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//! Arranges a collection into a re-usable trace structure.
//!
//! The `arrange` operator applies to a differential dataflow `Collection` and returns an `Arranged`
//! structure, provides access to both an indexed form of accepted updates as well as a stream of
//! batches of newly arranged updates.
//!
//! Several operators (`join`, `reduce`, and `count`, among others) are implemented against `Arranged`,
//! and can be applied directly to arranged data instead of the collection. Internally, the operators
//! will borrow the shared state, and listen on the timely stream for shared batches of data. The
//! resources to index the collection---communication, computation, and memory---are spent only once,
//! and only one copy of the index needs to be maintained as the collection changes.
//!
//! The arranged collection is stored in a trace, whose append-only operation means that it is safe to
//! share between the single `arrange` writer and multiple readers. Each reader is expected to interrogate
//! the trace only at times for which it knows the trace is complete, as indicated by the frontiers on its
//! incoming channels. Failing to do this is "safe" in the Rust sense of memory safety, but the reader may
//! see ill-defined data at times for which the trace is not complete. (All current implementations
//! commit only completed data to the trace).
use timely::dataflow::operators::{Enter, Map};
use timely::order::PartialOrder;
use timely::dataflow::{Scope, Stream, StreamCore};
use timely::dataflow::operators::generic::Operator;
use timely::dataflow::channels::pact::{ParallelizationContract, Pipeline, Exchange};
use timely::progress::Timestamp;
use timely::progress::Antichain;
use timely::dataflow::operators::Capability;
use crate::{Data, ExchangeData, Collection, AsCollection, Hashable};
use crate::difference::Semigroup;
use crate::lattice::Lattice;
use crate::trace::{self, Trace, TraceReader, Batch, BatchReader, Batcher, Builder, Cursor};
use crate::trace::implementations::{KeySpine, ValSpine};
use trace::wrappers::enter::{TraceEnter, BatchEnter,};
use trace::wrappers::enter_at::TraceEnter as TraceEnterAt;
use trace::wrappers::enter_at::BatchEnter as BatchEnterAt;
use trace::wrappers::filter::{TraceFilter, BatchFilter};
use super::TraceAgent;
/// An arranged collection of `(K,V)` values.
///
/// An `Arranged` allows multiple differential operators to share the resources (communication,
/// computation, memory) required to produce and maintain an indexed representation of a collection.
pub struct Arranged<G: Scope, Tr>
where
G::Timestamp: Lattice+Ord,
Tr: TraceReader+Clone,
{
/// A stream containing arranged updates.
///
/// This stream contains the same batches of updates the trace itself accepts, so there should
/// be no additional overhead to receiving these records. The batches can be navigated just as
/// the batches in the trace, by key and by value.
pub stream: Stream<G, Tr::Batch>,
/// A shared trace, updated by the `Arrange` operator and readable by others.
pub trace: Tr,
// TODO : We might have an `Option<Collection<G, (K, V)>>` here, which `as_collection` sets and
// returns when invoked, so as to not duplicate work with multiple calls to `as_collection`.
}
impl<G, Tr> Clone for Arranged<G, Tr>
where
G: Scope<Timestamp=Tr::Time>,
Tr: TraceReader + Clone,
{
fn clone(&self) -> Self {
Arranged {
stream: self.stream.clone(),
trace: self.trace.clone(),
}
}
}
use ::timely::dataflow::scopes::Child;
use ::timely::progress::timestamp::Refines;
use timely::Container;
use timely::container::PushInto;
impl<G, Tr> Arranged<G, Tr>
where
G: Scope<Timestamp=Tr::Time>,
Tr: TraceReader + Clone,
{
/// Brings an arranged collection into a nested scope.
///
/// This method produces a proxy trace handle that uses the same backing data, but acts as if the timestamps
/// have all been extended with an additional coordinate with the default value. The resulting collection does
/// not vary with the new timestamp coordinate.
pub fn enter<'a, TInner>(&self, child: &Child<'a, G, TInner>)
-> Arranged<Child<'a, G, TInner>, TraceEnter<Tr, TInner>>
where
TInner: Refines<G::Timestamp>+Lattice+Timestamp+Clone,
{
Arranged {
stream: self.stream.enter(child).map(|bw| BatchEnter::make_from(bw)),
trace: TraceEnter::make_from(self.trace.clone()),
}
}
/// Brings an arranged collection into a nested region.
