[ https://issues.apache.org/jira/browse/HUDI-5768?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Ethan Guo updated HUDI-5768: ---------------------------- Description: Using Hudi 0.13.0 and Spark 3.3.0, reading a table created by 0.13.0: {code:java} scala> val df = spark.read.format("hudi").load("/Users/ethan/Work/tmp/20230127-test-cli-bundle/hudi_trips_cow_backup/.hoodie/metadata") scala> df.count scala.MatchError: HFILE (of class org.apache.hudi.common.model.HoodieFileFormat) at org.apache.hudi.HoodieBaseRelation.x$2$lzycompute(HoodieBaseRelation.scala:216) at org.apache.hudi.HoodieBaseRelation.x$2(HoodieBaseRelation.scala:215) at org.apache.hudi.HoodieBaseRelation.fileFormat$lzycompute(HoodieBaseRelation.scala:215) at org.apache.hudi.HoodieBaseRelation.fileFormat(HoodieBaseRelation.scala:215) at org.apache.hudi.HoodieBaseRelation.canPruneRelationSchema(HoodieBaseRelation.scala:295) at org.apache.hudi.BaseMergeOnReadSnapshotRelation.canPruneRelationSchema(MergeOnReadSnapshotRelation.scala:102) at org.apache.spark.sql.execution.datasources.Spark33NestedSchemaPruning$$anonfun$apply0$1.applyOrElse(Spark33NestedSchemaPruning.scala:56) at org.apache.spark.sql.execution.datasources.Spark33NestedSchemaPruning$$anonfun$apply0$1.applyOrElse(Spark33NestedSchemaPruning.scala:50) at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:584) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:176) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:584) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:30) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$3(TreeNode.scala:589) at org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren(TreeNode.scala:1228) at org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren$(TreeNode.scala:1227) at org.apache.spark.sql.catalyst.plans.logical.Aggregate.mapChildren(basicLogicalOperators.scala:976) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:589) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:30) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:560) at org.apache.spark.sql.execution.datasources.Spark33NestedSchemaPruning.apply0(Spark33NestedSchemaPruning.scala:50) at org.apache.spark.sql.execution.datasources.Spark33NestedSchemaPruning.apply(Spark33NestedSchemaPruning.scala:44) at org.apache.spark.sql.execution.datasources.Spark33NestedSchemaPruning.apply(Spark33NestedSchemaPruning.scala:39) at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$2(RuleExecutor.scala:211) at scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126) at scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122) at scala.collection.immutable.List.foldLeft(List.scala:91) at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1(RuleExecutor.scala:208) at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1$adapted(RuleExecutor.scala:200) at scala.collection.immutable.List.foreach(List.scala:431) at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:200) at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$executeAndTrack$1(RuleExecutor.scala:179) at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:88) at org.apache.spark.sql.catalyst.rules.RuleExecutor.executeAndTrack(RuleExecutor.scala:179) at org.apache.spark.sql.execution.QueryExecution.$anonfun$optimizedPlan$1(QueryExecution.scala:126) at org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111) at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$2(QueryExecution.scala:185) at org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:510) at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:185) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779) at org.apache.spark.sql.execution.QueryExecution.executePhase(QueryExecution.scala:184) at org.apache.spark.sql.execution.QueryExecution.optimizedPlan$lzycompute(QueryExecution.scala:122) at org.apache.spark.sql.execution.QueryExecution.optimizedPlan(QueryExecution.scala:118) at org.apache.spark.sql.execution.QueryExecution.assertOptimized(QueryExecution.scala:136) at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:154) at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:151) at org.apache.spark.sql.execution.QueryExecution.simpleString(QueryExecution.scala:204) at org.apache.spark.sql.execution.QueryExecution.org$apache$spark$sql$execution$QueryExecution$$explainString(QueryExecution.scala:249) at org.apache.spark.sql.execution.QueryExecution.explainString(QueryExecution.scala:218) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:103) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:169) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:95) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3856) at org.apache.spark.sql.Dataset.count(Dataset.scala:3160) ... 