araddon/qlbridge 是一个golang 表达式执行器可以用来方便的构建基于sql 的查询引擎
同时已经内置了几种sql 的实现，同时也有一个dataux/dataux （但是不 维护了）的实现，
类似presto，以下是关于araddon/qlbridge 的简单学习
代码来自官方文档
核心代码
package main
import (
"bytes"
"database/sql"
"flag"
"fmt"
"net/mail"
"strings"
// Side-Effect Import the qlbridge sql driver
_ "github.com/araddon/qlbridge/qlbdriver"
"github.com/araddon/qlbridge/schema"
u "github.com/araddon/gou"
"github.com/araddon/qlbridge/datasource"
"github.com/araddon/qlbridge/expr"
"github.com/araddon/qlbridge/expr/builtins"
"github.com/araddon/qlbridge/value"
)
var (
sqlText string
flagCsvDelimiter = ","
logging = "info"
)
func init() {
flag.StringVar(&logging, "logging", "info", "logging [ debug,info ]")
flag.StringVar(&sqlText, "sql", "", "QL ish query multi-node such as [select user_id, yy(reg_date) from stdio];")
flag.StringVar(&flagCsvDelimiter, "delimiter", ",", "delimiter: default = comma [t,|]")
flag.Parse()
u.SetupLogging(logging)
u.SetColorOutput()
}
func main() {
if sqlText == "" {
u.Errorf("You must provide a valid select query in argument: --sql="select ..."")
return
}
// load all of our built-in functions
builtins.LoadAllBuiltins()
// Add a custom function to the VM to make available to SQL language
expr.FuncAdd("email_is_valid", &EmailIsValid{})
// We are registering the "csv" datasource, to show that
// the backend/sources can be easily created/added. This csv
// reader is an example datasource that is very, very simple.
exit := make(chan bool)
src, _ := datasource.NewCsvSource("stdin", 0, bytes.NewReader([]byte("##")), exit)
schema.RegisterSourceAsSchema("example_csv", src)
db, err := sql.Open("qlbridge", "example_csv")
if err != nil {
panic(err.Error())
}
defer db.Close()
rows, err := db.Query(sqlText)
if err != nil {
u.Errorf("could not execute query: %v", err)
return
}
defer rows.Close()
cols, _ := rows.Columns()
// this is just stupid hijinx for getting pointers for unknown len columns
readCols := make([]interface{}, len(cols))
writeCols := make([]string, len(cols))
for i := range writeCols {
readCols[i] = &writeCols[i]
}
fmt.Printf("
Scanning through CSV: (%v)
", strings.Join(cols, ","))
for rows.Next() {
rows.Scan(readCols
fmt.Println(strings.Join(writeCols, ", "))
}
fmt.Println("")
}
// Example of a custom Function, that we are adding into the Expression VM
//
// select
// user_id AS theuserid, email, item_count * 2, reg_date
// FROM stdio
// WHERE email_is_valid(email)
type EmailIsValid struct{}
func (m *EmailIsValid) Validate(n *expr.FuncNode) (expr.EvaluatorFunc, error) {
if len(n.Args) != 1 {
return nil, fmt.Errorf("Expected 1 arg for EmailIsValid(arg) but got %s", n)
}
return func(ctx expr.EvalContext, args []value.Value) (value.Value, bool) {
if args[0] == nil || args[0].Err() || args[0].Nil() {
return value.BoolValueFalse, true
}
if _, err := mail.ParseAddress(args[0].ToString()); err == nil {
return value.BoolValueTrue, true
}
return value.BoolValueFalse, true
}, nil
}
func (m *EmailIsValid) Type() value.ValueType { return value.BoolType }
csv 文件
user_id,email,interests,reg_date,item_count,deleted
9Ip1aKbeZe2njCDM,"aaron@email.com","fishing","2012-10-17T17:29:39.738Z",82,false
hT2impsOPUREcVPc,"bob@gmail.com","swimming","2009-12-11T19:53:31.547Z",12,true
hT2impsabc345c,"not_an_email","swimming","2009-12-11T19:53:31.547Z",12,false
运行效果
- 命令
go run main.go -sql '
select
user_id, email, item_count * 2, yy(reg_date) > 10
FROM stdin' < users.csv
- 效果
说明
araddon/qlbridge 的设计是比较灵活的，当然如果从选择的角度来说，dolthub/go-mysql-server 是另外一个开箱即用的不错选择
参考资料
https://github.com/araddon/qlbridge
https://github.com/dataux/dataux
https://github.com/dolthub/go-mysql-server