[jira] [Assigned] (SPARK-32380) sparksql cannot access hive table while data in hbase

2022-11-05 Thread Apache Spark (Jira) 


 [ 
https://issues.apache.org/jira/browse/SPARK-32380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-32380:


Assignee: Apache Spark

> sparksql cannot access hive table while data in hbase
> -
>
> Key: SPARK-32380
> URL: https://issues.apache.org/jira/browse/SPARK-32380
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 3.0.0
> Environment: ||component||version||
> |hadoop|2.8.5|
> |hive|2.3.7|
> |spark|3.0.0|
> |hbase|1.4.9|
>Reporter: deyzhong
>Assignee: Apache Spark
>Priority: Major
>   Original Estimate: 72h
>  Remaining Estimate: 72h
>
> * step1: create hbase table
> {code:java}
>  hbase(main):001:0>create 'hbase_test1', 'cf1'
>  hbase(main):001:0> put 'hbase_test', 'r1', 'cf1:c1', '123'
> {code}
>  * step2: create hive table related to hbase table
>  
> {code:java}
> hive> 
> CREATE EXTERNAL TABLE `hivetest.hbase_test`(
>   `key` string COMMENT '', 
>   `value` string COMMENT '')
> ROW FORMAT SERDE 
>   'org.apache.hadoop.hive.hbase.HBaseSerDe' 
> STORED BY 
>   'org.apache.hadoop.hive.hbase.HBaseStorageHandler' 
> WITH SERDEPROPERTIES ( 
>   'hbase.columns.mapping'=':key,cf1:v1', 
>   'serialization.format'='1')
> TBLPROPERTIES (
>   'hbase.table.name'='hbase_test')
>  {code}
>  * step3: sparksql query hive table while data in hbase
> {code:java}
> spark-sql --master yarn -e "select * from hivetest.hbase_test"
> {code}
>  
> The error log as follow: 
> java.io.IOException: Cannot create a record reader because of a previous 
> error. Please look at the previous logs lines from the task's full log for 
> more details.
>  at 
> org.apache.hadoop.hbase.mapreduce.TableInputFormatBase.getSplits(TableInputFormatBase.java:270)
>  at org.apache.spark.rdd.NewHadoopRDD.getPartitions(NewHadoopRDD.scala:131)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2158)
>  at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1004)
>  at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>  at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
>  at org.apache.spark.rdd.RDD.withScope(RDD.scala:388)
>  at org.apache.spark.rdd.RDD.collect(RDD.scala:1003)
>  at 
> org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:385)
>  at 
> org.apache.spark.sql.execution.SparkPlan.executeCollectPublic(SparkPlan.scala:412)
>  at 
> org.apache.spark.sql.execution.HiveResult$.hiveResultString(HiveResult.scala:58)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.$anonfun$run$1(SparkSQLDriver.scala:65)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
>  at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:763)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.run(SparkSQLDriver.scala:65)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:377)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.$anonfun$processLine$1(SparkSQLCLIDriver.scala:496)
>  at scala.collection.Iterator.foreach(Iterator.scala:941)
>  at scala.collection.Iterator.foreach$(Iterator.scala:941)
>  at

[jira] [Assigned] (SPARK-32380) sparksql cannot access hive table while data in hbase

2022-11-05 Thread Apache Spark (Jira) 


 [ 
https://issues.apache.org/jira/browse/SPARK-32380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-32380:


Assignee: (was: Apache Spark)

