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Programming language: Go
License: MIT License

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README

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KSQL the Keep it Simple SQL library

KSQL was created to offer an actually simple and satisfactory tool for interacting with SQL Databases in Golang.

The core idea on KSQL is to offer an easy to use interface, the actual communication with the database is decoupled so we can use KSQL on top of pgx, database/sql and possibly other tools. You can even create you own backend adapter for KSQL which is useful in some situations.

In this README you will find examples for "Getting Started" with the library, for more advanced use-cases please read our Wiki.

Let's start with some Code:

This short example below is a TLDR version for illustrating how easy it is to use KSQL.

You will find more complete examples on the sections below.

package main

import (
    "context"
    "fmt"
    "log"
    "os"

    "github.com/vingarcia/ksql"
    "github.com/vingarcia/ksql/adapters/kpgx"
)

var UsersTable = ksql.NewTable("users", "user_id")

type User struct {
    ID   int    `ksql:"user_id"`
    Name string `ksql:"name"`
    Type string `ksql:"type"`
}

func main() {
    ctx := context.Background()
    db, err := kpgx.New(ctx, os.Getenv("POSTGRES_URL"), ksql.Config{})
    if err != nil {
        log.Fatalf("unable connect to database: %s", err)
    }
    defer db.Close()

    // For querying only some attributes you can
    // create a custom struct like this:
    var count []struct {
        Count string `ksql:"count"`
        Type string `ksql:"type"`
    }
    err = db.Query(ctx, &count, "SELECT type, count(*) as count FROM users WHERE type = $1 GROUP BY type", "admin")
    if err != nil {
        log.Fatalf("unable to query users: %s", err)
    }

    fmt.Println("number of users by type:", count)

    // For loading entities from the database KSQL can build
    // the SELECT part of the query for you if you omit it like this:
    var users []User
    err = db.Query(ctx, &users, "FROM users WHERE type = $1", "admin")
    if err != nil {
        log.Fatalf("unable to query users: %s", err)
    }

    fmt.Println("users:", users)
}

We currently have 4 constructors available, one of them is illustrated above (kpgx.New()), the other ones have the exact same signature but work on different databases, they are:

  • kpgx.New(ctx, os.Getenv("DATABASE_URL"), ksql.Config{}) for Postgres, it works on top of pgxpool
  • kmysql.New(ctx, os.Getenv("DATABASE_URL"), ksql.Config{}) for MySQL, it works on top of database/sql
  • ksqlserver.New(ctx, os.Getenv("DATABASE_URL"), ksql.Config{}) for SQLServer, it works on top of database/sql
  • ksqlite3.New(ctx, os.Getenv("DATABASE_URL"), ksql.Config{}) for SQLite3, it works on top of database/sql

The KSQL Interface

The current interface contains the methods the users are expected to use, and it is also used for making it easy to mock the whole library if needed.

This interface is declared in the project as ksql.Provider and is displayed below.

We plan on keeping it very simple with a small number of well thought functions that cover all use-cases, so don't expect many additions:

// Provider describes the KSQL public behavior
//
// The Insert, Patch, Delete and QueryOne functions return `ksql.ErrRecordNotFound`
// if no record was found or no rows were changed during the operation.
type Provider interface {
    Insert(ctx context.Context, table Table, record interface{}) error
    Patch(ctx context.Context, table Table, record interface{}) error
    Delete(ctx context.Context, table Table, idOrRecord interface{}) error

    Query(ctx context.Context, records interface{}, query string, params ...interface{}) error
    QueryOne(ctx context.Context, record interface{}, query string, params ...interface{}) error
    QueryChunks(ctx context.Context, parser ChunkParser) error

    Exec(ctx context.Context, query string, params ...interface{}) (rowsAffected int64, _ error)
    Transaction(ctx context.Context, fn func(Provider) error) error
}

Using KSQL

In the example below we'll cover all the most common use-cases such as:

  1. Inserting records
  2. Updating records
  3. Deleting records
  4. Querying one or many records
  5. Making transactions

More advanced use cases are illustrated on their own pages on our Wiki:

For the more common use-cases please read the example below, which is also available [here](./examples/crud/crud.go) if you want to compile it yourself.

package main

import (
    "context"
    "fmt"

    "github.com/vingarcia/ksql"
    "github.com/vingarcia/ksql/adapters/ksqlite3"
    "github.com/vingarcia/ksql/nullable"
)

