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java.lang.LinkageError when execute spark sql #5
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hive 2.1.1 as metastore server or client,we only support builtin hive jars(1.2.1.spark2)as client jars |
thank for your response~ is there something i missed ? thank you. Regards, |
Hello, May I ask do you have the plan that spark-authorizer can support using higher version of ranger ? Regards, |
@west-xrz Glad I could help. |
Hello YaoOqinn, |
Hello,
I am using hive 2.1.1 and spark 2.1.2
when I execute the spark sql command, it show the following error:
scala> sql("show tables").show
18/09/26 09:54:02 WARN session.SessionState: METASTORE_FILTER_HOOK will be ignored, since hive.security.authorization.manager is set to instance of HiveAuthorizerFactory. java.lang.LinkageError: loader constraint violation: loader (instance of sun/misc/Launcher$AppClassLoader) previously initiated loading for a different type with name "org/apache/hadoop/hive/ql/security/authorization/plugin/HiveOperationType" at java.lang.ClassLoader.defineClass1(Native Method) at java.lang.ClassLoader.defineClass(ClassLoader.java:803) at java.security.SecureClassLoader.defineClass(SecureClassLoader.java:142) at java.net.URLClassLoader.defineClass(URLClassLoader.java:442) at java.net.URLClassLoader.access$100(URLClassLoader.java:64) at java.net.URLClassLoader$1.run(URLClassLoader.java:354) at java.net.URLClassLoader$1.run(URLClassLoader.java:348) at java.security.AccessController.doPrivileged(Native Method) at java.net.URLClassLoader.findClass(URLClassLoader.java:347) at java.lang.ClassLoader.loadClass(ClassLoader.java:425) at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:312) at java.lang.ClassLoader.loadClass(ClassLoader.java:358) at org.apache.spark.sql.catalyst.optimizer.Authorizer$.toHiveOperationType(Authorizer.scala:150) at org.apache.spark.sql.catalyst.optimizer.Authorizer$.apply(Authorizer.scala:54) at org.apache.spark.sql.catalyst.optimizer.Authorizer$.apply(Authorizer.scala:42) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:85) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:82) at scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124) at scala.collection.immutable.List.foldLeft(List.scala:84) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:82) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:74) at scala.collection.immutable.List.foreach(List.scala:381) at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74) at org.apache.spark.sql.execution.QueryExecution.optimizedPlan$lzycompute(QueryExecution.scala:78) at org.apache.spark.sql.execution.QueryExecution.optimizedPlan(QueryExecution.scala:78) at org.apache.spark.sql.execution.QueryExecution.sparkPlan$lzycompute(QueryExecution.scala:84) at org.apache.spark.sql.execution.QueryExecution.sparkPlan(QueryExecution.scala:80) at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:89) at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:89) at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:92) at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:92) at org.apache.spark.sql.Dataset.<init>(Dataset.scala:185) at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64) at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:600)
I just follow the instructions in readme , could you have any idea about this ?
or something I missed ?
Thank you~
Leon
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