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https://issues.apache.org/jira/browse/SPARK-9119?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14630340#comment-14630340
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Yin Huai commented on SPARK-9119:
---------------------------------
The current workaround is to explicitly specify the precision and scale when
create the decimal value.
{code}
import org.apache.spark.sql.Row
import
org.apache.spark.sql.types.{StructType,StructField,StringType,DecimalType}
import org.apache.spark.sql.types.Decimal
import java.math.BigDecimal
val schema = StructType(Array(StructField("name", DecimalType(10, 5), false)))
val rowRDD = sc.parallelize(Array(Row(Decimal(new BigDecimal("67123.45"), 10,
5))))
val df = sqlContext.createDataFrame(rowRDD, schema)
df.registerTempTable("test")
df.show()
// +-----------+
// | name|
// +-----------+
// |67123.45000|
// +-----------+
sqlContext.sql("create table testDecimal as select * from test")
sqlContext.table("testDecimal").show()
// +-----------+
// | name|
// +-----------+
// |67123.45000|
// +-----------+
{code}
> 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
> Priority: Critical
>
> {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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