cloud-fan commented on a change in pull request #25453: [WIP][SPARK-28730][SQL]
Configurable type coercion policy for table insertion
URL: https://github.com/apache/spark/pull/25453#discussion_r315280808
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File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
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@@ -1642,6 +1642,24 @@ object SQLConf {
.checkValues(PartitionOverwriteMode.values.map(_.toString))
.createWithDefault(PartitionOverwriteMode.STATIC.toString)
+ object StoreAssignmentPolicy extends Enumeration {
+ val LEGACY, STRICT = Value
+ }
+
+ val STORE_ASSIGNMENT_POLICY =
+ buildConf("spark.sql.storeAssignmentPolicy")
+ .doc("When inserting a value into a column with different data type,
Spark will perform " +
+ "type coercion. Currently we support 2 policies for the type coercion
rules: legacy and " +
+ "strict. With legacy policy, Spark allows casting any value to any
data type. " +
+ "The legacy policy is the only behavior in Spark 2.x and it is
compatible with Hive. " +
+ "With strict policy, Spark doesn't allow any possible precision loss
or data truncation " +
+ "in type coercion, e.g. `int` and `long`, `float` -> `double` are not
allowed."
Review comment:
e.g. `int` to `long`, `timestamp` to `date` ...
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