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[SPARK-53553][CONNECT] Fix handling of null values in LiteralValueProtoConverter #52310

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[SPARK-53553][CONNECT] Fix handling of null values in LiteralValueProtoConverter #52310

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[SPARK-53553] Fix handling of null values in LiteralValueProtoConverter
heyihong Sep 11, 2025
5c5f761
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heyihong Sep 12, 2025
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4 changes: 4 additions & 0 deletions sql/connect/client/jvm/src/test/scala/org/apache/spark/sql/PlanGenerationTestSuite.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -3419,8 +3419,12 @@ class PlanGenerationTestSuite
// Handle parameterized scala types e.g.: List, Seq and Map.
fn.typedLit(Some(1)),
fn.typedLit(Array(1, 2, 3)),
fn.typedLit[Array[Integer]](Array(null, null)),
fn.typedLit[Array[(Int, String)]](Array(null, null, (1, "a"), (2, null))),
fn.typedLit[Array[Option[(Int, String)]]](Array(None, None, Some((1, "a")))),
fn.typedLit(Seq(1, 2, 3)),
fn.typedLit(mutable.LinkedHashMap("a" -> 1, "b" -> 2)),
fn.typedLit(mutable.LinkedHashMap[String, Integer]("a" -> null, "b" -> null)),
fn.typedLit(("a", 2, 1.0)),
fn.typedLit[Option[Int]](None),
fn.typedLit[Array[Option[Int]]](Array(Some(1))),
Expand Down
7 changes: 7 additions & 0 deletions sql/connect/client/jvm/src/test/scala/org/apache/spark/sql/connect/ClientE2ETestSuite.scala
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Expand Up @@ -1785,6 +1785,13 @@ class ClientE2ETestSuite
assert(observation.get.contains("map"))
assert(observation.get("map") === Map("count" -> 10))
}

test("SPARK-53553: null value handling in literals") {
val df = spark.sql("select 1").select(typedlit(Array[Integer](1, null)).as("arr_col"))
val result = df.collect()
assert(result.length === 1)
assert(result(0).getAs[Array[Integer]]("arr_col") === Array(1, null))
}
}

private[sql] case class ClassData(a: String, b: Int)
Expand Down
30 changes: 23 additions & 7 deletions ...ommon/src/main/scala/org/apache/spark/sql/connect/common/LiteralValueProtoConverter.scala
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Expand Up @@ -40,6 +40,19 @@ import org.apache.spark.unsafe.types.CalendarInterval

object LiteralValueProtoConverter {

private def setNullValue(
builder: proto.Expression.Literal.Builder,
dataType: DataType,
needDataType: Boolean): proto.Expression.Literal.Builder = {
if (needDataType) {
builder.setNull(toConnectProtoType(dataType))
} else {
// No need data type but still set the null type to indicate that
// the value is null.
builder.setNull(ProtoDataTypes.NullType)
}
}

private def setArrayTypeAfterAddingElements(
ab: proto.Expression.Literal.Array.Builder,
elementType: DataType,
Expand Down Expand Up @@ -275,6 +288,14 @@ object LiteralValueProtoConverter {
}

(literal, dataType) match {
case (v: Option[_], _) =>
if (v.isDefined) {
toLiteralProtoBuilderInternal(v.get, dataType, options, needDataType)
} else {
setNullValue(builder, dataType, needDataType)
}
case (null, _) =>
setNullValue(builder, dataType, needDataType)
case (v: mutable.ArraySeq[_], ArrayType(_, _)) =>
toLiteralProtoBuilderInternal(v.array, dataType, options, needDataType)
case (v: immutable.ArraySeq[_], ArrayType(_, _)) =>
Expand All @@ -287,12 +308,6 @@ object LiteralValueProtoConverter {
builder.setMap(mapBuilder(v, keyType, valueType, valueContainsNull))
case (v, structType: StructType) =>
builder.setStruct(structBuilder(v, structType))
case (v: Option[_], _: DataType) =>
if (v.isDefined) {
toLiteralProtoBuilderInternal(v.get, options, needDataType)
} else {
builder.setNull(toConnectProtoType(dataType))
}
case (v: LocalTime, timeType: TimeType) =>
builder.setTime(
builder.getTimeBuilder
Expand Down Expand Up @@ -477,7 +492,7 @@ object LiteralValueProtoConverter {
}

