hive spark引擎开窗函数后引起异常求问各位大神这个差别

作者: 无来无去_A | 来源:发表于2020-07-10 19:41 被阅读0次

hdfs集群三个节点内存： 8G ，4G ，4G
Hive 配置spark 引擎提交查询

最新更新:使用sparlSql 也能执行成功，SparkSql 和 hive on spark 都是使用spark计算引擎，但是两#者在SQL 语法解析不相同。

目标: 请写出代码求得所有用户和活跃用户的总数及平均年龄。（活跃用户指连续两天都有访问记录的用户）日期用户年龄

解法1:

select 
        sum(allCount) ,sum(allAvg) ,sum(twiceCount) ,sum(twiceAvg) 
        from 
         (select 
         count(*) as allCount,
--       AVG(t.age) as avgAge ,
         sum(t.age) / count(*) as allAvg ,
         0 as twiceCount ,
         0 as twiceAvg
         from 
        (select 
         user_id  , age
         from user_age group by user_id  , age ) t
         union all
       select
        0 as allCount ,
       0 as allAvg ,
       count(*) as twiceCount ,
       sum(t4.age)/count(*) as twiceAvg
       from 
       (select 
       t3.user_id ,
       min(t3.age) as age
       from 
       ( select 
        t2.user_id ,
        t2.age 
        from 
        ( SELECT 
        t1.user_id ,
        t1.age ,
        date_sub(t1.dt , t1.rn) as  diff
        from 
        (select     
        t.user_id ,
        t.age ,
        t.dt ,
        ROW_NUMBER () over(PARTITION  by t.user_id  order by t.dt ) rn 
        from 
         (select 
        user_id ,
        age ,
        dt
        from  user_age  group by user_id , age ,dt ) t) t1 ) t2  group by  t2.user_id ,
        t2.age ,
        t2.diff HAVING count(t2.user_id) >= 2 ) t3 group by t3.user_id) t4 group by t4.user_id ) t5

解法2:

select 
        sum(allCount) ,
        sum(allAvg) ,
        sum(twiceCount) ,
        sum(twiceAvg) 
        from 
         (select 
         count(*) as allCount,
--       AVG(t.age) as avgAge ,
         sum(t.age) / count(*) as allAvg ,
         0 as twiceCount ,
         0 as twiceAvg
         from 
        (select 
         user_id  , age
         from user_age group by user_id  , age ) t
         union all
       select
        0 as allCount ,
       0 as allAvg ,
       count(*) as twiceCount ,
       sum(t4.age)/count(*) as twiceAvg
       from 
       (
       select 
       t3.user_id ,
       min(t3.age) as age
       from 
       ( 
       select 
        t2.user_id ,
        t2.age ,
        COUNT(t2.user_id) over(PARTITION BY t2.user_id,t2.diff) days
        from 
        ( SELECT 
        t1.user_id ,
        t1.age ,
        date_sub(t1.dt , t1.rn) as  diff
        from 
        (select     
        t.user_id ,
        t.age ,
        t.dt ,
        ROW_NUMBER () over(PARTITION  by t.user_id  order by t.dt ) rn 
        from 
         (select 
        user_id ,
        age ,
        dt
        from  user_age  group by user_id , age ,dt ) t) t1 ) t2  
      
        ) t3 where t3.days >=2  group by t3.user_id) t4 group by t4.user_id ) t5 ;

解法2 使用spark 引擎报错。

源数据

create table user_age(dt string,user_id string,age int)row format delimited fields terminated by ',';

2019-02-11,test_1,23
2019-02-11,test_2,19
2019-02-11,test_3,39
2019-02-11,test_1,23
2019-02-11,test_3,39
2019-02-11,test_1,23
2019-02-12,test_2,19
2019-02-13,test_1,23
2019-02-15,test_2,19
2019-02-16,test_2,19

