当前位置:  开发笔记 > 编程语言 > 正文

使用Python的Spark SQL:无法实例化org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient

如何解决《使用Python的SparkSQL:无法实例化org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient》经验,为你挑选了1个好方法。

我想用Spark SQL测试基本的东西.我想加载一个csv.文件,保存在我的笔记本电脑上,并在其上运行一些SQL查询.但不知何故,我无法使用sqlContext加载数据.我收到错误:

Unable to instantiate org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient. 

但是,我没有使用Hive.

我正在使用Windows 10并使用Anaconda安装了python.我为hadoop 2.6安装了Spark 2.0.2 prebuild.我使用iPython Notebook作为用户界面.

我的代码如下:

file = "C:/Andra/spark-2.0.2-bin-hadoop2.6/zip.csv"
df = sqlContext\
    .read \
    .format("com.databricks.spark.csv")\
    .option("header", "true")\
    .option("inferschema", "true")\
    .option("mode", "DROPMALFORMED")\
    .load(file)

问题在于Spark SQL,因为我可以使用加载相同的文件

textFile=sc.textFile("C:/Andra/spark-2.0.2-bin-hadoop2.6/zip.csv")

如果我想从Spark SQL文档https://spark.apache.org/docs/latest/sql-programming-guide.html运行示例,我会收到同样的错误.

from pyspark.sql import SparkSession

spark = SparkSession \
    .builder \
    .appName("Python Spark SQL basic example") \
    .config("spark.some.config.option", "some-value") \
    .getOrCreate()
df = spark.read.json("C:/Andra/spark-2.0.2-bin-hadoop2.6/examples/src/main/resources/people.json")

我的印象是我可以在不使用Hive的情况下使用Spark SQL,因为我使用的数据是在我的笔记本电脑上保存的.此外,上述相同的文档仅表明:

"Spark SQL的一个用途是执行SQL查询.Spark SQL 可用于从现有的Hive安装中读取数据.有关如何配置此功能的更多信息,请参阅Hive Tables部分."

还有使用Hive创建spark会话的示例.如果使用配置单元是必需的,那么上面的那个将是无用的.

但是,我想配置Hive以查看是否可以解决问题.文档指南(https://spark.apache.org/docs/latest/sql-programming-guide.html#hive-tables)说明

"通过在conf /中放置 hive-site.xml,core-site.xml (用于安全性配置)和hdfs-site.xml (用于HDFS配置)文件来完成Hive的配置."

但是,我找不到那些文件.

所以我的问题是:

我是否需要Hive才能使用Spark SQL?

如果没有,我该怎么做才能让Spark SQL正常工作?

如果是,我如何正确配置它是否可以找到所需的文件?

任何帮助表示赞赏!谢谢!

这是完整的错误声明:

---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
 in ()
      1 file = "C:/Andra/spark-2.0.2-bin-hadoop2.6/zip.csv"
----> 2 df = sqlContext    .read     .format("com.databricks.spark.csv")    .option("header", "true")    .option("inferschema", "true")    .option("mode", "DROPMALFORMED")    .load(file)

C:\Andra\spark-2.0.2-bin-hadoop2.6\python\pyspark\sql\readwriter.pyc in load(self, path, format, schema, **options)
    145         self.options(**options)
    146         if isinstance(path, basestring):
--> 147             return self._df(self._jreader.load(path))
    148         elif path is not None:
    149             if type(path) != list:

C:\Andra\spark-2.0.2-bin-hadoop2.6\python\lib\py4j-0.10.3-src.zip\py4j\java_gateway.py in __call__(self, *args)
   1131         answer = self.gateway_client.send_command(command)
   1132         return_value = get_return_value(
-> 1133             answer, self.gateway_client, self.target_id, self.name)
   1134 
   1135         for temp_arg in temp_args:

C:\Andra\spark-2.0.2-bin-hadoop2.6\python\pyspark\sql\utils.pyc in deco(*a, **kw)
     61     def deco(*a, **kw):
     62         try:
---> 63             return f(*a, **kw)
     64         except py4j.protocol.Py4JJavaError as e:
     65             s = e.java_exception.toString()

C:\Andra\spark-2.0.2-bin-hadoop2.6\python\lib\py4j-0.10.3-src.zip\py4j\protocol.py in get_return_value(answer, gateway_client, target_id, name)
    317                 raise Py4JJavaError(
    318                     "An error occurred while calling {0}{1}{2}.\n".
--> 319                     format(target_id, ".", name), value)
    320             else:
    321                 raise Py4JError(