///
/// This method only applies to *regions*, which are subscopes with the same timestamp
/// as their containing scope. In this case, the trace type does not need to change.
pub fn enter_region<'a>(&self, child: &Child<'a, G, G::Timestamp>)
-> Arranged<Child<'a, G, G::Timestamp>, Tr> {
Arranged {
stream: self.stream.enter(child),
trace: self.trace.clone(),
}
}
/// Brings an arranged collection into a nested scope.
///
/// This method produces a proxy trace handle that uses the same backing data, but acts as if the timestamps
/// have all been extended with an additional coordinate with the default value. The resulting collection does
/// not vary with the new timestamp coordinate.
pub fn enter_at<'a, TInner, F, P>(&self, child: &Child<'a, G, TInner>, logic: F, prior: P)
-> Arranged<Child<'a, G, TInner>, TraceEnterAt<Tr, TInner, F, P>>
where
TInner: Refines<G::Timestamp>+Lattice+Timestamp+Clone+'static,
F: FnMut(Tr::Key<'_>, Tr::Val<'_>, Tr::TimeGat<'_>)->TInner+Clone+'static,
P: FnMut(&TInner)->Tr::Time+Clone+'static,
{
let logic1 = logic.clone();
let logic2 = logic.clone();
Arranged {
trace: TraceEnterAt::make_from(self.trace.clone(), logic1, prior),
stream: self.stream.enter(child).map(move |bw| BatchEnterAt::make_from(bw, logic2.clone())),
}
}
/// Filters an arranged collection.
///
/// This method produces a new arrangement backed by the same shared
/// arrangement as `self`, paired with user-specified logic that can
/// filter by key and value. The resulting collection is restricted
/// to the keys and values that return true under the user predicate.
///
/// # Examples
///
/// ```
/// use differential_dataflow::input::Input;
/// use differential_dataflow::operators::arrange::ArrangeByKey;
///
/// ::timely::example(|scope| {
///
/// let arranged =
/// scope.new_collection_from(0 .. 10).1
/// .map(|x| (x, x+1))
/// .arrange_by_key();
///
/// arranged
/// .filter(|k,v| k == v)
/// .as_collection(|k,v| (*k,*v))
/// .assert_empty();
/// });
/// ```
pub fn filter<F>(&self, logic: F)
-> Arranged<G, TraceFilter<Tr, F>>
where
F: FnMut(Tr::Key<'_>, Tr::Val<'_>)->bool+Clone+'static,
{
let logic1 = logic.clone();
let logic2 = logic.clone();
Arranged {
trace: TraceFilter::make_from(self.trace.clone(), logic1),
stream: self.stream.map(move |bw| BatchFilter::make_from(bw, logic2.clone())),
}
}
/// Flattens the stream into a `Collection`.
///
/// The underlying `Stream<G, BatchWrapper<T::Batch>>` is a much more efficient way to access the data,
/// and this method should only be used when the data need to be transformed or exchanged, rather than
/// supplied as arguments to an operator using the same key-value structure.
pub fn as_collection<D: Data, L>(&self, mut logic: L) -> Collection<G, D, Tr::Diff>
where
L: FnMut(Tr::Key<'_>, Tr::Val<'_>) -> D+'static,
{
self.flat_map_ref(move |key, val| Some(logic(key,val)))
}
/// Extracts elements from an arrangement as a collection.
///
/// The supplied logic may produce an iterator over output values, allowing either
/// filtering or flat mapping as part of the extraction.
pub fn flat_map_ref<I, L>(&self, logic: L) -> Collection<G, I::Item, Tr::Diff>
where
I: IntoIterator,
I::Item: Data,
L: FnMut(Tr::Key<'_>, Tr::Val<'_>) -> I+'static,
{
Self::flat_map_batches(&self.stream, logic)
}
/// Extracts elements from a stream of batches as a collection.
///
/// The supplied logic may produce an iterator over output values, allowing either
/// filtering or flat mapping as part of the extraction.
///
/// This method exists for streams of batches without the corresponding arrangement.
