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+# Parallel Iterators
+
+These are some notes on the design of the parallel iterator traits.
+This file does not describe how to **use** parallel iterators.
+
+## The challenge
+
+Parallel iterators are more complicated than sequential iterators.
+The reason is that they have to be able to split themselves up and
+operate in parallel across the two halves.
+
+The current design for parallel iterators has two distinct modes in
+which they can be used; as we will see, not all iterators support both
+modes (which is why there are two):
+
+- **Pull mode** (the `Producer` and `UnindexedProducer` traits): in this mode,
+ the iterator is asked to produce the next item using a call to `next`. This
+ is basically like a normal iterator, but with a twist: you can split the
+ iterator in half to produce disjoint items in separate threads.
+ - in the `Producer` trait, splitting is done with `split_at`, which accepts
+ an index where the split should be performed. Only indexed iterators can
+ work in this mode, as they know exactly how much data they will produce,
+ and how to locate the requested index.
+ - in the `UnindexedProducer` trait, splitting is done with `split`, which
+ simply requests that the producer divide itself *approximately* in half.
+ This is useful when the exact length and/or layout is unknown, as with
+ `String` characters, or when the length might exceed `usize`, as with
+ `Range<u64>` on 32-bit platforms.
+ - In theory, any `Producer` could act unindexed, but we don't currently
+ use that possibility. When you know the exact length, a `split` can
+ simply be implemented as `split_at(length/2)`.
+- **Push mode** (the `Consumer` and `UnindexedConsumer` traits): in
+ this mode, the iterator instead is *given* each item in turn, which
+ is then processed. This is the opposite of a normal iterator. It's
+ more like a `for_each` call: each time a new item is produced, the
+ `consume` method is called with that item. (The traits themselves are
+ a bit more complex, as they support state that can be threaded
+ through and ultimately reduced.) Unlike producers, there are two
+ variants of consumers. The difference is how the split is performed:
+ - in the `Consumer` trait, splitting is done with `split_at`, which
+ accepts an index where the split should be performed. All
+ iterators can work in this mode. The resulting halves thus have an
+ idea about how much data they expect to consume.
+ - in the `UnindexedConsumer` trait, splitting is done with
+ `split_off_left`. There is no index: the resulting halves must be
+ prepared to process any amount of data, and they don't know where that
+ data falls in the overall stream.
+ - Not all consumers can operate in this mode. It works for
+ `for_each` and `reduce`, for example, but it does not work for
+ `collect_into_vec`, since in that case the position of each item is
+ important for knowing where it ends up in the target collection.
+
+## How iterator execution proceeds
+
+We'll walk through this example iterator chain to start. This chain
+demonstrates more-or-less the full complexity of what can happen.
+
+```rust
+vec1.par_iter()
+ .zip(vec2.par_iter())
+ .flat_map(some_function)
+ .for_each(some_other_function)
+```
+
+To handle an iterator chain, we start by creating consumers. This
+works from the end. So in this case, the call to `for_each` is the
+final step, so it will create a `ForEachConsumer` that, given an item,
+just calls `some_other_function` with that item. (`ForEachConsumer` is
+a very simple consumer because it doesn't need to thread any state
+between items at all.)
+
+Now, the `for_each` call will pass this consumer to the base iterator,
+which is the `flat_map`. It will do this by calling the `drive_unindexed`
+method on the `ParallelIterator` trait. `drive_unindexed` basically
+says "produce items for this iterator and feed them to this consumer";
+it only works for unindexed consumers.
+
+(As an aside, it is interesting that only some consumers can work in
+unindexed mode, but all producers can *drive* an unindexed consumer.
+In contrast, only some producers can drive an *indexed* consumer, but
+all consumers can be supplied indexes. Isn't variance neat.)
+
+As it happens, `FlatMap` only works with unindexed consumers anyway.
+This is because flat-map basically has no idea how many items it will
+produce. If you ask flat-map to produce the 22nd item, it can't do it,
+at least not without some intermediate state. It doesn't know whether
+processing the first item will create 1 item, 3 items, or 100;
+therefore, to produce an arbitrary item, it would basically just have
+to start at the beginning and execute sequentially, which is not what
+we want. But for unindexed consumers, this doesn't matter, since they
+don't need to know how much data they will get.
