mz_compute/render/context.rs
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// Copyright Materialize, Inc. and contributors. All rights reserved.
//
// Use of this software is governed by the Business Source License
// included in the LICENSE file.
//
// As of the Change Date specified in that file, in accordance with
// the Business Source License, use of this software will be governed
// by the Apache License, Version 2.0.
//! Management of dataflow-local state, like arrangements, while building a
//! dataflow.
use std::collections::BTreeMap;
use std::rc::{Rc, Weak};
use std::sync::mpsc;
use columnar::Columnar;
use differential_dataflow::consolidation::ConsolidatingContainerBuilder;
use differential_dataflow::lattice::Lattice;
use differential_dataflow::operators::arrange::Arranged;
use differential_dataflow::trace::cursor::IntoOwned;
use differential_dataflow::trace::{BatchReader, Cursor, TraceReader};
use differential_dataflow::{AsCollection, Collection, Data};
use mz_compute_types::dataflows::DataflowDescription;
use mz_compute_types::dyncfgs::ENABLE_COMPUTE_RENDER_FUELED_AS_SPECIFIC_COLLECTION;
use mz_compute_types::plan::{AvailableCollections, LirId};
use mz_dyncfg::ConfigSet;
use mz_expr::{Id, MapFilterProject, MirScalarExpr};
use mz_repr::fixed_length::ToDatumIter;
use mz_repr::{DatumVec, DatumVecBorrow, Diff, GlobalId, Row, RowArena, SharedRow};
use mz_storage_types::controller::CollectionMetadata;
use mz_storage_types::errors::DataflowError;
use mz_timely_util::containers::{columnar_exchange, Col2ValBatcher, ColumnBuilder};
use mz_timely_util::operator::{CollectionExt, StreamExt};
use timely::container::columnation::Columnation;
use timely::container::CapacityContainerBuilder;
use timely::dataflow::channels::pact::{ExchangeCore, Pipeline};
use timely::dataflow::operators::generic::OutputHandleCore;
use timely::dataflow::operators::Capability;
use timely::dataflow::scopes::Child;
use timely::dataflow::{Scope, Stream};
use timely::progress::timestamp::Refines;
use timely::progress::{Antichain, Timestamp};
use timely::Container;
use tracing::error;
use crate::compute_state::{ComputeState, HydrationEvent};
use crate::extensions::arrange::{KeyCollection, MzArrange, MzArrangeCore};
use crate::render::errors::ErrorLogger;
use crate::render::{LinearJoinSpec, RenderTimestamp};
use crate::row_spine::{DatumSeq, RowRowBuilder};
use crate::typedefs::{
ErrAgent, ErrBatcher, ErrBuilder, ErrEnter, ErrSpine, RowRowAgent, RowRowEnter, RowRowSpine,
};
/// Dataflow-local collections and arrangements.
///
/// A context means to wrap available data assets and present them in an easy-to-use manner.
/// These assets include dataflow-local collections and arrangements, as well as imported
/// arrangements from outside the dataflow.
///
/// Context has two timestamp types, one from `S::Timestamp` and one from `T`, where the
/// former must refine the latter. The former is the timestamp used by the scope in question,
/// and the latter is the timestamp of imported traces. The two may be different in the case
/// of regions or iteration.
pub struct Context<S: Scope, T = mz_repr::Timestamp>
where
T: Timestamp + Lattice + Columnation,
S::Timestamp: Lattice + Refines<T> + Columnation,
{
/// The scope within which all managed collections exist.
///
/// It is an error to add any collections not contained in this scope.
pub(crate) scope: S,
/// The debug name of the dataflow associated with this context.
pub debug_name: String,
/// The Timely ID of the dataflow associated with this context.
pub dataflow_id: usize,
/// Frontier before which updates should not be emitted.
///
/// We *must* apply it to sinks, to ensure correct outputs.
/// We *should* apply it to sources and imported traces, because it improves performance.
pub as_of_frontier: Antichain<T>,
/// Frontier after which updates should not be emitted.
/// Used to limit the amount of work done when appropriate.
pub until: Antichain<T>,
/// Bindings of identifiers to collections.
pub bindings: BTreeMap<Id, CollectionBundle<S, T>>,
/// A token that operators can probe to know whether the dataflow is shutting down.
pub(super) shutdown_token: ShutdownToken,
/// A logger that operators can use to report hydration events.
