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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2017/05/13 07:28:04 UTC
[jira] [Updated] (SPARK-18772) Unnecessary conversion try for
special floats in JSON
[ https://issues.apache.org/jira/browse/SPARK-18772?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon updated SPARK-18772:
---------------------------------
Affects Version/s: 2.2.0
Description:
It looks we can avoid some cases for unnecessary conversion try in special floats in JSON.
{code}
scala> import org.apache.spark.sql.types._
import org.apache.spark.sql.types._
scala> spark.read.schema(StructType(Seq(StructField("a", DoubleType)))).option("mode", "FAILFAST").json(Seq("""{"a": "nan"}""").toDS).show()
17/05/12 11:30:41 ERROR Executor: Exception in task 0.0 in stage 2.0 (TID 2)
java.lang.NumberFormatException: For input string: "nan"
...
{code}
was:
It looks we can avoid some cases for unnecessary conversion try in special floats in JSON.
Also, we could support some other cases for them such as {{+INF}}, {{INF}} and {{-INF}}.
For avoiding additional conversions, please refer the codes below:
{code}
scala> import org.apache.spark.sql.types._
import org.apache.spark.sql.types._
scala> spark.read.schema(StructType(Seq(StructField("a", DoubleType)))).option("mode", "FAILFAST").json(Seq("""{"a": "nan"}""").toDS).show()
17/05/12 11:30:41 ERROR Executor: Exception in task 0.0 in stage 2.0 (TID 2)
java.lang.NumberFormatException: For input string: "nan"
...
{code}
Summary: Unnecessary conversion try for special floats in JSON (was: Unnecessary conversion try and some missing cases for special floats in JSON)
> Unnecessary conversion try for special floats in JSON
> -----------------------------------------------------
>
> Key: SPARK-18772
> URL: https://issues.apache.org/jira/browse/SPARK-18772
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.2, 2.2.0
> Reporter: Nathan Howell
> Priority: Minor
>
> It looks we can avoid some cases for unnecessary conversion try in special floats in JSON.
> {code}
> scala> import org.apache.spark.sql.types._
> import org.apache.spark.sql.types._
> scala> spark.read.schema(StructType(Seq(StructField("a", DoubleType)))).option("mode", "FAILFAST").json(Seq("""{"a": "nan"}""").toDS).show()
> 17/05/12 11:30:41 ERROR Executor: Exception in task 0.0 in stage 2.0 (TID 2)
> java.lang.NumberFormatException: For input string: "nan"
> ...
> {code}
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