[SPARK-10648] Oracle dialect to handle nonspecific numeric types

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

@@ -139,6 +139,7 @@ object JdbcDialects {
   registerDialect(DB2Dialect)
   registerDialect(MsSqlServerDialect)
   registerDialect(DerbyDialect)
+  registerDialect(OracleDialect)
 
 
   /**
@@ -315,3 +316,27 @@ case object DerbyDialect extends JdbcDialect {
 
 }
 
+/**
+ * :: DeveloperApi ::
+ * Default Oracle dialect, mapping a nonspecific
+ * numeric type to a general decimal type.
+ * Solution by @cloud-fan and @bdolbeare (github.com)
+ */
+@DeveloperApi
+case object OracleDialect extends JdbcDialect {
+  override def canHandle(url: String): Boolean = url.startsWith("jdbc:oracle")
+  override def getCatalystType(
+      sqlType: Int, typeName: String, size: Int, md: MetadataBuilder): Option[DataType] = {
+    // Handle NUMBER fields that have no precision/scale in special way
+    // because JDBC ResultSetMetaData converts this to 0 procision and -127 scale
+    if (sqlType == Types.NUMERIC && size == 0) {
+      // This is sub-optimal as we have to pick a precision/scale in advance whereas the data
+      //  in Oracle is allowed to have different precision/scale for each value.
+      //  This conversion works in our domain for now though we need a more durable solution.
+      //  Look into changing JDBCRDD (line 406):
+      //    FROM:  mutableRow.update(i, Decimal(decimalVal, p, s))
+      //    TO:  mutableRow.update(i, Decimal(decimalVal))
+      Some(DecimalType(DecimalType.MAX_PRECISION, 10))
+    } else None
+  }
+}