BB.Caching is a library for (ASP) .NET developers with the goal of making caching as simple as possible. With out-of-the-box support for Redis on top of StackExchange.Redis, you can quickly get scalable, distributed caching up and running with minimal configuration overhead.
Note: This code is not production ready, but has a lot of tests that cover many cases.
- Smart caching (in-memory and/or distributed)
- Rate limiting
- Bloom filters
- Simple bitwise analytics
Check out the tests.
In your startup process:
- Define your cache settings either programmatically or using an app config file:
- if you're using a config file (including analytics tracking), call
Cache.LoadFromConfig(...) - if you're defining the setup programmatically, see this example
- if you're using a config file (including analytics tracking), call
- Then prepare the cache by calling
Cache.Prepare(). - Start using the cache!
// set a value both in local memory and on redis to make it available to other
// servers
Cache.Set("my-key", "some value", Cache.Store.MemoryAndRedis);
// set a value both in local memory and on redis, giving it an expiration
Cache.Set("my-key", 1234, TimeSpan.FromSeconds(30), Cache.Store.MemoryAndRedis);
// retrieve the data for ``"my-key"``. if the key isn't found in local memory,
// it'll look the key up in redis, and if it's found it'll store it in local
// memory for next time and return the value
Cache.Get<string>("my-key", Cache.Store.MemoryAndRedis);
// deletes the key from redis and all other servers
Cache.BroadcastDelete("my-key");
// track an event with 15 minute precision
BitwiseAnalytics.TrackEvent("video", "watch", 1L, TimePrecision.FifteenMinutes);
// get a key containing the users who watched a video and purchased anything in
// the last 30 minutes...
RedisKey watchVideoAndPurchase = Ops.And(
new Event("video", "watch", now.AddMinutes(-30), now, TimeInterval.FifteenMinutes),
new Event("anything", "purchase", now.AddMinutes(-30), now, TimeInterval.FifteenMinutes));
// ... now count the users
long count = BitwiseAnalytics.Count(watchVideoAndPurchase);
// ... now get the ids of the users
List<long> ids = new RedisKeyBitEnumerable(watchVideoAndPurchase).ToList();
Note: each method has an Async counterpart
- A simple-to-use caching interface, with method calls located under
Cache..- NOTE: The methods will serialize and compress objects using protobuf and gzip. Complex objects are assumed to be protobuf compatible.
- More advanced caching and redis use defined under
Cache.Shared.. These methods utilize the internal consistent hashing logic to distribute your keys across one or more redis nodes. - Uses consistent hashing to distribute keys across one or more redis nodes to support easier horizontal scaling.
- A shared
Statisticsimplementation to track simple statistics like count, min, max, mean, variance, and standard deviation. - Rate limiting capabilities.
- Bloom filter support.
- Consistent hashing & bloom filter both rely on Murmur hashing.
- Simple bitwise analytics.
Redis support for:
You'll find that this is rough around the edges, with unused code scattered throughout. I generally wait until I'm comfortable with a project before pushing it to GitHub but I felt that this could be perpetually in that stage, so I might as well move this to GitHub now since others might find that this scratches an itch.
Feel free to request features, report any bugs/issues you find, or make a pull request. I might not get to it as soon as you'd like (I have other projects / a job that also require my attention), but I'll do my best to fix/merge what comes in as soon as I can.
Machine: i7 950 @ 3.07GHz running two instances of redis on windows over ports 6379 and 6380.
Notes:
- consistent hashing adds some minor overhead
- the logic to time things kills the pipelining benefits provided by
StackExchange.Redis. I see throughput increase between a 6-8x across all the methods when it's actively pipelining requests
Shared Keys
'ExistsAsync' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0079] ms
Per Second [126,806]
Stdev Per Second [+/-520]
'ExpireAsync' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0086] ms
Per Second [115,962]
Stdev Per Second [+/-2,567]
'DeleteAsync' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0083] ms
Per Second [120,730]
Stdev Per Second [+/-980]
'PersistAsync' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0083] ms
Per Second [119,973]
Stdev Per Second [+/-1,076]
Shared Strings
'GetExpireAsync' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0159] ms
Per Second [62,706]
Stdev Per Second [+/-3,846]
'SetAsync' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0081] ms
Per Second [123,364]
Stdev Per Second [+/-2,258]
'GetAsync' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0075] ms
Per Second [133,256]
Stdev Per Second [+/-323]
Shared Hashes
'SetAsync' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0084] ms
Per Second [118,385]
Stdev Per Second [+/-1,357]
'GetAsync' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0082] ms
Per Second [122,089]
Stdev Per Second [+/-779]
Bloom Filter
'GetAsync' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0215] ms
Per Second [46,563]
Stdev Per Second [+/-3,779]
'SetAsync' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0214] ms
Per Second [46,753]
Stdev Per Second [+/-2,360]
RateLimiter
'IncrementAsync' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0127] ms
Per Second [78,600]
Stdev Per Second [+/-2,337]
Statistics
'SetAsync' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0133] ms
Per Second [75,228]
Stdev Per Second [+/-2,150]
'GetAsync' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0127] ms
Per Second [78,780]
Stdev Per Second [+/-2,398]
ConsistentHashRing
'GetNode' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0056] ms
Per Second [177,961]
Stdev Per Second [+/-435]
Murmur3
'HashSpeed' results summary:
Successes [10000]
Failures [0]
Average Exec Time [0.0029] ms
Per Second [347,367]
Stdev Per Second [+/-397]
Bitwise Analytics
'AndOneMonth' results summary:
Successes [100]
Failures [0]
Average Exec Time [92.6215] ms
Per Second [11]
Stdev Per Second [+/-59]
'AndOneMonthAsync' results summary:
Successes [100]
Failures [0]
Average Exec Time [19.6385] ms
Per Second [51]
Stdev Per Second [+/-229]
Memory Speed: (operations per second)
Set:
Raw: 500,000.0
Serialized: 361,445.78 (72.29)%
Serialized + Compressed: 36,275.7 (7.26)%
Get:
Raw: 10,000,000.0
Serialized: 1,153,846.15 (11.54)%
Serialized + Compressed: 909,090.91 (9.09)%
Memory Size:
Raw: 19,670.8KB
Serialized: 10,025.1KB (50.96%)
Serialized + Compressed: 1,851.3KB (9.41%)