使用开窗函数提示异常

 select 
        t2.user_id 
        ,t2.age 
        ,COUNT(t2.user_id) over(PARTITION BY t2.user_id,t2.diff) as days
        from 
         ( SELECT 
        t1.user_id ,
        t1.age ,
        date_sub(t1.dt , t1.rn) as  diff
        from 
        (select     
        t.user_id ,
        t.age ,
        t.dt ,
        ROW_NUMBER () over(PARTITION  by t.user_id  order by t.dt ) rn 
        from 
         (select 
        user_id ,
        age ,
        dt
        from  user_age  group by user_id , age ,dt ) t) t1 ) t2

DBeaver异常显示

org.jkiss.dbeaver.model.sql.DBSQLException: SQL 错误 [3] [42000]: Error while processing statement: FAILED: Execution Error, return code 3 from org.apache.hadoop.hive.ql.exec.spark.SparkTask. Spark job failed during runtime. Please check stacktrace for the root cause.
    at org.jkiss.dbeaver.model.impl.jdbc.exec.JDBCStatementImpl.executeStatement(JDBCStatementImpl.java:134)
    at org.jkiss.dbeaver.ui.editors.sql.execute.SQLQueryJob.executeStatement(SQLQueryJob.java:487)
    at org.jkiss.dbeaver.ui.editors.sql.execute.SQLQueryJob.lambda$0(SQLQueryJob.java:424)
    at org.jkiss.dbeaver.model.exec.DBExecUtils.tryExecuteRecover(DBExecUtils.java:164)
    at org.jkiss.dbeaver.ui.editors.sql.execute.SQLQueryJob.executeSingleQuery(SQLQueryJob.java:416)
    at org.jkiss.dbeaver.ui.editors.sql.execute.SQLQueryJob.extractData(SQLQueryJob.java:774)
    at org.jkiss.dbeaver.ui.editors.sql.SQLEditor$QueryResultsContainer.readData(SQLEditor.java:2914)
    at org.jkiss.dbeaver.ui.controls.resultset.ResultSetJobDataRead.lambda$0(ResultSetJobDataRead.java:110)
    at org.jkiss.dbeaver.model.exec.DBExecUtils.tryExecuteRecover(DBExecUtils.java:164)
    at org.jkiss.dbeaver.ui.controls.resultset.ResultSetJobDataRead.run(ResultSetJobDataRead.java:108)
    at org.jkiss.dbeaver.ui.controls.resultset.ResultSetViewer$17.run(ResultSetViewer.java:3421)
    at org.jkiss.dbeaver.model.runtime.AbstractJob.run(AbstractJob.java:103)
    at org.eclipse.core.internal.jobs.Worker.run(Worker.java:63)
Caused by: java.sql.SQLException: Error while processing statement: FAILED: Execution Error, return code 3 from org.apache.hadoop.hive.ql.exec.spark.SparkTask. Spark job failed during runtime. Please check stacktrace for the root cause.
    at org.apache.hive.jdbc.HiveStatement.waitForOperationToComplete(HiveStatement.java:354)
    at org.apache.hive.jdbc.HiveStatement.execute(HiveStatement.java:245)
    at org.jkiss.dbeaver.model.impl.jdbc.exec.JDBCStatementImpl.execute(JDBCStatementImpl.java:338)
    at org.jkiss.dbeaver.model.impl.jdbc.exec.JDBCStatementImpl.executeStatement(JDBCStatementImpl.java:131)
    ... 12 more

