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[SPARK-27441][SQL][TEST] Add read/write tests to Hive serde tables
## What changes were proposed in this pull request? The versions between Hive, Parquet and ORC after the built-in Hive upgraded to 2.3.5 for Hadoop 3.2: - built-in Hive is 1.2.1.spark2: | ORC | Parquet -- | -- | -- Spark datasource table | 1.5.5 | 1.10.1 Spark hive table | Hive built-in | 1.6.0 Apache Hive 1.2.1 | Hive built-in | 1.6.0 - built-in Hive is 2.3.5: | ORC | Parquet -- | -- | -- Spark datasource table | 1.5.5 | 1.10.1 Spark hive table | 1.5.5 | [1.10.1](apache#24346) Apache Hive 2.3.5 | 1.3.4 | 1.8.1 We should add a test for Hive Serde table. This pr adds tests to test read/write of all supported data types using Parquet and ORC. ## How was this patch tested? unit tests Closes apache#24345 from wangyum/SPARK-27441. Authored-by: Yuming Wang <yumwang@ebay.com> Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
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sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveSerDeReadWriteSuite.scala
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| /* | ||
| * 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. | ||
| */ | ||
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| package org.apache.spark.sql.hive.execution | ||
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| import java.sql.{Date, Timestamp} | ||
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| import org.apache.spark.sql.{QueryTest, Row} | ||
| import org.apache.spark.sql.hive.HiveUtils.{CONVERT_METASTORE_ORC, CONVERT_METASTORE_PARQUET} | ||
| import org.apache.spark.sql.hive.test.TestHiveSingleton | ||
| import org.apache.spark.sql.internal.SQLConf.ORC_IMPLEMENTATION | ||
| import org.apache.spark.sql.test.SQLTestUtils | ||
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| class HiveSerDeReadWriteSuite extends QueryTest with SQLTestUtils with TestHiveSingleton { | ||
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| private var originalConvertMetastoreParquet = CONVERT_METASTORE_PARQUET.defaultValueString | ||
| private var originalConvertMetastoreORC = CONVERT_METASTORE_ORC.defaultValueString | ||
| private var originalORCImplementation = ORC_IMPLEMENTATION.defaultValueString | ||
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| protected override def beforeAll(): Unit = { | ||
| super.beforeAll() | ||
| originalConvertMetastoreParquet = spark.conf.get(CONVERT_METASTORE_PARQUET.key) | ||
| originalConvertMetastoreORC = spark.conf.get(CONVERT_METASTORE_ORC.key) | ||
| originalORCImplementation = spark.conf.get(ORC_IMPLEMENTATION) | ||
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| spark.conf.set(CONVERT_METASTORE_PARQUET.key, "false") | ||
| spark.conf.set(CONVERT_METASTORE_ORC.key, "false") | ||
| spark.conf.set(ORC_IMPLEMENTATION.key, "hive") | ||
| } | ||
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| protected override def afterAll(): Unit = { | ||
| spark.conf.set(CONVERT_METASTORE_PARQUET.key, originalConvertMetastoreParquet) | ||
| spark.conf.set(CONVERT_METASTORE_ORC.key, originalConvertMetastoreORC) | ||
| spark.conf.set(ORC_IMPLEMENTATION.key, originalORCImplementation) | ||
| super.afterAll() | ||
| } | ||
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| private def checkNumericTypes(fileFormat: String, dataType: String, value: Any): Unit = { | ||
