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[SPARK-21165] [SQL] [2.2] Use executedPlan instead of analyzedPlan in INSERT AS SELECT #18386

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[SPARK-21165] [SQL] [2.2] Use executedPlan instead of analyzedPlan in INSERT AS SELECT #18386

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86ac975
fix.
gatorsmile Jun 22, 2017
00a63b2
fix.
gatorsmile Jun 22, 2017
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try
gatorsmile Jun 22, 2017
08015c8
fix.
gatorsmile Jun 23, 2017
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gatorsmile Jun 23, 2017
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fix.
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@gatorsmile
gatorsmile committed Jun 23, 2017
commit 08015c83c251cb44b52762b162a1cdaa40130820
12 changes: 11 additions & 1 deletion sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileFormatWriter.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -115,14 +115,24 @@ object FileFormatWriter extends Logging {
// Get the actual partition columns as attributes after matching them by name with
// the given columns names.
val partitionColumns = partitionColumnNames.map { col =>
allColumns.find(f => f.name.equalsIgnoreCase(col)).getOrElse {
val nameEquality = sparkSession.sessionState.conf.resolver
allColumns.find(f => nameEquality(f.name, col)).getOrElse {
throw new RuntimeException(
s"Partition column $col not found in schema ${queryExecution.executedPlan.schema}")
}
}
val partitionSet = AttributeSet(partitionColumns)
val dataColumns = allColumns.filterNot(partitionSet.contains)

queryExecution.executedPlan.output.zip(queryExecution.logical.output).foreach {
case (fieldExecuted, fieldAnalyzed) =>
if (fieldAnalyzed.name != fieldExecuted.name) {
// scalastyle:off println
println(s"analyzed: ${fieldAnalyzed.name}; executed: ${fieldExecuted.name}")
// scalastyle:on println
}
}

val bucketIdExpression = bucketSpec.map { spec =>
val bucketColumns = spec.bucketColumnNames.map(c => dataColumns.find(_.name == c).get)
// Use `HashPartitioning.partitionIdExpression` as our bucket id expression, so that we can
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16 changes: 5 additions & 11 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/rules.scala
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Expand Up @@ -127,11 +127,11 @@ case class PreprocessTableCreation(sparkSession: SparkSession) extends Rule[Logi
val resolver = sparkSession.sessionState.conf.resolver
val tableCols = existingTable.schema.map(_.name)

// As we are inserting into an existing table, we should respect the existing schema and
// adjust the column order of the given dataframe according to it, or throw exception
// if the column names do not match.
// As we are inserting into an existing table, we should respect the existing schema, preserve
// the case and adjust the column order of the given DataFrame according to it, or throw
// an exception if the column names do not match.
val adjustedColumns = tableCols.map { col =>
query.resolve(Seq(col), resolver).getOrElse {
query.resolve(Seq(col), resolver).map(Alias(_, col)()).getOrElse {
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@gatorsmile gatorsmile Jun 23, 2017

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Need to add an alias for enforcing the query to preserve the original name of table schema, whose case could be different from the underlying query schema

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@cloud-fan cloud-fan Jun 23, 2017

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ah good catch!

val inputColumns = query.schema.map(_.name).mkString(", ")
throw new AnalysisException(
s"cannot resolve '$col' given input columns: [$inputColumns]")
Expand Down Expand Up @@ -168,15 +168,9 @@ case class PreprocessTableCreation(sparkSession: SparkSession) extends Rule[Logi
""".stripMargin)
}

val newQuery = if (adjustedColumns != query.output) {
Project(adjustedColumns, query)
} else {
query
}

c.copy(
tableDesc = existingTable,
query = Some(newQuery))
query = Some(Project(adjustedColumns, query)))

// Here we normalize partition, bucket and sort column names, w.r.t. the case sensitivity
// config, and do various checks:
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