private def getScalaConverter(dataType: proto.DataType): proto.Expression.Literal => Any = {
dataType.getKindCase match {
val converter: proto.Expression.Literal => Any = dataType.getKindCase match {
case proto.DataType.KindCase.SHORT => v => v.getShort.toShort
case proto.DataType.KindCase.INTEGER => v => v.getInteger
case proto.DataType.KindCase.LONG => v => v.getLong
Expand Down Expand Up @@ -513,6 +528,7 @@ object LiteralValueProtoConverter {
case _ =>
throw InvalidPlanInput(s"Unsupported Literal Type: ${dataType.getKindCase}")
}
v => if (v.hasNull) null else converter(v)
}

private def getInferredDataType(
Expand Down
2 changes: 1 addition & 1 deletion sql/connect/common/src/test/resources/query-tests/explain-results/function_typedLit.explain
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Original file line number Diff line number Diff line change
@@ -1,2 +1,2 @@
Project [id#0L, id#0L, 1 AS 1#0, null AS NULL#0, true AS true#0, 68 AS 68#0, 9872 AS 9872#0, -8726532 AS -8726532#0, 7834609328726532 AS 7834609328726532#0L, 2.718281828459045 AS 2.718281828459045#0, -0.8 AS -0.8#0, 89.97620 AS 89.97620#0, 89889.7667231 AS 89889.7667231#0, connect! AS connect!#0, T AS T#0, ABCDEFGHIJ AS ABCDEFGHIJ#0, 0x78797A7B7C7D7E7F808182838485868788898A8B8C8D8E AS X'78797A7B7C7D7E7F808182838485868788898A8B8C8D8E'#0, 0x0806 AS X'0806'#0, [8,6] AS ARRAY(8, 6)#0, null AS NULL#0, 2020-10-10 AS DATE '2020-10-10'#0, 8.997620 AS 8.997620#0, 2023-02-23 04:31:59.808 AS TIMESTAMP '2023-02-23 04:31:59.808'#0, 1969-12-31 16:00:12.345 AS TIMESTAMP '1969-12-31 16:00:12.345'#0, 2023-02-23 20:36:00 AS TIMESTAMP_NTZ '2023-02-23 20:36:00'#0, 2023-02-23 AS DATE '2023-02-23'#0, INTERVAL '0 00:03:20' DAY TO SECOND AS INTERVAL '0 00:03:20' DAY TO SECOND#0, INTERVAL '0-0' YEAR TO MONTH AS INTERVAL '0-0' YEAR TO MONTH#0, 23:59:59.999999999 AS TIME '23:59:59.999999999'#0, 2 months 20 days 0.0001 seconds AS INTERVAL '2 months 20 days 0.0001 seconds'#0, [18545,1677155519808000,12345000,1677184560000000,19411,200000000,0,86399999999999,2 months 20 days 0.0001 seconds] AS NAMED_STRUCT('_1', DATE '2020-10-10', '_2', TIMESTAMP '2023-02-23 04:31:59.808', '_3', TIMESTAMP '1969-12-31 16:00:12.345', '_4', TIMESTAMP_NTZ '2023-02-23 20:36:00', '_5', DATE '2023-02-23', '_6', INTERVAL '0 00:03:20' DAY TO SECOND, '_7', INTERVAL '0-0' YEAR TO MONTH, '_8', TIME '23:59:59.999999999', '_9', INTERVAL '2 months 20 days 0.0001 seconds')#0, 1 AS 1#0, [1,2,3] AS ARRAY(1, 2, 3)#0, [1,2,3] AS ARRAY(1, 2, 3)#0, map(keys: [a,b], values: [1,2]) AS MAP('a', 1, 'b', 2)#0, [a,2,1.0] AS NAMED_STRUCT('_1', 'a', '_2', 2, '_3', 1.0D)#0, null AS NULL#0, [1] AS ARRAY(1)#0, map(keys: [1], values: [0]) AS MAP(1, 0)#0, map(keys: [1], values: [0]) AS MAP(1, 0)#0, map(keys: [1], values: [0]) AS MAP(1, 