[SPARK-12966][SQL] ArrayType(DecimalType) support in Postgres JDBC

Fixes error `org.postgresql.util.PSQLException: Unable to find server array type for provided name decimal(38,18)`.

* Passes scale metadata to JDBC dialect for usage in type conversions.
* Removes unused length/scale/precision parameters from `createArrayOf` parameter `typeName` (for writing).
* Adds configurable precision and scale to Postgres `DecimalType` (for reading).
* Adds a new kind of test that verifies the schema written by `DataFrame.write.jdbc`.

Author: Brandon Bradley <bradleytastic@gmail.com>

Closes #10928 from blbradley/spark-12966.

docker-integration-tests/src/test/scala/org/apache/spark/sql/jdbc/PostgresIntegrationSuite.scala

@@ -22,6 +22,7 @@ import java.util.Properties
 
 import org.apache.spark.sql.Column
 import org.apache.spark.sql.catalyst.expressions.Literal
+import org.apache.spark.sql.types.{ArrayType, DecimalType}
 import org.apache.spark.tags.DockerTest
 
 @DockerTest
@@ -42,10 +43,10 @@ class PostgresIntegrationSuite extends DockerJDBCIntegrationSuite {
     conn.prepareStatement("CREATE TYPE enum_type AS ENUM ('d1', 'd2')").executeUpdate()
     conn.prepareStatement("CREATE TABLE bar (c0 text, c1 integer, c2 double precision, c3 bigint, "
       + "c4 bit(1), c5 bit(10), c6 bytea, c7 boolean, c8 inet, c9 cidr, "
-      + "c10 integer[], c11 text[], c12 real[], c13 enum_type)").executeUpdate()
+      + "c10 integer[], c11 text[], c12 real[], c13 numeric(2,2)[], c14 enum_type)").executeUpdate()
     conn.prepareStatement("INSERT INTO bar VALUES ('hello', 42, 1.25, 123456789012345, B'0', "
       + "B'1000100101', E'\\\\xDEADBEEF', true, '172.16.0.42', '192.168.0.0/16', "
-      + """'{1, 2}', '{"a", null, "b"}', '{0.11, 0.22}', 'd1')""").executeUpdate()
+      + """'{1, 2}', '{"a", null, "b"}', '{0.11, 0.22}', '{0.11, 0.22}', 'd1')""").executeUpdate()
   }
 
   test("Type mapping for various types") {
@@ -53,7 +54,7 @@ class PostgresIntegrationSuite extends DockerJDBCIntegrationSuite {
     val rows = df.collect()
     assert(rows.length == 1)
     val types = rows(0).toSeq.map(x => x.getClass)
-    assert(types.length == 14)
+    assert(types.length == 15)
     assert(classOf[String].isAssignableFrom(types(0)))
     assert(classOf[java.lang.Integer].isAssignableFrom(types(1)))
     assert(classOf[java.lang.Double].isAssignableFrom(types(2)))
@@ -67,7 +68,8 @@ class PostgresIntegrationSuite extends DockerJDBCIntegrationSuite {
     assert(classOf[Seq[Int]].isAssignableFrom(types(10)))
     assert(classOf[Seq[String]].isAssignableFrom(types(11)))
     assert(classOf[Seq[Double]].isAssignableFrom(types(12)))
-    assert(classOf[String].isAssignableFrom(types(13)))
+    assert(classOf[Seq[BigDecimal]].isAssignableFrom(types(13)))
+    assert(classOf[String].isAssignableFrom(types(14)))
     assert(rows(0).getString(0).equals("hello"))
     assert(rows(0).getInt(1) == 42)
     assert(rows(0).getDouble(2) == 1.25)
@@ -84,13 +86,17 @@ class PostgresIntegrationSuite extends DockerJDBCIntegrationSuite {
     assert(rows(0).getSeq(10) == Seq(1, 2))
     assert(rows(0).getSeq(11) == Seq("a", null, "b"))
     assert(rows(0).getSeq(12).toSeq == Seq(0.11f, 0.22f))
-    assert(rows(0).getString(13) == "d1")
+    assert(rows(0).getSeq(13) == Seq("0.11", "0.22").map(BigDecimal(_).bigDecimal))
+    assert(rows(0).getString(14) == "d1")
   }
 
   test("Basic write test") {
     val df = sqlContext.read.jdbc(jdbcUrl, "bar", new Properties)
     // Test only that it doesn't crash.
     df.write.jdbc(jdbcUrl, "public.barcopy", new Properties)
+    // Test that written numeric type has same DataType as input
+    assert(sqlContext.read.jdbc(jdbcUrl, "public.barcopy", new Properties).schema(13).dataType ==
+      ArrayType(DecimalType(2, 2), true))
     // Test write null values.
     df.select(df.queryExecution.analyzed.output.map { a =>
       Column(Literal.create(null, a.dataType)).as(a.name)

