[SPARK-34512][BUILD][SQL] Upgrade built-in Hive to 2.3.9

dev/deps/spark-deps-hadoop-2.7-hive-2.3

@@ -83,21 +83,21 @@ hadoop-yarn-client/2.7.4//hadoop-yarn-client-2.7.4.jar
 hadoop-yarn-common/2.7.4//hadoop-yarn-common-2.7.4.jar
 hadoop-yarn-server-common/2.7.4//hadoop-yarn-server-common-2.7.4.jar
 hadoop-yarn-server-web-proxy/2.7.4//hadoop-yarn-server-web-proxy-2.7.4.jar
-hive-beeline/2.3.8//hive-beeline-2.3.8.jar
-hive-cli/2.3.8//hive-cli-2.3.8.jar
-hive-common/2.3.8//hive-common-2.3.8.jar
-hive-exec/2.3.8/core/hive-exec-2.3.8-core.jar
-hive-jdbc/2.3.8//hive-jdbc-2.3.8.jar
-hive-llap-common/2.3.8//hive-llap-common-2.3.8.jar
-hive-metastore/2.3.8//hive-metastore-2.3.8.jar
-hive-serde/2.3.8//hive-serde-2.3.8.jar
+hive-beeline/2.3.9//hive-beeline-2.3.9.jar
+hive-cli/2.3.9//hive-cli-2.3.9.jar
+hive-common/2.3.9//hive-common-2.3.9.jar
+hive-exec/2.3.9/core/hive-exec-2.3.9-core.jar
+hive-jdbc/2.3.9//hive-jdbc-2.3.9.jar
+hive-llap-common/2.3.9//hive-llap-common-2.3.9.jar
+hive-metastore/2.3.9//hive-metastore-2.3.9.jar
+hive-serde/2.3.9//hive-serde-2.3.9.jar
 hive-service-rpc/3.1.2//hive-service-rpc-3.1.2.jar
-hive-shims-0.23/2.3.8//hive-shims-0.23-2.3.8.jar
-hive-shims-common/2.3.8//hive-shims-common-2.3.8.jar
-hive-shims-scheduler/2.3.8//hive-shims-scheduler-2.3.8.jar
-hive-shims/2.3.8//hive-shims-2.3.8.jar
+hive-shims-0.23/2.3.9//hive-shims-0.23-2.3.9.jar
+hive-shims-common/2.3.9//hive-shims-common-2.3.9.jar
+hive-shims-scheduler/2.3.9//hive-shims-scheduler-2.3.9.jar
+hive-shims/2.3.9//hive-shims-2.3.9.jar
 hive-storage-api/2.7.2//hive-storage-api-2.7.2.jar
-hive-vector-code-gen/2.3.8//hive-vector-code-gen-2.3.8.jar
+hive-vector-code-gen/2.3.9//hive-vector-code-gen-2.3.9.jar
 hk2-api/2.6.1//hk2-api-2.6.1.jar
 hk2-locator/2.6.1//hk2-locator-2.6.1.jar
 hk2-utils/2.6.1//hk2-utils-2.6.1.jar