/// If you have the arrangement, its `flat_map_ref` method is equivalent to this.
pub fn flat_map_batches<I, L>(stream: &Stream<G, Tr::Batch>, mut logic: L) -> Collection<G, I::Item, Tr::Diff>
where
I: IntoIterator,
I::Item: Data,
L: FnMut(Tr::Key<'_>, Tr::Val<'_>) -> I+'static,
{
stream.unary(Pipeline, "AsCollection", move |_,_| move |input, output| {
input.for_each(|time, data| {
let mut session = output.session(&time);
for wrapper in data.iter() {
let batch = &wrapper;
let mut cursor = batch.cursor();
while let Some(key) = cursor.get_key(batch) {
while let Some(val) = cursor.get_val(batch) {
for datum in logic(key, val) {
cursor.map_times(batch, |time, diff| {
session.give((datum.clone(), time.into_owned(), diff.into_owned()));
});
}
cursor.step_val(batch);
}
cursor.step_key(batch);
}
}
});
})
.as_collection()
}
}
use crate::difference::Multiply;
// Direct join implementations.
impl<G, T1> Arranged<G, T1>
where
G: Scope<Timestamp=T1::Time>,
T1: TraceReader + Clone + 'static,
{
/// A direct implementation of the `JoinCore::join_core` method.
pub fn join_core<T2,I,L>(&self, other: &Arranged<G,T2>, mut result: L) -> Collection<G,I::Item,<T1::Diff as Multiply<T2::Diff>>::Output>
where
T2: for<'a> TraceReader<Key<'a>=T1::Key<'a>,Time=T1::Time>+Clone+'static,
T1::Diff: Multiply<T2::Diff>,
<T1::Diff as Multiply<T2::Diff>>::Output: Semigroup+'static,
I: IntoIterator,
I::Item: Data,
L: FnMut(T1::Key<'_>,T1::Val<'_>,T2::Val<'_>)->I+'static
{
let result = move |k: T1::Key<'_>, v1: T1::Val<'_>, v2: T2::Val<'_>, t: &G::Timestamp, r1: &T1::Diff, r2: &T2::Diff| {
let t = t.clone();
let r = (r1.clone()).multiply(r2);
result(k, v1, v2).into_iter().map(move |d| (d, t.clone(), r.clone()))
};
self.join_core_internal_unsafe(other, result)
}
/// A direct implementation of the `JoinCore::join_core_internal_unsafe` method.
pub fn join_core_internal_unsafe<T2,I,L,D,ROut> (&self, other: &Arranged<G,T2>, mut result: L) -> Collection<G,D,ROut>
where
T2: for<'a> TraceReader<Key<'a>=T1::Key<'a>, Time=T1::Time>+Clone+'static,
D: Data,
ROut: Semigroup+'static,
I: IntoIterator<Item=(D, G::Timestamp, ROut)>,
L: FnMut(T1::Key<'_>, T1::Val<'_>,T2::Val<'_>,&G::Timestamp,&T1::Diff,&T2::Diff)->I+'static,
{
use crate::operators::join::join_traces;
join_traces::<_, _, _, _, crate::consolidation::ConsolidatingContainerBuilder<_>>(
self,
other,
move |k, v1, v2, t, d1, d2, c| {
for datum in result(k, v1, v2, t, d1, d2) {
c.give(datum);
}
}
)
.as_collection()
}
}
use crate::trace::cursor::IntoOwned;
// Direct reduce implementations.
use crate::difference::Abelian;
impl<G, T1> Arranged<G, T1>
where
G: Scope<Timestamp = T1::Time>,
T1: TraceReader + Clone + 'static,
{
/// A direct implementation of `ReduceCore::reduce_abelian`.
pub fn reduce_abelian<L, K, V, T2>(&self, name: &str, mut logic: L) -> Arranged<G, TraceAgent<T2>>
where
for<'a> T1::Key<'a>: IntoOwned<'a, Owned = K>,
T2: for<'a> Trace<Key<'a>= T1::Key<'a>, Time=T1::Time>+'static,
K: Ord + 'static,
V: Data,
for<'a> T2::Val<'a> : IntoOwned<'a, Owned = V>,
T2::Diff: Abelian,
T2::Batch: Batch,
<T2::Builder as Builder>::Input: Container + PushInto<((K, V), T2::Time, T2::Diff)>,
L: FnMut(T1::Key<'_>, &[(T1::Val<'_>, T1::Diff)], &mut Vec<(V, T2::Diff)>)+'static,
{
self.reduce_core::<_,K,V,T2>(name, move |key, input, output, change| {
if !input.is_empty() {
logic(key, input, change);
}
change.extend(output.drain(..).map(|(x,mut d)| { d.negate(); (x, d) }));
crate::consolidation::consolidate(change);
})
}
/// A direct implementation of `ReduceCore::reduce_core`.