0)#0, [[1,2,3],[4,5,6],[7,8,9]] AS ARRAY(ARRAY(1, 2, 3), ARRAY(4, 5, 6), ARRAY(7, 8, 9))#0, [keys: [a,b], values: [1,2],keys: [a,b], values: [3,4],keys: [a,b], values: [5,6]] AS ARRAY(MAP('a', 1, 'b', 2), MAP('a', 3, 'b', 4), MAP('a', 5, 'b', 6))#0, [keys: [a,b], values: [[1,2],[3,4]],keys: [a,b], values: [[5,6],[7,8]],keys: [a,b], values: [[],[]]] AS ARRAY(MAP('a', ARRAY('1', '2'), 'b', ARRAY('3', '4')), MAP('a', ARRAY('5', '6'), 'b', ARRAY('7', '8')), MAP('a', ARRAY(), 'b', ARRAY()))#0, map(keys: [1,2], values: [keys: [a,b], values: [1,2],keys: [a,b], values: [3,4]]) AS MAP(1, MAP('a', 1, 'b', 2), 2, MAP('a', 3, 'b', 4))#0, [[1,2,3],keys: [a,b], values: [1,2],[a,keys: [1,2], values: [a,b]]] AS NAMED_STRUCT('_1', ARRAY(1, 2, 3), '_2', MAP('a', 1, 'b', 2), '_3', NAMED_STRUCT('_1', 'a', '_2', MAP(1, 'a', 2, 'b')))#0]
Project [id#0L, id#0L, 1 AS 1#0, null AS NULL#0, true AS true#0, 68 AS 68#0, 9872 AS 9872#0, -8726532 AS -8726532#0, 7834609328726532 AS 7834609328726532#0L, 2.718281828459045 AS 2.718281828459045#0, -0.8 AS -0.8#0, 89.97620 AS 89.97620#0, 89889.7667231 AS 89889.7667231#0, connect! AS connect!#0, T AS T#0, ABCDEFGHIJ AS ABCDEFGHIJ#0, 0x78797A7B7C7D7E7F808182838485868788898A8B8C8D8E AS X'78797A7B7C7D7E7F808182838485868788898A8B8C8D8E'#0, 0x0806 AS X'0806'#0, [8,6] AS ARRAY(8, 6)#0, null AS NULL#0, 2020-10-10 AS DATE '2020-10-10'#0, 8.997620 AS 8.997620#0, 2023-02-23 04:31:59.808 AS TIMESTAMP '2023-02-23 04:31:59.808'#0, 1969-12-31 16:00:12.345 AS TIMESTAMP '1969-12-31 16:00:12.345'#0, 2023-02-23 20:36:00 AS TIMESTAMP_NTZ '2023-02-23 20:36:00'#0, 2023-02-23 AS DATE '2023-02-23'#0, INTERVAL '0 00:03:20' DAY TO SECOND AS INTERVAL '0 00:03:20' DAY TO SECOND#0, INTERVAL '0-0' YEAR TO MONTH AS INTERVAL '0-0' YEAR TO MONTH#0, 23:59:59.999999999 AS TIME '23:59:59.999999999'#0, 2 months 20 days 0.0001 seconds AS INTERVAL '2 months 20 days 0.0001 seconds'#0, [18545,1677155519808000,12345000,1677184560000000,19411,200000000,0,86399999999999,2 months 20 days 0.0001 seconds] AS NAMED_STRUCT('_1', DATE '2020-10-10', '_2', TIMESTAMP '2023-02-23 04:31:59.808', '_3', TIMESTAMP '1969-12-31 16:00:12.345', '_4', TIMESTAMP_NTZ '2023-02-23 20:36:00', '_5', DATE '2023-02-23', '_6', INTERVAL '0 00:03:20' DAY TO SECOND, '_7', INTERVAL '0-0' YEAR TO MONTH, '_8', TIME '23:59:59.999999999', '_9', INTERVAL '2 months 20 days 0.0001 seconds')#0, 1 AS 1#0, [1,2,3] AS ARRAY(1, 2, 3)#0, [null,null] AS ARRAY(CAST(NULL AS INT), CAST(NULL AS INT))#0, [null,null,[1,a],[2,null]] AS ARRAY(NULL, NULL, NAMED_STRUCT('_1', 1, '_2', 'a'), NAMED_STRUCT('_1', 2, '_2', CAST(NULL AS STRING)))#0, [null,null,[1,a]] AS ARRAY(NULL, NULL, NAMED_STRUCT('_1', 1, '_2', 'a'))#0, [1,2,3] AS ARRAY(1, 2, 3)#0, map(keys: [a,b], values: [1,2]) AS MAP('a', 1, 'b', 2)#0, map(keys: [a,b], values: [null,null]) AS MAP('a', CAST(NULL AS INT), 'b', CAST(NULL AS INT))#0, [a,2,1.0] AS NAMED_STRUCT('_1', 'a', '_2', 2, '_3', 1.0D)#0, null AS NULL#0, [1] AS ARRAY(1)#0, map(keys: [1], values: [null]) AS MAP(1, CAST(NULL AS INT))#0, map(keys: [1], values: [null]) AS MAP(1, CAST(NULL AS INT))#0, map(keys: [1], values: [null]) AS MAP(1, CAST(NULL AS INT))#0, [[1,2,3],[4,5,6],[7,8,9]] AS ARRAY(ARRAY(1, 2, 3), ARRAY(4, 5, 6), ARRAY(7, 8, 9))#0, [keys: [a,b], values: [1,2],keys: [a,b], values: [3,4],keys: [a,b], values: [5,6]] AS ARRAY(MAP('a', 1, 'b', 2), MAP('a', 3, 'b', 4), MAP('a', 5, 'b', 6))#0, [keys: [a,b], values: [[1,2],[3,4]],keys: [a,b], values: [[5,6],[7,8]],keys: [a,b], values: [[],[]]] AS ARRAY(MAP('a', ARRAY('1', '2'), 'b', ARRAY('3', '4')), MAP('a', ARRAY('5', '6'), 'b', ARRAY('7', '8')), MAP('a', ARRAY(), 'b', ARRAY()))#0, map(keys: [1,2], values: [keys: [a,b], values: [1,2],keys: [a,b], values: [3,4]]) AS MAP(1, MAP('a', 1, 'b', 2), 2, MAP('a', 3, 'b', 4))#0, [[1,2,3],keys: [a,b], values: [1,2],[a,keys: [1,2], values: [a,b]]] AS NAMED_STRUCT('_1', ARRAY(1, 2, 3), '_2', MAP('a', 1, 'b', 2), '_3', NAMED_STRUCT('_1', 'a', '_2', MAP(1, 'a', 2, 'b')))#0]
+- LocalRelation <empty>, [id#0L, a#0, b#0]
249 changes: 248 additions & 1 deletion sql/connect/common/src/test/resources/query-tests/queries/function_typedLit.json
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Expand Up @@ -77,7 +77,8 @@
}, {
"literal": {
"null": {
"null": {
"string": {
"collation": "UTF8_BINARY"
}
}
},
Expand Down Expand Up @@ -821,6 +822,206 @@
}
}
}
}, {
"literal": {
"array": {
"elements": [{
"null": {
"integer": {
}
}
}, {
"null": {
"null": {
}
}
}],
"dataType": {
"containsNull": true
}
}
},
"common": {
"origin": {
"jvmOrigin": {
"stackTrace": [{
"classLoaderName": "app",
"declaringClass": "org.apache.spark.sql.functions$",
"methodName": "typedLit",
"fileName": "functions.scala"
}, {
"classLoaderName": "app",
"declaringClass": "org.apache.spark.sql.PlanGenerationTestSuite",
"methodName": "~~trimmed~anonfun~~",
"fileName": "PlanGenerationTestSuite.scala"
}]
}
}
}
}, {
"literal": {
"array": {
"elements": [{
"null": {
"struct": {
"fields": [{
"name": "_1",
"dataType": {
"integer": {
}
}
}, {
"name": "_2",
"dataType": {
"string": {
"collation": "UTF8_BINARY"
}
},
"nullable": true
}]
}
}
}, {
"null": {
"null": {
}
}
}, {
"struct": {
"elements": [{
"integer": 1
}, {
"string": "a"
}],
"dataTypeStruct": {
"fields": [{
"name": "_1"
}, {
"name": "_2",
"dataType": {
"string": {
"collation": "UTF8_BINARY"
}
},
"nullable": true
}]
}
}
}, {
"struct": {
"elements": [{
"integer": 2
}, {
"null": {
"string": {
"collation": "UTF8_BINARY"
}
}
}],
"dataTypeStruct": {
"fields": [{
"name": "_1"
}, {
"name": "_2",
"nullable": true
}]
}
}
}],
"dataType": {