///
/// `None` if no hydration events should be logged in this context.
pub(super) hydration_logger: Option<HydrationLogger>,
/// The logger, from Timely's logging framework, if logs are enabled.
pub(super) compute_logger: Option<crate::logging::compute::Logger>,
/// Specification for rendering linear joins.
pub(super) linear_join_spec: LinearJoinSpec,
/// The expiration time for dataflows in this context. The output's frontier should never advance
/// past this frontier, except the empty frontier.
pub dataflow_expiration: Antichain<T>,
/// The config set for this context.
pub config_set: Rc<ConfigSet>,
}
impl<S: Scope> Context<S>
where
S::Timestamp: Lattice + Refines<mz_repr::Timestamp> + Columnation,
{
/// Creates a new empty Context.
pub fn for_dataflow_in<Plan>(
dataflow: &DataflowDescription<Plan, CollectionMetadata>,
scope: S,
compute_state: &ComputeState,
until: Antichain<mz_repr::Timestamp>,
dataflow_expiration: Antichain<mz_repr::Timestamp>,
) -> Self {
use mz_ore::collections::CollectionExt as IteratorExt;
let dataflow_id = *scope.addr().into_first();
let as_of_frontier = dataflow
.as_of
.clone()
.unwrap_or_else(|| Antichain::from_elem(Timestamp::minimum()));
// Skip operator hydration logging for transient dataflows. We do this to avoid overhead
// for slow-path peeks, but it also affects subscribes. For now that seems fine, but we may
// want to reconsider in the future.
//
// Similarly, we won't capture a compute_logger for logging LIR->address mappings for transient dataflows.
let (hydration_logger, compute_logger) = if dataflow.is_transient() {
(None, None)
} else {
(
Some(HydrationLogger {
export_ids: dataflow.export_ids().collect(),
tx: compute_state.hydration_tx.clone(),
}),
compute_state.compute_logger.clone(),
)
};
Self {
scope,
debug_name: dataflow.debug_name.clone(),
dataflow_id,
as_of_frontier,
until,
bindings: BTreeMap::new(),
shutdown_token: Default::default(),
hydration_logger,
compute_logger,
linear_join_spec: compute_state.linear_join_spec,
dataflow_expiration,
config_set: Rc::clone(&compute_state.worker_config),
}
}
}
impl<S: Scope, T> Context<S, T>
where
T: Timestamp + Lattice + Columnation,
S::Timestamp: Lattice + Refines<T> + Columnation,
{
/// Insert a collection bundle by an identifier.
///
/// This is expected to be used to install external collections (sources, indexes, other views),
/// as well as for `Let` bindings of local collections.
pub fn insert_id(
&mut self,
id: Id,
collection: CollectionBundle<S, T>,
) -> Option<CollectionBundle<S, T>> {
self.bindings.insert(id, collection)
}
/// Remove a collection bundle by an identifier.
///
/// The primary use of this method is uninstalling `Let` bindings.
pub fn remove_id(&mut self, id: Id) -> Option<CollectionBundle<S, T>> {
self.bindings.remove(&id)
}
/// Melds a collection bundle to whatever exists.
pub fn update_id(&mut self, id: Id, collection: CollectionBundle<S, T>) {
if !self.bindings.contains_key(&id) {
self.bindings.insert(id, collection);
} else {
let binding = self
.bindings
.get_mut(&id)
.expect("Binding verified to exist");
if collection.collection.is_some() {
binding.collection = collection.collection;
}
for (key, flavor) in collection.arranged.into_iter() {
binding.arranged.insert(key, flavor);
}
}
}
/// Look up a collection bundle by an identifier.
pub fn lookup_id(&self, id: Id) -> Option<CollectionBundle<S, T>> {
self.bindings.get(&id).cloned()
}
pub(super) fn error_logger(&self) -> ErrorLogger {
ErrorLogger::new(self.shutdown_token.clone(), self.debug_name.clone())
}
}
impl<S: Scope, T> Context<S, T>
where
T: Timestamp + Lattice + Columnation,
S::Timestamp: Lattice + Refines<T> + Columnation,
{
/// Brings the underlying arrangements and collections into a region.
pub fn enter_region<'a>(
&self,
region: &Child<'a, S, S::Timestamp>,
bindings: Option<&std::collections::BTreeSet<Id>>,
) -> Context<Child<'a, S, S::Timestamp>, T> {
let bindings = self
.bindings
.iter()
.filter(|(key, _)| bindings.as_ref().map(|b| b.contains(key)).unwrap_or(true))
.map(|(key, bundle)| (*key, bundle.enter_region(region)))
.collect();
Context {
scope: region.clone(),
debug_name: self.debug_name.clone(),
dataflow_id: self.dataflow_id.clone(),
as_of_frontier: self.as_of_frontier.clone(),
until: self.until.clone(),
shutdown_token: self.shutdown_token.clone(),
hydration_logger: self.hydration_logger.clone(),
compute_logger: self.compute_logger.clone(),
linear_join_spec: self.linear_join_spec.clone(),
bindings,
dataflow_expiration: self.dataflow_expiration.clone(),
config_set: Rc::clone(&self.config_set),
}
}
}
/// Convenient wrapper around an optional `Weak` instance that can be used to check whether a
/// datalow is shutting down.
