ryan-johnson-databricks commented on code in PR #40545:
URL: https://github.com/apache/spark/pull/40545#discussion_r1150634235
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileSourceStrategy.scala:
##########
@@ -236,33 +247,42 @@ object FileSourceStrategy extends Strategy with
PredicateHelper with Logging {
// For generated metadata columns, they are set as nullable when passed
to readers,
// as the values will be null when trying to read the missing column
from the file.
// They are then replaced by the actual values later in the process.
- // All metadata columns will be non-null in the returned output.
- // We then change the nullability to non-nullable in the metadata
projection node below.
- val constantMetadataColumns: mutable.Buffer[Attribute] =
mutable.Buffer.empty
- val generatedMetadataColumns: mutable.Buffer[Attribute] =
mutable.Buffer.empty
+ // We then restore the specified nullability in the metadata projection
node below.
+ // Also remember the attribute for each column name, so we can easily
map back to it.
+ val constantMetadataColumns = mutable.Buffer.empty[Attribute]
+ val generatedMetadataColumns = mutable.Buffer.empty[Attribute]
+ val metadataColumnsByName = mutable.Map.empty[String, Attribute]
metadataStructOpt.foreach { metadataStruct =>
- metadataStruct.dataType.asInstanceOf[StructType].fields.foreach {
field =>
- field.name match {
- case FileFormat.ROW_INDEX =>
- if ((readDataColumns ++
partitionColumns).map(_.name.toLowerCase(Locale.ROOT))
- .contains(FileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME)) {
- throw new
AnalysisException(FileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME +
- " is a reserved column name that cannot be read in
combination with " +
- s"${FileFormat.METADATA_NAME}.${FileFormat.ROW_INDEX}
column.")
- }
- generatedMetadataColumns +=
- FileSourceGeneratedMetadataAttribute(
- FileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME, LongType,
nullable = true)
- case _ =>
- constantMetadataColumns +=
- FileSourceConstantMetadataAttribute(field.name, field.dataType)
- }
+ val schemaColumns = (readDataColumns ++ partitionColumns)
+ .map(_.name.toLowerCase(Locale.ROOT))
+ .toSet
+
+ def createMetadataColumn(field: StructField) = field match {
Review Comment:
I'm not convinced that introducing this single-use helper improves
readability or maintainability?
```scala
def helper(field: StructField) = field match {
case ...
case ...
}
metadataStruct.dataType.asInstanceOf[StructType].fields.foreach(createMetadataColumn)
```
vs. just inlining the logic:
```scala
metadataStruct.dataType.asInstanceOf[StructType].fields.foreach {
case ...
case ...
}
```
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileSourceStrategy.scala:
##########
@@ -236,33 +247,42 @@ object FileSourceStrategy extends Strategy with
PredicateHelper with Logging {
// For generated metadata columns, they are set as nullable when passed
to readers,
// as the values will be null when trying to read the missing column
from the file.
// They are then replaced by the actual values later in the process.
- // All metadata columns will be non-null in the returned output.
- // We then change the nullability to non-nullable in the metadata
projection node below.
- val constantMetadataColumns: mutable.Buffer[Attribute] =
mutable.Buffer.empty
- val generatedMetadataColumns: mutable.Buffer[Attribute] =
mutable.Buffer.empty
+ // We then restore the specified nullability in the metadata projection
node below.
+ // Also remember the attribute for each column name, so we can easily
map back to it.
+ val constantMetadataColumns = mutable.Buffer.empty[Attribute]
+ val generatedMetadataColumns = mutable.Buffer.empty[Attribute]
+ val metadataColumnsByName = mutable.Map.empty[String, Attribute]
metadataStructOpt.foreach { metadataStruct =>
- metadataStruct.dataType.asInstanceOf[StructType].fields.foreach {
field =>
- field.name match {
- case FileFormat.ROW_INDEX =>
- if ((readDataColumns ++
partitionColumns).map(_.name.toLowerCase(Locale.ROOT))
- .contains(FileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME)) {
- throw new
AnalysisException(FileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME +
- " is a reserved column name that cannot be read in
combination with " +
- s"${FileFormat.METADATA_NAME}.${FileFormat.ROW_INDEX}
column.")
