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https://issues.apache.org/jira/browse/SPARK-8892?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14633032#comment-14633032
]
Yijie Shen commented on SPARK-8892:
-----------------------------------
The bug was caused by precision lose introduced when converting from Long to
Double:
{code:title=branch-1.4: Cast.scala#castToDecimal}
private[this] def castToDecimal(from: DataType, target: DecimalType): Any =>
Any = from match {
case StringType =>
buildCast[UTF8String](_, s => try {
changePrecision(Decimal(s.toString.toDouble), target)
} catch {
case _: NumberFormatException => null
})
{code}
which was fixed by [SPARK-8052|https://issues.apache.org/jira/browse/SPARK-8052]
{code:title=master: Cast.scala#castToDecimal}
private[this] def castToDecimal(from: DataType, target: DecimalType): Any =>
Any = from match {
case StringType =>
buildCast[UTF8String](_, s => try {
changePrecision(Decimal(new JavaBigDecimal(s.toString)), target)
} catch {
case _: NumberFormatException => null
})
{code}
Therefore, apply [SPARK-8052|https://issues.apache.org/jira/browse/SPARK-8052]
also on branch-1.4 will resolve this bug.
> Column.cast(LongType) does not work for large values
> ----------------------------------------------------
>
> Key: SPARK-8892
> URL: https://issues.apache.org/jira/browse/SPARK-8892
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.4.0
> Reporter: Jason Moore
>
> It seems that casting a column from String to Long seems to go through an
> intermediate step of being cast to a Double (hits Cast.scala line 328 in
> castToDecimal). The result is that for large values, the wrong value is
> returned.
> This test reveals this bug:
> {code:java}
> import org.apache.spark.sql.types._
> import org.apache.spark.sql.{Row, SQLContext}
> import org.apache.spark.{SparkConf, SparkContext}
> import org.scalatest.FlatSpec
> import scala.util.Random
> class DataFrameCastBug extends FlatSpec {
> "DataFrame" should "cast StringType to LongType correctly" in {
> val sc = new SparkContext(new
> SparkConf().setMaster("local").setAppName("app"))
> val qc = new SQLContext(sc)
> val values = Seq.fill(100000)(Random.nextLong)
> val source = qc.createDataFrame(
> sc.parallelize(values.map(v => Row(v))),
> StructType(Seq(StructField("value", LongType))))
> val result = source.select(source("value"),
> source("value").cast(StringType).cast(LongType).as("castValue"))
> assert(result.where(result("value") !== result("castValue")).count() ===
> 0)
> }
> }
> {code}
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