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[SPARK-29187][SQL] Return null from date_part() for the null field #25865

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MaxGekk wants to merge 3 commits into from
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[SPARK-29187][SQL] Return null from date_part() for the null field #25865

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78c6c13
Handle null field
MaxGekk Sep 20, 2019
b111cf2
Handle null field
MaxGekk Sep 20, 2019
b39adaa
Add a test to date_part.sql
MaxGekk Sep 20, 2019
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13 changes: 9 additions & 4 deletions ...talyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/datetimeExpressions.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -2053,10 +2053,15 @@ case class DatePart(field: Expression, source: Expression, child: Expression)
if (!field.foldable) {
throw new AnalysisException("The field parameter needs to be a foldable string value.")
}
val fieldStr = field.eval().asInstanceOf[UTF8String].toString
DatePart.parseExtractField(fieldStr, source, {
throw new AnalysisException(s"Literals of type '$fieldStr' are currently not supported.")
})
val fieldEval = field.eval()
if (fieldEval == null) {
Literal(null, DoubleType)
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@adrian-wang adrian-wang Sep 20, 2019

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DoubleType ?

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@MaxGekk MaxGekk Sep 20, 2019

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See the example in the description. PostgreSQL returns NULL of the double precision type which is equivalent of DOUBLE type in Spark SQL. Which type would you use here?

} else {
val fieldStr = fieldEval.asInstanceOf[UTF8String].toString
DatePart.parseExtractField(fieldStr, source, {
throw new AnalysisException(s"Literals of type '$fieldStr' are currently not supported.")
})
}
})
}

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2 changes: 2 additions & 0 deletions sql/core/src/test/resources/sql-tests/inputs/date_part.sql
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Expand Up @@ -66,3 +66,5 @@ select date_part('secs', c) from t;
select date_part('not_supported', c) from t;

select date_part(c, c) from t;

select date_part(null, c) from t;
10 changes: 9 additions & 1 deletion sql/core/src/test/resources/sql-tests/results/date_part.sql.out
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@@ -1,5 +1,5 @@
-- Automatically generated by SQLQueryTestSuite
-- Number of queries: 51
-- Number of queries: 52


-- !query 0
Expand Down Expand Up @@ -410,3 +410,11 @@ struct<>
-- !query 50 output
org.apache.spark.sql.AnalysisException
The field parameter needs to be a foldable string value.;; line 1 pos 7


-- !query 51
select date_part(null, c) from t
-- !query 51 schema
struct<date_part(NULL, t.`c`):double>
-- !query 51 output
NULL
10 changes: 10 additions & 0 deletions sql/core/src/test/scala/org/apache/spark/sql/DateFunctionsSuite.scala
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Expand Up @@ -27,6 +27,7 @@ import org.apache.spark.sql.catalyst.util.DateTimeUtils
import org.apache.spark.sql.functions._
import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.test.SharedSparkSession
import org.apache.spark.sql.types.{DoubleType, StructField, StructType}
import org.apache.spark.unsafe.types.CalendarInterval

class DateFunctionsSuite extends QueryTest with SharedSparkSession {
Expand Down Expand Up @@ -796,4 +797,13 @@ class DateFunctionsSuite extends QueryTest with SharedSparkSession {
Seq(Row(Instant.parse(timestamp))))
}
}

test("handling null field by date_part") {
val input = Seq(Date.valueOf("2019-09-20")).toDF("d")
Seq("date_part(null, d)", "date_part(null, date'2019-09-20')").foreach { expr =>
val df = input.selectExpr(expr)
assert(df.schema.headOption.get.dataType == DoubleType)
checkAnswer(df, Row(null))
}
}
}