[SPARK-17895] Improve doc for rangeBetween and rowsBetween

## What changes were proposed in this pull request?

Copied description for row and range based frame boundary from https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/window/WindowExec.scala#L56

Added examples to show different behavior of rangeBetween and rowsBetween when involving duplicate values.

Please review https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark

 before opening a pull request.

Author: buzhihuojie <ren.weiluo@gmail.com>

Closes #15727 from david-weiluo-ren/improveDocForRangeAndRowsBetween.

(cherry picked from commit 742e0fea)
Signed-off-by: Reynold Xin <rxin@databricks.com>

sql/core/src/main/scala/org/apache/spark/sql/expressions/Window.scala

@@ -121,6 +121,32 @@ object Window {
    * and [[Window.currentRow]] to specify special boundary values, rather than using integral
    * values directly.
    *
+   * A row based boundary is based on the position of the row within the partition.
+   * An offset indicates the number of rows above or below the current row, the frame for the
+   * current row starts or ends. For instance, given a row based sliding frame with a lower bound
+   * offset of -1 and a upper bound offset of +2. The frame for row with index 5 would range from
+   * index 4 to index 6.
+   *
+   * {{{
+   *   import org.apache.spark.sql.expressions.Window
+   *   val df = Seq((1, "a"), (1, "a"), (2, "a"), (1, "b"), (2, "b"), (3, "b"))
+   *     .toDF("id", "category")
+   *   df.withColumn("sum",
+   *       sum('id) over Window.partitionBy('category).orderBy('id).rowsBetween(0,1))
+   *     .show()
+   *
+   *   +---+--------+---+
+   *   | id|category|sum|
+   *   +---+--------+---+
+   *   |  1|       b|  3|
+   *   |  2|       b|  5|
+   *   |  3|       b|  3|
+   *   |  1|       a|  2|
+   *   |  1|       a|  3|
+   *   |  2|       a|  2|
+   *   +---+--------+---+
+   * }}}
+   *
    * @param start boundary start, inclusive. The frame is unbounded if this is
    *              the minimum long value ([[Window.unboundedPreceding]]).
    * @param end boundary end, inclusive. The frame is unbounded if this is the
@@ -144,6 +170,35 @@ object Window {
    * and [[Window.currentRow]] to specify special boundary values, rather than using integral
    * values directly.
    *
+   * A range based boundary is based on the actual value of the ORDER BY
+   * expression(s). An offset is used to alter the value of the ORDER BY expression, for
+   * instance if the current order by expression has a value of 10 and the lower bound offset
+   * is -3, the resulting lower bound for the current row will be 10 - 3 = 7. This however puts a
+   * number of constraints on the ORDER BY expressions: there can be only one expression and this
+   * expression must have a numerical data type. An exception can be made when the offset is 0,
+   * because no value modification is needed, in this case multiple and non-numeric ORDER BY
+   * expression are allowed.
+   *
+   * {{{
+   *   import org.apache.spark.sql.expressions.Window
+   *   val df = Seq((1, "a"), (1, "a"), (2, "a"), (1, "b"), (2, "b"), (3, "b"))
+   *     .toDF("id", "category")
+   *   df.withColumn("sum",
+   *       sum('id) over Window.partitionBy('category).orderBy('id).rangeBetween(0,1))
+   *     .show()
+   *
+   *   +---+--------+---+
+   *   | id|category|sum|
+   *   +---+--------+---+
+   *   |  1|       b|  3|
+   *   |  2|       b|  5|
+   *   |  3|       b|  3|
+   *   |  1|       a|  4|
+   *   |  1|       a|  4|
+   *   |  2|       a|  2|
+   *   +---+--------+---+
+   * }}}
+   *
    * @param start boundary start, inclusive. The frame is unbounded if this is
    *              the minimum long value ([[Window.unboundedPreceding]]).
    * @param end boundary end, inclusive. The frame is unbounded if this is the

sql/core/src/main/scala/org/apache/spark/sql/expressions/WindowSpec.scala

@@ -89,6 +89,32 @@ class WindowSpec private[sql](
    * and [[Window.currentRow]] to specify special boundary values, rather than using integral
    * values directly.
    *
+   * A row based boundary is based on the position of the row within the partition.
+   * An offset indicates the number of rows above or below the current row, the frame for the
+   * current row starts or ends. For instance, given a row based sliding frame with a lower bound
+   * offset of -1 and a upper bound offset of +2. The frame for row with index 5 would range from
+   * index 4 to index 6.
+   *
+   * {{{
+   *   import org.apache.spark.sql.expressions.Window
+   *   val df = Seq((1, "a"), (1, "a"), (2, "a"), (1, "b"), (2, "b"), (3, "b"))
+   *     .toDF("id", "category")
+   *   df.withColumn("sum",
+   *       sum('id) over Window.partitionBy('category).orderBy('id).rowsBetween(0,1))
+   *     .show()
+   *
+   *   +---+--------+---+
+   *   | id|category|sum|
+   *   +---+--------+---+
+   *   |  1|       b|  3|
+   *   |  2|       b|  5|
+   *   |  3|       b|  3|
+   *   |  1|       a|  2|
+   *   |  1|       a|  3|
+   *   |  2|       a|  2|
+   *   +---+--------+---+
+   * }}}
+   *
    * @param start boundary start, inclusive. The frame is unbounded if this is
    *              the minimum long value ([[Window.unboundedPreceding]]).
    * @param end boundary end, inclusive. The frame is unbounded if this is the
@@ -111,6 +137,35 @@ class WindowSpec private[sql](
    * and [[Window.currentRow]] to specify special boundary values, rather than using integral
    * values directly.
    *
+   * A range based boundary is based on the actual value of the ORDER BY
+   * expression(s). An offset is used to alter the value of the ORDER BY expression, for
+   * instance if the current order by expression has a value of 10 and the lower bound offset
+   * is -3, the resulting lower bound for the current row will be 10 - 3 = 7. This however puts a
+   * number of constraints on the ORDER BY expressions: there can be only one expression and this
+   * expression must have a numerical data type. An exception can be made when the offset is 0,
+   * because no value modification is needed, in this case multiple and non-numeric ORDER BY
+   * expression are allowed.
+   *
+   * {{{
+   *   import org.apache.spark.sql.expressions.Window
+   *   val df = Seq((1, "a"), (1, "a"), (2, "a"), (1, "b"), (2, "b"), (3, "b"))
+   *     .toDF("id", "category")
+   *   df.withColumn("sum",
+   *       sum('id) over Window.partitionBy('category).orderBy('id).rangeBetween(0,1))
+   *     .show()
+   *
+   *   +---+--------+---+
+   *   | id|category|sum|
+   *   +---+--------+---+
+   *   |  1|       b|  3|
+   *   |  2|       b|  5|
+   *   |  3|       b|  3|
+   *   |  1|       a|  4|
+   *   |  1|       a|  4|
+   *   |  2|       a|  2|
+   *   +---+--------+---+
+   * }}}
+   *
    * @param start boundary start, inclusive. The frame is unbounded if this is
    *              the minimum long value ([[Window.unboundedPreceding]]).
    * @param end boundary end, inclusive. The frame is unbounded if this is the