Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/16944#discussion_r101888190
--- Diff:
sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveSchemaInferenceSuite.scala
---
@@ -0,0 +1,192 @@
+/*
+ * 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.hive
+
+import java.io.File
+import java.util.concurrent.{Executors, TimeUnit}
+
+import org.scalatest.BeforeAndAfterEach
+
+import org.apache.spark.metrics.source.HiveCatalogMetrics
+import org.apache.spark.sql.catalyst.TableIdentifier
+import org.apache.spark.sql.catalyst.catalog._
+import org.apache.spark.sql.execution.datasources.FileStatusCache
+import org.apache.spark.sql.QueryTest
+import org.apache.spark.sql.hive.client.HiveClient
+import org.apache.spark.sql.hive.test.TestHiveSingleton
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.internal.SQLConf.HiveCaseSensitiveInferenceMode
+import org.apache.spark.sql.test.SQLTestUtils
+import org.apache.spark.sql.types._
+
+class HiveSchemaInferenceSuite
+ extends QueryTest with TestHiveSingleton with SQLTestUtils with
BeforeAndAfterEach {
+
+ import HiveSchemaInferenceSuite._
+
+ override def beforeEach(): Unit = {
+ super.beforeEach()
+ FileStatusCache.resetForTesting()
+ }
+
+ override def afterEach(): Unit = {
+ super.afterEach()
+ FileStatusCache.resetForTesting()
+ }
+
+ private val externalCatalog =
spark.sharedState.externalCatalog.asInstanceOf[HiveExternalCatalog]
+ private val lowercaseSchema = StructType(Seq(
+ StructField("fieldone", LongType),
+ StructField("partcol1", IntegerType),
+ StructField("partcol2", IntegerType)))
+ private val caseSensitiveSchema = StructType(Seq(
+ StructField("fieldOne", LongType),
+ // Partition columns remain case-insensitive
+ StructField("partcol1", IntegerType),
+ StructField("partcol2", IntegerType)))
+
+ // Create a CatalogTable instance modeling an external Hive Metastore
table backed by
+ // Parquet data files.
+ private def hiveExternalCatalogTable(
+ tableName: String,
+ location: String,
+ schema: StructType,
+ partitionColumns: Seq[String],
+ properties: Map[String, String] = Map.empty): CatalogTable = {
+ CatalogTable(
+ identifier = TableIdentifier(table = tableName, database =
Option(DATABASE)),
+ tableType = CatalogTableType.EXTERNAL,
+ storage = CatalogStorageFormat(
+ locationUri = Option(location),
+ inputFormat =
Option("org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat"),
+ outputFormat =
Option("org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat"),
+ serde =
Option("org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe"),
+ compressed = false,
+ properties = Map("serialization.format" -> "1")),
+ schema = schema,
+ provider = Option("hive"),
+ partitionColumnNames = partitionColumns,
+ properties = properties)
+ }
+
+ // Creates CatalogTablePartition instances for adding partitions of data
to our test table.
+ private def hiveCatalogPartition(location: String, index: Int):
CatalogTablePartition
+ = CatalogTablePartition(
+ spec = Map("partcol1" -> index.toString, "partcol2" ->
index.toString),
+ storage = CatalogStorageFormat(
+ locationUri =
Option(s"${location}/partCol1=$index/partCol2=$index/"),
+ inputFormat =
Option("org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat"),
+ outputFormat =
Option("org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat"),
+ serde =
Option("org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe"),
+ compressed = false,
+ properties = Map("serialization.format" -> "1")))
+
+ // Creates a case-sensitive external Hive table for testing schema
inference options. Table
+ // will not have Spark-specific table properties set.
+ private def setupCaseSensitiveTable(
+ tableName: String,
+ dir: File): Unit = {
+ spark.range(NUM_RECORDS)
+ .selectExpr("id as fieldOne", "id as partCol1", "id as partCol2")
+ .write
+ .partitionBy("partCol1", "partCol2")
+ .mode("overwrite")
+ .parquet(dir.getAbsolutePath)
+
+
+ val client = externalCatalog.client
+
+ val catalogTable = hiveExternalCatalogTable(
+ tableName,
+ dir.getAbsolutePath,
+ lowercaseSchema,
+ Seq("partcol1", "partcol2"))
+ client.createTable(catalogTable, true)
+
+ val partitions = (0 until
NUM_RECORDS).map(hiveCatalogPartition(dir.getAbsolutePath, _)).toSeq
+ client.createPartitions(DATABASE, tableName, partitions, true)
+ }
+
+ // Create a test table used for a single unit test, with data stored in
the specified directory.
+ private def withTestTable(dir: File)(f: File => Unit): Unit = {
+ setupCaseSensitiveTable(TEST_TABLE_NAME, dir)
+ try f(dir) finally spark.sql(s"DROP TABLE IF EXISTS $TEST_TABLE_NAME")
+ }
+
+ private val inferenceKey = SQLConf.HIVE_CASE_SENSITIVE_INFERENCE.key
+
+ test("Schema should be inferred and written to table properties when
INFER_AND_SAVE is " +
+ "specified") {
+ withSQLConf(inferenceKey ->
HiveCaseSensitiveInferenceMode.INFER_AND_SAVE.toString) {
+ withTempDir { dir =>
+ withTestTable(dir) { dir =>
+ assert(spark.sql(FIELD_QUERY).count == NUM_RECORDS)
--- End diff --
Could we have a check for `originalTable` like below to see if its
`schemaPreservesCase` is false and there is no `DATASOURCE_SCHEMA_NUMPARTS`
property?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastruct...@apache.org or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