"containsNull": true
}
}
},
"common": {
"origin": {
"jvmOrigin": {
"stackTrace": [{
"classLoaderName": "app",
"declaringClass": "org.apache.spark.sql.functions$",
"methodName": "typedLit",
"fileName": "functions.scala"
}, {
"classLoaderName": "app",
"declaringClass": "org.apache.spark.sql.PlanGenerationTestSuite",
"methodName": "~~trimmed~anonfun~~",
"fileName": "PlanGenerationTestSuite.scala"
}]
}
}
}
}, {
"literal": {
"array": {
"elements": [{
"null": {
"struct": {
"fields": [{
"name": "_1",
"dataType": {
"integer": {
}
}
}, {
"name": "_2",
"dataType": {
"string": {
"collation": "UTF8_BINARY"
}
},
"nullable": true
}]
}
}
}, {
"null": {
"null": {
}
}
}, {
"struct": {
"elements": [{
"integer": 1
}, {
"string": "a"
}],
"dataTypeStruct": {
"fields": [{
"name": "_1"
}, {
"name": "_2",
"dataType": {
"string": {
"collation": "UTF8_BINARY"
}
},
"nullable": true
}]
}
}
}],
"dataType": {
"containsNull": true
}
}
},
"common": {
"origin": {
"jvmOrigin": {
"stackTrace": [{
"classLoaderName": "app",
"declaringClass": "org.apache.spark.sql.functions$",
"methodName": "typedLit",
"fileName": "functions.scala"
}, {
"classLoaderName": "app",
"declaringClass": "org.apache.spark.sql.PlanGenerationTestSuite",
"methodName": "~~trimmed~anonfun~~",
"fileName": "PlanGenerationTestSuite.scala"
}]
}
}
}
}, {
"literal": {
"array": {
Expand Down Expand Up @@ -891,6 +1092,52 @@
}
}
}
}, {
"literal": {
"map": {
"keys": [{
"string": "a"
}, {
"string": "b"
}],
"values": [{
"null": {
"integer": {
}
}
}, {
"null": {
"null": {
}
}
}],
"dataType": {
"keyType": {
"string": {
"collation": "UTF8_BINARY"
}
},
"valueContainsNull": true
}
}
},
"common": {
"origin": {
"jvmOrigin": {
"stackTrace": [{
"classLoaderName": "app",
"declaringClass": "org.apache.spark.sql.functions$",
"methodName": "typedLit",
"fileName": "functions.scala"
}, {
"classLoaderName": "app",
"declaringClass": "org.apache.spark.sql.PlanGenerationTestSuite",
"methodName": "~~trimmed~anonfun~~",
"fileName": "PlanGenerationTestSuite.scala"
}]
}
}
}
}, {
"literal": {
"struct": {
Expand Down
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4 changes: 4 additions & 0 deletions ...est/scala/org/apache/spark/sql/connect/planner/LiteralExpressionProtoConverterSuite.scala
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Expand Up @@ -53,7 +53,11 @@ class LiteralExpressionProtoConverterSuite extends AnyFunSuite { // scalastyle:i
}
}

// The goal of this test is to check that converting a Scala value -> Proto -> Catalyst value
// is equivalent to converting a Scala value directly to a Catalyst value.
Seq[(Any, DataType)](
(Array[String](null, "a", null), ArrayType(StringType)),
(Map[String, String]("a" -> null, "b" -> null), MapType(StringType, StringType)),
(
(1, "string", true),
StructType(
Expand Down