[SPARK-8232] [SQL] Add sort_array support

This PR is based on #7581 , just fix the conflict.

Author: Cheng Hao <hao.cheng@intel.com>
Author: Davies Liu <davies@databricks.com>

Closes #7851 from davies/sort_array and squashes the following commits:

a80ef66 [Davies Liu] fix conflict
7cfda65 [Davies Liu] Merge branch 'master' of github.com:apache/spark into sort_array
664c960 [Cheng Hao] update the sort_array by using the ArrayData
276d2d5 [Cheng Hao] add empty line
0edab9c [Cheng Hao] Add asending/descending support for sort_array
80fc0f8 [Cheng Hao] Add type checking
a42b678 [Cheng Hao] Add sort_array support

Author: chenghao-intel

python/pyspark/sql/functions.py

@@ -51,6 +51,7 @@
     'sha1',
     'sha2',
     'size',
+    'sort_array',
     'sparkPartitionId',
     'struct',
     'udf',
@@ -570,8 +571,10 @@ def length(col):
 def format_number(col, d):
     """Formats the number X to a format like '#,###,###.##', rounded to d decimal places,
        and returns the result as a string.
+
     :param col: the column name of the numeric value to be formatted
     :param d: the N decimal places
+
     >>> sqlContext.createDataFrame([(5,)], ['a']).select(format_number('a', 4).alias('v')).collect()
     [Row(v=u'5.0000')]
     """
@@ -954,6 +957,23 @@ def size(col):
     return Column(sc._jvm.functions.size(_to_java_column(col)))
 
 
+@since(1.5)
+def sort_array(col, asc=True):
+    """
+    Collection function: sorts the input array for the given column in ascending order.
+
+    :param col: name of column or expression
+
+    >>> df = sqlContext.createDataFrame([([2, 1, 3],),([1],),([],)], ['data'])
+    >>> df.select(sort_array(df.data).alias('r')).collect()
+    [Row(r=[1, 2, 3]), Row(r=[1]), Row(r=[])]
+    >>> df.select(sort_array(df.data, asc=False).alias('r')).collect()
+    [Row(r=[3, 2, 1]), Row(r=[1]), Row(r=[])]
+     """
+    sc = SparkContext._active_spark_context
+    return Column(sc._jvm.functions.sort_array(_to_java_column(col), asc))
+
+
 @since
 @ignore_unicode_prefix
 def soundex(col):

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala

@@ -233,6 +233,7 @@ object FunctionRegistry {
 
     // collection functions
     expression[Size]("size"),
+    expression[SortArray]("sort_array"),
 
     // misc functions
     expression[Crc32]("crc32"),

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala

@@ -16,7 +16,10 @@
  */
 package org.apache.spark.sql.catalyst.expressions
 
-import org.apache.spark.sql.catalyst.expressions.codegen.{CodeGenContext, GeneratedExpressionCode}
+import java.util.Comparator
+
+import org.apache.spark.sql.catalyst.analysis.TypeCheckResult
+import org.apache.spark.sql.catalyst.expressions.codegen.{CodegenFallback, CodeGenContext, GeneratedExpressionCode}
 import org.apache.spark.sql.types._
 
