[jira] [Commented] (SPARK-28043) Reading json with duplicate columns drops the first column value

["Liang-Chi Hsieh (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-28043?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16863680#comment-16863680 ] 

Liang-Chi Hsieh commented on SPARK-28043:
-----------------------------------------

I tried to look around that, like https://stackoverflow.com/questions/21832701/does-json-syntax-allow-duplicate-keys-in-an-object.

So JSON doesn't disallow duplicate keys. Spark SQL doesn't disallow duplicate field names, although it can be impose some difficulties when using a DataFrame with duplicate field names. To clarify it, just because Spark SQL allows duplicate field names that doesn't mean that we should use such feature. But I think that, to some extent, the current behavior isn't consistent.

{code}
scala> val jsonRDD = spark.sparkContext.parallelize(Seq("[{ \"a\": \"blah\", \"a\": \"blah2\"} ]"))
jsonRDD: org.apache.spark.rdd.RDD[String] = ParallelCollectionRDD[1] at parallelize at <console>:23
scala> val df = spark.read.json(jsonRDD)
df: org.apache.spark.sql.DataFrame = [a: string, a: string]                     
scala> df.show
+----+-----+
|   a|    a|
+----+-----+
|null|blah2|
+----+-----+
{code}

> Reading json with duplicate columns drops the first column value
> ----------------------------------------------------------------
>
>                 Key: SPARK-28043
>                 URL: https://issues.apache.org/jira/browse/SPARK-28043
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 2.4.0
>            Reporter: Mukul Murthy
>            Priority: Major
>
> When reading a JSON blob with duplicate fields, Spark appears to ignore the value of the first one. JSON recommends unique names but does not require it; since JSON and Spark SQL both allow duplicate field names, we should fix the bug where the first column value is getting dropped.
>  
> I'm guessing somewhere when parsing JSON, we're turning it into a Map which is causing the first value to be overridden.
>  
> Repro (Python, 2.4):
> >>> jsonRDD = spark.sparkContext.parallelize(["\\{ \"a\": \"blah\", \"a\": \"blah2\"}"])
>  >>> df = spark.read.json(jsonRDD)
>  >>> df.show()
>  +-----+----+
> |a|a|
> +-----+----+
> |null|blah2|
> +-----+----+
>  
> The expected response would be:
> +-----+----+
> |a|a|
> +-----+----+
> |blah|blah2|
> +-----+----+



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