[jira] [Created] (SPARK-18484) case class datasets - ability to specify decimal precision and scale

["Damian Momot (JIRA)" <ji...@apache.org>]

Damian Momot created SPARK-18484:
------------------------------------

             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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