github.com/coocood/badger@v1.5.1-0.20200528065104-c02ac3616d04/cache/README.md (about) 1 # Ristretto 2 [![Go Doc](https://img.shields.io/badge/godoc-reference-blue.svg)](http://godoc.org/github.com/dgraph-io/ristretto) 3 [![Go Report Card](https://img.shields.io/badge/go%20report-A%2B-brightgreen)](https://goreportcard.com/report/github.com/dgraph-io/ristretto) 4 [![Coverage](https://img.shields.io/badge/coverage-100%25-brightgreen)](https://gocover.io/github.com/dgraph-io/ristretto) 5 ![Tests](https://github.com/dgraph-io/ristretto/workflows/tests/badge.svg) 6 7 Ristretto is a fast, concurrent cache library built with a focus on performance and correctness. 8 9 The motivation to build Ristretto comes from the need for a contention-free 10 cache in [Dgraph][]. 11 12 [Dgraph]: https://github.com/dgraph-io/dgraph 13 14 ## Features 15 16 * **High Hit Ratios** - with our unique admission/eviction policy pairing, Ristretto's performance is best in class. 17 * **Eviction: SampledLFU** - on par with exact LRU and better performance on Search and Database traces. 18 * **Admission: TinyLFU** - extra performance with little memory overhead (12 bits per counter). 19 * **Fast Throughput** - we use a variety of techniques for managing contention and the result is excellent throughput. 20 * **Cost-Based Eviction** - any large new item deemed valuable can evict multiple smaller items (cost could be anything). 21 * **Fully Concurrent** - you can use as many goroutines as you want with little throughput degradation. 22 * **Metrics** - optional performance metrics for throughput, hit ratios, and other stats. 23 * **Simple API** - just figure out your ideal `Config` values and you're off and running. 24 25 ## Status 26 27 Ristretto is usable but still under active development. We expect it to be production ready in the near future. 28 29 ## Table of Contents 30 31 * [Usage](#Usage) 32 * [Example](#Example) 33 * [Config](#Config) 34 * [NumCounters](#Config) 35 * [MaxCost](#Config) 36 * [BufferItems](#Config) 37 * [Metrics](#Config) 38 * [OnEvict](#Config) 39 * [KeyToHash](#Config) 40 * [Cost](#Config) 41 * [Benchmarks](#Benchmarks) 42 * [Hit Ratios](#Hit-Ratios) 43 * [Search](#Search) 44 * [Database](#Database) 45 * [Looping](#Looping) 46 * [CODASYL](#CODASYL) 47 * [Throughput](#Throughput) 48 * [Mixed](#Mixed) 49 * [Read](#Read) 50 * [Write](#Write) 51 * [FAQ](#FAQ) 52 53 ## Usage 54 55 ### Example 56 57 ```go 58 func main() { 59 cache, err := ristretto.NewCache(&ristretto.Config{ 60 NumCounters: 1e7, // number of keys to track frequency of (10M). 61 MaxCost: 1 << 30, // maximum cost of cache (1GB). 62 BufferItems: 64, // number of keys per Get buffer. 63 }) 64 if err != nil { 65 panic(err) 66 } 67 68 // set a value with a cost of 1 69 cache.Set("key", "value", 1) 70 71 // wait for value to pass through buffers 72 time.Sleep(10 * time.Millisecond) 73 74 value, found := cache.Get("key") 75 if !found { 76 panic("missing value") 77 } 78 fmt.Println(value) 79 cache.Del("key") 80 } 81 ``` 82 83 ### Config 84 85 The `Config` struct is passed to `NewCache` when creating Ristretto instances (see the example above). 86 87 **NumCounters** `int64` 88 89 NumCounters is the number of 4-bit access counters to keep for admission and eviction. We've seen good performance in setting this to 10x the number of items you expect to keep in the cache when full. 90 91 For example, if you expect each item to have a cost of 1 and MaxCost is 100, set NumCounters to 1,000. Or, if you use variable cost values but expect the cache to hold around 10,000 items when full, set NumCounters to 100,000. The important thing is the *number of unique items* in the full cache, not necessarily the MaxCost value. 92 93 **MaxCost** `int64` 94 95 MaxCost is how eviction decisions are made. For example, if MaxCost is 100 and a new item with a cost of 1 increases total cache cost to 101, 1 item will be evicted. 96 97 MaxCost can also be used to denote the max size in bytes. For example, if MaxCost is 1,000,000 (1MB) and the cache is full with 1,000 1KB items, a new item (that's accepted) would cause 5 1KB items to be evicted. 98 99 MaxCost could be anything as long as it matches how you're using the cost values when calling Set. 100 101 **BufferItems** `int64` 102 103 BufferItems is the size of the Get buffers. The best value we've found for this is 64. 104 105 If for some reason you see Get performance decreasing with lots of contention (you shouldn't), try increasing this value in increments of 64. This is a fine-tuning mechanism and you probably won't have to touch this. 106 107 **Metrics** `bool` 108 109 Metrics is true when you want real-time logging of a variety of stats. The reason this is a Config flag is because there's a 10% throughput performance overhead. 