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From "Hyukjin Kwon (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-23448) Dataframe returns wrong result when column don't respect datatype
Date Wed, 28 Feb 2018 02:02:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-23448?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Hyukjin Kwon reassigned SPARK-23448:
------------------------------------

    Assignee: Liang-Chi Hsieh

> Dataframe returns wrong result when column don't respect datatype
> -----------------------------------------------------------------
>
>                 Key: SPARK-23448
>                 URL: https://issues.apache.org/jira/browse/SPARK-23448
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.0.2
>         Environment: Local
>            Reporter: Ahmed ZAROUI
>            Assignee: Liang-Chi Hsieh
>            Priority: Major
>             Fix For: 2.3.1
>
>
> I have the following json file that contains some noisy data(String instead of Array):
>  
> {code:java}
> {"attr1":"val1","attr2":"[\"val2\"]"}
> {"attr1":"val1","attr2":["val2"]}
> {code}
> And i need to specify schema programatically like this:
>  
> {code:java}
> implicit val spark = SparkSession
>   .builder()
>   .master("local[*]")
>   .config("spark.ui.enabled", false)
>   .config("spark.sql.caseSensitive", "True")
>   .getOrCreate()
> import spark.implicits._
> val schema = StructType(
>   Seq(StructField("attr1", StringType, true),
>       StructField("attr2", ArrayType(StringType, true), true)))
> spark.read.schema(schema).json(input).collect().foreach(println)
> {code}
> The result given by this code is:
> {code:java}
> [null,null]
> [val1,WrappedArray(val2)]
> {code}
> Instead of putting null in corrupted column, all columns of the first message are null
>  
>  



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