add migration guide

Author: gengliangwang

docs/sql-migration-guide.md

@@ -23,6 +23,7 @@ license: |
 {:toc}
 
 ## Upgrading from Spark SQL 2.4 to 3.0
+  - Since Spark 3.0, when inserting a value into a table column with a different data type, the type coercion is performed as per ANSI SQL standard. Certain unreasonable type conversions such as converting `string` to `int` and `double` to `boolean` are disallowed. A runtime exception will be thrown if the value is out-of-range for the data type of the column. In Spark version 2.4 and earlier, type conversions during table insertion are allowed as long as they are valid `Cast`. When inserting an out-of-range value to a integral field, the low-order bits of the value is inserted(the same as Java/Scala numeric type casting). For example, if 257 is inserted to a field of byte type, the result is 1. The behavior is controlled by the option `spark.sql.storeAssignmentPolicy`, with a default value as "ANSI". Setting the option as "Legacy" restores the previous behavior.
 
   - In Spark 3.0, the deprecated methods `SQLContext.createExternalTable` and `SparkSession.createExternalTable` have been removed in favor of its replacement, `createTable`.