dev/deps/spark-deps-hadoop-3.2-hive-2.3

@@ -61,21 +61,21 @@ guava/14.0.1//guava-14.0.1.jar
 hadoop-client-api/3.2.2//hadoop-client-api-3.2.2.jar
 hadoop-client-runtime/3.2.2//hadoop-client-runtime-3.2.2.jar
 hadoop-yarn-server-web-proxy/3.2.2//hadoop-yarn-server-web-proxy-3.2.2.jar
-hive-beeline/2.3.8//hive-beeline-2.3.8.jar
-hive-cli/2.3.8//hive-cli-2.3.8.jar
-hive-common/2.3.8//hive-common-2.3.8.jar
-hive-exec/2.3.8/core/hive-exec-2.3.8-core.jar
-hive-jdbc/2.3.8//hive-jdbc-2.3.8.jar
-hive-llap-common/2.3.8//hive-llap-common-2.3.8.jar
-hive-metastore/2.3.8//hive-metastore-2.3.8.jar
-hive-serde/2.3.8//hive-serde-2.3.8.jar
+hive-beeline/2.3.9//hive-beeline-2.3.9.jar
+hive-cli/2.3.9//hive-cli-2.3.9.jar
+hive-common/2.3.9//hive-common-2.3.9.jar
+hive-exec/2.3.9/core/hive-exec-2.3.9-core.jar
+hive-jdbc/2.3.9//hive-jdbc-2.3.9.jar
+hive-llap-common/2.3.9//hive-llap-common-2.3.9.jar
+hive-metastore/2.3.9//hive-metastore-2.3.9.jar
+hive-serde/2.3.9//hive-serde-2.3.9.jar
 hive-service-rpc/3.1.2//hive-service-rpc-3.1.2.jar
-hive-shims-0.23/2.3.8//hive-shims-0.23-2.3.8.jar
-hive-shims-common/2.3.8//hive-shims-common-2.3.8.jar
-hive-shims-scheduler/2.3.8//hive-shims-scheduler-2.3.8.jar
-hive-shims/2.3.8//hive-shims-2.3.8.jar
+hive-shims-0.23/2.3.9//hive-shims-0.23-2.3.9.jar
+hive-shims-common/2.3.9//hive-shims-common-2.3.9.jar
+hive-shims-scheduler/2.3.9//hive-shims-scheduler-2.3.9.jar
+hive-shims/2.3.9//hive-shims-2.3.9.jar
 hive-storage-api/2.7.2//hive-storage-api-2.7.2.jar
-hive-vector-code-gen/2.3.8//hive-vector-code-gen-2.3.8.jar
+hive-vector-code-gen/2.3.9//hive-vector-code-gen-2.3.9.jar
 hk2-api/2.6.1//hk2-api-2.6.1.jar
 hk2-locator/2.6.1//hk2-locator-2.6.1.jar
 hk2-utils/2.6.1//hk2-utils-2.6.1.jar

docs/building-spark.md

@@ -83,9 +83,9 @@ Example:
 
 To enable Hive integration for Spark SQL along with its JDBC server and CLI,
 add the `-Phive` and `-Phive-thriftserver` profiles to your existing build options.
-By default Spark will build with Hive 2.3.8.
+By default Spark will build with Hive 2.3.9.
 
-    # With Hive 2.3.8 support
+    # With Hive 2.3.9 support
     ./build/mvn -Pyarn -Phive -Phive-thriftserver -DskipTests clean package
 
 ## Packaging without Hadoop Dependencies for YARN

docs/sql-data-sources-hive-tables.md

@@ -127,10 +127,10 @@ The following options can be used to configure the version of Hive that is used
   <tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr>
   <tr>
     <td><code>spark.sql.hive.metastore.version</code></td>
-    <td><code>2.3.8</code></td>
+    <td><code>2.3.9</code></td>
     <td>
       Version of the Hive metastore. Available
-      options are <code>0.12.0</code> through <code>2.3.8</code> and <code>3.0.0</code> through <code>3.1.2</code>.
+      options are <code>0.12.0</code> through <code>2.3.9</code> and <code>3.0.0</code> through <code>3.1.2</code>.
     </td>
     <td>1.4.0</td>
   </tr>
@@ -142,9 +142,9 @@ The following options can be used to configure the version of Hive that is used
       property can be one of four options:
       <ol>
         <li><code>builtin</code></li>
-        Use Hive 2.3.8, which is bundled with the Spark assembly when <code>-Phive</code> is
+        Use Hive 2.3.9, which is bundled with the Spark assembly when <code>-Phive</code> is
         enabled. When this option is chosen, <code>spark.sql.hive.metastore.version</code> must be
-        either <code>2.3.8</code> or not defined.
+        either <code>2.3.9</code> or not defined.
         <li><code>maven</code></li>
         Use Hive jars of specified version downloaded from Maven repositories. This configuration
         is not generally recommended for production deployments.

docs/sql-migration-guide.md

@@ -921,7 +921,7 @@ Python UDF registration is unchanged.
 Spark SQL is designed to be compatible with the Hive Metastore, SerDes and UDFs.
 Currently, Hive SerDes and UDFs are based on built-in Hive,
 and Spark SQL can be connected to different versions of Hive Metastore
-(from 0.12.0 to 2.3.8 and 3.0.0 to 3.1.2. Also see [Interacting with Different Versions of Hive Metastore](sql-data-sources-hive-tables.html#interacting-with-different-versions-of-hive-metastore)).
+(from 0.12.0 to 2.3.9 and 3.0.0 to 3.1.2. Also see [Interacting with Different Versions of Hive Metastore](sql-data-sources-hive-tables.html#interacting-with-different-versions-of-hive-metastore)).
 
