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196 lines
5.8 KiB
Markdown
196 lines
5.8 KiB
Markdown
# sqlxmq
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[![CI Status](https://github.com/Diggsey/sqlxmq/workflows/CI/badge.svg)](https://github.com/Diggsey/sqlxmq/actions?query=workflow%3ACI)
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[![Documentation](https://docs.rs/sqlxmq/badge.svg)](https://docs.rs/sqlxmq)
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[![crates.io](https://img.shields.io/crates/v/sqlxmq.svg)](https://crates.io/crates/sqlxmq)
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A job queue built on `sqlx` and `PostgreSQL`.
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This library allows a CRUD application to run background jobs without complicating its
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deployment. The only runtime dependency is `PostgreSQL`, so this is ideal for applications
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already using a `PostgreSQL` database.
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Although using a SQL database as a job queue means compromising on latency of
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delivered jobs, there are several show-stopping issues present in ordinary job
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queues which are avoided altogether.
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With most other job queues, in-flight jobs are state that is not covered by normal
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database backups. Even if jobs _are_ backed up, there is no way to restore both
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a database and a job queue to a consistent point-in-time without manually
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resolving conflicts.
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By storing jobs in the database, existing backup procedures will store a perfectly
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consistent state of both in-flight jobs and persistent data. Additionally, jobs can
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be spawned and completed as part of other transactions, making it easy to write correct
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application code.
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Leveraging the power of `PostgreSQL`, this job queue offers several features not
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present in other job queues.
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# Features
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- **Send/receive multiple jobs at once.**
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This reduces the number of queries to the database.
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- **Send jobs to be executed at a future date and time.**
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Avoids the need for a separate scheduling system.
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- **Reliable delivery of jobs.**
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- **Automatic retries with exponential backoff.**
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Number of retries and initial backoff parameters are configurable.
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- **Transactional sending of jobs.**
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Avoids sending spurious jobs if a transaction is rolled back.
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- **Transactional completion of jobs.**
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If all side-effects of a job are updates to the database, this provides
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true exactly-once execution of jobs.
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- **Transactional check-pointing of jobs.**
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Long-running jobs can check-point their state to avoid having to restart
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from the beginning if there is a failure: the next retry can continue
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from the last check-point.
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- **Opt-in strictly ordered job delivery.**
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Jobs within the same channel will be processed strictly in-order
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if this option is enabled for the job.
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- **Fair job delivery.**
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A channel with a lot of jobs ready to run will not starve a channel with fewer
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jobs.
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- **Opt-in two-phase commit.**
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This is particularly useful on an ordered channel where a position can be "reserved"
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in the job order, but not committed until later.
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- **JSON and/or binary payloads.**
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Jobs can use whichever is most convenient.
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- **Automatic keep-alive of jobs.**
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Long-running jobs will automatically be "kept alive" to prevent them being
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retried whilst they're still ongoing.
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- **Concurrency limits.**
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Specify the minimum and maximum number of concurrent jobs each runner should
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handle.
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- **Built-in job registry via an attribute macro.**
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Jobs can be easily registered with a runner, and default configuration specified
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on a per-job basis.
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- **Implicit channels.**
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Channels are implicitly created and destroyed when jobs are sent and processed,
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so no setup is required.
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- **Channel groups.**
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Easily subscribe to multiple channels at once, thanks to the separation of
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channel name and channel arguments.
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- **NOTIFY-based polling.**
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This saves resources when few jobs are being processed.
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# Getting started
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## Database schema
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This crate expects certain database tables and stored procedures to exist.
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You can copy the migration files from this crate into your own migrations
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folder.
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All database items created by this crate are prefixed with `mq`, so as not
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to conflict with your own schema.
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## Defining jobs
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The first step is to define a function to be run on the job queue.
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```rust
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use sqlxmq::{job, CurrentJob};
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// Arguments to the `#[job]` attribute allow setting default job options.
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#[job(channel_name = "foo")]
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async fn example_job(
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// The first argument should always be the current job.
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mut current_job: CurrentJob,
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// Additional arguments are optional, but can be used to access context
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// provided via `JobRegistry::set_context`.
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message: &'static str,
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) -> sqlx::Result<()> {
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// Decode a JSON payload
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let who: Option<String> = current_job.json()?;
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// Do some work
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println!("{}, {}!", message, who.as_deref().unwrap_or("world"));
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// Mark the job as complete
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current_job.complete().await?;
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Ok(())
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}
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```
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## Listening for jobs
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Next we need to create a job runner: this is what listens for new jobs
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and executes them.
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```rust
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use sqlxmq::JobRegistry;
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#[tokio::main]
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async fn main() -> Result<(), Box<dyn Error>> {
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// You'll need to provide a Postgres connection pool.
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let pool = connect_to_db().await?;
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// Construct a job registry from our single job.
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let mut registry = JobRegistry::new(&[example_job]);
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// Here is where you can configure the registry
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// registry.set_error_handler(...)
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// And add context
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registry.set_context("Hello");
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let runner = registry
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// Create a job runner using the connection pool.
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.runner(&pool)
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// Here is where you can configure the job runner
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// Aim to keep 10-20 jobs running at a time.
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.set_concurrency(10, 20)
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// Start the job runner in the background.
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.run()
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.await?;
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// The job runner will continue listening and running
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// jobs until `runner` is dropped.
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}
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```
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## Spawning a job
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The final step is to actually run a job.
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```rust
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example_job.builder()
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// This is where we can override job configuration
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.set_channel_name("bar")
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.set_json("John")
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.spawn(&pool)
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.await?;
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```
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