///
/// Instances created through the `Default` impl act as if the dataflow never shuts down.
/// Instances created through [`ShutdownToken::new`] defer to the wrapped token.
#[derive(Clone, Default)]
pub(super) struct ShutdownToken(Option<Weak<()>>);
impl ShutdownToken {
/// Construct a `ShutdownToken` instance that defers to `token`.
pub(super) fn new(token: Weak<()>) -> Self {
Self(Some(token))
}
/// Probe the token for dataflow shutdown.
///
/// This method is meant to be used with the `?` operator: It returns `None` if the dataflow is
/// in the process of shutting down and `Some` otherwise.
pub(super) fn probe(&self) -> Option<()> {
match &self.0 {
Some(t) => t.upgrade().map(|_| ()),
None => Some(()),
}
}
/// Returns whether the dataflow is in the process of shutting down.
pub(super) fn in_shutdown(&self) -> bool {
self.probe().is_none()
}
/// Returns a reference to the wrapped `Weak`.
pub(crate) fn get_inner(&self) -> Option<&Weak<()>> {
self.0.as_ref()
}
}
/// A logger for operator hydration events emitted for a dataflow export.
#[derive(Clone)]
pub(super) struct HydrationLogger {
export_ids: Vec<GlobalId>,
tx: mpsc::Sender<HydrationEvent>,
}
impl HydrationLogger {
/// Log a hydration event for the identified LIR node.
///
/// The expectation is that rendering code arranges for `hydrated = false` to be logged for
/// each LIR node when a dataflow is first created. Then `hydrated = true` should be logged as
/// operators become hydrated.
pub fn log(&self, lir_id: LirId, hydrated: bool) {
for &export_id in &self.export_ids {
let event = HydrationEvent {
export_id,
lir_id,
hydrated,
};
if self.tx.send(event).is_err() {
error!("hydration event receiver dropped unexpectely");
}
}
}
}
/// Describes flavor of arrangement: local or imported trace.
#[derive(Clone)]
pub enum ArrangementFlavor<S: Scope, T = mz_repr::Timestamp>
where
T: Timestamp + Lattice + Columnation,
S::Timestamp: Lattice + Refines<T> + Columnation,
{
/// A dataflow-local arrangement.
Local(
Arranged<S, RowRowAgent<S::Timestamp, Diff>>,
Arranged<S, ErrAgent<S::Timestamp, Diff>>,
),
/// An imported trace from outside the dataflow.
///
/// The `GlobalId` identifier exists so that exports of this same trace
/// can refer back to and depend on the original instance.
Trace(
GlobalId,
Arranged<S, RowRowEnter<T, Diff, S::Timestamp>>,
Arranged<S, ErrEnter<T, S::Timestamp>>,
),
}
impl<S: Scope, T> ArrangementFlavor<S, T>
where
T: Timestamp + Lattice + Columnation,
S::Timestamp: Lattice + Refines<T> + Columnation,
{
/// Presents `self` as a stream of updates.
///
/// Deprecated: This function is not fueled and hence risks flattening the whole arrangement.
///
/// This method presents the contents as they are, without further computation.
/// If you have logic that could be applied to each record, consider using the
/// `flat_map` methods which allows this and can reduce the work done.
#[deprecated(note = "Use `flat_map` instead.")]
pub fn as_collection(&self) -> (Collection<S, Row, Diff>, Collection<S, DataflowError, Diff>) {
let mut datums = DatumVec::new();
let logic = move |k: DatumSeq, v: DatumSeq| {
let mut datums_borrow = datums.borrow();
datums_borrow.extend(k);
datums_borrow.extend(v);
SharedRow::pack(&**datums_borrow)
};
match &self {
ArrangementFlavor::Local(oks, errs) => (
oks.as_collection(logic),
errs.as_collection(|k, &()| k.clone()),
),
ArrangementFlavor::Trace(_, oks, errs) => (
oks.as_collection(logic),
errs.as_collection(|k, &()| k.clone()),
),
}
}
/// Constructs and applies logic to elements of `self` and returns the results.
///
/// The `logic` receives a vector of datums, a timestamp, and a diff, and produces
/// an iterator of `(D, S::Timestamp, Diff)` updates.
