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[SPARK-37646][SQL]Avoid touching Scala reflection APIs in the lit function #34901

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[SPARK-37646][SQL]Avoid touching Scala reflection APIs in the lit function #34901

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c10b577
optimize lit
zsxwing Dec 10, 2021
f288b9f
typedLit -> typedlit in comment
zsxwing Dec 15, 2021
d287a4a
Update sql/core/src/main/scala/org/apache/spark/sql/functions.scala
zsxwing Dec 15, 2021
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15 changes: 14 additions & 1 deletion sql/core/src/main/scala/org/apache/spark/sql/functions.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -113,7 +113,17 @@ object functions {
* @group normal_funcs
* @since 1.3.0
*/
def lit(literal: Any): Column = typedLit(literal)
def lit(literal: Any): Column = literal match {
case c: Column => c
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@srowen srowen Dec 15, 2021

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Can you pass a column as a literal? if so, does it work this way currently?

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@zsxwing zsxwing Dec 15, 2021

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Yep. I just inlined typedlit(literal) and changed Column(Literal.create(literal)) to Column(Literal(literal)). I don't expect there is any behavior difference.

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@srowen srowen Dec 15, 2021

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Oh OK. That just seems odd that it's allowed? a literal that isn't a literal

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@zsxwing zsxwing Dec 15, 2021

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Agree it's odd. I don't know the context either 😄

case s: Symbol => new ColumnName(s.name)
case _ =>
// This is different from `typedlit`. `typedlit` calls `Literal.create` to use
// `ScalaReflection` to get the type of `literal`. However, since we use `Any` in this method,
// `typedLit[Any](literal)` will always fail and fallback to `Literal.apply`. Hence, we can
// just manually call `Literal.apply` to skip the expensive `ScalaReflection` code. This is
// significantly better when there are many threads calling `lit` concurrently.
Column(Literal(literal))
}

/**
* Creates a [[Column]] of literal value.
Expand All @@ -134,6 +144,9 @@ object functions {
* The difference between this function and [[lit]] is that this function
* can handle parameterized scala types e.g.: List, Seq and Map.
*
* @note `typedlit` will call expensive Scala reflection APIs. `lit` is preferred if parameterized
* Scala types are not used.
*
* @group normal_funcs
* @since 3.2.0
*/
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12 changes: 12 additions & 0 deletions sql/core/src/test/scala/org/apache/spark/sql/ColumnExpressionSuite.scala
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Expand Up @@ -932,7 +932,19 @@ class ColumnExpressionSuite extends QueryTest with SharedSparkSession {
testData2.collect().toSeq.map(r => Row(r.getInt(0) ^ r.getInt(1) ^ 39)))
}

test("SPARK-37646: lit") {
assert(lit($"foo") == $"foo")
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@zsxwing zsxwing Dec 14, 2021

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I don't find any unit tests like this. So just add simple tests to cover 3 cases in the code.

assert(lit('foo) == $"foo")
assert(lit(1) == Column(Literal(1)))
assert(lit(null) == Column(Literal(null, NullType)))
}

test("typedLit") {
assert(typedLit($"foo") == $"foo")
assert(typedLit('foo) == $"foo")
assert(typedLit(1) == Column(Literal(1)))
assert(typedLit[String](null) == Column(Literal(null, StringType)))
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@zsxwing zsxwing Dec 14, 2021

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I was trying to switch the order in Literal.create like this

  def create[T : TypeTag](v: T): Literal = 
 Try {
    Literal(v)
 }.getOrElse {
       Try {
          val ScalaReflection.Schema(dataType, _) = ScalaReflection.schemaFor[T]
          val convert = CatalystTypeConverters.createToCatalystConverter(dataType)
          Literal(convert(v), dataType)
        }.getOrElse {
          Literal(v)
        }
  }

and then realized this would break this use case. So just added this test to ensure we won't make such change in future.


val df = Seq(Tuple1(0)).toDF("a")
// Only check the types `lit` cannot handle
checkAnswer(
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