Github user vanzin commented on a diff in the pull request:
https://github.com/apache/spark/pull/19250#discussion_r143246203
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/TimestampTableTimeZone.scala
---
@@ -0,0 +1,213 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.sql.execution.datasources
+
+import org.apache.spark.sql.{AnalysisException, SparkSession}
+import org.apache.spark.sql.catalyst.TableIdentifier
+import org.apache.spark.sql.catalyst.analysis.UnresolvedException
+import org.apache.spark.sql.catalyst.catalog.CatalogTable
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Project}
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.catalyst.util.DateTimeUtils
+import org.apache.spark.sql.types.{StringType, TimestampType}
+
+/**
+ * Apply a correction to data loaded from, or saved to, Parquet, so that
it timestamps can be read
+ * like TIMESTAMP WITHOUT TIMEZONE. This gives correct behavior if you
process data with
+ * machines in different timezones, or if you access the data from
multiple SQL engines.
+ */
+private[sql] case class TimestampTableTimeZone(sparkSession: SparkSession)
--- End diff --
I'm also trying to see if this can be simplified; I guess the main thing is
Imran's comment about not being able to use `transformUp`. I need to take a
look at whether that's really the case.
This rule also doesn't seem to handle `InsertIntoHiveTable`, which is in
the hive module so can't be handled here. Probably will need a new rule based
on this one in the hive module.
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