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[SPARK-21804][SQL] json_tuple returns null values within repeated columns except the first one #19017

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[SPARK-21804][SQL] json_tuple returns null values within repeated columns except the first one #19017

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f04b896
SPARK-21804: json_tuple returns null values within repeated columns e…
jmchung Aug 22, 2017
8a25e92
change functional transformations to while loop
jmchung Aug 23, 2017
ff01e04
change to meaningful name to variable
jmchung Aug 24, 2017
792f350
simplify the codes
jmchung Aug 24, 2017
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16 changes: 14 additions & 2 deletions sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/jsonExpressions.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -436,7 +436,8 @@ case class JsonTuple(children: Seq[Expression])
while (parser.nextToken() != JsonToken.END_OBJECT) {
if (parser.getCurrentToken == JsonToken.FIELD_NAME) {
// check to see if this field is desired in the output
val idx = fieldNames.indexOf(parser.getCurrentName)
val jsonField = parser.getCurrentName
var idx = fieldNames.indexOf(jsonField)
if (idx >= 0) {
// it is, copy the child tree to the correct location in the output row
val output = new ByteArrayOutputStream()
Expand All @@ -447,7 +448,18 @@ case class JsonTuple(children: Seq[Expression])
generator => copyCurrentStructure(generator, parser)
}

row(idx) = UTF8String.fromBytes(output.toByteArray)
val jsonValue = UTF8String.fromBytes(output.toByteArray)
row(idx) = jsonValue
idx = idx + 1

// SPARK-21804: json_tuple returns null values within repeated columns
// except the first one; so that we need to check the remaining fields.
while (idx < fieldNames.length) {
if (fieldNames(idx) == jsonField) {
row(idx) = jsonValue
}
idx = idx + 1
}

@gatorsmile gatorsmile Aug 24, 2017 •
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Could you rewrite it using less lines? A more Scala way?

@viirya viirya Aug 24, 2017 •
edited
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We have followed @HyukjinKwon's suggestion #19017 (review) to avoid functional transformation with a while-loop, since this is a hot path. It makes sense to me.

@gatorsmile gatorsmile Aug 24, 2017

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You still can simplify the codes a lot without functional transformation.

@jmchung jmchung Aug 24, 2017

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If I comment out the L451-452, the repeated fields still have the same jsonValue because fieldNames(idx) == jsonField, but the first comparison is not necessary since idx >= 0 means matched.

Could you please give me some advice?

@HyukjinKwon HyukjinKwon Aug 24, 2017

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Would you maybe have a suggestion? The current status looks fine.

@gatorsmile gatorsmile Aug 24, 2017

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            row(idx) = jsonValue
            idx = idx + 1

            // SPARK-21804: json_tuple returns null values within repeated columns
            // except the first one; so that we need to check the remaining fields.
            while (idx < fieldNames.length) {
              if (fieldNames(idx) == jsonField) {
                row(idx) = jsonValue
              }
              idx = idx + 1
            }

->

            do {
              row(idx) = jsonValue
              idx = fieldNames.indexOf(jsonField, idx + 1)
            } while (idx >= 0)

@gatorsmile gatorsmile Aug 24, 2017

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I am also thinking if we should use a Hash table. However,,, the number of columns is not large. Thus, it might not get a noticeable benefit.

}
}
}
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10 changes: 10 additions & 0 deletions ...alyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/JsonExpressionsSuite.scala
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Expand Up @@ -373,6 +373,16 @@ class JsonExpressionsSuite extends SparkFunSuite with ExpressionEvalHelper {
InternalRow(UTF8String.fromString("1"), null, UTF8String.fromString("2")))
}

test("SPARK-21804: json_tuple returns null values within repeated columns except the first one") {
checkJsonTuple(
JsonTuple(Literal("""{"f1": 1, "f2": 2}""") ::
NonFoldableLiteral("f1") ::
NonFoldableLiteral("cast(NULL AS STRING)") ::
NonFoldableLiteral("f1") ::
Nil),
InternalRow(UTF8String.fromString("1"), null, UTF8String.fromString("1")))
}

val gmtId = Option(DateTimeUtils.TimeZoneGMT.getID)

test("from_json") {
Expand Down