///
/// If `key` is set, this is a promise that `logic` will produce no results on
/// records for which the key does not evaluate to the value. This is used to
/// leap directly to exactly those records.
pub fn flat_map<D, I, L>(
&self,
key: Option<Row>,
mut logic: L,
) -> (Stream<S, I::Item>, Collection<S, DataflowError, Diff>)
where
I: IntoIterator<Item = (D, S::Timestamp, Diff)>,
D: Data,
L: for<'a, 'b> FnMut(&'a mut DatumVecBorrow<'b>, S::Timestamp, Diff) -> I + 'static,
{
// Set a number of tuples after which the operator should yield.
// This allows us to remain responsive even when enumerating a substantial
// arrangement, as well as provides time to accumulate our produced output.
let refuel = 1000000;
let mut datums = DatumVec::new();
let logic = move |k: DatumSeq, v: DatumSeq, t, d| {
let mut datums_borrow = datums.borrow();
datums_borrow.extend(k);
datums_borrow.extend(v);
logic(&mut datums_borrow, t, d)
};
match &self {
ArrangementFlavor::Local(oks, errs) => {
let oks = CollectionBundle::<S, T>::flat_map_core(oks, key, logic, refuel);
let errs = errs.as_collection(|k, &()| k.clone());
(oks, errs)
}
ArrangementFlavor::Trace(_, oks, errs) => {
let oks = CollectionBundle::<S, T>::flat_map_core(oks, key, logic, refuel);
let errs = errs.as_collection(|k, &()| k.clone());
(oks, errs)
}
}
}
}
impl<S: Scope, T> ArrangementFlavor<S, T>
where
T: Timestamp + Lattice + Columnation,
S::Timestamp: Lattice + Refines<T> + Columnation,
{
/// The scope containing the collection bundle.
pub fn scope(&self) -> S {
match self {
ArrangementFlavor::Local(oks, _errs) => oks.stream.scope(),
ArrangementFlavor::Trace(_gid, oks, _errs) => oks.stream.scope(),
}
}
/// Brings the arrangement flavor into a region.
pub fn enter_region<'a>(
&self,
region: &Child<'a, S, S::Timestamp>,
) -> ArrangementFlavor<Child<'a, S, S::Timestamp>, T> {
match self {
ArrangementFlavor::Local(oks, errs) => {
ArrangementFlavor::Local(oks.enter_region(region), errs.enter_region(region))
}
ArrangementFlavor::Trace(gid, oks, errs) => {
ArrangementFlavor::Trace(*gid, oks.enter_region(region), errs.enter_region(region))
}
}
}
}
impl<'a, S: Scope, T> ArrangementFlavor<Child<'a, S, S::Timestamp>, T>
where
T: Timestamp + Lattice + Columnation,
S::Timestamp: Lattice + Refines<T> + Columnation,
{
/// Extracts the arrangement flavor from a region.
pub fn leave_region(&self) -> ArrangementFlavor<S, T> {
match self {
ArrangementFlavor::Local(oks, errs) => {
ArrangementFlavor::Local(oks.leave_region(), errs.leave_region())
}
ArrangementFlavor::Trace(gid, oks, errs) => {
ArrangementFlavor::Trace(*gid, oks.leave_region(), errs.leave_region())
}
}
}
}
/// A bundle of the various ways a collection can be represented.
///
/// This type maintains the invariant that it does contain at least one valid
/// source of data, either a collection or at least one arrangement.
#[derive(Clone)]
pub struct CollectionBundle<S: Scope, T = mz_repr::Timestamp>
where
T: Timestamp + Lattice + Columnation,
S::Timestamp: Lattice + Refines<T> + Columnation,
{
pub collection: Option<(Collection<S, Row, Diff>, Collection<S, DataflowError, Diff>)>,
pub arranged: BTreeMap<Vec<MirScalarExpr>, ArrangementFlavor<S, T>>,
}
impl<S: Scope, T: Lattice> CollectionBundle<S, T>
where
T: Timestamp + Lattice + Columnation,
S::Timestamp: Lattice + Refines<T> + Columnation,
{
/// Construct a new collection bundle from update streams.
pub fn from_collections(
oks: Collection<S, Row, Diff>,
errs: Collection<S, DataflowError, Diff>,
) -> Self {
Self {
collection: Some((oks, errs)),
arranged: BTreeMap::default(),
}
}
/// Inserts arrangements by the expressions on which they are keyed.
pub fn from_expressions(
exprs: Vec<MirScalarExpr>,
arrangements: ArrangementFlavor<S, T>,
) -> Self {
let mut arranged = BTreeMap::new();
arranged.insert(exprs, arrangements);
Self {
collection: None,
arranged,
}
}
/// Inserts arrangements by the columns on which they are keyed.