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRDD.scala

@@ -137,7 +137,9 @@ private[sql] object JDBCRDD extends Logging {
             val fieldScale = rsmd.getScale(i + 1)
             val isSigned = rsmd.isSigned(i + 1)
             val nullable = rsmd.isNullable(i + 1) != ResultSetMetaData.columnNoNulls
-            val metadata = new MetadataBuilder().putString("name", columnName)
+            val metadata = new MetadataBuilder()
+              .putString("name", columnName)
+              .putLong("scale", fieldScale)
             val columnType =
               dialect.getCatalystType(dataType, typeName, fieldSize, metadata).getOrElse(
                 getCatalystType(dataType, fieldSize, fieldScale, isSigned))

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala

@@ -194,8 +194,11 @@ object JdbcUtils extends Logging {
                 case DateType => stmt.setDate(i + 1, row.getAs[java.sql.Date](i))
                 case t: DecimalType => stmt.setBigDecimal(i + 1, row.getDecimal(i))
                 case ArrayType(et, _) =>
+                  // remove type length parameters from end of type name
+                  val typeName = getJdbcType(et, dialect).databaseTypeDefinition
+                    .toLowerCase.split("\\(")(0)
                   val array = conn.createArrayOf(
-                    getJdbcType(et, dialect).databaseTypeDefinition.toLowerCase,
+                    typeName,
                     row.getSeq[AnyRef](i).toArray)
                   stmt.setArray(i + 1, array)
                 case _ => throw new IllegalArgumentException(

sql/core/src/main/scala/org/apache/spark/sql/jdbc/PostgresDialect.scala

@@ -32,14 +32,18 @@ private object PostgresDialect extends JdbcDialect {
     if (sqlType == Types.BIT && typeName.equals("bit") && size != 1) {
       Some(BinaryType)
     } else if (sqlType == Types.OTHER) {
-      toCatalystType(typeName).filter(_ == StringType)
-    } else if (sqlType == Types.ARRAY && typeName.length > 1 && typeName(0) == '_') {
-      toCatalystType(typeName.drop(1)).map(ArrayType(_))
+      Some(StringType)
+    } else if (sqlType == Types.ARRAY) {
+      val scale = md.build.getLong("scale").toInt
+      // postgres array type names start with underscore
+      toCatalystType(typeName.drop(1), size, scale).map(ArrayType(_))
     } else None
   }
 
-  // TODO: support more type names.
-  private def toCatalystType(typeName: String): Option[DataType] = typeName match {
+  private def toCatalystType(
+      typeName: String,
+      precision: Int,
+      scale: Int): Option[DataType] = typeName match {
     case "bool" => Some(BooleanType)
     case "bit" => Some(BinaryType)
     case "int2" => Some(ShortType)
@@ -52,7 +56,7 @@ private object PostgresDialect extends JdbcDialect {
     case "bytea" => Some(BinaryType)
     case "timestamp" | "timestamptz" | "time" | "timetz" => Some(TimestampType)
     case "date" => Some(DateType)
-    case "numeric" => Some(DecimalType.SYSTEM_DEFAULT)
+    case "numeric" | "decimal" => Some(DecimalType.bounded(precision, scale))
     case _ => None
   }
 
@@ -62,6 +66,8 @@ private object PostgresDialect extends JdbcDialect {
     case BooleanType => Some(JdbcType("BOOLEAN", Types.BOOLEAN))
     case FloatType => Some(JdbcType("FLOAT4", Types.FLOAT))
     case DoubleType => Some(JdbcType("FLOAT8", Types.DOUBLE))
+    case t: DecimalType => Some(
+      JdbcType(s"NUMERIC(${t.precision},${t.scale})", java.sql.Types.NUMERIC))
     case ArrayType(et, _) if et.isInstanceOf[AtomicType] =>
       getJDBCType(et).map(_.databaseTypeDefinition)
         .orElse(JdbcUtils.getCommonJDBCType(et).map(_.databaseTypeDefinition))