【问题标题】:Delta Table Insert not Working Correctly, Read Errors out with - org.apache.spark.sql.AnalysisException: Table does not support reads增量表插入无法正常工作,使用 - org.apache.spark.sql.AnalysisException 读取错误:表不支持读取
【发布时间】:2020-11-28 01:14:54
【问题描述】:

我在 Apache Zeppelin Notebook 上使用 Spark 版本 3.0.0,delta 版本:io.delta:delta-core_2.12:0.7.0。

在以下场景中,我尝试将数据插入增量表 PFB Apache Zeppeline Screenshot

STEP 1:

spark.sql("drop table if exists delta_dummy3")
spark.sql("create table delta_dummy3 (number integer,fname string) using DELTA options(path='/tmp/dummy_delta3')")

STEP 2:
%spark3
spark.sql("insert into delta_dummy3 values ( 1,'sid','1')")

STEP 3:
%spark3
val a = spark.sql("select * from delta_dummy3")
a.printSchema()
Result:
root
 |-- number: integer (nullable = true)
 |-- fname: string (nullable = true)
 |-- col1: integer (nullable = true)
 |-- col2: string (nullable = true)
 |-- col3: string (nullable = true)

%spark3
val events_delta = spark.read.format("delta").load("/tmp/dummy_delta3/")
events_delta.show()
+------+-----+----+----+----+
|number|fname|col1|col2|col3|
+------+-----+----+----+----+
|  null| null|   1| sid|   1|
|  null| null|   1| sid|null|
|  null| null|   1| sid|null|
+------+-----+----+----+----+

如您所见,一个不正确的插入方案正在运行,预计会引发错误(当我使用 PARQUET 表时确实会发生这种情况)

另外,当我尝试通过 Spark-SQL 选项读取数据时,我也会收到错误消息:

spark.sql("select * from delta_dummy3").show()

org.apache.spark.sql.AnalysisException: Table does not support reads: datahub.delta_dummy3;
  at org.apache.spark.sql.execution.datasources.v2.DataSourceV2Implicits$TableHelper.asReadable(DataSourceV2Implicits.scala:33)
  at org.apache.spark.sql.execution.datasources.v2.V2ScanRelationPushDown$$anonfun$apply$1.applyOrElse(V2ScanRelationPushDown.scala:34)
  at org.apache.spark.sql.execution.datasources.v2.V2ScanRelationPushDown$$anonfun$apply$1.applyOrElse(V2ScanRelationPushDown.scala:32)
  at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDown$1(TreeNode.scala:309)
  at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:72)
  at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:309)
  at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDown(LogicalPlan.scala:29)
  at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDown(AnalysisHelper.scala:149)
  at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDown$(AnalysisHelper.scala:147)
  at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
  at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
  at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDown$3(TreeNode.scala:314)
  at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$mapChildren$1(TreeNode.scala:399)
  at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:237)
  at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:397)
  at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:350)
  at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:314)
  at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDown(LogicalPlan.scala:29)
  at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDown(AnalysisHelper.scala:149)
  at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDown$(AnalysisHelper.scala:147)
  at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
  at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
  at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDown$3(TreeNode.scala:314)
  at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$mapChildren$1(TreeNode.scala:399)
  at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:237)
  at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:397)
  at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:350)
  at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:314)
  at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDown(LogicalPlan.scala:29)
  at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDown(AnalysisHelper.scala:149)
  at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDown$(AnalysisHelper.scala:147)
  at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
  at org.apache.spark.sql.execution.datasources.v2.V2ScanRelationPushDown$.apply(V2ScanRelationPushDown.scala:32)
  at org.apache.spark.sql.execution.datasources.v2.V2ScanRelationPushDown$.apply(V2ScanRelationPushDown.scala:29)
  at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$2(RuleExecutor.scala:149)
  at scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126)
  at scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122)
  at scala.collection.immutable.List.foldLeft(List.scala:89)
  at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1(RuleExecutor.scala:146)
  at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1$adapted(RuleExecutor.scala:138)
  at scala.collection.immutable.List.foreach(List.scala:392)
  at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:138)
  at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$executeAndTrack$1(RuleExecutor.scala:116)
  at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:88)
  at org.apache.spark.sql.catalyst.rules.RuleExecutor.executeAndTrack(RuleExecutor.scala:116)
  at org.apache.spark.sql.execution.QueryExecution.$anonfun$optimizedPlan$1(QueryExecution.scala:82)
  at org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111)
  at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:133)
  at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:763)
  at org.apache.spark.sql.execution.QueryExecution.executePhase(QueryExecution.scala:133)
  at org.apache.spark.sql.execution.QueryExecution.optimizedPlan$lzycompute(QueryExecution.scala:82)
  at org.apache.spark.sql.execution.QueryExecution.optimizedPlan(QueryExecution.scala:79)
  at org.apache.spark.sql.execution.QueryExecution.assertOptimized(QueryExecution.scala:85)
  at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:103)
  at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:100)
  at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:98)
  at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
  at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
  at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:763)
  at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
  at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3614)
  at org.apache.spark.sql.Dataset.head(Dataset.scala:2695)
  at org.apache.spark.sql.Dataset.take(Dataset.scala:2902)
  at org.apache.spark.sql.Dataset.getRows(Dataset.scala:300)
  at org.apache.spark.sql.Dataset.showString(Dataset.scala:337)
  at org.apache.spark.sql.Dataset.show(Dataset.scala:824)
  at org.apache.spark.sql.Dataset.show(Dataset.scala:783)
  at org.apache.spark.sql.Dataset.show(Dataset.scala:792)
  ... 53 elided

我无法在这里找出问题的根本原因。

【问题讨论】:

    标签: scala apache-spark apache-spark-sql apache-zeppelin delta-lake


    【解决方案1】:

    我建议您按顺序执行以下操作。

    %sql DROP TABLE delta_dummy3
    %scala dbutils.fs.rm('/tmp/dummy_delta3', true)
    

    执行完这两个命令后,你就可以执行你的步骤了……

    spark.sql("create table delta_dummy3 (number integer,fname string) using DELTA options(path='/tmp/dummy_delta3')")
    
    STEP 2:
    %spark3
    spark.sql("insert into delta_dummy3 values ( 1,'sid','1')")
    
    STEP 3:
    %spark3
    val a = spark.sql("select * from delta_dummy3")
    a.printSchema()
    

    【讨论】:

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