pub fn from_columns<I: IntoIterator<Item = usize>>(
columns: I,
arrangements: ArrangementFlavor<S, T>,
) -> Self {
let mut keys = Vec::new();
for column in columns {
keys.push(MirScalarExpr::Column(column));
}
Self::from_expressions(keys, arrangements)
}
/// The scope containing the collection bundle.
pub fn scope(&self) -> S {
if let Some((oks, _errs)) = &self.collection {
oks.inner.scope()
} else {
self.arranged
.values()
.next()
.expect("Must contain a valid collection")
.scope()
}
}
/// Brings the collection bundle into a region.
pub fn enter_region<'a>(
&self,
region: &Child<'a, S, S::Timestamp>,
) -> CollectionBundle<Child<'a, S, S::Timestamp>, T> {
CollectionBundle {
collection: self
.collection
.as_ref()
.map(|(oks, errs)| (oks.enter_region(region), errs.enter_region(region))),
arranged: self
.arranged
.iter()
.map(|(key, bundle)| (key.clone(), bundle.enter_region(region)))
.collect(),
}
}
}
impl<'a, S: Scope, T> CollectionBundle<Child<'a, S, S::Timestamp>, T>
where
T: Timestamp + Lattice + Columnation,
S::Timestamp: Lattice + Refines<T> + Columnation,
{
/// Extracts the collection bundle from a region.
pub fn leave_region(&self) -> CollectionBundle<S, T> {
CollectionBundle {
collection: self
.collection
.as_ref()
.map(|(oks, errs)| (oks.leave_region(), errs.leave_region())),
arranged: self
.arranged
.iter()
.map(|(key, bundle)| (key.clone(), bundle.leave_region()))
.collect(),
}
}
}
impl<S: Scope, T> CollectionBundle<S, T>
where
T: Timestamp + Lattice + Columnation,
S::Timestamp: Lattice + Refines<T> + Columnation,
{
/// Asserts that the arrangement for a specific key
/// (or the raw collection for no key) exists,
/// and returns the corresponding collection.
///
/// This returns the collection as-is, without
/// doing any unthinning transformation.
/// Therefore, it should be used when the appropriate transformation
/// was planned as part of a following MFP.
///
/// If `key` is specified, the function converts the arrangement to a collection. It uses either
/// the fueled `flat_map` or `as_collection` method, depending on the flag
/// [`ENABLE_COMPUTE_RENDER_FUELED_AS_SPECIFIC_COLLECTION`].
pub fn as_specific_collection(
&self,
key: Option<&[MirScalarExpr]>,
config_set: &ConfigSet,
) -> (Collection<S, Row, Diff>, Collection<S, DataflowError, Diff>) {
// Any operator that uses this method was told to use a particular
// collection during LIR planning, where we should have made
// sure that that collection exists.
//
// If it doesn't, we panic.
match key {
None => self
.collection
.clone()
.expect("The unarranged collection doesn't exist."),
Some(key) => {
let arranged = self.arranged.get(key).unwrap_or_else(|| {
panic!("The collection arranged by {:?} doesn't exist.", key)
});
if ENABLE_COMPUTE_RENDER_FUELED_AS_SPECIFIC_COLLECTION.get(config_set) {
let (ok, err) = arranged.flat_map(None, |borrow, t, r| {
Some((SharedRow::pack(borrow.iter()), t, r))
});
(ok.as_collection(), err)
} else {
#[allow(deprecated)]
arranged.as_collection()
}
}
}
}
/// Constructs and applies logic to elements of a collection and returns the results.
///
/// `constructor` takes a permutation and produces the logic to apply on elements. The logic
/// conceptually receives `(&Row, &Row)` pairs in the form of a slice. Only after borrowing
/// the elements and applying the permutation the datums will be in the expected order.
///
/// If `key_val` is set, this is a promise that `logic` will produce no results on
/// records for which the key does not evaluate to the value. This is used when we
/// have an arrangement by that key to leap directly to exactly those records.
/// It is important that `logic` still guard against data that does not satisfy
/// this constraint, as this method does not statically know that it will have
/// that arrangement.
pub fn flat_map<D, I, L>(
&self,
key_val: Option<(Vec<MirScalarExpr>, Option<Row>)>,
mut logic: L,
) -> (Stream<S, I::Item>, Collection<S, DataflowError, Diff>)
where
I: IntoIterator<Item = (D, S::Timestamp, Diff)>,
D: Data,
L: for<'a> FnMut(&'a mut DatumVecBorrow<'_>, S::Timestamp, Diff) -> I + 'static,
{
// If `key_val` is set, we should have to use the corresponding arrangement.
