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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2016/03/28 07:11:25 UTC
[jira] [Updated] (SPARK-14189) JSON data source infers a field type
as StringType when some are inferred as DecimalType not capable of
IntegralType.
[ https://issues.apache.org/jira/browse/SPARK-14189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon updated SPARK-14189:
---------------------------------
Description:
When inferred types in the same field during finding competible {{DataType}} are {{IntegralType}} and {{DecimalType}} but {{DecimalType}} is not capable of the given {{IntegralType}}, JSON data source simply parses this as {{StringType}}.
This can be observed when {{floatAsBigDecimal}} is enabled.
{code}
def mixedIntegerAndDoubleRecords: RDD[String] =
sqlContext.sparkContext.parallelize(
"""{"a": 3, "b": 1.1}""" ::
"""{"a": 3.1, "b": 1}""" :: Nil)
val jsonDF = sqlContext.read
.option("floatAsBigDecimal", "true")
.json(mixedIntegerAndDoubleRecords)
.printSchema()
{code}
produces below:
{code}
root
|-- a: string (nullable = true)
|-- b: string (nullable = true)
{code}
When {{floatAsBigDecimal}} is disabled.
{code}
def mixedIntegerAndDoubleRecords: RDD[String] =
sqlContext.sparkContext.parallelize(
"""{"a": 3, "b": 1.1}""" ::
"""{"a": 3.1, "b": 1}""" :: Nil)
val jsonDF = sqlContext.read
.option("floatAsBigDecimal", "false")
.json(mixedIntegerAndDoubleRecords)
.printSchema()
{code}
produces below correctly:
{code}
root
|-- a: double (nullable = true)
|-- b: double (nullable = true)
{code}
was:
When inferred types in the same field during finding competible {{DataType}} are {{IntegralType}} and {{DecimalType}} but {{DecimalType}} is not capable of the given {{IntegralType}}, JSON data source simply parse this as {{StringType}}.
This can be observed when {{floatAsBigDecimal}} is enabled.
{code}
def mixedIntegerAndDoubleRecords: RDD[String] =
sqlContext.sparkContext.parallelize(
"""{"a": 3, "b": 1.1}""" ::
"""{"a": 3.1, "b": 1}""" :: Nil)
val jsonDF = sqlContext.read
.option("floatAsBigDecimal", "true")
.json(mixedIntegerAndDoubleRecords)
.printSchema()
{code}
produces below:
{code}
root
|-- a: string (nullable = true)
|-- b: string (nullable = true)
{code}
When {{floatAsBigDecimal}} is disabled.
{code}
def mixedIntegerAndDoubleRecords: RDD[String] =
sqlContext.sparkContext.parallelize(
"""{"a": 3, "b": 1.1}""" ::
"""{"a": 3.1, "b": 1}""" :: Nil)
val jsonDF = sqlContext.read
.option("floatAsBigDecimal", "false")
.json(mixedIntegerAndDoubleRecords)
.printSchema()
{code}
produces below correctly:
{code}
root
|-- a: double (nullable = true)
|-- b: double (nullable = true)
{code}
> JSON data source infers a field type as StringType when some are inferred as DecimalType not capable of IntegralType.
> ---------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-14189
> URL: https://issues.apache.org/jira/browse/SPARK-14189
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.0
> Reporter: Hyukjin Kwon
>
> When inferred types in the same field during finding competible {{DataType}} are {{IntegralType}} and {{DecimalType}} but {{DecimalType}} is not capable of the given {{IntegralType}}, JSON data source simply parses this as {{StringType}}.
> This can be observed when {{floatAsBigDecimal}} is enabled.
> {code}
> def mixedIntegerAndDoubleRecords: RDD[String] =
> sqlContext.sparkContext.parallelize(
> """{"a": 3, "b": 1.1}""" ::
> """{"a": 3.1, "b": 1}""" :: Nil)
> val jsonDF = sqlContext.read
> .option("floatAsBigDecimal", "true")
> .json(mixedIntegerAndDoubleRecords)
> .printSchema()
> {code}
> produces below:
> {code}
> root
> |-- a: string (nullable = true)
> |-- b: string (nullable = true)
> {code}
> When {{floatAsBigDecimal}} is disabled.
> {code}
> def mixedIntegerAndDoubleRecords: RDD[String] =
> sqlContext.sparkContext.parallelize(
> """{"a": 3, "b": 1.1}""" ::
> """{"a": 3.1, "b": 1}""" :: Nil)
> val jsonDF = sqlContext.read
> .option("floatAsBigDecimal", "false")
> .json(mixedIntegerAndDoubleRecords)
> .printSchema()
> {code}
> produces below correctly:
> {code}
> root
> |-- a: double (nullable = true)
> |-- b: double (nullable = true)
> {code}
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