github.com/peterbourgon/diskv@v2.0.1+incompatible/README.md (about) 1 # What is diskv? 2 3 Diskv (disk-vee) is a simple, persistent key-value store written in the Go 4 language. It starts with an incredibly simple API for storing arbitrary data on 5 a filesystem by key, and builds several layers of performance-enhancing 6 abstraction on top. The end result is a conceptually simple, but highly 7 performant, disk-backed storage system. 8 9 [![Build Status][1]][2] 10 11 [1]: https://drone.io/github.com/peterbourgon/diskv/status.png 12 [2]: https://drone.io/github.com/peterbourgon/diskv/latest 13 14 15 # Installing 16 17 Install [Go 1][3], either [from source][4] or [with a prepackaged binary][5]. 18 Then, 19 20 ```bash 21 $ go get github.com/peterbourgon/diskv 22 ``` 23 24 [3]: http://golang.org 25 [4]: http://golang.org/doc/install/source 26 [5]: http://golang.org/doc/install 27 28 29 # Usage 30 31 ```go 32 package main 33 34 import ( 35 "fmt" 36 "github.com/peterbourgon/diskv" 37 ) 38 39 func main() { 40 // Simplest transform function: put all the data files into the base dir. 41 flatTransform := func(s string) []string { return []string{} } 42 43 // Initialize a new diskv store, rooted at "my-data-dir", with a 1MB cache. 44 d := diskv.New(diskv.Options{ 45 BasePath: "my-data-dir", 46 Transform: flatTransform, 47 CacheSizeMax: 1024 * 1024, 48 }) 49 50 // Write three bytes to the key "alpha". 51 key := "alpha" 52 d.Write(key, []byte{'1', '2', '3'}) 53 54 // Read the value back out of the store. 55 value, _ := d.Read(key) 56 fmt.Printf("%v\n", value) 57 58 // Erase the key+value from the store (and the disk). 59 d.Erase(key) 60 } 61 ``` 62 63 More complex examples can be found in the "examples" subdirectory. 64 65 66 # Theory 67 68 ## Basic idea 69 70 At its core, diskv is a map of a key (`string`) to arbitrary data (`[]byte`). 71 The data is written to a single file on disk, with the same name as the key. 72 The key determines where that file will be stored, via a user-provided 73 `TransformFunc`, which takes a key and returns a slice (`[]string`) 74 corresponding to a path list where the key file will be stored. The simplest 75 TransformFunc, 76 77 ```go 78 func SimpleTransform (key string) []string { 79 return []string{} 80 } 81 ``` 82 83 will place all keys in the same, base directory. The design is inspired by 84 [Redis diskstore][6]; a TransformFunc which emulates the default diskstore 85 behavior is available in the content-addressable-storage example. 86 87 [6]: http://groups.google.com/group/redis-db/browse_thread/thread/d444bc786689bde9?pli=1 88 89 **Note** that your TransformFunc should ensure that one valid key doesn't 90 transform to a subset of another valid key. That is, it shouldn't be possible 91 to construct valid keys that resolve to directory names. As a concrete example, 92 if your TransformFunc splits on every 3 characters, then 93 94 ```go 95 d.Write("abcabc", val) // OK: written to <base>/abc/abc/abcabc 96 d.Write("abc", val) // Error: attempted write to <base>/abc/abc, but it's a directory 97 ``` 98 99 This will be addressed in an upcoming version of diskv. 100 101 Probably the most important design principle behind diskv is that your data is 102 always flatly available on the disk. diskv will never do anything that would 103 prevent you from accessing, copying, backing up, or otherwise interacting with 104 your data via common UNIX commandline tools. 105 106 ## Adding a cache 107 108 An in-memory caching layer is provided by combining the BasicStore 109 functionality with a simple map structure, and keeping it up-to-date as 110 appropriate. Since the map structure in Go is not threadsafe, it's combined 111 with a RWMutex to provide safe concurrent access. 112 113 ## Adding order 114 115 diskv is a key-value store and therefore inherently unordered. An ordering 116 system can be injected into the store by passing something which satisfies the 117 diskv.Index interface. (A default implementation, using Google's 118 [btree][7] package, is provided.) Basically, diskv keeps an ordered (by a 119 user-provided Less function) index of the keys, which can be queried. 120 121 [7]: https://github.com/google/btree 122 123 ## Adding compression 124 125 Something which implements the diskv.Compression interface may be passed 126 during store creation, so that all Writes and Reads are filtered through 127 a compression/decompression pipeline. Several default implementations, 128 using stdlib compression algorithms, are provided. Note that data is cached 129 compressed; the cost of decompression is borne with each Read. 130 131 ## Streaming 132 133 diskv also now provides ReadStream and WriteStream methods, to allow very large 134 data to be handled efficiently. 135 136 137 # Future plans 138 139 * Needs plenty of robust testing: huge datasets, etc... 140 * More thorough benchmarking 141 * Your suggestions for use-cases I haven't thought of