// If there isn't one, that implies an error in the contract between
// key-production and available arrangements.
if let Some((key, val)) = key_val {
self.arrangement(&key)
.expect("Should have ensured during planning that this arrangement exists.")
.flat_map(val, logic)
} else {
use timely::dataflow::operators::Map;
let (oks, errs) = self
.collection
.clone()
.expect("Invariant violated: CollectionBundle contains no collection.");
let mut datums = DatumVec::new();
let oks = oks
.inner
.flat_map(move |(v, t, d)| logic(&mut datums.borrow_with(&v), t, d));
(oks, errs)
}
}
/// Factored out common logic for using literal keys in general traces.
///
/// This logic is sufficiently interesting that we want to write it only
/// once, and thereby avoid any skew in the two uses of the logic.
///
/// The function presents the contents of the trace as `(key, value, time, delta)` tuples,
/// where key and value are potentially specialized, but convertible into rows.
fn flat_map_core<Tr, K, D, I, L>(
trace: &Arranged<S, Tr>,
key: Option<K>,
mut logic: L,
refuel: usize,
) -> Stream<S, I::Item>
where
for<'a> Tr::Key<'a>: ToDatumIter + IntoOwned<'a, Owned = K>,
for<'a> Tr::Val<'a>: ToDatumIter,
Tr: TraceReader<Time = S::Timestamp, Diff = mz_repr::Diff> + Clone + 'static,
K: PartialEq + 'static,
I: IntoIterator<Item = (D, Tr::Time, Tr::Diff)>,
D: Data,
L: FnMut(Tr::Key<'_>, Tr::Val<'_>, S::Timestamp, mz_repr::Diff) -> I + 'static,
{
use differential_dataflow::consolidation::ConsolidatingContainerBuilder as CB;
let mode = if key.is_some() { "index" } else { "scan" };
let name = format!("ArrangementFlatMap({})", mode);
use timely::dataflow::operators::Operator;
trace
.stream
.unary::<CB<_>, _, _, _>(Pipeline, &name, move |_, info| {
// Acquire an activator to reschedule the operator when it has unfinished work.
let activator = trace.stream.scope().activator_for(info.address);
// Maintain a list of work to do, cursor to navigate and process.
let mut todo = std::collections::VecDeque::new();
move |input, output| {
// First, dequeue all batches.
input.for_each(|time, data| {
let capability = time.retain();
for batch in data.iter() {
// enqueue a capability, cursor, and batch.
todo.push_back(PendingWork::new(
capability.clone(),
batch.cursor(),
batch.clone(),
));
}
});
// Second, make progress on `todo`.
let mut fuel = refuel;
while !todo.is_empty() && fuel > 0 {
todo.front_mut()
.unwrap()
.do_work(&key, &mut logic, &mut fuel, output);
if fuel > 0 {
todo.pop_front();
}
}
// If we have not finished all work, re-activate the operator.
if !todo.is_empty() {
activator.activate();
}
}
})
}
/// Look up an arrangement by the expressions that form the key.
///
/// The result may be `None` if no such arrangement exists, or it may be one of many
/// "arrangement flavors" that represent the types of arranged data we might have.
pub fn arrangement(&self, key: &[MirScalarExpr]) -> Option<ArrangementFlavor<S, T>> {
self.arranged.get(key).map(|x| x.clone())
}
}
impl<S, T> CollectionBundle<S, T>
where
T: Timestamp + Lattice + Columnation,
S: Scope,
S::Timestamp: Refines<T> + RenderTimestamp,
<S::Timestamp as Columnar>::Container: Clone + Send,
for<'a> <S::Timestamp as Columnar>::Ref<'a>: Ord + Copy,
{
/// Presents `self` as a stream of updates, having been subjected to `mfp`.
///
/// This operator is able to apply the logic of `mfp` early, which can substantially
/// reduce the amount of data produced when `mfp` is non-trivial.
///
/// The `key_val` argument, when present, indicates that a specific arrangement should
/// be used, and if, in addition, the `val` component is present,
/// that we can seek to the supplied row.
pub fn as_collection_core(
&self,
mut mfp: MapFilterProject,
key_val: Option<(Vec<MirScalarExpr>, Option<Row>)>,
until: Antichain<mz_repr::Timestamp>,
config_set: &ConfigSet,
) -> (
Collection<S, mz_repr::Row, Diff>,
Collection<S, DataflowError, Diff>,
) {
mfp.optimize();
let mfp_plan = mfp.into_plan().unwrap();
// If the MFP is trivial, we can just call `as_collection`.