| withTable("hive_serde") { | ||
| hiveClient.runSqlHive(s"CREATE TABLE hive_serde (c1 $dataType) STORED AS $fileFormat") | ||
| hiveClient.runSqlHive("INSERT INTO TABLE hive_serde values(1)") | ||
| checkAnswer(spark.table("hive_serde"), Row(1)) | ||
| spark.sql(s"INSERT INTO TABLE hive_serde values($value)") | ||
| checkAnswer(spark.table("hive_serde"), Seq(Row(1), Row(value))) | ||
| } | ||
| } | ||
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| private def checkDateTimeTypes(fileFormat: String): Unit = { | ||
| // TIMESTAMP | ||
| withTable("hive_serde") { | ||
| hiveClient.runSqlHive(s"CREATE TABLE hive_serde (c1 TIMESTAMP) STORED AS $fileFormat") | ||
| hiveClient.runSqlHive("INSERT INTO TABLE hive_serde values('2019-04-11 15:50:00')") | ||
| checkAnswer(spark.table("hive_serde"), Row(Timestamp.valueOf("2019-04-11 15:50:00"))) | ||
| spark.sql("INSERT INTO TABLE hive_serde values('2019-04-12 15:50:00')") | ||
| checkAnswer( | ||
| spark.table("hive_serde"), | ||
| Seq(Row(Timestamp.valueOf("2019-04-11 15:50:00")), | ||
| Row(Timestamp.valueOf("2019-04-12 15:50:00")))) | ||
| } | ||
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| // DATE | ||
| withTable("hive_serde") { | ||
| hiveClient.runSqlHive(s"CREATE TABLE hive_serde (c1 DATE) STORED AS $fileFormat") | ||
| hiveClient.runSqlHive("INSERT INTO TABLE hive_serde values('2019-04-11')") | ||
| checkAnswer(spark.table("hive_serde"), Row(Date.valueOf("2019-04-11"))) | ||
| spark.sql("INSERT INTO TABLE hive_serde values('2019-04-12')") | ||
| checkAnswer( | ||
| spark.table("hive_serde"), | ||
| Seq(Row(Date.valueOf("2019-04-11")), Row(Date.valueOf("2019-04-12")))) | ||
| } | ||
| } | ||
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| private def checkStringTypes(fileFormat: String, dataType: String, value: String): Unit = { | ||
| withTable("hive_serde") { | ||
| hiveClient.runSqlHive(s"CREATE TABLE hive_serde (c1 $dataType) STORED AS $fileFormat") | ||
| hiveClient.runSqlHive("INSERT INTO TABLE hive_serde values('s')") | ||
| checkAnswer(spark.table("hive_serde"), Row("s")) | ||
| spark.sql(s"INSERT INTO TABLE hive_serde values('$value')") | ||
| checkAnswer(spark.table("hive_serde"), Seq(Row("s"), Row(value))) | ||
| } | ||
| } | ||
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| private def checkCharTypes(fileFormat: String): Unit = { | ||
| withTable("hive_serde") { | ||
| hiveClient.runSqlHive(s"CREATE TABLE hive_serde (c1 CHAR(10)) STORED AS $fileFormat") | ||
| hiveClient.runSqlHive("INSERT INTO TABLE hive_serde values('s')") | ||
| checkAnswer(spark.table("hive_serde"), Row("s" + " " * 9)) | ||
| spark.sql(s"INSERT INTO TABLE hive_serde values('s3')") | ||
| checkAnswer(spark.table("hive_serde"), Seq(Row("s" + " " * 9), Row("s3" + " " * 8))) | ||
| } | ||
| } | ||
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| private def checkMiscTypes(fileFormat: String): Unit = { | ||
| // BOOLEAN | ||
| withTable("hive_serde") { | ||
| hiveClient.runSqlHive(s"CREATE TABLE hive_serde (c1 BOOLEAN) STORED AS $fileFormat") | ||
| hiveClient.runSqlHive("INSERT INTO TABLE hive_serde values(false)") | ||
| checkAnswer(spark.table("hive_serde"), Row(false)) | ||
| spark.sql("INSERT INTO TABLE hive_serde values(true)") | ||
| checkAnswer(spark.table("hive_serde"), Seq(Row(false), Row(true))) | ||
| } | ||
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| // BINARY | ||