pub fn reduce_core<L, K, V, T2>(&self, name: &str, logic: L) -> Arranged<G, TraceAgent<T2>>
where
for<'a> T1::Key<'a>: IntoOwned<'a, Owned = K>,
T2: for<'a> Trace<Key<'a>=T1::Key<'a>, Time=T1::Time>+'static,
K: Ord + 'static,
V: Data,
for<'a> T2::Val<'a> : IntoOwned<'a, Owned = V>,
T2::Batch: Batch,
<T2::Builder as Builder>::Input: Container + PushInto<((K, V), T2::Time, T2::Diff)>,
L: FnMut(T1::Key<'_>, &[(T1::Val<'_>, T1::Diff)], &mut Vec<(V, T2::Diff)>, &mut Vec<(V, T2::Diff)>)+'static,
{
use crate::operators::reduce::reduce_trace;
reduce_trace::<_,_,_,_,V,_>(self, name, logic)
}
}
impl<'a, G, Tr> Arranged<Child<'a, G, G::Timestamp>, Tr>
where
G: Scope<Timestamp=Tr::Time>,
Tr: TraceReader + Clone,
{
/// Brings an arranged collection out of a nested region.
///
/// This method only applies to *regions*, which are subscopes with the same timestamp
/// as their containing scope. In this case, the trace type does not need to change.
pub fn leave_region(&self) -> Arranged<G, Tr> {
use timely::dataflow::operators::Leave;
Arranged {
stream: self.stream.leave(),
trace: self.trace.clone(),
}
}
}
/// A type that can be arranged as if a collection of updates.
pub trait Arrange<G, C>
where
G: Scope,
G::Timestamp: Lattice,
{
/// Arranges updates into a shared trace.
fn arrange<Tr>(&self) -> Arranged<G, TraceAgent<Tr>>
where
Tr: Trace<Time=G::Timestamp> + 'static,
Tr::Batch: Batch,
Tr::Batcher: Batcher<Input=C>,
{
self.arrange_named("Arrange")
}
/// Arranges updates into a shared trace, with a supplied name.
fn arrange_named<Tr>(&self, name: &str) -> Arranged<G, TraceAgent<Tr>>
where
Tr: Trace<Time=G::Timestamp> + 'static,
Tr::Batch: Batch,
Tr::Batcher: Batcher<Input=C>,
;
}
impl<G, K, V, R> Arrange<G, Vec<((K, V), G::Timestamp, R)>> for Collection<G, (K, V), R>
where
G: Scope,
G::Timestamp: Lattice,
K: ExchangeData + Hashable,
V: ExchangeData,
R: ExchangeData + Semigroup,
{
fn arrange_named<Tr>(&self, name: &str) -> Arranged<G, TraceAgent<Tr>>
where
Tr: Trace<Time=G::Timestamp> + 'static,
Tr::Batch: Batch,
Tr::Batcher: Batcher<Input=Vec<((K, V), G::Timestamp, R)>>,
{
let exchange = Exchange::new(move |update: &((K,V),G::Timestamp,R)| (update.0).0.hashed().into());
arrange_core(&self.inner, exchange, name)
}
}
/// Arranges a stream of updates by a key, configured with a name and a parallelization contract.
///
/// This operator arranges a stream of values into a shared trace, whose contents it maintains.
/// It uses the supplied parallelization contract to distribute the data, which does not need to
/// be consistently by key (though this is the most common).
pub fn arrange_core<G, P, Tr>(stream: &StreamCore<G, <Tr::Batcher as Batcher>::Input>, pact: P, name: &str) -> Arranged<G, TraceAgent<Tr>>
where
G: Scope,
G::Timestamp: Lattice,
P: ParallelizationContract<G::Timestamp, <Tr::Batcher as Batcher>::Input>,
Tr: Trace<Time=G::Timestamp>+'static,
Tr::Batch: Batch,
<Tr::Batcher as Batcher>::Input: timely::Container,
{
// The `Arrange` operator is tasked with reacting to an advancing input
// frontier by producing the sequence of batches whose lower and upper
// bounds are those frontiers, containing updates at times greater or
// equal to lower and not greater or equal to upper.
//
// The operator uses its batch type's `Batcher`, which accepts update
// triples and responds to requests to "seal" batches (presented as new
// upper frontiers).
