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<main>
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<h1 id="dataloader"><a class="header" href="#dataloader">DataLoader</a></h1>
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<p>DataLoader pattern, named after the correspondent <a href="https://github.com/graphql/dataloader"><code>dataloader</code> NPM package</a>, represents a mechanism of batching and caching data requests in a delayed manner for solving the <a href="n_plus_1.html">N+1 problem</a>.</p>
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<blockquote>
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<p>A port of the "Loader" API originally developed by <a href="https://github.com/schrockn">@schrockn</a> at Facebook in 2010 as a simplifying force to coalesce the sundry key-value store back-end APIs which existed at the time. At Facebook, "Loader" became one of the implementation details of the "Ent" framework, a privacy-aware data entity loading and caching layer within web server product code. This ultimately became the underpinning for Facebook's GraphQL server implementation and type definitions.</p>
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</blockquote>
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<p>In <a href="https://www.rust-lang.org">Rust</a> ecosystem, DataLoader pattern is introduced with the <a href="https://docs.rs/crate/dataloader"><code>dataloader</code> crate</a>, naturally usable with <a href="https://docs.rs/juniper">Juniper</a>.</p>
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<p>Let's remake our <a href="n_plus_1.html">example of N+1 problem</a>, so it's solved by applying the DataLoader pattern:</p>
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<pre><pre class="playground"><code class="language-rust edition2021"><span class="boring">extern crate anyhow;
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</span><span class="boring">extern crate dataloader;
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</span><span class="boring">extern crate juniper;
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</span><span class="boring">use std::{collections::HashMap, sync::Arc};
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</span><span class="boring">use anyhow::anyhow;
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</span><span class="boring">use dataloader::non_cached::Loader;
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</span><span class="boring">use juniper::{graphql_object, GraphQLObject};
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</span><span class="boring">
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</span><span class="boring">type CultId = i32;
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</span><span class="boring">type UserId = i32;
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</span><span class="boring">
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</span><span class="boring">struct Repository;
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</span><span class="boring">
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</span><span class="boring">impl Repository {
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</span><span class="boring"> async fn load_cults_by_ids(&self, cult_ids: &[CultId]) -> anyhow::Result<HashMap<CultId, Cult>> { unimplemented!() }
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</span><span class="boring"> async fn load_all_persons(&self) -> anyhow::Result<Vec<Person>> { unimplemented!() }
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</span><span class="boring">}
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</span><span class="boring">
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</span>struct Context {
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repo: Repository,
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cult_loader: CultLoader,
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}
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impl juniper::Context for Context {}
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#[derive(Clone, GraphQLObject)]
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struct Cult {
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id: CultId,
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name: String,
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}
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struct CultBatcher {
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repo: Repository,
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}
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// Since `BatchFn` doesn't provide any notion of fallible loading, like
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// `try_load()` returning `Result<HashMap<K, V>, E>`, we handle possible
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// errors as loaded values and unpack them later in the resolver.
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impl dataloader::BatchFn<CultId, Result<Cult, Arc<anyhow::Error>>> for CultBatcher {
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async fn load(
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&mut self,
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cult_ids: &[CultId],
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) -> HashMap<CultId, Result<Cult, Arc<anyhow::Error>>> {
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// Effectively performs the following SQL query:
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// SELECT id, name FROM cults WHERE id IN (${cult_id1}, ${cult_id2}, ...)
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match self.repo.load_cults_by_ids(cult_ids).await {
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Ok(found_cults) => {
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found_cults.into_iter().map(|(id, cult)| (id, Ok(cult))).collect()
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}
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// One could choose a different strategy to deal with fallible loads,
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// like consider values that failed to load as absent, or just panic.
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// See cksac/dataloader-rs#35 for details:
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// https://github.com/cksac/dataloader-rs/issues/35
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Err(e) => {
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// Since `anyhow::Error` doesn't implement `Clone`, we have to
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// work around here.
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let e = Arc::new(e);
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cult_ids.iter().map(|k| (k.clone(), Err(e.clone()))).collect()
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}
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}
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}
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}
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type CultLoader = Loader<CultId, Result<Cult, Arc<anyhow::Error>>, CultBatcher>;
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fn new_cult_loader(repo: Repository) -> CultLoader {
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CultLoader::new(CultBatcher { repo })
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// Usually a `Loader` will coalesce all individual loads which occur
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// within a single frame of execution before calling a `BatchFn::load()`
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// with all the collected keys. However, sometimes this behavior is not
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// desirable or optimal (perhaps, a request is expected to be spread out
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// over a few subsequent ticks).