> sparksql cannot access hive table while data in hbase
> -
>
> Key: SPARK-32380
> URL: https://issues.apache.org/jira/browse/SPARK-32380
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 3.0.0
> Environment: ||component||version||
> |hadoop|2.8.5|
> |hive|2.3.7|
> |spark|3.0.0|
> |hbase|1.4.9|
>Reporter: deyzhong
>Priority: Major
>   Original Estimate: 72h
>  Remaining Estimate: 72h
>
> * step1: create hbase table
> {code:java}
>  hbase(main):001:0>create 'hbase_test1', 'cf1'
>  hbase(main):001:0> put 'hbase_test', 'r1', 'cf1:c1', '123'
> {code}
>  * step2: create hive table related to hbase table
>  
> {code:java}
> hive> 
> CREATE EXTERNAL TABLE `hivetest.hbase_test`(
>   `key` string COMMENT '', 
>   `value` string COMMENT '')
> ROW FORMAT SERDE 
>   'org.apache.hadoop.hive.hbase.HBaseSerDe' 
> STORED BY 
>   'org.apache.hadoop.hive.hbase.HBaseStorageHandler' 
> WITH SERDEPROPERTIES ( 
>   'hbase.columns.mapping'=':key,cf1:v1', 
>   'serialization.format'='1')
> TBLPROPERTIES (
>   'hbase.table.name'='hbase_test')
>  {code}
>  * step3: sparksql query hive table while data in hbase
> {code:java}
> spark-sql --master yarn -e "select * from hivetest.hbase_test"
> {code}
>  
> The error log as follow: 
> java.io.IOException: Cannot create a record reader because of a previous 
> error. Please look at the previous logs lines from the task's full log for 
> more details.
>  at 
> org.apache.hadoop.hbase.mapreduce.TableInputFormatBase.getSplits(TableInputFormatBase.java:270)
>  at org.apache.spark.rdd.NewHadoopRDD.getPartitions(NewHadoopRDD.scala:131)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2158)
>  at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1004)
>  at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>  at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
>  at org.apache.spark.rdd.RDD.withScope(RDD.scala:388)
>  at org.apache.spark.rdd.RDD.collect(RDD.scala:1003)
>  at 
> org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:385)
>  at 
> org.apache.spark.sql.execution.SparkPlan.executeCollectPublic(SparkPlan.scala:412)
>  at 
> org.apache.spark.sql.execution.HiveResult$.hiveResultString(HiveResult.scala:58)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.$anonfun$run$1(SparkSQLDriver.scala:65)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
>  at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:763)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.run(SparkSQLDriver.scala:65)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:377)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.$anonfun$processLine$1(SparkSQLCLIDriver.scala:496)
>  at scala.collection.Iterator.foreach(Iterator.scala:941)
>  at scala.collection.Iterator.foreach$(Iterator.scala:941)
>  at scala.collection.AbstractIterator.foreach(Iterator.scala:1429)
>  at

[jira] [Assigned] (SPARK-32380) sparksql cannot access hive table while data in hbase

2020-07-21 Thread Apache Spark (Jira) 


 [ 
https://issues.apache.org/jira/browse/SPARK-32380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-32380:


Assignee: Apache Spark

> sparksql cannot access hive table while data in hbase
> -
>
> Key: SPARK-32380
> URL: https://issues.apache.org/jira/browse/SPARK-32380
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 3.0.0
> Environment: ||component||version||
> |hadoop|2.8.5|
> |hive|2.3.7|
> |spark|3.0.0|
> |hbase|1.4.9|
>Reporter: deyzhong
>Assignee: Apache Spark
>Priority: Major
>   Original Estimate: 72h
>  Remaining Estimate: 72h
>
> * step1: create hbase table
> {code:java}
>  hbase(main):001:0>create 'hbase_test1', 'cf1'
>  hbase(main):001:0> put 'hbase_test', 'r1', 'cf1:c1', '123'
> {code}
>  * step2: create hive table related to hbase table
>  
> {code:java}
> hive> 
> CREATE EXTERNAL TABLE `hivetest.hbase_test`(
>   `key` string COMMENT '', 
>   `value` string COMMENT '')
> ROW FORMAT SERDE 
>   'org.apache.hadoop.hive.hbase.HBaseSerDe' 
> STORED BY 
>   'org.apache.hadoop.hive.hbase.HBaseStorageHandler' 
> WITH SERDEPROPERTIES ( 
>   'hbase.columns.mapping'=':key,cf1:v1', 
>   'serialization.format'='1')
> TBLPROPERTIES (
>   'hbase.table.name'='hbase_test')
>  {code}
>  * step3: sparksql query hive table while data in hbase
> {code:java}
> spark-sql --master yarn -e "select * from hivetest.hbase_test"
> {code}
>  
> The error log as follow: 
> java.io.IOException: Cannot create a record reader because of a previous 
> error. Please look at the previous logs lines from the task's full log for 
> more details.
>  at 
> org.apache.hadoop.hbase.mapreduce.TableInputFormatBase.getSplits(TableInputFormatBase.java:270)
>  at org.apache.spark.rdd.NewHadoopRDD.getPartitions(NewHadoopRDD.scala:131)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2158)
>  at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1004)
>  at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>  at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
>  at org.apache.spark.rdd.RDD.withScope(RDD.scala:388)
>  at org.apache.spark.rdd.RDD.collect(RDD.scala:1003)
>  at 
> org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:385)
>  at 
> org.apache.spark.sql.execution.SparkPlan.executeCollectPublic(SparkPlan.scala:412)
>  at 
> org.apache.spark.sql.execution.HiveResult$.hiveResultString(HiveResult.scala:58)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.$anonfun$run$1(SparkSQLDriver.scala:65)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
>  at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:763)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.run(SparkSQLDriver.scala:65)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:377)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.$anonfun$processLine$1(SparkSQLCLIDriver.scala:496)
>  at scala.collection.Iterator.foreach(Iterator.scala:941)
>  at scala.collection.Iterator.foreach$(Iterator.scala:941)
>  at

