Motivation:
RediStack today represents a command as a temporary object for the purpose of writing to the channel.
While it is useful to have an object for that purpose, commands handled in this way require immediate execution
and aren't available for other purposes.
Commands can serve a better purpose as a lightweight object to support delayed execution,
so that pipeling as described in issue #63 could be possible.
Modifications:
- Add: `get` overloads for JSON codable interaction on `RedisClient`
- Add: New `RedisZRangeResultOption` type for better interactions with zrange operations that can optionally return scores
- Add: New `RedisHashFieldKey` for type-safety when working with Hash field keys much like `RedisKey`
- Change: A few API types from enums to structs for library evolution
- Change: `RedisCommandHandler` to operate on a tuple of `RESPValue, EventLoopPromise<RESPValue>` rather than `RedisCommand`
- Change: `RedisCommand` to be a generic struct with the keyword, arguments, and a transform closure to defer execution
- Change: Almost all `RedisClient` command extensions to be factory methods on `RedisCommand` instead
- Change: Many response types to be optional to avoid developers having to do `isNull` checks on their own
- Change: `RedisClient.send(command:arguments:)` to be generic with `send(_:)` as the signature
- Rename: RedisClient extensions for scan methods to be more discoverable and legible as `scanHashField`, etc.
Result:
It should be easier to support a clean pipelining API with deferred command execution,
with extensions being easier for 2nd party developers, and the maintenance overhead of all of the command extensions
should be a little lighter when it comes to changing HOW commands are sent such as adding a context parameter
Motivation:
Users of Redis will frequently want to be able to run queries in
parallel, while bounding the number of connections they use. They will
also often want to be able to reuse connections, without having to
arrange to manage those connections themselves. These are jobs usually
done by a Connection Pool.
This new connection pool will conform to `RedisClient` so a pool of clients and a single connection are interchangeable.
Connection Pools come in a wide range of shapes and sizes. In NIO
applications and frameworks, there are a number of questions that have
to be answered by any pool implementation:
1. Is the pool safe to share across EventLoops: that is, is its
interface thread-safe?
2. Is the pool _tied_ to an EventLoop: that is, can the pool return
connections that belong on lots of event loops, or just one?
3. If the pool is not tied to an EventLoop, is it possible to influence
its choice about what event loop it uses for a given connection?
Question 1 is straightforward: it is almost always a trivial win to
ensure that the public interface to a connection pool is thread-safe.
NIO makes it possible to do this fairly cheaply in the case when the
pool is only used on a single loop.
Question 2 is a lot harder. Pools that are not tied to a specific
EventLoop have two advantages. The first is that it is easier to bound
maximum concurrency by simply configuring the pool, instead of needing
to do math on the number of pools and the number of event loops. The
second is that non-tied pools can arrange to keep busy applications
close to this maximum concurrency regardless of how the application
spreads its load across loops.
However, pools that are tied to a specific EventLoop have advantages
too. The first is one of implementation simplicity. As they always serve
connections on a single EventLoop, they can arrange to have all of their
state on that event loop too. This avoids the need to acquire locks on
that loop, making internal state management easier and more obviously
correct without having to worry about how long locks are held for.
The second advantage is that they can be used for latency sensitive
use-cases without needing to go to the work of (3). In cases where
latency is very important, it can be valuable to ensure that any Channel
that needs a connection can get one on the same event loop as itself.
This avoids the need to thread-hop in order to communicate between the
pooled connection and the user connection, reducing the latency of
operations.
Given the simplicity and latency benefits (which we deem particularly
important for Redis use-cases), we concluded that a good initial
implementation will be a pool that has a thread-safe interface, but is
tied to a single EventLoop. This allows a compact, easy-to-verify
implementation of the pool with great low-latency performance and simple
implementation logic, that can still be accessed from any EventLoop in
cases when latency is not a concern.
Modifications:
- Add new internal `ConnectionPool` object
- Add new `RedisConnectionPool` object
- Add new `RedisConnectionPoolError` type
- Add tests for new types
Results:
Users will have access to a pooled Redis client.
Fabian Fett
Nathan Harris
Lukasa