Damian Momot created SPARK-18484:
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Summary: case class datasets - ability to specify decimal
precision and scale
Key: SPARK-18484
URL: https://issues.apache.org/jira/browse/SPARK-18484
Project: Spark
Issue Type: Improvement
Affects Versions: 2.0.1, 2.0.0
Reporter: Damian Momot
Currently when using decimal type (BigDecimal in scala case class) there's no
way to enforce precision and scale. This is quite critical when saving data -
regarding space usage and compatibility with external systems (for example Hive
table) because spark saves data as Decimal(38,18)
{code:scala}
val spark: SparkSession = ???
case class TestClass(id: String, money: BigDecimal)
val testDs = spark.createDataset(Seq(
TestClass("1", BigDecimal("22.50")),
TestClass("2", BigDecimal("500.66"))
))
testDs.printSchema()
{code}
{code}
root
|-- id: string (nullable = true)
|-- money: decimal(38,18) (nullable = true)
{code}
Workaround is to convert dataset to dataframe before saving and manually cast
to specific decimal scale/precision:
{code:scala}
import org.apache.spark.sql.types.DecimalType
val testDf = testDs.toDF()
testDf
.withColumn("money", testDf("money").cast(DecimalType(10,2)))
.printSchema()
{code}
{code}
root
|-- id: string (nullable = true)
|-- money: decimal(10,2) (nullable = true)
{code}
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