[jira] [Assigned] (SPARK-32380) sparksql cannot access hive table while data in hbase

2020-07-21 Thread Apache Spark (Jira) 


 [ 
https://issues.apache.org/jira/browse/SPARK-32380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-32380:


Assignee: (was: Apache Spark)

> sparksql cannot access hive table while data in hbase
> -
>
> Key: SPARK-32380
> URL: https://issues.apache.org/jira/browse/SPARK-32380
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 3.0.0
> Environment: ||component||version||
> |hadoop|2.8.5|
> |hive|2.3.7|
> |spark|3.0.0|
> |hbase|1.4.9|
>Reporter: deyzhong
>Priority: Major
>   Original Estimate: 72h
>  Remaining Estimate: 72h
>
> * step1: create hbase table
> {code:java}
>  hbase(main):001:0>create 'hbase_test1', 'cf1'
>  hbase(main):001:0> put 'hbase_test', 'r1', 'cf1:c1', '123'
> {code}
>  * step2: create hive table related to hbase table
>  
> {code:java}
> hive> 
> CREATE EXTERNAL TABLE `hivetest.hbase_test`(
>   `key` string COMMENT '', 
>   `value` string COMMENT '')
> ROW FORMAT SERDE 
>   'org.apache.hadoop.hive.hbase.HBaseSerDe' 
> STORED BY 
>   'org.apache.hadoop.hive.hbase.HBaseStorageHandler' 
> WITH SERDEPROPERTIES ( 
>   'hbase.columns.mapping'=':key,cf1:v1', 
>   'serialization.format'='1')
> TBLPROPERTIES (
>   'hbase.table.name'='hbase_test')
>  {code}
>  * step3: sparksql query hive table while data in hbase
> {code:java}
> spark-sql --master yarn -e "select * from hivetest.hbase_test"
> {code}
>  
> The error log as follow: 
> java.io.IOException: Cannot create a record reader because of a previous 
> error. Please look at the previous logs lines from the task's full log for 
> more details.
>  at 
> org.apache.hadoop.hbase.mapreduce.TableInputFormatBase.getSplits(TableInputFormatBase.java:270)
>  at org.apache.spark.rdd.NewHadoopRDD.getPartitions(NewHadoopRDD.scala:131)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
>  at org.apache.spark.rdd.RDD.$anonfun$partitions$2(RDD.scala:276)
>  at scala.Option.getOrElse(Option.scala:189)
>  at org.apache.spark.rdd.RDD.partitions(RDD.scala:272)
>  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2158)
>  at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1004)
>  at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>  at 
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
>  at org.apache.spark.rdd.RDD.withScope(RDD.scala:388)
>  at org.apache.spark.rdd.RDD.collect(RDD.scala:1003)
>  at 
> org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:385)
>  at 
> org.apache.spark.sql.execution.SparkPlan.executeCollectPublic(SparkPlan.scala:412)
>  at 
> org.apache.spark.sql.execution.HiveResult$.hiveResultString(HiveResult.scala:58)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.$anonfun$run$1(SparkSQLDriver.scala:65)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
>  at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:763)
>  at 
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.run(SparkSQLDriver.scala:65)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:377)
>  at 
> org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.$anonfun$processLine$1(SparkSQLCLIDriver.scala:496)
>  at scala.collection.Iterator.foreach(Iterator.scala:941)
>  at scala.collection.Iterator.foreach$(Iterator.scala:941)
>  at scala.collection.AbstractIterator.foreach(Iterator.scala:1429)
>  at