[SPARK-34856][SQL] ANSI mode: Allow casting complex types as string type #31954
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -686,6 +686,117 @@ abstract class CastSuiteBase extends SparkFunSuite with ExpressionEvalHelper { | |
| checkEvaluation(cast(value, DoubleType), Double.NaN) | ||
| } | ||
| } | ||
|
|
||
| test("SPARK-22825 Cast array to string") { | ||
| val ret1 = cast(Literal.create(Array(1, 2, 3, 4, 5)), StringType) | ||
| checkEvaluation(ret1, "[1, 2, 3, 4, 5]") | ||
| val ret2 = cast(Literal.create(Array("ab", "cde", "f")), StringType) | ||
| checkEvaluation(ret2, "[ab, cde, f]") | ||
| Seq(false, true).foreach { omitNull => | ||
| withSQLConf(SQLConf.LEGACY_COMPLEX_TYPES_TO_STRING.key -> omitNull.toString) { | ||
| val ret3 = cast(Literal.create(Array("ab", null, "c")), StringType) | ||
| checkEvaluation(ret3, s"[ab,${if (omitNull) "" else " null"}, c]") | ||
| } | ||
| } | ||
| val ret4 = | ||
| cast(Literal.create(Array("ab".getBytes, "cde".getBytes, "f".getBytes)), StringType) | ||
| checkEvaluation(ret4, "[ab, cde, f]") | ||
| val ret5 = cast( | ||
| Literal.create(Array("2014-12-03", "2014-12-04", "2014-12-06").map(Date.valueOf)), | ||
| StringType) | ||
| checkEvaluation(ret5, "[2014-12-03, 2014-12-04, 2014-12-06]") | ||
| val ret6 = cast( | ||
| Literal.create(Array("2014-12-03 13:01:00", "2014-12-04 15:05:00") | ||
| .map(Timestamp.valueOf)), | ||
| StringType) | ||
| checkEvaluation(ret6, "[2014-12-03 13:01:00, 2014-12-04 15:05:00]") | ||
| val ret7 = cast(Literal.create(Array(Array(1, 2, 3), Array(4, 5))), StringType) | ||
| checkEvaluation(ret7, "[[1, 2, 3], [4, 5]]") | ||
| val ret8 = cast( | ||
| Literal.create(Array(Array(Array("a"), Array("b", "c")), Array(Array("d")))), | ||
| StringType) | ||
| checkEvaluation(ret8, "[[[a], [b, c]], [[d]]]") | ||
| } | ||
|
|
||
| test("SPARK-33291: Cast array with null elements to string") { | ||
| Seq(false, true).foreach { omitNull => | ||
| withSQLConf(SQLConf.LEGACY_COMPLEX_TYPES_TO_STRING.key -> omitNull.toString) { | ||
| val ret1 = cast(Literal.create(Array(null, null)), StringType) | ||
| checkEvaluation( | ||
| ret1, | ||
| s"[${if (omitNull) "" else "null"},${if (omitNull) "" else " null"}]") | ||
| } | ||
| } | ||
| } | ||
|
|
||
| test("SPARK-22973 Cast map to string") { | ||
| Seq( | ||
| false -> ("{", "}"), | ||
| true -> ("[", "]")).foreach { case (legacyCast, (lb, rb)) => | ||
| withSQLConf(SQLConf.LEGACY_COMPLEX_TYPES_TO_STRING.key -> legacyCast.toString) { | ||
| val ret1 = cast(Literal.create(Map(1 -> "a", 2 -> "b", 3 -> "c")), StringType) | ||
| checkEvaluation(ret1, s"${lb}1 -> a, 2 -> b, 3 -> c$rb") | ||
| val ret2 = cast( | ||
| Literal.create(Map("1" -> "a".getBytes, "2" -> null, "3" -> "c".getBytes)), | ||
| StringType) | ||
| checkEvaluation(ret2, s"${lb}1 -> a, 2 ->${if (legacyCast) "" else " null"}, 3 -> c$rb") | ||
| val ret3 = cast( | ||
| Literal.create(Map( | ||
| 1 -> Date.valueOf("2014-12-03"), | ||
| 2 -> Date.valueOf("2014-12-04"), | ||
| 3 -> Date.valueOf("2014-12-05"))), | ||
| StringType) | ||
| checkEvaluation(ret3, s"${lb}1 -> 2014-12-03, 2 -> 2014-12-04, 3 -> 2014-12-05$rb") | ||
| val ret4 = cast( | ||
| Literal.create(Map( | ||
| 1 -> Timestamp.valueOf("2014-12-03 13:01:00"), | ||
| 2 -> Timestamp.valueOf("2014-12-04 15:05:00"))), | ||
| StringType) | ||
| checkEvaluation(ret4, s"${lb}1 -> 2014-12-03 13:01:00, 2 -> 2014-12-04 15:05:00$rb") | ||
| val ret5 = cast( | ||
| Literal.create(Map( | ||
| 1 -> Array(1, 2, 3), | ||
| 2 -> Array(4, 5, 6))), | ||
| StringType) | ||
| checkEvaluation(ret5, s"${lb}1 -> [1, 2, 3], 2 -> [4, 5, 6]$rb") | ||
| } | ||
| } | ||
| } | ||
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||
