[jira] [Resolved] (SPARK-8359) Spark SQL Decimal type precision loss on multiplication

2015-08-05 Thread Davies Liu (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-8359?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Davies Liu resolved SPARK-8359.
---
   Resolution: Fixed
Fix Version/s: 1.5.0

Issue resolved by pull request 7925
[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
 Fix For: 1.5.0


 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..



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[jira] [Resolved] (SPARK-8359) Spark SQL Decimal type precision loss on multiplication

2015-06-23 Thread Davies Liu (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-8359?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Davies Liu resolved SPARK-8359.
---
   Resolution: Fixed
Fix Version/s: 1.5.0

Issue resolved by pull request 6814
[https://github.com/apache/spark/pull/6814]

 Spark SQL Decimal type precision loss on multiplication
 ---

 Key: SPARK-8359
 URL: https://issues.apache.org/jira/browse/SPARK-8359
 Project: Spark
  Issue Type: Bug
  Components: SQL
Affects Versions: 1.5.0
Reporter: Rene Treffer
 Fix For: 1.5.0


 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..



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