110 111 **OnEvict** `func(hashes [2]uint64, value interface{}, cost int64)` 112 113 OnEvict is called for every eviction. 114 115 **KeyToHash** `func(key interface{}) [2]uint64` 116 117 KeyToHash is the hashing algorithm used for every key. If this is nil, Ristretto has a variety of [defaults depending on the underlying interface type](https://github.com/dgraph-io/ristretto/blob/master/z/z.go#L19-L41). 118 119 Note that if you want 128bit hashes you should use the full `[2]uint64`, 120 otherwise just fill the `uint64` at the `0` position and it will behave like 121 any 64bit hash. 122 123 **Cost** `func(value interface{}) int64` 124 125 Cost is an optional function you can pass to the Config in order to evaluate 126 item cost at runtime, and only for the Set calls that aren't dropped (this is 127 useful if calculating item cost is particularly expensive and you don't want to 128 waste time on items that will be dropped anyways). 129 130 To signal to Ristretto that you'd like to use this Cost function: 131 132 1. Set the Cost field to a non-nil function. 133 2. When calling Set for new items or item updates, use a `cost` of 0. 134 135 ## Benchmarks 136 137 The benchmarks can be found in https://github.com/dgraph-io/benchmarks/tree/master/cachebench/ristretto. 138 139 ### Hit Ratios 140 141 #### Search 142 143 This trace is described as "disk read accesses initiated by a large commercial 144 search engine in response to various web search requests." 145 146 <p align="center"> 147 <img src="https://raw.githubusercontent.com/karlmcguire/karlmcguire.com/master/docs/Hit%20Ratios%20-%20Search%20(ARC-S3).svg?sanitize=true"> 148 </p> 149 150 #### Database 151 152 This trace is described as "a database server running at a commercial site 153 running an ERP application on top of a commercial database." 154 155 <p align="center"> 156 <img src="https://raw.githubusercontent.com/karlmcguire/karlmcguire.com/master/docs/Hit%20Ratios%20-%20Database%20(ARC-DS1).svg?sanitize=true"> 157 </p> 158 159 #### Looping 160 161 This trace demonstrates a looping access pattern. 162 163 <p align="center"> 164 <img src="https://raw.githubusercontent.com/karlmcguire/karlmcguire.com/master/docs/Hit%20Ratios%20-%20Glimpse%20(LIRS-GLI).svg?sanitize=true"> 165 </p> 166 167 #### CODASYL 168 169 This trace is described as "references to a CODASYL database for a one hour 170 period." 171 172 <p align="center"> 173 <img src="https://raw.githubusercontent.com/karlmcguire/karlmcguire.com/master/docs/Hit%20Ratios%20-%20CODASYL%20(ARC-OLTP).svg?sanitize=true"> 174 </p> 175 176 ### Throughput 177 178 All throughput benchmarks were ran on an Intel Core i7-8700K (3.7GHz) with 16gb 179 of RAM. 180 181 #### Mixed 182 183 <p align="center"> 184 <img src="https://raw.githubusercontent.com/karlmcguire/karlmcguire.com/master/docs/Throughput%20-%20Mixed.svg?sanitize=true"> 185 </p> 186 187 #### Read 188 189 <p align="center"> 190 <img src="https://raw.githubusercontent.com/karlmcguire/karlmcguire.com/master/docs/Throughput%20-%20Read%20(Zipfian).svg?sanitize=true"> 191 </p> 192 193 #### Write 194 195 <p align="center"> 196 <img src="https://raw.githubusercontent.com/karlmcguire/karlmcguire.com/master/docs/Throughput%20-%20Write%20(Zipfian).svg?sanitize=true"> 197 </p> 198 199 ## FAQ 200 201 ### How are you achieving this performance? What shortcuts are you taking? 202 203 We go into detail in the [Ristretto blog post](https://blog.dgraph.io/post/introducing-ristretto-high-perf-go-cache/), but in short: our throughput performance can be attributed to a mix of batching and eventual consistency. Our hit ratio performance is mostly due to an excellent [admission policy](https://arxiv.org/abs/1512.00727) and SampledLFU eviction policy. 204 205 As for "shortcuts," the only thing Ristretto does that could be construed as one is dropping some Set calls. That means a Set call for a new item (updates are guaranteed) isn't guaranteed to make it into the cache. The new item could be dropped at two points: when passing through the Set buffer or when passing through the admission policy. However, this doesn't affect hit ratios much at all as we expect the most popular items to be Set multiple times and eventually make it in the cache. 206 207 ### Is Ristretto distributed? 208 209 No, it's just like any other Go library that you can import into your project and use in a single process.