dongjoon-hyun commented on a change in pull request #31319:
URL: https://github.com/apache/spark/pull/31319#discussion_r564267501
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File path: sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
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@@ -3868,6 +3868,43 @@ class SQLQuerySuite extends QueryTest with
SharedSparkSession with AdaptiveSpark
assert(unions.size == 1)
}
+
+ test("SPARK-34212 Parquet should read decimals correctly") {
+ // Decimal(2, 1) for INT32-backed decimal, Decimal(17, 2) for INT64-backed
decimal
+ val df = sql("SELECT 1.0 a, CAST(100 AS DECIMAL(17, 2)) b, map(1, 2) c")
+
+ withTempPath { path =>
+ df.write.parquet(path.toString)
+
+ // 1. Complex schema disables vectorization automatically.
Review comment:
Yep. I agree with you, @cloud-fan . Initially, this test case is
designed to demonstrate that why some customers don't need to turn off the
Spark's default configuration (enableVector...) in their environment. It's a
leftover. Since the review is finished, I'll remove this ASAP.
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