[SPARK-2871] [PySpark] add zipWithIndex() and zipWithUniqueId()

[davies]

RDD.zipWithIndex()

 Zips this RDD with its element indices.
The ordering is first based on the partition index and then the
ordering of items within each partition. So the first item in
the first partition gets index 0, and the last item in the last
partition receives the largest index.
This method needs to trigger a spark job when this RDD contains
more than one partitions.
>>> sc.parallelize(range(4), 2).zipWithIndex().collect()
[(0, 0), (1, 1), (2, 2), (3, 3)]

RDD.zipWithUniqueId()

 Zips this RDD with generated unique Long ids.
Items in the kth partition will get ids k, n+k, 2*n+k, ..., where
n is the number of partitions. So there may exist gaps, but this
method won't trigger a spark job, which is different from
L{zipWithIndex}
>>> sc.parallelize(range(4), 2).zipWithUniqueId().collect()
[(0, 0), (2, 1), (1, 2), (3, 3)]

[SparkQA]

QA tests have started for PR 2092 at commit 0d2a128.

• This patch merges cleanly.

[SparkQA]

QA tests have finished for PR 2092 at commit 0d2a128.

• This patch passes unit tests.
• This patch merges cleanly.
• This patch adds no public classes.

[mattf]

are you going to add tests for these?

[davies]

I think doc tests should be enough.

[mattf]

fair enough

+1 lgtm

[JoshRosen]

This isn't the best example because it's not clear which element is the item and which element is its index. In the Scala API, this is clear from the method's return type. Maybe we should update the documentation to explicitly state that the second element is the id (like the Scala API).

I think this implementation has things backwards w.r.t. the Scala one:

>>>sc.parallelize(['a', 'b', 'c', 'd'], 2).zipWithIndex().collect()
[(0, 'a'), (1, 'b'), (2, 'c'), (3, 'd')]

versus

scala> sc.parallelize(Seq('a', 'b', 'c', 'd')).zipWithIndex().collect()
res0:Array[(Char, Long)] =Array((a,0), (b,1), (c,2), (d,3))

[davies]

I will change it.

[davies]

Jenkins, test this please.

[SparkQA]

QA tests have started for PR 2092 at commit cebe5bf.

• This patch merges cleanly.

[SparkQA]

QA tests have finished for PR 2092 at commit cebe5bf.

• This patch passes unit tests.
• This patch merges cleanly.
• This patch adds the following public classes (experimental):
  • class BoundedFloat(float):
  • class JoinedRow2 extends Row
  • class JoinedRow3 extends Row
  • class JoinedRow4 extends Row
  • class JoinedRow5 extends Row
  • class GenericRow(protected[sql] val values: Array[Any]) extends Row
  • abstract class MutableValue extends Serializable
  • final class MutableInt extends MutableValue
  • final class MutableFloat extends MutableValue
  • final class MutableBoolean extends MutableValue
  • final class MutableDouble extends MutableValue
  • final class MutableShort extends MutableValue
  • final class MutableLong extends MutableValue
  • final class MutableByte extends MutableValue
  • final class MutableAny extends MutableValue
  • final class SpecificMutableRow(val values: Array[MutableValue]) extends MutableRow
  • case class CountDistinct(expressions: Seq[Expression]) extends PartialAggregate
  • case class CollectHashSet(expressions: Seq[Expression]) extends AggregateExpression
  • case class CollectHashSetFunction(
  • case class CombineSetsAndCount(inputSet: Expression) extends AggregateExpression
  • case class CombineSetsAndCountFunction(
  • case class CountDistinctFunction(
  • case class MaxOf(left: Expression, right: Expression) extends Expression
  • case class NewSet(elementType: DataType) extends LeafExpression
  • case class AddItemToSet(item: Expression, set: Expression) extends Expression
  • case class CombineSets(left: Expression, right: Expression) extends BinaryExpression
  • case class CountSet(child: Expression) extends UnaryExpression

[JoshRosen]

LGTM, so I've merged this into master. Thanks!

[JoshRosen]

I also merged this into branch-1.1, since it's an often-requested feature and only adds code to this file (so it's low-risk to merge).