sunchao commented on code in PR #36995:
URL: https://github.com/apache/spark/pull/36995#discussion_r954156009
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sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/DistributionAndOrderingUtils.scala:
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@@ -17,22 +17,33 @@
package org.apache.spark.sql.execution.datasources.v2
-import org.apache.spark.sql.catalyst.expressions.Expression
+import org.apache.spark.sql.catalyst.analysis.{AnsiTypeCoercion, TypeCoercion}
+import org.apache.spark.sql.catalyst.expressions.{Expression, Literal,
SortOrder, TransformExpression, V2ExpressionUtils}
import org.apache.spark.sql.catalyst.expressions.V2ExpressionUtils._
import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan,
RebalancePartitions, RepartitionByExpression, Sort}
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.connector.catalog.FunctionCatalog
+import org.apache.spark.sql.connector.catalog.functions.ScalarFunction
import org.apache.spark.sql.connector.distributions._
import org.apache.spark.sql.connector.write.{RequiresDistributionAndOrdering,
Write}
import org.apache.spark.sql.errors.QueryCompilationErrors
object DistributionAndOrderingUtils {
- def prepareQuery(write: Write, query: LogicalPlan): LogicalPlan = write
match {
+ def prepareQuery(
Review Comment:
Sorry for the late reply here. Yes, I think it should be OK as long as the
task writer uses the bucket expression to decide which bucket the input record
should go. There will be some extra work to achieve V1 and V2 compatibility but
it's not that relevant to this PR now.
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