Question

我正在Zeppelin笔记本电脑上使用Spark 2.3.1。我通过从Hive加载来创建一个数据框。以下是如何创建数据框：

val df = hive.executeQuery("select trim(a_vno) as dst, trim(s_vno) as src, share, administrator, account, all_shares from ebyn.babs_edges_2016 where (share <> 0 or administrator <> 0 or account <> 0 or all_shares <> 0 ) and trim(date) = '201601'")

当我打电话

df.show

它显示前20行。但是当我打电话

df.where("src = 'XXXXX' and dst = 'YYYYY'").show

它给出以下错误：

        org.apache.spark.SparkException: Job aborted due to stage failure: Task 3 in stage 303.0 failed 4 times, most recent failure: Lost task 3.3 in stage 303.0 (TID 10797, analitik10.host, executor 96): org.apache.spark.util.TaskCompletionListenerException: null
    at org.apache.spark.TaskContextImpl.invokeListeners(TaskContextImpl.scala:139)
    at org.apache.spark.TaskContextImpl.markTaskCompleted(TaskContextImpl.scala:117)
    at org.apache.spark.scheduler.Task.run(Task.scala:125)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)

Driver stacktrace:
  at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1602)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1590)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1589)
  at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
  at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
  at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1589)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
  at scala.Option.foreach(Option.scala:257)
  at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1823)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1772)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1761)
  at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
  at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074)
  at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:363)
  at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
  at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3273)
  at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2484)
  at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2484)
  at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3254)
  at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
  at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3253)
  at org.apache.spark.sql.Dataset.head(Dataset.scala:2484)
  at org.apache.spark.sql.Dataset.take(Dataset.scala:2698)
  at org.apache.spark.sql.Dataset.showString(Dataset.scala:254)
  at org.apache.spark.sql.Dataset.show(Dataset.scala:723)
  at org.apache.spark.sql.Dataset.show(Dataset.scala:682)
  at org.apache.spark.sql.Dataset.show(Dataset.scala:691)
  ... 56 elided
Caused by: org.apache.spark.util.TaskCompletionListenerException: null
  at org.apache.spark.TaskContextImpl.invokeListeners(TaskContextImpl.scala:139)
  at org.apache.spark.TaskContextImpl.markTaskCompleted(TaskContextImpl.scala:117)
  at org.apache.spark.scheduler.Task.run(Task.scala:125)
  at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
  ... 3 more

以下是Hive表的属性：

      CREATE TABLE `EBYN.BABS_EDGES_2016    `(
  `date` string, 
  `a_vno` string, 
  `s_vno` string, 
  `amount` double, 
  `number` int, 
  `share` int, 
  `share_ratio` int, 
  `administrator` int, 
  `account` int, 
  `all_sharelik` int)
COMMENT 'Imported by sqoop on 2018/10/17 14:53:12'
ROW FORMAT SERDE 
  'org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe' 
WITH SERDEPROPERTIES ( 
  'field.delim'='', 
  'line.delim'='\n', 
  'serialization.format'='') 
STORED AS INPUTFORMAT 
  'org.apache.hadoop.mapred.TextInputFormat' 
OUTPUTFORMAT 
  'org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat'
LOCATION
  'hdfs://ggmprod/warehouse/tablespace/managed/hive/ebyn.db/babs_edges_2016    '
TBLPROPERTIES (
  'bucketing_version'='2', 
  'last_modified_by'='hadoop_etluser', 
  'last_modified_time'='1539867401', 
  'transactional'='true', 
  'transactional_properties'='insert_only',

显示数据帧但在调用已过滤的数据帧时失败的原因是什么？

Spark Show适用于整个数据框，但无法过滤相同的数据框

0 个答案: