Awesome
Table of Contents
Description
Package pudge is a fast and simple key/value store written using Go's standard library.
It presents the following:
- Supporting very efficient lookup, insertions and deletions
- Performance is comparable to hash tables
- Ability to get the data in sorted order, which enables additional operations like range scan
- Select with limit/offset/from key, with ordering or by prefix
- Safe for use in goroutines
- Space efficient
- Very short and simple codebase
- Well tested, used in production
Usage
package main
import (
"log"
"github.com/recoilme/pudge"
)
func main() {
// Close all database on exit
defer pudge.CloseAll()
// Set (directories will be created)
pudge.Set("../test/test", "Hello", "World")
// Get (lazy open db if needed)
output := ""
pudge.Get("../test/test", "Hello", &output)
log.Println("Output:", output)
ExampleSelect()
}
//ExampleSelect
func ExampleSelect() {
cfg := &pudge.Config{
SyncInterval: 1} // every second fsync
db, err := pudge.Open("../test/db", cfg)
if err != nil {
log.Panic(err)
}
defer db.DeleteFile()
type Point struct {
X int
Y int
}
for i := 100; i >= 0; i-- {
p := &Point{X: i, Y: i}
db.Set(i, p)
}
var point Point
db.Get(8, &point)
log.Println(point)
// Output: {8 8}
// Select 2 keys, from 7 in ascending order
keys, _ := db.Keys(7, 2, 0, true)
for _, key := range keys {
var p Point
db.Get(key, &p)
log.Println(p)
}
// Output: {8 8}
// Output: {9 9}
}
Cookbook
- Store data of any type. Pudge uses Gob encoder/decoder internally. No limits on keys/values size.
pudge.Set("strings", "Hello", "World")
pudge.Set("numbers", 1, 42)
type User struct {
Id int
Name string
}
u := &User{Id: 1, Name: "name"}
pudge.Set("users", u.Id, u)
-
Pudge is stateless and safe for use in goroutines. You don't need to create/open files before use. Just write data to pudge, don't worry about state. web server example
-
Pudge is parallel. Readers don't block readers, but a writer - does, but by the stateless nature of pudge it's safe to use multiples files for storages.
- Default store system: like memcache + file storage. Pudge uses in-memory hashmap for keys, and writes values to files (no value data stored in memory). But you may use inmemory mode for values, with custom config:
cfg = pudge.DefaultConfig()
cfg.StoreMode = 2
db, err := pudge.Open(dbPrefix+"/"+group, cfg)
...
db.Counter(key, val)
In that case, all data is stored in memory and will be stored on disk only on Close.
Example server for highload, with http api
- You may use pudge as an engine for creating databases.
- Don't forget to close all opened databases on shutdown/kill.
// Wait for interrupt signal to gracefully shutdown the server
quit := make(chan os.Signal)
signal.Notify(quit, os.Interrupt, os.Kill)
<-quit
log.Println("Shutdown Server ...")
if err := pudge.CloseAll(); err != nil {
log.Println("Pudge Shutdown err:", err)
}
example recovery function for gin framework
- Pudge has a primitive select/query engine.
// Select 2 keys, from 7 in ascending order
keys, _ := db.Keys(7, 2, 0, true)
// select keys from db where key>7 order by keys asc limit 2 offset 0
- Pudge will work well on SSD or spined disks. Pudge doesn't eat memory or storage or your sandwich. No hidden compaction/rebalancing/resizing and so on tasks. No LSM Tree. No MMap. It's a very simple database with less than 500 LOC. It's good for simple social network or highload system
Disadvantages
- No transaction system. All operations are isolated, but you don't may batching them with automatic rollback.
- Keys function (select/query engine) may be slow. Speed of query may vary from 10ms to 1sec per million keys. Pudge don't use BTree/Skiplist or Adaptive radix tree for store keys in ordered way on every insert. Ordering operation is "lazy" and run only if needed.
- If you need storage or database for hundreds of millions keys - take a look at Sniper or b52. They are optimized for highload (pudge - not).
- No fsync on every insert. Most of database fsync data by the timer too
- Deleted data don't remove from physically (but upsert will try to reuse space). You may shrink database only with backup right now
pudge.BackupAll("backup")
- Keys automatically convert to binary and ordered with binary comparator. It's simple for use, but ordering will not work correctly for negative numbers for example
- Author of project don't work at Google or Facebook and his name not Howard Chu or Brad Fitzpatrick. But I'm open for issue or contributions.
Motivation
Some databases very well for writing. Some of the databases very well for reading. But pudge is well balanced for both types of operations. It has small cute api, and don't have hidden graveyards. It's just hashmap where values written in files. And you may use one database for in-memory/persistent storage in a stateless stressfree way
Benchmarks
Some tests, MacBook Pro (Retina, 13-inch, Early 2015)
Test 1
Number of keys: 1000000 Minimum key size: 16, maximum key size: 64 Minimum value size: 128, maximum value size: 512 Concurrency: 2
pogreb | goleveldb | bolt | badgerdb | pudge | slowpoke | pudge(mem) | |
---|---|---|---|---|---|---|---|
1M (Put+Get), seconds | 187 | 38 | 126 | 34 | 23 | 23 | 2 |
1M Put, ops/sec | 5336 | 34743 | 8054 | 33539 | 47298 | 46789 | 439581 |
1M Get, ops/sec | 1782423 | 98406 | 499871 | 220597 | 499172 | 445783 | 1652069 |
FileSize,Mb | 568 | 357 | 552 | 487 | 358 | 358 | 358 |
Test 4
Number of keys: 10000000 Key size: 8 Value size: 16 Concurrency: 100
goleveldb | badgerdb | pudge | |
---|---|---|---|
10M (Put+Get), seconds | 165 | 120 | 243 |
10M Put, ops/sec | 122933 | 135709 | 43843 |
10M Get, ops/sec | 118722 | 214981 | 666067 |
FileSize,Mb | 312 | 1370 | 381 |