// In the case that we weren't going to apply the `key_val` optimization,
// this path results in a slightly smaller and faster
// dataflow graph, and is intended to fix
// https://github.com/MaterializeInc/database-issues/issues/3111
let has_key_val = if let Some((_key, Some(_val))) = &key_val {
true
} else {
false
};
if mfp_plan.is_identity() && !has_key_val {
let key = key_val.map(|(k, _v)| k);
return self.as_specific_collection(key.as_deref(), config_set);
}
let (stream, errors) = self.flat_map(key_val, {
let mut datum_vec = DatumVec::new();
// Wrap in an `Rc` so that lifetimes work out.
let until = std::rc::Rc::new(until);
move |row_datums, time, diff| {
let binding = SharedRow::get();
let mut row_builder = binding.borrow_mut();
let until = std::rc::Rc::clone(&until);
let temp_storage = RowArena::new();
let row_iter = row_datums.iter();
let mut datums_local = datum_vec.borrow();
datums_local.extend(row_iter);
let time = time.clone();
let event_time = time.event_time();
mfp_plan
.evaluate(
&mut datums_local,
&temp_storage,
event_time,
diff.clone(),
move |time| !until.less_equal(time),
&mut row_builder,
)
.map(move |x| match x {
Ok((row, event_time, diff)) => {
// Copy the whole time, and re-populate event time.
let mut time: S::Timestamp = time.clone();
*time.event_time_mut() = event_time;
(Ok(row), time, diff)
}
Err((e, event_time, diff)) => {
// Copy the whole time, and re-populate event time.
let mut time: S::Timestamp = time.clone();
*time.event_time_mut() = event_time;
(Err(e), time, diff)
}
})
}
});
use differential_dataflow::AsCollection;
let (oks, errs) = stream
.as_collection()
.map_fallible::<CapacityContainerBuilder<_>, CapacityContainerBuilder<_>, _, _, _>(
"OkErr",
|x| x,
);
(oks, errors.concat(&errs))
}
pub fn ensure_collections(
mut self,
collections: AvailableCollections,
input_key: Option<Vec<MirScalarExpr>>,
input_mfp: MapFilterProject,
until: Antichain<mz_repr::Timestamp>,
config_set: &ConfigSet,
) -> Self {
if collections == Default::default() {
return self;
}
// Cache collection to avoid reforming it each time.
//
// TODO(mcsherry): In theory this could be faster run out of another arrangement,
// as the `map_fallible` that follows could be run against an arrangement itself.
//
// Note(btv): If we ever do that, we would then only need to make the raw collection here
// if `collections.raw` is true.
// We need the collection if either (1) it is explicitly demanded, or (2) we are going to render any arrangement
let form_raw_collection = collections.raw
|| collections
.arranged
.iter()
.any(|(key, _, _)| !self.arranged.contains_key(key));
if form_raw_collection && self.collection.is_none() {
self.collection = Some(self.as_collection_core(
input_mfp,
input_key.map(|k| (k, None)),
until,
config_set,
));
}
for (key, _, thinning) in collections.arranged {
if !self.arranged.contains_key(&key) {
// TODO: Consider allowing more expressive names.
let name = format!("ArrangeBy[{:?}]", key);
let (oks, errs) = self
.collection
.clone()
.expect("Collection constructed above");
let (oks, errs_keyed) =
Self::arrange_collection(&name, oks, key.clone(), thinning.clone());
let errs: KeyCollection<_, _, _> = errs.concat(&errs_keyed).into();
let errs = errs.mz_arrange::<ErrBatcher<_, _>, ErrBuilder<_, _>, ErrSpine<_, _>>(
&format!("{}-errors", name),
);
self.arranged
.insert(key, ArrangementFlavor::Local(oks, errs));
}
}
self
}
/// Builds an arrangement from a collection, using the specified key and value thinning.
///
/// The arrangement's key is based on the `key` expressions, and the value the input with
/// the `thinning` applied to it. It selects which of the input columns are included in the
/// value of the arrangement. The thinning is in support of permuting arrangements such that
/// columns in the key are not included in the value.
fn arrange_collection(
name: &String,
oks: Collection<S, Row, i64>,
key: Vec<MirScalarExpr>,
thinning: Vec<usize>,
) -> (
Arranged<S, RowRowAgent<S::Timestamp, Diff>>,
Collection<S, DataflowError, i64>,
) {
// The following `unary_fallible` implements a `map_fallible`, but produces columnar updates
// for the ok stream. The `map_fallible` cannot be used here because the closure cannot
// return references, which is what we need to push into columnar streams. Instead, we use
// a bespoke operator that also optimizes reuse of allocations across individual updates.