| test("SPARK-22981 Cast struct to string") { | ||
| Seq( | ||
| false -> ("{", "}"), | ||
| true -> ("[", "]")).foreach { case (legacyCast, (lb, rb)) => | ||
| withSQLConf(SQLConf.LEGACY_COMPLEX_TYPES_TO_STRING.key -> legacyCast.toString) { | ||
| val ret1 = cast(Literal.create((1, "a", 0.1)), StringType) | ||
| checkEvaluation(ret1, s"${lb}1, a, 0.1$rb") | ||
| val ret2 = cast(Literal.create(Tuple3[Int, String, String](1, null, "a")), StringType) | ||
| checkEvaluation(ret2, s"${lb}1,${if (legacyCast) "" else " null"}, a$rb") | ||
| val ret3 = cast(Literal.create( | ||
| (Date.valueOf("2014-12-03"), Timestamp.valueOf("2014-12-03 15:05:00"))), StringType) | ||
| checkEvaluation(ret3, s"${lb}2014-12-03, 2014-12-03 15:05:00$rb") | ||
| val ret4 = cast(Literal.create(((1, "a"), 5, 0.1)), StringType) | ||
| checkEvaluation(ret4, s"$lb${lb}1, a$rb, 5, 0.1$rb") | ||
| val ret5 = cast(Literal.create((Seq(1, 2, 3), "a", 0.1)), StringType) | ||
| checkEvaluation(ret5, s"$lb[1, 2, 3], a, 0.1$rb") | ||
| val ret6 = cast(Literal.create((1, Map(1 -> "a", 2 -> "b", 3 -> "c"))), StringType) | ||
| checkEvaluation(ret6, s"${lb}1, ${lb}1 -> a, 2 -> b, 3 -> c$rb$rb") | ||
| } | ||
| } | ||
| } | ||
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||
| test("SPARK-33291: Cast struct with null elements to string") { | ||
| Seq( | ||
| false -> ("{", "}"), | ||
| true -> ("[", "]")).foreach { case (legacyCast, (lb, rb)) => | ||
| withSQLConf(SQLConf.LEGACY_COMPLEX_TYPES_TO_STRING.key -> legacyCast.toString) { | ||
| val ret1 = cast(Literal.create(Tuple2[String, String](null, null)), StringType) | ||
| checkEvaluation( | ||
| ret1, | ||
| s"$lb${if (legacyCast) "" else "null"},${if (legacyCast) "" else " null"}$rb") | ||
| } | ||
| } | ||
| } | ||
| } | ||
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| abstract class AnsiCastSuiteBase extends CastSuiteBase { | ||
|
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@@ -851,12 +962,6 @@ abstract class AnsiCastSuiteBase extends CastSuiteBase { | |
| assert(cast(booleanLiteral, DateType).checkInputDataTypes().isFailure) | ||
| } | ||
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| test("cast from invalid string to numeric should throw NumberFormatException") { | ||
| // cast to IntegerType | ||
| Seq(IntegerType, ShortType, ByteType, LongType).foreach { dataType => | ||
|
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@@ -1569,117 +1674,6 @@ class CastSuite extends CastSuiteBase { | |
| checkEvaluation(cast("abcd", DecimalType(38, 1)), null) | ||
| } | ||
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| test("data type casting II") { | ||
| checkEvaluation( | ||
| cast(cast(cast(cast(cast(cast("5", ByteType), TimestampType), | ||
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Does this affect the coming year-month and day-time interval?
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Yes
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@cloud-fan . Usually, we do the explicitly allowed-list approach in case of types. Is this change okay?
If this PR aims for
complex typeonly, why don't we add them explicitly instead of doing this widely.There was a problem hiding this comment.
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Also, cc @MaxGekk
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df.showneeds to cast the column to string, I think we need to support casting from all the data types here, otherwisedf.showmay still be broken under some cases.There was a problem hiding this comment.
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So far, we don't support such casting. I opened the JIRAs for that: SPARK-34667 and SPARK-34668