yarn监控:任务执行结果

image.png

Failure Reason

Job aborted due to stage failure: Task 0 in stage 7.0 failed 4 times, most recent failure: Lost task 0.3 in stage 7.0 (TID 18, hadoop102, executor 2): java.lang.RuntimeException: java.lang.NullPointerException
    at org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.processVectorRow(SparkReduceRecordHandler.java:543)
    at org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.processRow(SparkReduceRecordHandler.java:300)
    at org.apache.hadoop.hive.ql.exec.spark.HiveReduceFunctionResultList.processNextRecord(HiveReduceFunctionResultList.java:56)
    at org.apache.hadoop.hive.ql.exec.spark.HiveReduceFunctionResultList.processNextRecord(HiveReduceFunctionResultList.java:28)
    at org.apache.hadoop.hive.ql.exec.spark.HiveBaseFunctionResultList.hasNext(HiveBaseFunctionResultList.java:85)
    at scala.collection.convert.Wrappers$JIteratorWrapper.hasNext(Wrappers.scala:42)
    at scala.collection.Iterator$class.foreach(Iterator.scala:891)
    at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
    at org.apache.spark.rdd.AsyncRDDActions$$anonfun$foreachAsync$1$$anonfun$apply$12.apply(AsyncRDDActions.scala:127)
    at org.apache.spark.rdd.AsyncRDDActions$$anonfun$foreachAsync$1$$anonfun$apply$12.apply(AsyncRDDActions.scala:127)
    at org.apache.spark.SparkContext$$anonfun$37.apply(SparkContext.scala:2212)
    at org.apache.spark.SparkContext$$anonfun$37.apply(SparkContext.scala:2212)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:123)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.NullPointerException
    at org.apache.hadoop.hive.ql.exec.vector.expressions.VectorUDFDateAddColCol.evaluate(VectorUDFDateAddColCol.java:96)
    at org.apache.hadoop.hive.ql.exec.vector.ptf.VectorPTFOperator.process(VectorPTFOperator.java:366)
    at org.apache.hadoop.hive.ql.exec.Operator.vectorForward(Operator.java:966)
    at org.apache.hadoop.hive.ql.exec.Operator.forward(Operator.java:939)
    at org.apache.hadoop.hive.ql.exec.vector.VectorSelectOperator.process(VectorSelectOperator.java:158)
    at org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.forwardBatch(SparkReduceRecordHandler.java:549)
    at org.apache.hadoop.hive.ql.exec.spark.SparkReduceRecordHandler.processVectorRow(SparkReduceRecordHandler.java:453)
    ... 19 more

Driver stacktrace:

失败阶段详情:

image.png

如果使用分组函数就不会查询失败

 select 
        t2.user_id 
        ,t2.age 
        
        from 
         ( SELECT 
        t1.user_id ,
        t1.age ,
        
        date_sub(t1.dt , t1.rn) as  diff
        from 
        (select     
        t.user_id ,
        t.age ,
        t.dt ,
        ROW_NUMBER () over(PARTITION  by t.user_id  order by t.dt ) rn 
        from 
         (select 
        user_id ,
        age ,
        dt
        from  user_age  group by user_id , age ,dt ) t) t1 ) t2  
        group by  t2.user_id ,
        t2.age ,
        t2.diff HAVING count(t2.user_id) >= 2

设置执行引擎为 MR 也可以运行

        set hive.execution.engine=mr

 select 
        t2.user_id 
        ,t2.age 
        ,COUNT(t2.user_id) over(PARTITION BY t2.user_id,t2.diff) as days
        from 
         ( SELECT 
        t1.user_id ,
        t1.age ,
        date_sub(t1.dt , t1.rn) as  diff
        from 
        (select     
        t.user_id ,
        t.age ,
        t.dt ,
        ROW_NUMBER () over(PARTITION  by t.user_id  order by t.dt ) rn 
        from 
         (select 
        user_id ,
        age ,
        dt
        from  user_age  group by user_id , age ,dt ) t) t1 ) t2

MR 提交的JOB全部执行成功

image.png

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hive spark引擎开窗函数后引起异常求问各位大神这个差别

最新更新:使用sparlSql 也能执行成功，SparkSql 和 hive on spark 都是使用spark计算引擎，但是两#者在SQL 语法解析不相同。

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hive spark引擎开窗函数后引起异常 求问各位大神这个差别

最新更新:使用sparlSql 也能执行成功，SparkSql 和 hive on spark 都是使用spark计算引擎，但是两#者在SQL 语法解析不相同。

相关文章

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热点阅读

hive spark引擎开窗函数后引起异常求问各位大神这个差别