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Posted to issues@spark.apache.org by "Thomas Prelle (Jira)" <ji...@apache.org> on 2020/02/18 21:55:00 UTC
[jira] [Created] (SPARK-30870) catalyst inception of lateral view
explode with struct raise a Catalyst error
Thomas Prelle created SPARK-30870:
-------------------------------------
Summary: catalyst inception of lateral view explode with struct raise a Catalyst error
Key: SPARK-30870
URL: https://issues.apache.org/jira/browse/SPARK-30870
Project: Spark
Issue Type: Bug
Components: Spark Core, SQL
Affects Versions: 3.0.0
Reporter: Thomas Prelle
On spark 3.0.0.preview2 version I found a bug who are not in 3.0.0.preview version.
With the table
{code:java}
spark.sql("select * from tmp").printSchema
root
|-- value: struct (nullable = true)
| |-- array: array (nullable = true)
| | |-- element: struct (containsNull = true)
| | | |-- subarray: array (nullable = true)
| | | | |-- element: struct (containsNull = true)
| | | | | |-- key1: string (nullable = true)
| | | | | |-- key2: string (nullable = true)
{code}
when you try a double lateral view explode
{code:java}
spark.sql("select subexplod.* from tmp lateral view explode(tmp.value.array) explod as array_explod lateral view explode(explod.array_explod.subarray) subexplod").show()
{code}
It's raising an error :
{code:java}
org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute, tree: _gen_alias_127#127
at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56)
at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:75)
at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:74)
at org.apache.spark.sql.catalyst.trees.TreeNode.$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.trees.TreeNode.$anonfun$transformDown$3(TreeNode.scala:314)
at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$mapChildren$1(TreeNode.scala:399)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:237)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:397)
at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:350)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:314)
at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:298)
at org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:74)
at org.apache.spark.sql.catalyst.expressions.BindReferences$.$anonfun$bindReferences$1(BoundAttribute.scala:96)
at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:238)
at scala.collection.immutable.List.foreach(List.scala:392)
at scala.collection.TraversableLike.map(TraversableLike.scala:238)
at scala.collection.TraversableLike.map$(TraversableLike.scala:231)
at scala.collection.immutable.List.map(List.scala:298)
at org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReferences(BoundAttribute.scala:96)
at org.apache.spark.sql.execution.ProjectExec.doConsume(basicPhysicalOperators.scala:65)
at org.apache.spark.sql.execution.CodegenSupport.consume(WholeStageCodegenExec.scala:194)
at org.apache.spark.sql.execution.CodegenSupport.consume$(WholeStageCodegenExec.scala:149)
at org.apache.spark.sql.execution.InputAdapter.consume(WholeStageCodegenExec.scala:496)
at org.apache.spark.sql.execution.InputRDDCodegen.doProduce(WholeStageCodegenExec.scala:483)
at org.apache.spark.sql.execution.InputRDDCodegen.doProduce$(WholeStageCodegenExec.scala:456)
at org.apache.spark.sql.execution.InputAdapter.doProduce(WholeStageCodegenExec.scala:496)
at org.apache.spark.sql.execution.CodegenSupport.$anonfun$produce$1(WholeStageCodegenExec.scala:95)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:212)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:209)
at org.apache.spark.sql.execution.CodegenSupport.produce(WholeStageCodegenExec.scala:90)
at org.apache.spark.sql.execution.CodegenSupport.produce$(WholeStageCodegenExec.scala:90)
at org.apache.spark.sql.execution.InputAdapter.produce(WholeStageCodegenExec.scala:496)
at org.apache.spark.sql.execution.ProjectExec.doProduce(basicPhysicalOperators.scala:51)
at org.apache.spark.sql.execution.CodegenSupport.$anonfun$produce$1(WholeStageCodegenExec.scala:95)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:212)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:209)
at org.apache.spark.sql.execution.CodegenSupport.produce(WholeStageCodegenExec.scala:90)
at org.apache.spark.sql.execution.CodegenSupport.produce$(WholeStageCodegenExec.scala:90)
at org.apache.spark.sql.execution.ProjectExec.produce(basicPhysicalOperators.scala:41)
at org.apache.spark.sql.execution.WholeStageCodegenExec.doCodeGen(WholeStageCodegenExec.scala:632)