47 elided{code} Using Hudi 0.12.0 and Spark 3.2.1 hit the same issue as above. Using Hudi 0.11.1 and Spark 3.2.1 can read the same metadata table. was: Using Hudi 0.13.0 and Spark 3.3, reading a table created by 0.13.0: {code:java} scala> val df = spark.read.format("hudi").load("/Users/ethan/Work/tmp/20230127-test-cli-bundle/hudi_trips_cow_backup/.hoodie/metadata") scala> df.count scala.MatchError: HFILE (of class org.apache.hudi.common.model.HoodieFileFormat) at org.apache.hudi.HoodieBaseRelation.x$2$lzycompute(HoodieBaseRelation.scala:216) at org.apache.hudi.HoodieBaseRelation.x$2(HoodieBaseRelation.scala:215) at org.apache.hudi.HoodieBaseRelation.fileFormat$lzycompute(HoodieBaseRelation.scala:215) at org.apache.hudi.HoodieBaseRelation.fileFormat(HoodieBaseRelation.scala:215) at org.apache.hudi.HoodieBaseRelation.canPruneRelationSchema(HoodieBaseRelation.scala:295) at org.apache.hudi.BaseMergeOnReadSnapshotRelation.canPruneRelationSchema(MergeOnReadSnapshotRelation.scala:102) at org.apache.spark.sql.execution.datasources.Spark33NestedSchemaPruning$$anonfun$apply0$1.applyOrElse(Spark33NestedSchemaPruning.scala:56) at org.apache.spark.sql.execution.datasources.Spark33NestedSchemaPruning$$anonfun$apply0$1.applyOrElse(Spark33NestedSchemaPruning.scala:50) at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:584) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:176) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:584) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:30) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$3(TreeNode.scala:589) at org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren(TreeNode.scala:1228) at org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren$(TreeNode.scala:1227) at org.apache.spark.sql.catalyst.plans.logical.Aggregate.mapChildren(basicLogicalOperators.scala:976) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:589) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:30) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:560) at org.apache.spark.sql.execution.datasources.Spark33NestedSchemaPruning.apply0(Spark33NestedSchemaPruning.scala:50) at org.apache.spark.sql.execution.datasources.Spark33NestedSchemaPruning.apply(Spark33NestedSchemaPruning.scala:44) at org.apache.spark.sql.execution.datasources.Spark33NestedSchemaPruning.apply(Spark33NestedSchemaPruning.scala:39) at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$2(RuleExecutor.scala:211) at scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126) at scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122) at scala.collection.immutable.List.foldLeft(List.scala:91) at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1(RuleExecutor.scala:208) at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1$adapted(RuleExecutor.scala:200) at scala.collection.immutable.List.foreach(List.scala:431) at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:200) at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$executeAndTrack$1(RuleExecutor.scala:179) at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:88) at org.apache.spark.sql.catalyst.rules.RuleExecutor.executeAndTrack(RuleExecutor.scala:179) at org.apache.spark.sql.execution.QueryExecution.$anonfun$optimizedPlan$1(QueryExecution.scala:126) at org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111) at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$2(QueryExecution.scala:185) at org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:510) at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:185) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779) at org.apache.spark.sql.execution.QueryExecution.executePhase(QueryExecution.scala:184) at org.apache.spark.sql.execution.QueryExecution.optimizedPlan$lzycompute(QueryExecution.scala:122) at org.apache.spark.sql.execution.QueryExecution.optimizedPlan(QueryExecution.scala:118) at org.apache.spark.sql.execution.QueryExecution.assertOptimized(QueryExecution.scala:136) at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:154) at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:151) at org.apache.spark.sql.execution.QueryExecution.simpleString(QueryExecution.scala:204) at org.apache.spark.sql.execution.QueryExecution.org$apache$spark$sql$execution$QueryExecution$$explainString(QueryExecution.scala:249) at org.apache.spark.sql.execution.QueryExecution.explainString(QueryExecution.scala:218) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:103) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:169) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:95) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3856) at org.apache.spark.sql.Dataset.count(Dataset.scala:3160) ... 47 elided{code} Using Hudi 0.11.1 and Spark 3.2 can read the same metadata table. > Fail to read metadata table in Spark Datasource > ----------------------------------------------- > > Key: HUDI-5768 > URL: https://issues.apache.org/jira/browse/HUDI-5768 > Project: Apache Hudi > Issue Type: Bug > Affects Versions: 0.12.0, 0.12.1, 0.12.2 > Reporter: Ethan Guo > Priority: Blocker > Fix For: 0.13.0 > > > Using Hudi 0.13.0 and Spark 3.3.0, reading a table created by 0.13.0: > {code:java} > scala> val df = > spark.read.format("hudi").load("/Users/ethan/Work/tmp/20230127-test-cli-bundle/hudi_trips_cow_backup/.hoodie/metadata") > scala> df.count > scala.MatchError: HFILE (of class > org.apache.hudi.common.model.HoodieFileFormat) > at > org.apache.hudi.HoodieBaseRelation.x$2$lzycompute(HoodieBaseRelation.scala:216) > at org.apache.hudi.HoodieBaseRelation.x$2(HoodieBaseRelation.scala:215) > at > org.apache.hudi.HoodieBaseRelation.fileFormat$lzycompute(HoodieBaseRelation.scala:215) > at > org.apache.hudi.HoodieBaseRelation.fileFormat(HoodieBaseRelation.scala:215) > at > org.apache.hudi.HoodieBaseRelation.canPruneRelationSchema(HoodieBaseRelation.scala:295) > at > org.apache.hudi.BaseMergeOnReadSnapshotRelation.canPruneRelationSchema(MergeOnReadSnapshotRelation.scala:102) > at > org.apache.spark.sql.execution.datasources.Spark33NestedSchemaPruning$$anonfun$apply0$1.applyOrElse(Spark33NestedSchemaPruning.scala:56) > at > org.apache.spark.sql.execution.datasources.Spark33NestedSchemaPruning$$anonfun$apply0$1.applyOrElse(Spark33NestedSchemaPruning.scala:50) > at > org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:584) > at > org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:176) > at > org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:584) > at > org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:30) > at > org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267) > at > org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263) > at > org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) > at > org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) > at > org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$3(TreeNode.scala:589) > at > org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren(TreeNode.scala:1228) > at > org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren$(TreeNode.scala:1227) > at > org.apache.spark.sql.catalyst.plans.logical.Aggregate.mapChildren(basicLogicalOperators.scala:976) > at > org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:589) > at > org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:30) > at > org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267) > at > org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263) > at > org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) > at > org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30) > at > org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:560) > at > org.apache.spark.sql.execution.datasources.Spark33NestedSchemaPruning.apply0(Spark33NestedSchemaPruning.scala:50) > at > org.apache.spark.sql.execution.datasources.Spark33NestedSchemaPruning.apply(Spark33NestedSchemaPruning.scala:44) > at > org.apache.spark.sql.execution.datasources.Spark33NestedSchemaPruning.apply(Spark33NestedSchemaPruning.scala:39) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$2(RuleExecutor.scala:211) > at > scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126) > at > scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122) > at scala.collection.immutable.List.foldLeft(List.scala:91) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1(RuleExecutor.scala:208) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1$adapted(RuleExecutor.scala:200) > at scala.collection.immutable.List.foreach(List.scala:431) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:200) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$executeAndTrack$1(RuleExecutor.scala:179) > at > org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:88) > at > org.apache.spark.sql.catalyst.rules.RuleExecutor.executeAndTrack(RuleExecutor.scala:179) > at > org.apache.spark.sql.execution.QueryExecution.$anonfun$optimizedPlan$1(QueryExecution.scala:126) > at > org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111) > at > org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$2(QueryExecution.scala:185) > at > org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:510) > at > org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:185) > at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779) > at > org.apache.spark.sql.execution.QueryExecution.executePhase(QueryExecution.scala:184) > at > org.apache.spark.sql.execution.QueryExecution.optimizedPlan$lzycompute(QueryExecution.scala:122) > at > org.apache.spark.sql.execution.QueryExecution.optimizedPlan(QueryExecution.scala:118) > at > org.apache.spark.sql.execution.QueryExecution.assertOptimized(QueryExecution.scala:136) > at > org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:154) > at > org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:151) > at > org.apache.spark.sql.execution.QueryExecution.simpleString(QueryExecution.scala:204) > at > org.apache.spark.sql.execution.QueryExecution.org$apache$spark$sql$execution$QueryExecution$$explainString(QueryExecution.scala:249) > at > org.apache.spark.sql.execution.QueryExecution.explainString(QueryExecution.scala:218) > at > org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:103) > at > org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:169) > at > org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:95) > at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779) > at > org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) > at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3856) > at org.apache.spark.sql.Dataset.count(Dataset.scala:3160) > ... 47 elided{code} > Using Hudi 0.12.0 and Spark 3.2.1 hit the same issue as above. > Using Hudi 0.11.1 and Spark 3.2.1 can read the same metadata table. -- This message was sent by Atlassian Jira (v8.20.10#820010)