp /opt/cloudera/parcels/CDH/lib/spark/conf/spark-env.sh /etc/hive/conf/
cp /opt/cloudera/parcels/CDH/lib/spark/conf/spark-defaults.conf /etc/hive/conf/

通过这种方式，让hive加载指定的spark配置信息。这一步在运行sql，出现了不能创建java 虚拟机的异常了。部分异常代码如下：

Caused by: java.lang.RuntimeException: spark-submit process failed with exit code 1 and error "Error: Could not create the Java Virtual Machine.","Error: A fatal exception has occurred. Program will exit."
        at org.apache.hive.spark.client.SparkClientImpl$2.run(SparkClientImpl.java:495) ~[hive-exec-2.1.1-cdh6.3.2.jar:2.1.1-cdh6.3.2]
        ... 1 more
ERROR : FAILED: Execution Error, return code 30041 from org.apache.hadoop.hive.ql.exec.spark.SparkTask. Failed to create Spark client for Spark session 0e5cca78-2a7e-4414-b5c9-c73b41b0a2c7_0: java.lang.RuntimeException: spark-submit process failed with exit code 1 and error "Error: Could not create the Java Virtual Machine.","Error: A fatal exception has occurred. Program will exit."
Error: Error while processing statement: FAILED: Execution Error, return code 30041 from org.apache.hadoop.hive.ql.exec.spark.SparkTask. Failed to create Spark client for Spark session 0e5cca78-2a7e-4414-b5c9-c73b41b0a2c7_0: java.lang.RuntimeException: spark-submit process failed with exit code 1 and error "Error: Could not create the Java Virtual Machine.","Error: A fatal exception has occurred. Program will exit." (state=42000,code=30041)

这说明hive-cli客户端正常加载了spark的配置信息。

问题解决

注释掉/etc/hive/conf/spark-defaults.conf配置文件里面的如下信息：

#spark.master=yarn
#spark.submit.deployMode=client

关于为什么beeline客户端在执行的时候正常加载了spark的信息，但是hive-cli没有正常加载，这块就不细研究了。hive-cli本身就已经过时，正常情况下都不会使用这种方式进行提交任务。