at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:692)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:174)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:212)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:209)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:170)
at org.apache.spark.sql.execution.GenerateExec.doExecute(GenerateExec.scala:80)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:174)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:212)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:209)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:170)
at org.apache.spark.sql.execution.InputAdapter.inputRDD(WholeStageCodegenExec.scala:525)
at org.apache.spark.sql.execution.InputRDDCodegen.inputRDDs(WholeStageCodegenExec.scala:453)
at org.apache.spark.sql.execution.InputRDDCodegen.inputRDDs$(WholeStageCodegenExec.scala:452)
at org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:496)
at org.apache.spark.sql.execution.ProjectExec.inputRDDs(basicPhysicalOperators.scala:47)
at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:720)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:174)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:212)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:209)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:170)
at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:315)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:433)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:419)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:47)
at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3537)
at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2590)
at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3527)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:762)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3525)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2590)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2797)
at org.apache.spark.sql.Dataset.getRows(Dataset.scala:297)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:334)
at org.apache.spark.sql.Dataset.show(Dataset.scala:821)
at org.apache.spark.sql.Dataset.show(Dataset.scala:780)
at org.apache.spark.sql.Dataset.show(Dataset.scala:789)
... 47 elided
Caused by: java.lang.RuntimeException: Couldn't find _gen_alias_127#127 in [array_explod#119]
at scala.sys.package$.error(package.scala:30)
at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.$anonfun$applyOrElse$1(BoundAttribute.scala:81)
at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
... 133 more
{code}
To recreate the bug
{code:java}
import org.apache.spark.sql.Row
import org.apache.spark.sql.types.{StringType, StructField, StructType, ArrayType}
val structValue = StructType(StructField(name = "value", StringType, nullable = false) :: Nil)
val struct : StructType = StructType(StructField("array", ArrayType(StructType(StructField("subarray", ArrayType(StructType(StructField("key1",StringType, true)::StructField("key2",StringType, true)::Nil)), nullable = false) :: Nil)), nullable = false) :: Nil)
val value = "{\"array\": [{\"subarray\" : [{\"key1\":\"val1\",\"key2\":\"val2\"},{\"key1\":\"val11\",\"key2\":\"val12\"}]}]}"
spark.createDataFrame(spark.sparkContext.parallelize(Seq(Row(value))),structValue).withColumn("value", from_json(col("value"),struct)).createOrReplaceTempView("tmp")
spark.sql("select subexplod.* from tmp lateral view explode(tmp.value.array) explod as array_explod lateral view explode(explod.array_explod.subarray) subexplod").show()
{code}
If you just avec an Array of Array of String it's working
{code:java}
import org.apache.spark.sql.Row
import org.apache.spark.sql.types.{StringType, StructField, StructType, ArrayType}
val structValue = StructType(StructField(name = "value", StringType, nullable = false) :: Nil)
val struct : StructType = StructType(StructField("array", ArrayType(StructType(StructField("subarray", ArrayType(StringType, true), nullable = false) :: Nil)), nullable = false) :: Nil)
val value = "{\"array\": [{\"subarray\" : [\"val1\",\"val2\"]}]}"
spark.createDataFrame(spark.sparkContext.parallelize(Seq(Row(value))),structValue).withColumn("value", from_json(col("value"),struct)).createOrReplaceTempView("tmp")
spark.sql("select subexplod.* from tmp lateral view explode(tmp.value.array) explod as array_explod lateral view explode(explod.array_explod.subarray) subexplod").show()
{code}
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