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// A larger yield count will allow more keys to be appended to the batch,
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// but will wait longer before the actual load. For more details see:
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// https://github.com/cksac/dataloader-rs/issues/12
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// https://github.com/graphql/dataloader#batch-scheduling
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.with_yield_count(100)
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}
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struct Person {
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id: UserId,
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name: String,
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cult_id: CultId,
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}
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#[graphql_object]
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#[graphql(context = Context)]
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impl Person {
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fn id(&self) -> CultId {
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self.id
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}
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fn name(&self) -> &str {
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self.name.as_str()
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}
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async fn cult(&self, ctx: &Context) -> anyhow::Result<Cult> {
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ctx.cult_loader
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// Here, we don't run the `CultBatcher::load()` eagerly, but rather
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// only register the `self.cult_id` value in the `cult_loader` and
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// wait for other concurrent resolvers to do the same.
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// The actual batch loading happens once all the resolvers register
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// their IDs and there is nothing more to execute.
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.try_load(self.cult_id)
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.await
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// The outer error is the `io::Error` returned by `try_load()` if
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// no value is present in the `HashMap` for the specified
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// `self.cult_id`, meaning that there is no `Cult` with such ID
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// in the `Repository`.
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.map_err(|_| anyhow!("No cult exists for ID `{}`", self.cult_id))?
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// The inner error is the one returned by the `CultBatcher::load()`
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// if the `Repository::load_cults_by_ids()` fails, meaning that
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// running the SQL query failed.
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.map_err(|arc_err| anyhow!("{arc_err}"))
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}
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}
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struct Query;
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#[graphql_object]
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#[graphql(context = Context)]
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impl Query {
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async fn persons(ctx: &Context) -> anyhow::Result<Vec<Person>> {
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// Effectively performs the following SQL query:
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// SELECT id, name, cult_id FROM persons
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ctx.repo.load_all_persons().await
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}
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}
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fn main() {
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}</code></pre></pre>
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<p>And now, performing a <a href="n_plus_1.html">GraphQL query which lead to N+1 problem</a></p>
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<pre><code class="language-graphql">query {
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persons {
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id
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name
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cult {
|
||
|
id
|
||
|
name
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
</code></pre>
|
||
|
<p>will lead to efficient <a href="https://en.wikipedia.org/wiki/SQL">SQL</a> queries, just as expected:</p>
|
||
|
<pre><code class="language-sql">SELECT id, name, cult_id FROM persons;
|
||
|
SELECT id, name FROM cults WHERE id IN (1, 2, 3, 4);
|
||
|
</code></pre>
|
||
|
<h2 id="caching"><a class="header" href="#caching">Caching</a></h2>
|
||
|
<p><a href="https://docs.rs/dataloader/latest/dataloader/cached/index.html"><code>dataloader::cached</code></a> provides a <a href="https://en.wikipedia.org/wiki/Memoization">memoization</a> cache: after <code>BatchFn::load()</code> is called once with given keys, the resulting values are cached to eliminate redundant loads.</p>
|
||
|
<p>DataLoader caching does not replace <a href="https://redis.io">Redis</a>, <a href="https://memcached.org">Memcached</a>, or any other shared application-level cache. DataLoader is first and foremost a data loading mechanism, and its cache only serves the purpose of not repeatedly loading the same data <a href="https://github.com/graphql/dataloader#caching">in the context of a single request</a>.</p>
|
||
|
<blockquote>
|
||
|
<p><strong>WARNING</strong>: A DataLoader should be created per-request to avoid risk of bugs where one client is able to load cached/batched data from another client outside its authenticated scope. Creating a DataLoader within an individual resolver will prevent batching from occurring and will nullify any benefits of it.</p>
|
||
|
</blockquote>
|
||
|
<h2 id="full-example"><a class="header" href="#full-example">Full example</a></h2>
|
||
|
<p>For a full example using DataLoaders in <a href="https://docs.rs/juniper">Juniper</a> check out the <a href="https://github.com/jayy-lmao/rust-graphql-docker"><code>jayy-lmao/rust-graphql-docker</code> repository</a>.</p>
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