Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/5555#discussion_r29816340
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala ---
@@ -0,0 +1,205 @@
+/*
+ * 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.
+ */
+
+package org.apache.spark.sql.jdbc
+
+import org.apache.spark.sql.types._
+import org.apache.spark.annotation.DeveloperApi
+
+import java.sql.Types
+
+
+/**
+ * :: DeveloperApi ::
+ * Encapsulates everything (extensions, workarounds, quirks) to handle the
+ * SQL dialect of a certain database or jdbc driver.
+ * Lots of databases define types that aren't explicitly supported
+ * by the JDBC spec. Some JDBC drivers also report inaccurate
+ * information---for instance, BIT(n>1) being reported as a BIT type is
quite
+ * common, even though BIT in JDBC is meant for single-bit values. Also,
there
+ * does not appear to be a standard name for an unbounded string or binary
+ * type; we use BLOB and CLOB by default but override with
database-specific
+ * alternatives when these are absent or do not behave correctly.
+ *
+ * Currently, the only thing done by the dialect is type mapping.
+ * `getCatalystType` is used when reading from a JDBC table and
`getJDBCType`
+ * is used when writing to a JDBC table. If `getCatalystType` returns
`null`,
+ * the default type handling is used for the given JDBC type. Similarly,
+ * if `getJDBCType` returns `(null, None)`, the default type handling is
used
+ * for the given Catalyst type.
+ */
+@DeveloperApi
+abstract class JdbcDialect {
+ /**
+ * Check if this dialect instance can handle a certain jdbc url.
+ * @param url the jdbc url.
+ * @return True if the dialect can be applied on the given jdbc url.
+ * @throws NullPointerException if the url is null.
+ */
+ def canHandle(url : String): Boolean
+
+ /**
+ * Get the custom datatype mapping for the given jdbc meta information.
+ * @param sqlType The sql type (see java.sql.Types)
+ * @param typeName The sql type name (e.g. "BIGINT UNSIGNED")
+ * @param size The size of the type.
+ * @param md Result metadata associated with this type.
+ * @return The actual DataType (subclasses of
[[org.apache.spark.sql.types.DataType]])
+ * or null if the default type mapping should be used.
+ */
+ def getCatalystType(sqlType: Int, typeName: String, size: Int, md:
MetadataBuilder): DataType =
+ null
+
+ /**
+ * Retrieve the jdbc / sql type for a give datatype.
+ * @param dt The datatype (e.g.
[[org.apache.spark.sql.types.StringType]])
+ * @return A tuple of sql type name and sql type, or {{{(null, None)}}}
for no change.
+ */
+ def getJDBCType(dt: DataType): (String, Option[Int]) = (null, None)
--- End diff --
It seems a little incongruous to mix use of `null` and `None` here and
above. Also, I think it would be good if this was easily used from java as
well. What do you think about creating a case class so that they don't need to
use tuples?
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