 #### Deploying in Existing Hive Warehouses
 {:.no_toc}

pom.xml

@@ -128,8 +128,8 @@
     <hive.group>org.apache.hive</hive.group>
     <hive.classifier>core</hive.classifier>
     <!-- Version used in Maven Hive dependency -->
-    <hive.version>2.3.8</hive.version>
-    <hive23.version>2.3.8</hive23.version>
+    <hive.version>2.3.9</hive.version>
+    <hive23.version>2.3.9</hive23.version>
     <!-- Version used for internal directory structure -->
     <hive.version.short>2.3</hive.version.short>
     <!-- note that this should be compatible with Kafka brokers version 0.10 and up -->

sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala

@@ -3642,7 +3642,7 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark
 
   test("SPARK-33084: Add jar support Ivy URI in SQL") {
     val sc = spark.sparkContext
-    val hiveVersion = "2.3.8"
+    val hiveVersion = "2.3.9"
     // transitive=false, only download specified jar
     sql(s"ADD JAR ivy://org.apache.hive.hcatalog:hive-hcatalog-core:$hiveVersion?transitive=false")
     assert(sc.listJars()

sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveUtils.scala

@@ -71,7 +71,7 @@ private[spark] object HiveUtils extends Logging {
 
   val HIVE_METASTORE_VERSION = buildStaticConf("spark.sql.hive.metastore.version")
     .doc("Version of the Hive metastore. Available options are " +
-        "<code>0.12.0</code> through <code>2.3.8</code> and " +
+        "<code>0.12.0</code> through <code>2.3.9</code> and " +
         "<code>3.0.0</code> through <code>3.1.2</code>.")
     .version("1.4.0")
     .stringConf

sql/hive/src/main/scala/org/apache/spark/sql/hive/client/package.scala

@@ -102,7 +102,7 @@ package object client {
 
     // Since HIVE-23980, calcite-core included in Hive package jar.
     // For spark, only VersionsSuite currently creates a hive materialized view for testing.
-    case object v2_3 extends HiveVersion("2.3.8",
+    case object v2_3 extends HiveVersion("2.3.9",
       exclusions = Seq("org.apache.calcite:calcite-core",
         "org.apache.calcite:calcite-druid",
         "org.apache.calcite.avatica:avatica",

sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveExternalCatalogVersionsSuite.scala

@@ -203,7 +203,7 @@ class HiveExternalCatalogVersionsSuite extends SparkSubmitTestUtils {
         tryDownloadSpark(version, sparkTestingDir.getCanonicalPath)
       }
 
-      // Extract major.minor for testing Spark 3.1.x and 3.0.x with metastore 2.3.8 and Java 11.
+      // Extract major.minor for testing Spark 3.1.x and 3.0.x with metastore 2.3.9 and Java 11.
       val hiveMetastoreVersion = """^\d+\.\d+""".r.findFirstIn(hiveVersion).get
       val args = Seq(
         "--name", "prepare testing tables",

sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveSerDeReadWriteSuite.scala

@@ -185,4 +185,35 @@ class HiveSerDeReadWriteSuite extends QueryTest with SQLTestUtils with TestHiveS
       checkComplexTypes(fileFormat)
     }
   }
+
+  test("SPARK-34512: Disable validate default values when parsing Avro schemas") {
+    withTable("t1") {
+      hiveClient.runSqlHive(
+        """
+          |CREATE TABLE t1
+          |  ROW FORMAT SERDE
+          |    'org.apache.hadoop.hive.serde2.avro.AvroSerDe'
+          |  STORED AS INPUTFORMAT
+          |    'org.apache.hadoop.hive.ql.io.avro.AvroContainerInputFormat'
+          |  OUTPUTFORMAT
+          |    'org.apache.hadoop.hive.ql.io.avro.AvroContainerOutputFormat'
+          |  TBLPROPERTIES (
+          |    'avro.schema.literal'='{
+          |      "namespace": "org.apache.spark.sql.hive.test",
+          |      "name": "schema_with_default_value",
+          |      "type": "record",
+          |      "fields": [
+          |         {
+          |           "name": "ARRAY_WITH_DEFAULT",
+          |           "type": {"type": "array", "items": "string"},
+          |           "default": null
+          |         }
+          |       ]
+          |    }')
+          |""".stripMargin)
+
+      hiveClient.runSqlHive("INSERT INTO t1 SELECT array('SPARK-34512', 'HIVE-24797')")
+      checkAnswer(spark.table("t1"), Seq(Row(Array("SPARK-34512", "HIVE-24797"))))
+    }
+  }
 }