let (oks, errs) = oks
.inner
.unary_fallible::<ColumnBuilder<((Row, Row), S::Timestamp, i64)>, _, _, _>(
Pipeline,
"FormArrangementKey",
move |_, _| {
Box::new(move |input, ok, err| {
let mut key_buf = Row::default();
let mut val_buf = Row::default();
let mut datums = DatumVec::new();
let temp_storage = RowArena::new();
while let Some((time, data)) = input.next() {
let mut ok_session = ok.session_with_builder(&time);
let mut err_session = err.session(&time);
for (row, time, diff) in data.iter() {
temp_storage.clear();
let datums = datums.borrow_with(row);
let key_iter = key.iter().map(|k| k.eval(&datums, &temp_storage));
match key_buf.packer().try_extend(key_iter) {
Ok(()) => {
let val_datum_iter = thinning.iter().map(|c| datums[*c]);
val_buf.packer().extend(val_datum_iter);
ok_session.give(((&*key_buf, &*val_buf), time, diff));
}
Err(e) => {
err_session.give((e.into(), time.clone(), *diff));
}
}
}
}
})
},
);
let oks = oks
.mz_arrange_core::<_, Col2ValBatcher<_, _,_, _>, RowRowBuilder<_, _>, RowRowSpine<_, _>>(
ExchangeCore::<ColumnBuilder<_>, _>::new_core(columnar_exchange::<Row, Row, S::Timestamp, Diff>),name
);
(oks, errs.as_collection())
}
}
struct PendingWork<C>
where
C: Cursor,
C::Time: Timestamp,
{
capability: Capability<C::Time>,
cursor: C,
batch: C::Storage,
}
impl<C> PendingWork<C>
where
C: Cursor,
C::Time: Timestamp,
{
/// Create a new bundle of pending work, from the capability, cursor, and backing storage.
fn new(capability: Capability<C::Time>, cursor: C, batch: C::Storage) -> Self {
Self {
capability,
cursor,
batch,
}
}
/// Perform roughly `fuel` work through the cursor, applying `logic` and sending results to `output`.
fn do_work<I, D, L, K>(
&mut self,
key: &Option<K>,
logic: &mut L,
fuel: &mut usize,
output: &mut OutputHandleCore<
'_,
C::Time,
ConsolidatingContainerBuilder<Vec<I::Item>>,
timely::dataflow::channels::pushers::Tee<C::Time, Vec<I::Item>>,
>,
) where
I: IntoIterator<Item = (D, C::Time, C::Diff)>,
D: Data,
L: FnMut(C::Key<'_>, C::Val<'_>, C::Time, C::Diff) -> I + 'static,
K: PartialEq + Sized,
for<'a> C::Key<'a>: IntoOwned<'a, Owned = K>,
{
use differential_dataflow::consolidation::consolidate;
// Attempt to make progress on this batch.
let mut work: usize = 0;
let mut session = output.session_with_builder(&self.capability);
let mut buffer = Vec::new();
if let Some(key) = key {
if self
.cursor
.get_key(&self.batch)
.map(|k| k == IntoOwned::borrow_as(key))
!= Some(true)
{
self.cursor.seek_key(&self.batch, IntoOwned::borrow_as(key));
}
if self
.cursor
.get_key(&self.batch)
.map(|k| k == IntoOwned::borrow_as(key))
== Some(true)
{
let key = self.cursor.key(&self.batch);
while let Some(val) = self.cursor.get_val(&self.batch) {
self.cursor.map_times(&self.batch, |time, diff| {
buffer.push((time.into_owned(), diff.into_owned()));
});
consolidate(&mut buffer);
for (time, diff) in buffer.drain(..) {
for datum in logic(key, val, time, diff) {
session.give(datum);
work += 1;
}
}
self.cursor.step_val(&self.batch);
if work >= *fuel {
*fuel = 0;
return;
}
}
}
} else {
while let Some(key) = self.cursor.get_key(&self.batch) {
while let Some(val) = self.cursor.get_val(&self.batch) {
self.cursor.map_times(&self.batch, |time, diff| {
buffer.push((time.into_owned(), diff.into_owned()));
});
consolidate(&mut buffer);
for (time, diff) in buffer.drain(..) {
for datum in logic(key, val, time, diff) {
session.give(datum);
work += 1;
}
}
self.cursor.step_val(&self.batch);
if work >= *fuel {
*fuel = 0;
return;
}
}
self.cursor.step_key(&self.batch);
}
}
*fuel -= work;
}
}