 /**
@@ -35,3 +38,79 @@ case class Size(child: Expression) extends UnaryExpression with ExpectsInputType
     nullSafeCodeGen(ctx, ev, c => s"${ev.primitive} = ($c).numElements();")
   }
 }
+
+/**
+ * Sorts the input array in ascending / descending order according to the natural ordering of
+ * the array elements and returns it.
+ */
+case class SortArray(base: Expression, ascendingOrder: Expression)
+  extends BinaryExpression with ExpectsInputTypes with CodegenFallback {
+
+  def this(e: Expression) = this(e, Literal(true))
+
+  override def left: Expression = base
+  override def right: Expression = ascendingOrder
+  override def dataType: DataType = base.dataType
+  override def inputTypes: Seq[AbstractDataType] = Seq(ArrayType, BooleanType)
+
+  override def checkInputDataTypes(): TypeCheckResult = base.dataType match {
+    case _ @ ArrayType(n: AtomicType, _) => TypeCheckResult.TypeCheckSuccess
+    case _ @ ArrayType(n, _) => TypeCheckResult.TypeCheckFailure(
+                    s"Type $n is not the AtomicType, we can not perform the ordering operations")
+    case other =>
+      TypeCheckResult.TypeCheckFailure(s"ArrayType(AtomicType) is expected, but we got $other")
+  }
+
+  @transient
+  private lazy val lt = {
+    val ordering = base.dataType match {
+      case _ @ ArrayType(n: AtomicType, _) => n.ordering.asInstanceOf[Ordering[Any]]
+    }
+
+    new Comparator[Any]() {
+      override def compare(o1: Any, o2: Any): Int = {
+        if (o1 == null && o2 == null) {
+          0
+        } else if (o1 == null) {
+          -1
+        } else if (o2 == null) {
+          1
+        } else {
+          ordering.compare(o1, o2)
+        }
+      }
+    }
+  }
+
+  @transient
+  private lazy val gt = {
+    val ordering = base.dataType match {
+      case _ @ ArrayType(n: AtomicType, _) => n.ordering.asInstanceOf[Ordering[Any]]
+    }
+
+    new Comparator[Any]() {
+      override def compare(o1: Any, o2: Any): Int = {
+        if (o1 == null && o2 == null) {
+          0
+        } else if (o1 == null) {
+          1
+        } else if (o2 == null) {
+          -1
+        } else {
+          -ordering.compare(o1, o2)
+        }
+      }
+    }
+  }
+
+  override def nullSafeEval(array: Any, ascending: Any): Any = {
+    val elementType = base.dataType.asInstanceOf[ArrayType].elementType
+    val data = array.asInstanceOf[ArrayData].toArray[AnyRef](elementType)
+    java.util.Arrays.sort(
+      data,
+      if (ascending.asInstanceOf[Boolean]) lt else gt)
+    new GenericArrayData(data.asInstanceOf[Array[Any]])
+  }
+
+  override def prettyName: String = "sort_array"
+}

sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/CollectionFunctionsSuite.scala

@@ -43,4 +43,26 @@ class CollectionFunctionsSuite extends SparkFunSuite with ExpressionEvalHelper {
     checkEvaluation(Literal.create(null, MapType(StringType, StringType)), null)
     checkEvaluation(Literal.create(null, ArrayType(StringType)), null)
   }
+
+  test("Sort Array") {
+    val a0 = Literal.create(Seq(2, 1, 3), ArrayType(IntegerType))
+    val a1 = Literal.create(Seq[Integer](), ArrayType(IntegerType))
+    val a2 = Literal.create(Seq("b", "a"), ArrayType(StringType))
+    val a3 = Literal.create(Seq("b", null, "a"), ArrayType(StringType))
+
+    checkEvaluation(new SortArray(a0), Seq(1, 2, 3))
+    checkEvaluation(new SortArray(a1), Seq[Integer]())
+    checkEvaluation(new SortArray(a2), Seq("a", "b"))
+    checkEvaluation(new SortArray(a3), Seq(null, "a", "b"))
+    checkEvaluation(SortArray(a0, Literal(true)), Seq(1, 2, 3))
+    checkEvaluation(SortArray(a1, Literal(true)), Seq[Integer]())
+    checkEvaluation(SortArray(a2, Literal(true)), Seq("a", "b"))
+    checkEvaluation(new SortArray(a3, Literal(true)), Seq(null, "a", "b"))
+    checkEvaluation(SortArray(a0, Literal(false)), Seq(3, 2, 1))
+    checkEvaluation(SortArray(a1, Literal(false)), Seq[Integer]())
+    checkEvaluation(SortArray(a2, Literal(false)), Seq("b", "a"))
+    checkEvaluation(new SortArray(a3, Literal(false)), Seq("b", "a", null))
+
+    checkEvaluation(Literal.create(null, ArrayType(StringType)), null)
+  }
 }

sql/core/src/main/scala/org/apache/spark/sql/functions.scala

@@ -2223,19 +2223,30 @@ object functions {
   //////////////////////////////////////////////////////////////////////////////////////////////
 
