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https://issues.apache.org/jira/browse/SPARK-9119?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-9119:
-----------------------------------

    Assignee: Apache Spark  (was: Davies Liu)

> In some cases, we may save wrong decimal values to parquet
> ----------------------------------------------------------
>
>                 Key: SPARK-9119
>                 URL: https://issues.apache.org/jira/browse/SPARK-9119
>             Project: Spark
>          Issue Type: Sub-task
>          Components: SQL
>            Reporter: Yin Huai
>            Assignee: Apache Spark
>            Priority: Blocker
>
> {code}
> > 
> import org.apache.spark.sql.Row
> import 
> org.apache.spark.sql.types.{StructType,StructField,StringType,DecimalType}
> import org.apache.spark.sql.types.Decimal
> ​
> val schema = StructType(Array(StructField("name", DecimalType(10, 5), false)))
> val rowRDD = sc.parallelize(Array(Row(Decimal("67123.45"))))
> val df = sqlContext.createDataFrame(rowRDD, schema)
> df.registerTempTable("test")
> df.show()
> ​
> // +--------+
> // |    name|
> // +--------+
> // |67123.45|
> // +--------+
> sqlContext.sql("create table testDecimal as select * from test")
> sqlContext.table("testDecimal").show()
> // +--------+
> // |    name|
> // +--------+
> // |67.12345|
> // +--------+
> {code}
> The problem is when we do conversions, we do not use precision/scale info in 
> the schema.



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