[ https://issues.apache.org/jira/browse/AMBARI-23043?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Vitaly Brodetskyi resolved AMBARI-23043. ---------------------------------------- Resolution: Fixed > 'Table or view not found error' with livy/livy2 interpreter on upgraded > cluster > ------------------------------------------------------------------------------- > > Key: AMBARI-23043 > URL: https://issues.apache.org/jira/browse/AMBARI-23043 > Project: Ambari > Issue Type: Bug > Components: ambari-server > Reporter: Vitaly Brodetskyi > Assignee: Vitaly Brodetskyi > Priority: Critical > Labels: pull-request-available > Fix For: 2.6.2 > > Time Spent: 1h 40m > Remaining Estimate: 0h > > The test has been performed as below: > CentOS6 + Ambari-2.5.1 + HDP-2.6.1 -> AU to Ambari-2.6.2 -> Full EU to > HDP-2.6.5.0-74 -> Run stack tests > I see that with livy2 interpreter, anytime we register a temporary view or > table - the corresponding query on that table will fail with 'Table or view > not found error' > {code:java} > org.apache.spark.sql.AnalysisException: Table or view not found: word_counts; > line 2 pos 24 > at > org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42) > at > org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.org$apache$spark$sql$catalyst$analysis$Analyzer$ResolveRelations$$lookupTableFromCatalog(Analyzer.scala:649) > at > org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.resolveRelation(Analyzer.scala:601) > at > org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$8.applyOrElse(Analyzer.scala:631) > at > org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$8.applyOrElse(Analyzer.scala:624) > at > org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:62) > at > org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:62) > at > org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70) > at > org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:61) > at > org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$1.apply(LogicalPlan.scala:59) > at > org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$1.apply(LogicalPlan.scala:59) > at > org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306) > at > org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187) > at > org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304) > at > org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:59) > at > org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$1.apply(LogicalPlan.scala:59) > at > org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$1.apply(LogicalPlan.scala:59) > at > org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:306) > at > org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:187) > at > org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:304) > at > org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:59) > at > org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:624) > at > org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:570) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor$$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$1.apply(RuleExecutor.scala:74) > at scala.collection.immutable.List.foreach(List.scala:381) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74) > at > org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:69) > at > org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:67) > at > org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:50) > at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:67) > at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:637) > ... 50 elided > {code} -- This message was sent by Atlassian JIRA (v7.6.3#76005)