   /**
-   * Returns length of array or map
+   * Returns length of array or map.
+   *
    * @group collection_funcs
    * @since 1.5.0
    */
-  def size(columnName: String): Column = size(Column(columnName))
+  def size(e: Column): Column = Size(e.expr)
 
   /**
-   * Returns length of array or map
+   * Sorts the input array for the given column in ascending order,
+   * according to the natural ordering of the array elements.
+   *
    * @group collection_funcs
    * @since 1.5.0
    */
-  def size(column: Column): Column = Size(column.expr)
+  def sort_array(e: Column): Column = sort_array(e, true)
 
+  /**
+   * Sorts the input array for the given column in ascending / descending order,
+   * according to the natural ordering of the array elements.
+   *
+   * @group collection_funcs
+   * @since 1.5.0
+   */
+  def sort_array(e: Column, asc: Boolean): Column = SortArray(e.expr, lit(asc).expr)
 
   //////////////////////////////////////////////////////////////////////////////////////////////
   //////////////////////////////////////////////////////////////////////////////////////////////

sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala

@@ -267,14 +267,61 @@ class DataFrameFunctionsSuite extends QueryTest {
     )
   }
 
+  test("sort_array function") {
+    val df = Seq(
+      (Array[Int](2, 1, 3), Array("b", "c", "a")),
+      (Array[Int](), Array[String]()),
+      (null, null)
+    ).toDF("a", "b")
+    checkAnswer(
+      df.select(sort_array($"a"), sort_array($"b")),
+      Seq(
+        Row(Seq(1, 2, 3), Seq("a", "b", "c")),
+        Row(Seq[Int](), Seq[String]()),
+        Row(null, null))
+    )
+    checkAnswer(
+      df.select(sort_array($"a", false), sort_array($"b", false)),
+      Seq(
+        Row(Seq(3, 2, 1), Seq("c", "b", "a")),
+        Row(Seq[Int](), Seq[String]()),
+        Row(null, null))
+    )
+    checkAnswer(
+      df.selectExpr("sort_array(a)", "sort_array(b)"),
+      Seq(
+        Row(Seq(1, 2, 3), Seq("a", "b", "c")),
+        Row(Seq[Int](), Seq[String]()),
+        Row(null, null))
+    )
+    checkAnswer(
+      df.selectExpr("sort_array(a, true)", "sort_array(b, false)"),
+      Seq(
+        Row(Seq(1, 2, 3), Seq("c", "b", "a")),
+        Row(Seq[Int](), Seq[String]()),
+        Row(null, null))
+    )
+
+    val df2 = Seq((Array[Array[Int]](Array(2)), "x")).toDF("a", "b")
+    assert(intercept[AnalysisException] {
+      df2.selectExpr("sort_array(a)").collect()
+    }.getMessage().contains("Type ArrayType(IntegerType,false) is not the AtomicType, " +
+      "we can not perform the ordering operations"))
+
+    val df3 = Seq(("xxx", "x")).toDF("a", "b")
+    assert(intercept[AnalysisException] {
+      df3.selectExpr("sort_array(a)").collect()
+    }.getMessage().contains("ArrayType(AtomicType) is expected, but we got StringType"))
+  }
+
   test("array size function") {
     val df = Seq(
       (Array[Int](1, 2), "x"),
       (Array[Int](), "y"),
       (Array[Int](1, 2, 3), "z")
     ).toDF("a", "b")
     checkAnswer(
-      df.select(size("a")),
+      df.select(size($"a")),
       Seq(Row(2), Row(0), Row(3))
     )
     checkAnswer(
@@ -290,7 +337,7 @@ class DataFrameFunctionsSuite extends QueryTest {
       (Map[Int, Int](1 -> 1, 2 -> 2, 3 -> 3), "z")
     ).toDF("a", "b")
     checkAnswer(
-      df.select(size("a")),
+      df.select(size($"a")),
       Seq(Row(2), Row(0), Row(3))
     )
     checkAnswer(