[SPARK-19107][SQL] support creating hive table with DataFrameWriter and Catalog

## What changes were proposed in this pull request?

After unifying the CREATE TABLE syntax in https://github.com/apache/spark/pull/16296, it's pretty easy to support creating hive table with `DataFrameWriter` and `Catalog` now.

This PR basically just removes the hive provider check in `DataFrameWriter.saveAsTable` and `Catalog.createExternalTable`, and add tests.

## How was this patch tested?

new tests in `HiveDDLSuite`

Author: Wenchen Fan <wenchen@databricks.com>

Closes #16487 from cloud-fan/hive-table.

2 files changed, 77 insertions, 20 deletions

diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/MetastoreDataSourcesSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/MetastoreDataSourcesSuite.scala
index aed825e2f3..13ef79e3b7 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/MetastoreDataSourcesSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/MetastoreDataSourcesSuite.scala
@@ -1169,26 +1169,6 @@ class MetastoreDataSourcesSuite extends QueryTest with SQLTestUtils with TestHiv
     }
   }
 
-  test("save API - format hive") {
-    withTempDir { dir =>
-      val path = dir.getCanonicalPath
-      val e = intercept[ClassNotFoundException] {
-        spark.range(10).write.format("hive").mode(SaveMode.Ignore).save(path)
-      }.getMessage
-      assert(e.contains("Failed to find data source: hive"))
-    }
-  }
-
-  test("saveAsTable API - format hive") {
-    val tableName = "tab1"
-    withTable(tableName) {
-      val e = intercept[AnalysisException] {
-        spark.range(10).write.format("hive").mode(SaveMode.Overwrite).saveAsTable(tableName)
-      }.getMessage
-      assert(e.contains("Cannot create hive serde table with saveAsTable API"))
-    }
-  }
-
   test("create a temp view using hive") {
     val tableName = "tab1"
     withTable (tableName) {
diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala
index 3ac07d0933..77285282a6 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala
@@ -33,6 +33,7 @@ import org.apache.spark.sql.hive.test.TestHiveSingleton
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.internal.StaticSQLConf.CATALOG_IMPLEMENTATION
 import org.apache.spark.sql.test.SQLTestUtils
+import org.apache.spark.sql.types.StructType
 
 class HiveDDLSuite
   extends QueryTest with SQLTestUtils with TestHiveSingleton with BeforeAndAfterEach {
@@ -1289,4 +1290,80 @@ class HiveDDLSuite
       }
     }
   }
+
+  test("create hive serde table with Catalog") {
+    withTable("t") {
+      withTempDir { dir =>
+        val df = spark.catalog.createExternalTable(
+          "t",
+          "hive",
+          new StructType().add("i", "int"),
+          Map("path" -> dir.getCanonicalPath, "fileFormat" -> "parquet"))
+        assert(df.collect().isEmpty)
+
+        val table = spark.sessionState.catalog.getTableMetadata(TableIdentifier("t"))
+        assert(DDLUtils.isHiveTable(table))
+        assert(table.storage.inputFormat ==
+          Some("org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat"))
+        assert(table.storage.outputFormat ==
+          Some("org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat"))
+        assert(table.storage.serde ==
+          Some("org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe"))
+
+        sql("INSERT INTO t SELECT 1")
+        checkAnswer(spark.table("t"), Row(1))
+      }
+    }
+  }
+
+  test("create hive serde table with DataFrameWriter.saveAsTable") {
+    withTable("t", "t2") {
+      Seq(1 -> "a").toDF("i", "j")
+        .write.format("hive").option("fileFormat", "avro").saveAsTable("t")
+      checkAnswer(spark.table("t"), Row(1, "a"))
+
+      val table = spark.sessionState.catalog.getTableMetadata(TableIdentifier("t"))
+      assert(DDLUtils.isHiveTable(table))
+      assert(table.storage.inputFormat ==
+        Some("org.apache.hadoop.hive.ql.io.avro.AvroContainerInputFormat"))
+      assert(table.storage.outputFormat ==
+        Some("org.apache.hadoop.hive.ql.io.avro.AvroContainerOutputFormat"))
+      assert(table.storage.serde ==
+        Some("org.apache.hadoop.hive.serde2.avro.AvroSerDe"))
+
+      sql("INSERT INTO t SELECT 2, 'b'")
+      checkAnswer(spark.table("t"), Row(1, "a") :: Row(2, "b") :: Nil)
+
+      val e = intercept[AnalysisException] {
+        Seq(1 -> "a").toDF("i", "j").write.format("hive").partitionBy("i").saveAsTable("t2")
+      }
+      assert(e.message.contains("A Create Table As Select (CTAS) statement is not allowed " +
+        "to create a partitioned table using Hive"))
+
+      val e2 = intercept[AnalysisException] {
+        Seq(1 -> "a").toDF("i", "j").write.format("hive").bucketBy(4, "i").saveAsTable("t2")
+      }
+      assert(e2.message.contains("Creating bucketed Hive serde table is not supported yet"))
+
+      val e3 = intercept[AnalysisException] {
+        spark.table("t").write.format("hive").mode("overwrite").saveAsTable("t")
+      }
+      assert(e3.message.contains(
+        "CTAS for hive serde tables does not support append or overwrite semantics"))
+    }
+  }
+
+  test("read/write files with hive data source is not allowed") {
+    withTempDir { dir =>
+      val e = intercept[AnalysisException] {
+        spark.read.format("hive").load(dir.getAbsolutePath)
+      }
+      assert(e.message.contains("Hive data source can only be used with tables"))
+
+      val e2 = intercept[AnalysisException] {
+        Seq(1 -> "a").toDF("i", "j").write.format("hive").save(dir.getAbsolutePath)
+      }
+      assert(e2.message.contains("Hive data source can only be used with tables"))
+    }
+  }
 }