//
// Each sealed batch is presented to the trace, and if at all possible
// transmitted along the outgoing channel. Empty batches may not have
// a corresponding capability, as they are only retained for actual data
// held by the batcher, which may prevents the operator from sending an
// empty batch.
let mut reader: Option<TraceAgent<Tr>> = None;
// fabricate a data-parallel operator using the `unary_notify` pattern.
let reader_ref = &mut reader;
let scope = stream.scope();
let stream = stream.unary_frontier(pact, name, move |_capability, info| {
// Acquire a logger for arrange events.
let logger = {
let register = scope.log_register();
register.get::<crate::logging::DifferentialEvent>("differential/arrange")
};
// Where we will deposit received updates, and from which we extract batches.
let mut batcher = Tr::Batcher::new(logger.clone(), info.global_id);
// Capabilities for the lower envelope of updates in `batcher`.
let mut capabilities = Antichain::<Capability<G::Timestamp>>::new();
let activator = Some(scope.activator_for(info.address.clone()));
let mut empty_trace = Tr::new(info.clone(), logger.clone(), activator);
// If there is default exertion logic set, install it.
if let Some(exert_logic) = scope.config().get::<trace::ExertionLogic>("differential/default_exert_logic").cloned() {
empty_trace.set_exert_logic(exert_logic);
}
let (reader_local, mut writer) = TraceAgent::new(empty_trace, info, logger);
*reader_ref = Some(reader_local);
// Initialize to the minimal input frontier.
let mut prev_frontier = Antichain::from_elem(<G::Timestamp as Timestamp>::minimum());
move |input, output| {
// As we receive data, we need to (i) stash the data and (ii) keep *enough* capabilities.
// We don't have to keep all capabilities, but we need to be able to form output messages
// when we realize that time intervals are complete.
input.for_each(|cap, data| {
capabilities.insert(cap.retain());
batcher.push_container(data);
});
// The frontier may have advanced by multiple elements, which is an issue because
// timely dataflow currently only allows one capability per message. This means we
// must pretend to process the frontier advances one element at a time, batching
// and sending smaller bites than we might have otherwise done.
// Assert that the frontier never regresses.
assert!(PartialOrder::less_equal(&prev_frontier.borrow(), &input.frontier().frontier()));
// Test to see if strict progress has occurred, which happens whenever the new
// frontier isn't equal to the previous. It is only in this case that we have any
// data processing to do.
if prev_frontier.borrow() != input.frontier().frontier() {
// There are two cases to handle with some care:
//
// 1. If any held capabilities are not in advance of the new input frontier,
// we must carve out updates now in advance of the new input frontier and
// transmit them as batches, which requires appropriate *single* capabilites;
// Until timely dataflow supports multiple capabilities on messages, at least.
//
// 2. If there are no held capabilities in advance of the new input frontier,
// then there are no updates not in advance of the new input frontier and
// we can simply create an empty input batch with the new upper frontier
// and feed this to the trace agent (but not along the timely output).
// If there is at least one capability not in advance of the input frontier ...
if capabilities.elements().iter().any(|c| !input.frontier().less_equal(c.time())) {
let mut upper = Antichain::new(); // re-used allocation for sealing batches.
// For each capability not in advance of the input frontier ...
for (index, capability) in capabilities.elements().iter().enumerate() {
if !input.frontier().less_equal(capability.time()) {
// Assemble the upper bound on times we can commit with this capabilities.
// We must respect the input frontier, and *subsequent* capabilities, as
// we are pretending to retire the capability changes one by one.
upper.clear();
for time in input.frontier().frontier().iter() {
upper.insert(time.clone());
}
for other_capability in &capabilities.elements()[(index + 1) .. ] {
upper.insert(other_capability.time().clone());
}
// Extract updates not in advance of `upper`.
let batch = batcher.seal::<Tr::Builder>(upper.clone());
writer.insert(batch.clone(), Some(capability.time().clone()));
// send the batch to downstream consumers, empty or not.
output.session(&capabilities.elements()[index]).give(batch);
}
}
// Having extracted and sent batches between each capability and the input frontier,
// we should downgrade all capabilities to match the batcher's lower update frontier.