+
+Therefore, `FlatMap` can wrap the `ForEachConsumer` with a
+`FlatMapConsumer` that feeds to it. This `FlatMapConsumer` will be
+given one item. It will then invoke `some_function` to get a parallel
+iterator out. It will then ask this new parallel iterator to drive the
+`ForEachConsumer`. The `drive_unindexed` method on `flat_map` can then
+pass the `FlatMapConsumer` up the chain to the previous item, which is
+`zip`. At this point, something interesting happens.
+
+## Switching from push to pull mode
+
+If you think about `zip`, it can't really be implemented as a
+consumer, at least not without an intermediate thread and some
+channels or something (or maybe coroutines). The problem is that it
+has to walk two iterators *in lockstep*. Basically, it can't call two
+`drive` methods simultaneously, it can only call one at a time. So at
+this point, the `zip` iterator needs to switch from *push mode* into
+*pull mode*.
+
+You'll note that `Zip` is only usable if its inputs implement
+`IndexedParallelIterator`, meaning that they can produce data starting
+at random points in the stream. This need to switch to push mode is
+exactly why. If we want to split a zip iterator at position 22, we
+need to be able to start zipping items from index 22 right away,
+without having to start from index 0.
+
+Anyway, so at this point, the `drive_unindexed` method for `Zip` stops
+creating consumers. Instead, it creates a *producer*, a `ZipProducer`,
+to be exact, and calls the `bridge` function in the `internals`
+module. Creating a `ZipProducer` will in turn create producers for
+the two iterators being zipped. This is possible because they both
+implement `IndexedParallelIterator`.
+
+The `bridge` function will then connect the consumer, which is
+handling the `flat_map` and `for_each`, with the producer, which is
+handling the `zip` and its preecessors. It will split down until the
+chunks seem reasonably small, then pull items from the producer and
+feed them to the consumer.
+
+## The base case
+
+The other time that `bridge` gets used is when we bottom out in an
+indexed producer, such as a slice or range. There is also a
+`bridge_unindexed` equivalent for - you guessed it - unindexed producers,
+such as string characters.
+
+<a name="producer-callback">
+
+## What on earth is `ProducerCallback`?
+
+We saw that when you call a parallel action method like
+`par_iter.reduce()`, that will create a "reducing" consumer and then
+invoke `par_iter.drive_unindexed()` (or `par_iter.drive()`) as
+appropriate. This may create yet more consumers as we proceed up the
+parallel iterator chain. But at some point we're going to get to the
+start of the chain, or to a parallel iterator (like `zip()`) that has
+to coordinate multiple inputs. At that point, we need to start
+converting parallel iterators into producers.
+
+The way we do this is by invoking the method `with_producer()`, defined on
+`IndexedParallelIterator`. This is a callback scheme. In an ideal world,
+it would work like this:
+
+```rust
+base_iter.with_producer(|base_producer| {
+ // here, `base_producer` is the producer for `base_iter`
+});
+```
+
+In that case, we could implement a combinator like `map()` by getting
+the producer for the base iterator, wrapping it to make our own
+`MapProducer`, and then passing that to the callback. Something like
+this:
+
+```rust
+struct MapProducer<'f, P, F: 'f> {
+ base: P,
+ map_op: &'f F,
+}
+
+impl<I, F> IndexedParallelIterator for Map<I, F>
+ where I: IndexedParallelIterator,
+ F: MapOp<I::Item>,
+{
+ fn with_producer<CB>(self, callback: CB) -> CB::Output {
+ let map_op = &self.map_op;
+ self.base_iter.with_producer(|base_producer| {
+ // Here `producer` is the producer for `self.base_iter`.
+ // Wrap that to make a `MapProducer`
+ let map_producer = MapProducer {
+ base: base_producer,
+ map_op: map_op
+ };
+
+ // invoke the callback with the wrapped version
+ callback(map_producer)
+ });
+ }
+});
+```
+
+This example demonstrates some of the power of the callback scheme.
