TimelyDataflow / TimelyDataflow/differential-dataflow

Is this the most efficient way to do a left join?

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Dominant language
Rust
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Description

I want to left-join fairly regularly in my data flow, and have written this helper:

fn left_join<G: Scope, K: Data, V: Data, R: Diff, V2: Data>(a: &Collection<G, (K, V), R>, b: &Collection<G, (K, V2), R>) -> Collection<G, (V,Option<V2>), <R as Mul<R>>::Output>
where R: Mul<R, Output = R>, K: Data + Hashable, G::Timestamp: Lattice + Ord {
    let with = a.join_map(b, |_, v, v2| (v.clone(), Some(v2.clone())));
    let without = a.antijoin(&b.map(|(k, _)| k)).map(|(_, v)| (v, None));
    with.concat(&without)
}

FWIW, I often combine this with a

   .group(move |_key, input, output| {
        let out = input.into_iter().filter_map(|&(opt, _)| opt.as_ref()).cloned().collect::<Vec<_>>();
        output.push((out, 1));
    })

which gives me a Collection<G, (V, Vec<V2>), R>.

Is this reasonably efficient? (Also curious if we could get something similar in the standard library?)

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Research direction

Start with the shown left_join helper and its join_map, antijoin, concat, and group calls; compare their behavior and costs before considering a library API. The issue names no files or tests, so done is not defined beyond establishing an efficient left join and deciding whether a standard helper should exist.

Written by the indexing model from the issue text.

Assessment

Tech stack
rust
Domain
data-engineering
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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