// This may involve discarding capabilities, which is fine as any new updates arrive
// in messages with new capabilities.
let mut new_capabilities = Antichain::new();
for time in batcher.frontier().iter() {
if let Some(capability) = capabilities.elements().iter().find(|c| c.time().less_equal(time)) {
new_capabilities.insert(capability.delayed(time));
}
else {
panic!("failed to find capability");
}
}
capabilities = new_capabilities;
}
else {
// Announce progress updates, even without data.
let _batch = batcher.seal::<Tr::Builder>(input.frontier().frontier().to_owned());
writer.seal(input.frontier().frontier().to_owned());
}
prev_frontier.clear();
prev_frontier.extend(input.frontier().frontier().iter().cloned());
}
writer.exert();
}
});
Arranged { stream, trace: reader.unwrap() }
}
impl<G: Scope, K: ExchangeData+Hashable, R: ExchangeData+Semigroup> Arrange<G, Vec<((K, ()), G::Timestamp, R)>> for Collection<G, K, R>
where
G::Timestamp: Lattice+Ord,
{
fn arrange_named<Tr>(&self, name: &str) -> Arranged<G, TraceAgent<Tr>>
where
Tr: Trace<Time=G::Timestamp> + 'static,
Tr::Batch: Batch,
Tr::Batcher: Batcher<Input=Vec<((K, ()), G::Timestamp, R)>>,
{
let exchange = Exchange::new(move |update: &((K,()),G::Timestamp,R)| (update.0).0.hashed().into());
arrange_core(&self.map(|k| (k, ())).inner, exchange, name)
}
}
/// Arranges something as `(Key,Val)` pairs according to a type `T` of trace.
///
/// This arrangement requires `Key: Hashable`, and uses the `hashed()` method to place keys in a hashed
/// map. This can result in many hash calls, and in some cases it may help to first transform `K` to the
/// pair `(u64, K)` of hash value and key.
pub trait ArrangeByKey<G: Scope, K: Data+Hashable, V: Data, R: Ord+Semigroup+'static>
where G::Timestamp: Lattice+Ord {
/// Arranges a collection of `(Key, Val)` records by `Key`.
///
/// This operator arranges a stream of values into a shared trace, whose contents it maintains.
/// This trace is current for all times completed by the output stream, which can be used to
/// safely identify the stable times and values in the trace.
fn arrange_by_key(&self) -> Arranged<G, TraceAgent<ValSpine<K, V, G::Timestamp, R>>>;
/// As `arrange_by_key` but with the ability to name the arrangement.
fn arrange_by_key_named(&self, name: &str) -> Arranged<G, TraceAgent<ValSpine<K, V, G::Timestamp, R>>>;
}
impl<G: Scope, K: ExchangeData+Hashable, V: ExchangeData, R: ExchangeData+Semigroup> ArrangeByKey<G, K, V, R> for Collection<G, (K,V), R>
where
G::Timestamp: Lattice+Ord
{
fn arrange_by_key(&self) -> Arranged<G, TraceAgent<ValSpine<K, V, G::Timestamp, R>>> {
self.arrange_by_key_named("ArrangeByKey")
}
fn arrange_by_key_named(&self, name: &str) -> Arranged<G, TraceAgent<ValSpine<K, V, G::Timestamp, R>>> {
self.arrange_named(name)
}
}
/// Arranges something as `(Key, ())` pairs according to a type `T` of trace.
///
/// This arrangement requires `Key: Hashable`, and uses the `hashed()` method to place keys in a hashed
/// map. This can result in many hash calls, and in some cases it may help to first transform `K` to the
/// pair `(u64, K)` of hash value and key.
pub trait ArrangeBySelf<G: Scope, K: Data+Hashable, R: Ord+Semigroup+'static>
where
G::Timestamp: Lattice+Ord
{
/// Arranges a collection of `Key` records by `Key`.
///
/// This operator arranges a collection of records into a shared trace, whose contents it maintains.
/// This trace is current for all times complete in the output stream, which can be used to safely
/// identify the stable times and values in the trace.
fn arrange_by_self(&self) -> Arranged<G, TraceAgent<KeySpine<K, G::Timestamp, R>>>;
/// As `arrange_by_self` but with the ability to name the arrangement.
fn arrange_by_self_named(&self, name: &str) -> Arranged<G, TraceAgent<KeySpine<K, G::Timestamp, R>>>;
}
impl<G: Scope, K: ExchangeData+Hashable, R: ExchangeData+Semigroup> ArrangeBySelf<G, K, R> for Collection<G, K, R>
where
G::Timestamp: Lattice+Ord
{
fn arrange_by_self(&self) -> Arranged<G, TraceAgent<KeySpine<K, G::Timestamp, R>>> {
self.arrange_by_self_named("ArrangeBySelf")
}
fn arrange_by_self_named(&self, name: &str) -> Arranged<G, TraceAgent<KeySpine<K, G::Timestamp, R>>> {
self.map(|k| (k, ()))
.arrange_named(name)
}
}