Github user dongjoon-hyun commented on a diff in the pull request:
https://github.com/apache/spark/pull/20208#discussion_r162835707
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/SchemaEvolutionTest.scala
---
@@ -0,0 +1,406 @@
+/*
+ * 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.execution.datasources
+
+import java.io.File
+
+import org.apache.spark.sql.{QueryTest, Row}
+import org.apache.spark.sql.functions._
+import org.apache.spark.sql.test.{SharedSQLContext, SQLTestUtils}
+
+/**
+ * Schema can evolve in several ways and the followings are supported in
file-based data sources.
+ *
+ * 1. Add a column
+ * 2. Remove a column
+ * 3. Change a column position
+ * 4. Change a column type
+ *
+ * Here, we consider safe evolution without data loss. For example, data
type evolution should be
+ * from small types to larger types like `int`-to-`long`, not vice versa.
+ *
+ * So far, file-based data sources have schema evolution coverages like
the followings.
+ *
+ * | File Format | Coverage | Note
|
+ * | ------------ | ------------ |
------------------------------------------------------ |
+ * | TEXT | N/A | Schema consists of a single string
column. |
+ * | CSV | 1, 2, 4 |
|
+ * | JSON | 1, 2, 3, 4 |
|
+ * | ORC | 1, 2, 3, 4 | Native vectorized ORC reader has the
widest coverage. |
+ * | PARQUET | 1, 2, 3 |
|
--- End diff --
Correct, and this is not about schema merging.
The final correct schema is given by users (or Hive).
In this PR, all schema is given by users, but for Hive table, we uses the
Hive Metastore Schema.
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