[jira] [Commented] (SPARK-40678) JSON conversion of ArrayType is not properly supported in Spark 3.2/2.13

["Cédric Chantepie (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-40678?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17613529#comment-17613529 ] 

Cédric Chantepie commented on SPARK-40678:
------------------------------------------

In Scala 2.13, the pattern `Seq[_]` doesn't match `scala.collection.immutable.Seq` .

```
...
      case (s: Seq[_], ArrayType(elementType, _)) =>
        iteratorToJsonArray(s.iterator, elementType)
      case (m: Map[String @unchecked, _], MapType(StringType, valueType, _)) =>
        new JObject(m.toList.sortBy(_._1).map {
          case (k, v) => k -> toJson(v, valueType)
        })
      case (m: Map[_, _], MapType(keyType, valueType, _)) =>
        new JArray(m.iterator.map {
          case (k, v) =>
            new JObject("key" -> toJson(k, keyType) :: "value" -> toJson(v, valueType) :: Nil)
        }.toList)
      case (r: Row, _) => r.jsonValue
      case (v: Any, udt: UserDefinedType[Any @unchecked]) =>
        val dataType = udt.sqlType
        toJson(CatalystTypeConverters.convertToScala(udt.serialize(v), dataType), dataType)
      case _ =>
        throw new IllegalArgumentException(s"Failed to convert value $value " +
          s"(class of ${value.getClass}}) with the type of $dataType to JSON.")
...
```

> JSON conversion of ArrayType is not properly supported in Spark 3.2/2.13
> ------------------------------------------------------------------------
>
>                 Key: SPARK-40678
>                 URL: https://issues.apache.org/jira/browse/SPARK-40678
>             Project: Spark
>          Issue Type: Bug
>          Components: Input/Output
>    Affects Versions: 3.2.0
>            Reporter: Cédric Chantepie
>            Priority: Major
>
> In Spark 3.2 (Scala 2.13), values with {{ArrayType}} are no longer properly support with JSON; e.g.
> {noformat}
> import org.apache.spark.sql.SparkSession
> case class KeyValue(key: String, value: Array[Byte])
> val spark = SparkSession.builder().master("local[1]").appName("test").getOrCreate()
> import spark.implicits._
> val df = Seq(Array(KeyValue("foo", "bar".getBytes))).toDF()
> df.foreach(r => println(r.json))
> {noformat}
> Expected:
> {noformat}
> [{foo, bar}]
> {noformat}
> Encountered:
> {noformat}
> java.lang.IllegalArgumentException: Failed to convert value ArraySeq([foo,[B@dcdb68f]) (class of class scala.collection.mutable.ArraySeq$ofRef}) with the type of ArrayType(Seq(StructField(key,StringType,false), StructField(value,BinaryType,false)),true) to JSON.
> 	at org.apache.spark.sql.Row.toJson$1(Row.scala:604)
> 	at org.apache.spark.sql.Row.jsonValue(Row.scala:613)
> 	at org.apache.spark.sql.Row.jsonValue$(Row.scala:552)
> 	at org.apache.spark.sql.catalyst.expressions.GenericRow.jsonValue(rows.scala:166)
> 	at org.apache.spark.sql.Row.json(Row.scala:535)
> 	at org.apache.spark.sql.Row.json$(Row.scala:535)
> 	at org.apache.spark.sql.catalyst.expressions.GenericRow.json(rows.scala:166)
> {noformat}



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