Py4JJavaError: An error occurred while calling o110.load.
: java.lang.RuntimeException: java.lang.RuntimeException: Unable to instantiate org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient
    at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:522)
    at org.apache.spark.sql.hive.client.HiveClientImpl.(HiveClientImpl.scala:189)
    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.spark.sql.hive.client.IsolatedClientLoader.createClient(IsolatedClientLoader.scala:258)
    at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:359)
    at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:263)
    at org.apache.spark.sql.hive.HiveSharedState.metadataHive$lzycompute(HiveSharedState.scala:39)
    at org.apache.spark.sql.hive.HiveSharedState.metadataHive(HiveSharedState.scala:38)
    at org.apache.spark.sql.hive.HiveSharedState.externalCatalog$lzycompute(HiveSharedState.scala:46)
    at org.apache.spark.sql.hive.HiveSharedState.externalCatalog(HiveSharedState.scala:45)
    at org.apache.spark.sql.hive.HiveSessionState.catalog$lzycompute(HiveSessionState.scala:50)
    at org.apache.spark.sql.hive.HiveSessionState.catalog(HiveSessionState.scala:48)
    at org.apache.spark.sql.hive.HiveSessionState$$anon$1.(HiveSessionState.scala:63)
    at org.apache.spark.sql.hive.HiveSessionState.analyzer$lzycompute(HiveSessionState.scala:63)
    at org.apache.spark.sql.hive.HiveSessionState.analyzer(HiveSessionState.scala:62)
    at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:49)
    at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64)
    at org.apache.spark.sql.SparkSession.baseRelationToDataFrame(SparkSession.scala:382)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:143)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:132)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:280)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:214)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.RuntimeException: Unable to instantiate org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient
    at org.apache.hadoop.hive.metastore.MetaStoreUtils.newInstance(MetaStoreUtils.java:1523)
    at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.(RetryingMetaStoreClient.java:86)
    at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.getProxy(RetryingMetaStoreClient.java:132)
    at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.getProxy(RetryingMetaStoreClient.java:104)
    at org.apache.hadoop.hive.ql.metadata.Hive.createMetaStoreClient(Hive.java:3005)
    at org.apache.hadoop.hive.ql.metadata.Hive.getMSC(Hive.java:3024)
    at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:503)
    ... 33 more
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.metastore.MetaStoreUtils.newInstance(MetaStoreUtils.java:1521)
    ... 39 more
Caused by: java.lang.NullPointerException
    at org.apache.thrift.transport.TSocket.open(TSocket.java:170)
    at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.open(HiveMetaStoreClient.java:420)
    at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.(HiveMetaStoreClient.java:236)
    at org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient.(SessionHiveMetaStoreClient.java:74)
    ... 44 more

AEDWIP.. 7

我最近遇到了同样的问题.在我的情况下,我同时在我的本地计算机上运行两个python jupyter笔记本.第一台笔记本工作正常.第二个一直在扔可怕的

Caused by: java.lang.RuntimeException: Unable to instantiate org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient 我不确定权限是如何工作的.它似乎是运行一些如何锁定本地元存储的第一个笔记本.理解为不能在两个不同的会话之间共享元存储.

也许有人知道如何启用多个笔记本?

安迪



1> AEDWIP..:

我最近遇到了同样的问题.在我的情况下,我同时在我的本地计算机上运行两个python jupyter笔记本.第一台笔记本工作正常.第二个一直在扔可怕的

Caused by: java.lang.RuntimeException: Unable to instantiate org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient 我不确定权限是如何工作的.它似乎是运行一些如何锁定本地元存储的第一个笔记本.理解为不能在两个不同的会话之间共享元存储.

也许有人知道如何启用多个笔记本?

安迪


读完之后,我假设有一个锁定在那个文件上,"重新启动"我的系统,它就像一个魅力.
推荐阅读
Chloemw
这个屌丝很懒,什么也没留下!
DevBox开发工具箱 | 专业的在线开发工具网站    京公网安备 11010802040832号  |  京ICP备19059560号-6
Copyright © 1998 - 2020 DevBox.CN. All Rights Reserved devBox.cn 开发工具箱 版权所有