+It winds up being a very flexible setup. For one thing, it means we
+can take ownership of `par_iter`; we can then in turn give ownership
+away of its bits and pieces into the producer (this is very useful if
+the iterator owns an `&mut` slice, for example), or create shared
+references and put *those* in the producer. In the case of map, for
+example, the parallel iterator owns the `map_op`, and we borrow
+references to it which we then put into the `MapProducer` (this means
+the `MapProducer` can easily split itself and share those references).
+The `with_producer` method can also create resources that are needed
+during the parallel execution, since the producer does not have to be
+returned.
+
+Unfortunately there is a catch. We can't actually use closures the way
+I showed you. To see why, think about the type that `map_producer`
+would have to have. If we were going to write the `with_producer`
+method using a closure, it would have to look something like this:
+
+```rust
+pub trait IndexedParallelIterator: ParallelIterator {
+ type Producer;
+ fn with_producer<CB, R>(self, callback: CB) -> R
+ where CB: FnOnce(Self::Producer) -> R;
+ ...
+}
+```
+
+Note that we had to add this associated type `Producer` so that
+we could specify the argument of the callback to be `Self::Producer`.
+Now, imagine trying to write that `MapProducer` impl using this style:
+
+```rust
+impl<I, F> IndexedParallelIterator for Map<I, F>
+ where I: IndexedParallelIterator,
+ F: MapOp<I::Item>,
+{
+ type MapProducer = MapProducer<'f, P::Producer, F>;
+ // ^^ wait, what is this `'f`?
+
+ fn with_producer<CB, R>(self, callback: CB) -> R
+ where CB: FnOnce(Self::Producer) -> R
+ {
+ let map_op = &self.map_op;
+ // ^^^^^^ `'f` is (conceptually) the lifetime of this reference,
+ // so it will be different for each call to `with_producer`!
+ }
+}
+```
+
+This may look familiar to you: it's the same problem that we have
+trying to define an `Iterable` trait. Basically, the producer type
+needs to include a lifetime (here, `'f`) that refers to the body of
+`with_producer` and hence is not in scope at the impl level.
+
+If we had [associated type constructors][1598], we could solve this
+problem that way. But there is another solution. We can use a
+dedicated callback trait like `ProducerCallback`, instead of `FnOnce`:
+
+[1598]: https://github.com/rust-lang/rfcs/pull/1598
+
+```rust
+pub trait ProducerCallback<T> {
+ type Output;
+ fn callback<P>(self, producer: P) -> Self::Output
+ where P: Producer<Item=T>;
+}
+```
+
+Using this trait, the signature of `with_producer()` looks like this:
+
+```rust
+fn with_producer<CB: ProducerCallback<Self::Item>>(self, callback: CB) -> CB::Output;
+```
+
+Notice that this signature **never has to name the producer type** --
+there is no associated type `Producer` anymore. This is because the
+`callback()` method is generically over **all** producers `P`.
+
+The problem is that now the `||` sugar doesn't work anymore. So we
+have to manually create the callback struct, which is a mite tedious.
+So our `MapProducer` code looks like this:
+
+```rust
+impl<I, F> IndexedParallelIterator for Map<I, F>
+ where I: IndexedParallelIterator,
+ F: MapOp<I::Item>,
+{
+ fn with_producer<CB>(self, callback: CB) -> CB::Output
+ where CB: ProducerCallback<Self::Item>
+ {
+ return self.base.with_producer(Callback { callback: callback, map_op: self.map_op });
+ // ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+ // Manual version of the closure sugar: create an instance
+ // of a struct that implements `ProducerCallback`.
+
+ // The struct declaration. Each field is something that need to capture from the
+ // creating scope.
+ struct Callback<CB, F> {
+ callback: CB,
+ map_op: F,
+ }
+
+ // Implement the `ProducerCallback` trait. This is pure boilerplate.
+ impl<T, F, CB> ProducerCallback<T> for Callback<CB, F>
+ where F: MapOp<T>,
+ CB: ProducerCallback<F::Output>
+ {
+ type Output = CB::Output;
+
+ fn callback<P>(self, base: P) -> CB::Output
+ where P: Producer<Item=T>
+ {
+ // The body of the closure is here:
+ let producer = MapProducer { base: base,
+ map_op: &self.map_op };
+ self.callback.callback(producer)
+ }
+ }
+ }
+}
+```
+
+OK, a bit tedious, but it works!