2016-12-21 253 views
1

我试图在访问Hive表的Cloud 4.2 Enterprise上的BigInsights上运行pyspark脚本。Spark Hive报告pyspark.sql.utils.AnalysisException:u'Table not found:XXX'在纱线群集上运行时

首先,我创建的蜂巢表:

[[email protected] ~]$ hive 
hive> CREATE TABLE pokes (foo INT, bar STRING); 
OK 
Time taken: 2.147 seconds 
hive> LOAD DATA LOCAL INPATH '/usr/iop/4.2.0.0/hive/doc/examples/files/kv1.txt' OVERWRITE INTO TABLE pokes; 
Loading data to table default.pokes 
Table default.pokes stats: [numFiles=1, numRows=0, totalSize=5812, rawDataSize=0] 
OK 
Time taken: 0.49 seconds 
hive> 

然后,我创建一个简单的pyspark脚本:

[[email protected] ~]$ cat test_pokes.py 
from pyspark import SparkContext 

sc = SparkContext() 

from pyspark.sql import HiveContext 
hc = HiveContext(sc) 

pokesRdd = hc.sql('select * from pokes') 
print(pokesRdd.collect()) 

我尝试与执行:

[[email protected] ~]$ spark-submit \ 
    --master yarn-cluster \ 
    --deploy-mode cluster \ 
    --jars /usr/iop/4.2.0.0/hive/lib/datanucleus-api-jdo-3.2.6.jar, \ 
      /usr/iop/4.2.0.0/hive/lib/datanucleus-core-3.2.10.jar, \ 
      /usr/iop/4.2.0.0/hive/lib/datanucleus-rdbms-3.2.9.jar \ 
    test_pokes.py 

不过,我遇到错误:

Traceback (most recent call last): 
    File "test_pokes.py", line 8, in <module> 
    pokesRdd = hc.sql('select * from pokes') 
    File "/disk6/local/usercache/biadmin/appcache/application_1477084339086_0481/container_e09_1477084339086_0481_01_000001/pyspark.zip/pyspark/sql/context.py", line 580, in sql 
    File "/disk6/local/usercache/biadmin/appcache/application_1477084339086_0481/container_e09_1477084339086_0481_01_000001/py4j-0.9-src.zip/py4j/java_gateway.py", line 813, in __call__ 
    File "/disk6/local/usercache/biadmin/appcache/application_1477084339086_0481/container_e09_1477084339086_0481_01_000001/pyspark.zip/pyspark/sql/utils.py", line 51, in deco 
pyspark.sql.utils.AnalysisException: u'Table not found: pokes; line 1 pos 14' 
End of LogType:stdout 

如果我运行火花提交独立的,我可以看到表中存在确定:

[[email protected] ~]$ spark-submit test_pokes.py 
… 
… 
16/12/21 13:09:13 INFO Executor: Finished task 0.0 in stage 0.0 (TID 0). 18962 bytes result sent to driver 
16/12/21 13:09:13 INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 168 ms on localhost (1/1) 
16/12/21 13:09:13 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool 
16/12/21 13:09:13 INFO DAGScheduler: ResultStage 0 (collect at /home/biadmin/test_pokes.py:9) finished in 0.179 s 
16/12/21 13:09:13 INFO DAGScheduler: Job 0 finished: collect at /home/biadmin/test_pokes.py:9, took 0.236558 s 
[Row(foo=238, bar=u'val_238'), Row(foo=86, bar=u'val_86'), Row(foo=311, bar=u'val_311') 
… 
… 

见与此相关的问题我刚才的问题:hive spark yarn-cluster job fails with: "ClassNotFoundException: org.datanucleus.api.jdo.JDOPersistenceManagerFactory"

这个问题是类似于此的其他问题: Spark can access Hive table from pyspark but not from spark-submit。但是,不像那个问题我使用HiveContext。


更新:在这里看到最终的解决方案https://stackoverflow.com/a/41272260/1033422

回答

4

这是因为火花提交的工作是无法找到hive-site.xml,所以它不能连接到蜂巢metastore。请将--files /usr/iop/4.2.0.0/hive/conf/hive-site.xml添加到您的spark-submit命令中。

+0

这并不能解释为什么它在独立模式下工作 –

+0

这让我更进一步。我现在收到错误:'MetaException(message:Failed to instance listener named:com.ibm.biginsights.bigsql.sync.BIEventListener,reason:java.lang.ClassNotFoundException:com.ibm.biginsights.bigsql.sync.BIEventListener)' –

+0

对不起,我应该解释一下。如果您独立运行,则驱动程序会在机器上运行。因此它会从本地类路径中选取'hive-site.xml'。如果你运行在'cluster-mode'上,这个xml文件不会被传输到集群上的容器,所以你必须手工指定它,Spark会把它放到你的类路径中。 –

2

它看起来像你受到这个bug的影响:https://issues.apache.org/jira/browse/SPARK-15345



我在HDP-2.5.0.0有过类似的问题,与星火1.6.2和2.0.0:
我的目标是创建一个从蜂巢SQL查询数据帧,在这些条件下:

  • 蟒API,
  • 集群部署模式
  • 使用纱(在执行节点中的一个上运行的驱动程序)来管理执行的JVM(而不是一个独立的Spark主实例)。

初始测试给出以下结果:

  1. spark-submit --deploy-mode client --master local ... => WORKING
  2. spark-submit --deploy-mode client --master yarn ... =>WORKING
  3. spark-submit --deploy-mode cluster --master yarn ...。=>NOT WORKING

在情况#3中,在其中一个执行程序节点上运行的驱动程序可以找到数据库。错误是:上面所列

pyspark.sql.utils.AnalysisException: 'Table or view not found: `database_name`.`table_name`; line 1 pos 14' 



Fokko Driesprong的回答为我工作。
随着,下面列出的命令,执行器节点上运行的驱动程序能够访问在数据库中的配置单元表这是不default

$ /usr/hdp/current/spark2-client/bin/spark-submit \ 
--deploy-mode cluster --master yarn \ 
--files /usr/hdp/current/spark2-client/conf/hive-site.xml \ 
/path/to/python/code.py 



的Python代码我已经使用与星火1.6.2测试和星火2.0.0: (更改SPARK_VERSION 1星火1.6.2测试确保更新相应的火花提交命令的路径。)

SPARK_VERSION=2  
APP_NAME = 'spark-sql-python-test_SV,' + str(SPARK_VERSION) 



def spark1(): 
    from pyspark.sql import HiveContext 
    from pyspark import SparkContext, SparkConf 

    conf = SparkConf().setAppName(APP_NAME) 
    sc = SparkContext(conf=conf) 
    hc = HiveContext(sc) 

    query = 'select * from database_name.table_name limit 5' 
    df = hc.sql(query) 
    printout(df) 




def spark2(): 
    from pyspark.sql import SparkSession 
    spark = SparkSession.builder.appName(APP_NAME).enableHiveSupport().getOrCreate() 
    query = 'select * from database_name.table_name limit 5' 
    df = spark.sql(query) 
    printout(df) 




def printout(df): 
    print('\n########################################################################') 
    df.show() 
    print(df.count()) 

    df_list = df.collect() 
    print(df_list) 
    print(df_list[0]) 
    print(df_list[1]) 
    print('########################################################################\n') 




def main(): 
    if SPARK_VERSION == 1: 
     spark1() 
    elif SPARK_VERSION == 2: 
     spark2() 




if __name__ == '__main__': 
    main() 
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