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Apache Spark commented on SPARK-8359: ------------------------------------- User 'davies' has created a pull request for this issue: https://github.com/apache/spark/pull/7925 > Spark SQL Decimal type precision loss on multiplication > ------------------------------------------------------- > > Key: SPARK-8359 > URL: https://issues.apache.org/jira/browse/SPARK-8359 > Project: Spark > Issue Type: Sub-task > Components: SQL > Affects Versions: 1.5.0 > Reporter: Rene Treffer > Assignee: Davies Liu > > It looks like the precision of decimal can not be raised beyond ~2^112 > without causing full value truncation. > The following code computes the power of two up to a specific point > {code} > import org.apache.spark.sql.types.Decimal > val one = Decimal(1) > val two = Decimal(2) > def pow(n : Int) : Decimal = if (n <= 0) { one } else { > val a = pow(n - 1) > a.changePrecision(n,0) > two.changePrecision(n,0) > a * two > } > (109 to 120).foreach(n => > println(pow(n).toJavaBigDecimal.unscaledValue.toString)) > 649037107316853453566312041152512 > 1298074214633706907132624082305024 > 2596148429267413814265248164610048 > 5192296858534827628530496329220096 > 1038459371706965525706099265844019 > 2076918743413931051412198531688038 > 4153837486827862102824397063376076 > 8307674973655724205648794126752152 > 1661534994731144841129758825350430 > 3323069989462289682259517650700860 > 6646139978924579364519035301401720 > 1329227995784915872903807060280344 > {code} > Beyond ~2^112 the precision is truncated even if the precision was set to n > and should thus handle 10^n without problems.. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org