From 821db4854c0e685aac3168da75a1c839681dbfc4 Mon Sep 17 00:00:00 2001 From: Marco Gaido Date: Tue, 4 Dec 2018 10:33:27 -0800 Subject: [PATCH] [SPARK-26233][SQL] CheckOverflow when encoding a decimal value When we encode a Decimal from external source we don't check for overflow. That method is useful not only in order to enforce that we can represent the correct value in the specified range, but it also changes the underlying data to the right precision/scale. Since in our code generation we assume that a decimal has exactly the same precision and scale of its data type, missing to enforce it can lead to corrupted output/results when there are subsequent transformations. added UT Closes #23210 from mgaido91/SPARK-26233. Authored-by: Marco Gaido Signed-off-by: Dongjoon Hyun --- .../apache/spark/sql/catalyst/encoders/RowEncoder.scala | 4 ++-- .../test/scala/org/apache/spark/sql/DatasetSuite.scala | 9 +++++++++ 2 files changed, 11 insertions(+), 2 deletions(-) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/encoders/RowEncoder.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/encoders/RowEncoder.scala index 3340789398f9c..13f72bd3eb87f 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/encoders/RowEncoder.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/encoders/RowEncoder.scala @@ -108,12 +108,12 @@ object RowEncoder { returnNullable = false) case d: DecimalType => - StaticInvoke( + CheckOverflow(StaticInvoke( Decimal.getClass, d, "fromDecimal", inputObject :: Nil, - returnNullable = false) + returnNullable = false), d) case StringType => StaticInvoke( diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala index 4e593ff046a53..f6f51b5cac8e8 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala @@ -1547,6 +1547,15 @@ class DatasetSuite extends QueryTest with SharedSQLContext { df.where($"city".contains(new java.lang.Character('A'))), Seq(Row("Amsterdam"))) } + + test("SPARK-26233: serializer should enforce decimal precision and scale") { + val s = StructType(Seq(StructField("a", StringType), StructField("b", DecimalType(38, 8)))) + val encoder = RowEncoder(s) + implicit val uEnc = encoder + val df = spark.range(2).map(l => Row(l.toString, BigDecimal.valueOf(l + 0.1111))) + checkAnswer(df.groupBy(col("a")).agg(first(col("b"))), + Seq(Row("0", BigDecimal.valueOf(0.1111)), Row("1", BigDecimal.valueOf(1.1111)))) + } } case class TestDataUnion(x: Int, y: Int, z: Int)