- }
- generatedMetadataColumns +=
- FileSourceGeneratedMetadataAttribute(
- FileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME, LongType,
nullable = true)
- case _ =>
- constantMetadataColumns +=
- FileSourceConstantMetadataAttribute(field.name, field.dataType)
- }
+ val schemaColumns = (readDataColumns ++ partitionColumns)
+ .map(_.name.toLowerCase(Locale.ROOT))
+ .toSet
+
+ def createMetadataColumn(field: StructField) = field match {
+ case FileSourceGeneratedMetadataStructField(field, internalName) =>
+ if (schemaColumns.contains(internalName)) {
+ throw new AnalysisException(internalName +
+ s"${internalName} is a reserved column name that cannot be
read in combination " +
+ s"with ${FileFormat.METADATA_NAME}.${field.name} column.")
+ }
+
+ // NOTE: Readers require the internal column to be nullable
because it's not part of the
+ // file's public schema. The projection below will restore the
correct nullability for
+ // the column while constructing the final metadata struct.
+ val attr = field.copy(internalName, nullable = true).toAttribute
+ metadataColumnsByName.put(field.name, attr)
+ generatedMetadataColumns += attr
+
+ case FileSourceConstantMetadataStructField(field) =>
+ val attr = field.toAttribute
+ metadataColumnsByName.put(field.name, attr)
+ constantMetadataColumns += attr
+
+ case field => throw new AnalysisException(s"Unrecognized file
metadata field: $field")
}
- }
- val metadataColumns: Seq[Attribute] =
- constantMetadataColumns.toSeq ++ generatedMetadataColumns.toSeq
+
metadataStruct.dataType.asInstanceOf[StructType].fields.foreach(createMetadataColumn)
Review Comment:
Rather than cast the struct here, would it make sense to directly match on
it?
```scala
metadataStructOpt.foreach { case AttributeReference(_, schema: StructType,
_, _) =>
...
schema.fields.foreach(...)
}
```
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/namedExpressions.scala:
##########
@@ -501,80 +506,93 @@ object FileSourceMetadataAttribute {
val FILE_SOURCE_METADATA_COL_ATTR_KEY = "__file_source_metadata_col"
+ val METADATA: Metadata = new MetadataBuilder()
+ .withMetadata(MetadataAttribute.METADATA)
+ .putBoolean(METADATA_COL_ATTR_KEY, value = true)
Review Comment:
Isn't this already part of `MetadataAttribute.METADATA`?
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileSourceStrategy.scala:
##########
@@ -282,29 +302,21 @@ object FileSourceStrategy extends Strategy with
PredicateHelper with Logging {
// all references will be bound to output attributes which are either
// [[FileSourceConstantMetadataAttribute]] or
[[FileSourceGeneratedMetadataAttribute]] after
// the flattening from the metadata struct.
- def rebindFileSourceMetadataAttributesInFilters(
- filters: Seq[Expression]): Seq[Expression] = {
- // The row index field attribute got renamed.
- def newFieldName(name: String) = name match {
- case FileFormat.ROW_INDEX =>
FileFormat.ROW_INDEX_TEMPORARY_COLUMN_NAME
- case other => other
- }
-
+ def rebindFileSourceMetadataAttributesInFilters(filters:
Seq[Expression]): Seq[Expression] =
filters.map { filter =>
filter.transform {
// Replace references to the _metadata column. This will affect
references to the column
// itself but also where fields from the metadata struct are used.
case MetadataStructColumn(AttributeReference(_, fields @
StructType(_), _, _)) =>
Review Comment:
aside: `fields @ StructType(_)` is equialent to `fields: StructType`, no?
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