class RaceSeq does Iterable does Sequence { }

An RaceSeq is the intermediate object used when the operator race is invoked on a Seq. In general, it's not intended for direct consumption by the developer.

Methods

method iterator

method iterator(RaceSeq:D: --> Iterator:D)

Returns the underlying iterator.

method grep

method grep(RaceSeq:D: $matcher, *%options)

Applies grep to the RaceSeq similarly to how it would do it on a Seq.

my @raced = (^10000).map(*²).race;
@raced.grep( * %% 3 ).say;
# OUTPUT: «(0 9 36 81 144 …» 

When you use race on a Seq, this is the method that is actually called.

method map

method map(RaceSeq:D: $matcher, *%options)

Uses maps on the RaceSeq, generally created by application of .race to a preexisting Seq.

method invert

method invert(RaceSeq:D:)

Inverts the RaceSeq created from a Seq by .race.

method race

method race(RaceSeq:D:)

Returns the object.

method hyper

method hyper(RaceSeq:D:)

Creates a HyperSeq object out of the current one.

method serial

multi method serial(RaceSeq:D:)

Converts the object to a Seq and returns it.

method is-lazy

method is-lazy(--> False )

Returns False.

method sink

Defined as:

method sink(--> Nil)

Sinks the underlying data structure, producing any side effects.

Type Graph

Expand above chart

Routines supplied by role Iterable

RaceSeq does role Iterable, which provides the following routines:

(Iterable) method iterator

Defined as:

method iterator(--> Iterator:D)

Method stub that ensures all classes doing the Iterable role have a method iterator.

It is supposed to return an Iterator.

say (1..10).iterator;

(Iterable) method flat

Defined as:

method flat(--> Iterable)

Returns another Iterable that flattens out all iterables that the first one returns.

For example

say (<a b>, 'c').elems;         # OUTPUT: «2␤» 
say (<a b>, 'c').flat.elems;    # OUTPUT: «3␤»

because <a b> is a List and thus iterable, so (<a b>, 'c').flat returns ('a', 'b', 'c'), which has three elems.

Note that the flattening is recursive, so ((("a", "b"), "c"), "d").flat returns ("a", "b", "c", "d"), but it does not flatten itemized sublists:

say ($('a', 'b'), 'c').perl;    # OUTPUT: «($("a", "b"), "c")␤»

(Iterable) method lazy

Defined as:

method lazy(--> Iterable)

Returns a lazy iterable wrapping the invocant.

say (1 ... 1000).is-lazy;      # OUTPUT: «False␤» 
say (1 ... 1000).lazy.is-lazy; # OUTPUT: «True␤»

(Iterable) method hyper

Defined as:

method hyper(Int(Cool) :$batch = 64, Int(Cool) :$degree = 4)

Returns another Iterable that is potentially iterated in parallel, with a given batch size and degree of parallelism.

The order of elements is preserved.

say ([1..100].hyper.map({ $_ +1 }).list);

Use hyper in situations where it is OK to do the processing of items in parallel, and the output order should be kept relative to the input order. See race for situations where items are processed in parallel and the output order does not matter.

Options degree and batch

The degree option (short for "degree of parallelism") configures how many parallel workers should be started. To start 4 workers (e.g. to use at most 4 cores), pass :4degree to the hyper or race method. Note that in some cases, choosing a degree higher than the available CPU cores can make sense, for example I/O bound work or latency-heavy tasks like web crawling. For CPU-bound work, however, it makes no sense to pick a number higher than the CPU core count.

The batch size option configures the number of items sent to a given parallel worker at once. It allows for making a throughput/latency trade-off. If, for example, an operation is long-running per item, and you need the first results as soon as possible, set it to 1. That means every parallel worker gets 1 item to process at a time, and reports the result as soon as possible. In consequence, the overhead for inter-thread communication is maximized. In the other extreme, if you have 1000 items to process and 10 workers, and you give every worker a batch of 100 items, you will incur minimal overhead for dispatching the items, but you will only get the first results when 100 items are processed by the fastest worker (or, for hyper, when the worker getting the first batch returns.) Also, if not all items take the same amount of time to process, you might run into the situation where some workers are already done and sit around without being able to help with the remaining work. In situations where not all items take the same time to process, and you don't want too much inter-thread communication overhead, picking a number somewhere in the middle makes sense. Your aim might be to keep all workers about evenly busy to make best use of the resources available.

You can also check out this blog post on the semantics of hyper and race

(Iterable) method race

Defined as:

method race(Int(Cool) :$batch = 64, Int(Cool) :$degree = 4 --> Iterable)

Returns another Iterable that is potentially iterated in parallel, with a given batch size and degree of parallelism (number of parallel workers).

Unlike hyper, race does not preserve the order of elements.

say ([1..100].race.map({ $_ +1 }).list);

Use race in situations where it is OK to do the processing of items in parallel, and the output order does not matter. See hyper for situations where you want items processed in parallel and the output order should be kept relative to the input order.

Blog post on the semantics of hyper and race

See hyper for an explanation of :$batch and :$degree.