cloud-fan commented on a change in pull request #31319:
URL: https://github.com/apache/spark/pull/31319#discussion_r564227086
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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:
Since we have case 2, why do we test case 1? To prove that complex
schema disables vectorization? That's kind of something we already tested well
and we don't need to repeat it here.
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