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[SPARK-24574][SQL] array_contains, array_position, array_remove and element_at functions deal with Column type #21581

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[SPARK-24574][SQL] array_contains, array_position, array_remove and element_at functions deal with Column type #21581

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27733f9
array_contains function deals with Column type for the second parameter.
Jun 17, 2018
28aa515
add unit test for Column type
Jun 17, 2018
e65611e
array_position deals with Column Type
Jun 18, 2018
b6e150c
array_remove function deals with Column Type
Jun 18, 2018
eabdb6e
element_at function deals with Column Type
Jun 18, 2018
8440d5b
reset doc for array_contains function
Jun 18, 2018
f8c5b43
use lit() and add unit tests
Jun 20, 2018
ddd94f7
use lit() to unify the cases
Jun 20, 2018
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20 changes: 16 additions & 4 deletions 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 @@ -3082,7 +3082,10 @@ object functions {
* @since 1.5.0
*/
def array_contains(column: Column, value: Any): Column = withExpr {
ArrayContains(column.expr, Literal(value))
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Other similar expressions are ArrayPosition, ElementAt, ArrayRemove.

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Oh, I just found @maropu has pointed it out in #21581 (comment).

value match {
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On second thoughts, we should use lit(), e.g., ArrayContains(column.expr, lit(value).expr)? WDYT? @viirya @maropu @HyukjinKwon

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Yup, that's what I was thinking too from my glance.

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Yes, I think so.

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+1

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@chongguang I mean, use just ArrayContains(column.expr, lit(value).expr) instead of value match { .... The lit() should handle literals and columns well.

case c: Column => ArrayContains(column.expr, c.expr)
case _ => ArrayContains(column.expr, Literal(value))
}
}

/**
Expand Down Expand Up @@ -3146,7 +3149,10 @@ object functions {
* @since 2.4.0
*/
def array_position(column: Column, value: Any): Column = withExpr {
ArrayPosition(column.expr, Literal(value))
value match {
case c: Column => ArrayPosition(column.expr, c.expr)
case _ => ArrayPosition(column.expr, Literal(value))
}
}

/**
Expand All @@ -3157,7 +3163,10 @@ object functions {
* @since 2.4.0
*/
def element_at(column: Column, value: Any): Column = withExpr {
ElementAt(column.expr, Literal(value))
value match {
case c: Column => ElementAt(column.expr, c.expr)
case _ => ElementAt(column.expr, Literal(value))
}
}

/**
Expand All @@ -3175,7 +3184,10 @@ object functions {
* @since 2.4.0
*/
def array_remove(column: Column, element: Any): Column = withExpr {
ArrayRemove(column.expr, Literal(element))
element match {
case c: Column => ArrayRemove(column.expr, c.expr)
case _ => ArrayRemove(column.expr, Literal(element))
}
}

/**
Expand Down
49 changes: 34 additions & 15 deletions sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala
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Expand Up @@ -558,9 +558,9 @@ class DataFrameFunctionsSuite extends QueryTest with SharedSQLContext {

test("array contains function") {
val df = Seq(
(Seq[Int](1, 2), "x"),
(Seq[Int](), "x")
).toDF("a", "b")
(Seq[Int](1, 2), "x", 1),
(Seq[Int](), "x", 1)
).toDF("a", "b", "c")

// Simple test cases
checkAnswer(
Expand All @@ -571,6 +571,10 @@ class DataFrameFunctionsSuite extends QueryTest with SharedSQLContext {
df.selectExpr("array_contains(a, 1)"),
Seq(Row(true), Row(false))
)
checkAnswer(
df.select(array_contains(df("a"), df("c"))),
Seq(Row(true), Row(false))
)
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Can you add another test to use selectExpr, e.g., df.selectExpr("array_contains(a, c)")?


// In hive, this errors because null has no type information
intercept[AnalysisException] {
Expand Down Expand Up @@ -785,9 +789,9 @@ class DataFrameFunctionsSuite extends QueryTest with SharedSQLContext {

test("array position function") {
val df = Seq(
(Seq[Int](1, 2), "x"),
(Seq[Int](), "x")
).toDF("a", "b")
(Seq[Int](1, 2), "x", 1),
(Seq[Int](), "x", 1)
).toDF("a", "b", "c")

checkAnswer(
df.select(array_position(df("a"), 1)),
Expand All @@ -797,7 +801,10 @@ class DataFrameFunctionsSuite extends QueryTest with SharedSQLContext {
df.selectExpr("array_position(a, 1)"),
Seq(Row(1L), Row(0L))
)

checkAnswer(
df.select(array_position(df("a"), df("c"))),
Seq(Row(1L), Row(0L))
)
checkAnswer(
df.select(array_position(df("a"), null)),
Seq(Row(null), Row(null))
Expand All @@ -824,10 +831,10 @@ class DataFrameFunctionsSuite extends QueryTest with SharedSQLContext {

test("element_at function") {
val df = Seq(
(Seq[String]("1", "2", "3")),
(Seq[String](null, "")),
(Seq[String]())
).toDF("a")
(Seq[String]("1", "2", "3"), 1),
(Seq[String](null, ""), -1),
(Seq[String](), 2)
).toDF("a", "b")

intercept[Exception] {
checkAnswer(
Expand All @@ -845,6 +852,10 @@ class DataFrameFunctionsSuite extends QueryTest with SharedSQLContext {
df.select(element_at(df("a"), 4)),
Seq(Row(null), Row(null), Row(null))
)
checkAnswer(
df.select(element_at(df("a"), df("b"))),
Seq(Row("1"), Row(""), Row(null))
)

checkAnswer(
df.select(element_at(df("a"), 1)),
Expand Down Expand Up @@ -1112,10 +1123,10 @@ class DataFrameFunctionsSuite extends QueryTest with SharedSQLContext {

test("array remove") {
val df = Seq(
(Array[Int](2, 1, 2, 3), Array("a", "b", "c", "a"), Array("", "")),
(Array.empty[Int], Array.empty[String], Array.empty[String]),
(null, null, null)
).toDF("a", "b", "c")
(Array[Int](2, 1, 2, 3), Array("a", "b", "c", "a"), Array("", ""), 2),
(Array.empty[Int], Array.empty[String], Array.empty[String], 2),
(null, null, null, 2)
).toDF("a", "b", "c", "d")
checkAnswer(
df.select(array_remove($"a", 2), array_remove($"b", "a"), array_remove($"c", "")),
Seq(
Expand All @@ -1124,6 +1135,14 @@ class DataFrameFunctionsSuite extends QueryTest with SharedSQLContext {
Row(null, null, null))
)

checkAnswer(
df.select(array_remove($"a", $"d")),
Seq(
Row(Seq(1, 3)),
Row(Seq.empty[Int]),
Row(null))
)

checkAnswer(
df.selectExpr("array_remove(a, 2)", "array_remove(b, \"a\")",
"array_remove(c, \"\")"),
Expand Down