| withTable("hive_serde") { | ||
| hiveClient.runSqlHive(s"CREATE TABLE hive_serde (c1 BINARY) STORED AS $fileFormat") | ||
| hiveClient.runSqlHive("INSERT INTO TABLE hive_serde values('1')") | ||
| checkAnswer(spark.table("hive_serde"), Row("1".getBytes)) | ||
| spark.sql("INSERT INTO TABLE hive_serde values('2')") | ||
| checkAnswer(spark.table("hive_serde"), Seq(Row("1".getBytes), Row("2".getBytes))) | ||
| } | ||
| } | ||
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| private def checkComplexTypes(fileFormat: String): Unit = { | ||
| // ARRAY<data_type> | ||
| withTable("hive_serde") { | ||
| hiveClient.runSqlHive(s"CREATE TABLE hive_serde (c1 ARRAY <STRING>) STORED AS $fileFormat") | ||
| hiveClient.runSqlHive("INSERT INTO TABLE hive_serde SELECT ARRAY('a','b') FROM (SELECT 1) t") | ||
| checkAnswer(spark.table("hive_serde"), Row(Array("a", "b"))) | ||
| spark.sql("INSERT INTO TABLE hive_serde SELECT ARRAY('c', 'd')") | ||
| checkAnswer(spark.table("hive_serde"), Seq(Row(Array("a", "b")), Row(Array("c", "d")))) | ||
| } | ||
| // MAP<primitive_type, data_type> | ||
| withTable("hive_serde") { | ||
| hiveClient.runSqlHive(s"CREATE TABLE hive_serde (c1 MAP <INT, STRING>) STORED AS $fileFormat") | ||
| hiveClient.runSqlHive("INSERT INTO TABLE hive_serde SELECT MAP(1, 'a') FROM (SELECT 1) t") | ||
| checkAnswer(spark.table("hive_serde"), Row(Map(1 -> "a"))) | ||
| spark.sql("INSERT INTO TABLE hive_serde SELECT MAP(2, 'b')") | ||
| checkAnswer(spark.table("hive_serde"), Seq(Row(Map(1 -> "a")), Row(Map(2 -> "b")))) | ||
| } | ||
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| // STRUCT<col_name : data_type [COMMENT col_comment], ...> | ||
| withTable("hive_serde") { | ||
| hiveClient.runSqlHive( | ||
| s"CREATE TABLE hive_serde (c1 STRUCT <k: INT>) STORED AS $fileFormat") | ||
| hiveClient.runSqlHive( | ||
| "INSERT INTO TABLE hive_serde SELECT NAMED_STRUCT('k', 1) FROM (SELECT 1) t") | ||
| checkAnswer(spark.table("hive_serde"), Row(Row(1))) | ||
| spark.sql("INSERT INTO TABLE hive_serde SELECT NAMED_STRUCT('k', 2)") | ||
| checkAnswer(spark.table("hive_serde"), Seq(Row(Row(1)), Row(Row(2)))) | ||
| } | ||
| } | ||
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| Seq("PARQUET", "ORC").foreach { fileFormat => | ||
| test(s"Read/Write Hive $fileFormat serde table") { | ||
| // Numeric Types | ||
| checkNumericTypes(fileFormat, "TINYINT", 2) | ||
| checkNumericTypes(fileFormat, "SMALLINT", 2) | ||
| checkNumericTypes(fileFormat, "INT", 2) | ||
| checkNumericTypes(fileFormat, "BIGINT", 2) | ||
| checkNumericTypes(fileFormat, "FLOAT", 2.1F) | ||
| checkNumericTypes(fileFormat, "DOUBLE", 2.1D) | ||
| checkNumericTypes(fileFormat, "DECIMAL(9, 2)", 2.1D) | ||
| checkNumericTypes(fileFormat, "DECIMAL(18, 2)", 2.1D) | ||
| checkNumericTypes(fileFormat, "DECIMAL(38, 2)", 2.1D) | ||
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| // Date/Time Types | ||
| checkDateTimeTypes(fileFormat) | ||
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| // String Types | ||
| checkStringTypes(fileFormat, "STRING", "s1") | ||
| checkStringTypes(fileFormat, "VARCHAR(10)", "s2") | ||
| checkCharTypes(fileFormat) | ||
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| // Misc Types | ||
| checkMiscTypes(fileFormat) | ||
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| // Complex Types | ||
| checkComplexTypes(fileFormat) | ||
| } | ||
| } | ||
| } |