// User ...
type User struct {
    ID   int    `ksql:"id"`
    Name string `ksql:"name"`
    Age  int    `ksql:"age"`

    // This field will be saved as JSON in the database
    Address Address `ksql:"address,json"`
}

// PartialUpdateUser ...
type PartialUpdateUser struct {
    ID      int      `ksql:"id"`
    Name    *string  `ksql:"name"`
    Age     *int     `ksql:"age"`
    Address *Address `ksql:"address,json"`
}

// Address ...
type Address struct {
    State string `json:"state"`
    City  string `json:"city"`
}

// UsersTable informs KSQL the name of the table and that it can
// use the default value for the primary key column name: "id"
var UsersTable = ksql.NewTable("users")

func main() {
    ctx := context.Background()

    // The available adapters are:
    // - kpgx.New(ctx, connURL, ksql.Config{})
    // - kmysql.New(ctx, connURL, ksql.Config{})
    // - ksqlserver.New(ctx, connURL, ksql.Config{})
    // - ksqlite3.New(ctx, connURL, ksql.Config{})
    //
    // For more detailed examples see:
    // - `./examples/all_adapters/all_adapters.go`
    //
    // In this example we'll use sqlite3:
    db, err := ksqlite3.New(ctx, "/tmp/hello.sqlite", ksql.Config{
        MaxOpenConns: 1,
    })
    if err != nil {
        panic(err.Error())
    }
    defer db.Close()

    // In the definition below, please note that BLOB is
    // the only type we can use in sqlite for storing JSON.
    _, err = db.Exec(ctx, `CREATE TABLE IF NOT EXISTS users (
      id INTEGER PRIMARY KEY,
        age INTEGER,
        name TEXT,
        address BLOB
    )`)
    if err != nil {
        panic(err.Error())
    }

    var alison = User{
        Name: "Alison",
        Age:  22,
        Address: Address{
            State: "MG",
        },
    }
    err = db.Insert(ctx, UsersTable, &alison)
    if err != nil {
        panic(err.Error())
    }
    fmt.Println("Alison ID:", alison.ID)

    // Inserting inline:
    err = db.Insert(ctx, UsersTable, &User{
        Name: "Cristina",
        Age:  27,
        Address: Address{
            State: "SP",
        },
    })
    if err != nil {
        panic(err.Error())
    }

    // Deleting Alison:
    err = db.Delete(ctx, UsersTable, alison.ID)
    if err != nil {
        panic(err.Error())
    }

    // Retrieving Cristina, note that if you omit the SELECT part of the query
    // KSQL will build it for you (efficiently) based on the fields from the struct:
    var cris User
    err = db.QueryOne(ctx, &cris, "FROM users WHERE name = ? ORDER BY id", "Cristina")
    if err != nil {
        panic(err.Error())
    }
    fmt.Printf("Cristina: %#v\n", cris)

    // Updating all fields from Cristina:
    cris.Name = "Cris"
    err = db.Patch(ctx, UsersTable, cris)

    // Changing the age of Cristina but not touching any other fields:

    // Partial update technique 1:
    err = db.Patch(ctx, UsersTable, struct {
        ID  int `ksql:"id"`
        Age int `ksql:"age"`
    }{ID: cris.ID, Age: 28})
    if err != nil {
        panic(err.Error())
    }

    // Partial update technique 2:
    err = db.Patch(ctx, UsersTable, PartialUpdateUser{
        ID:  cris.ID,
        Age: nullable.Int(28), // (just a pointer to an int, if null it won't be updated)
    })
    if err != nil {
        panic(err.Error())
    }

    // Listing first 10 users from the database
    // (each time you run this example a new Cristina is created)
    //
    // Note: Using this function it is recommended to set a LIMIT, since
    // not doing so can load too many users on your computer's memory or
    // cause an Out Of Memory Kill.
    //
    // If you need to query very big numbers of users we recommend using
    // the `QueryChunks` function.
    var users []User
    err = db.Query(ctx, &users, "FROM users LIMIT 10")
    if err != nil {
        panic(err.Error())
    }

    // Making transactions:
    err = db.Transaction(ctx, func(db ksql.Provider) error {
        var cris2 User
        err = db.QueryOne(ctx, &cris2, "FROM users WHERE id = ?", cris.ID)
        if err != nil {
            // This will cause an automatic rollback:
            return err
        }

        err = db.Patch(ctx, UsersTable, PartialUpdateUser{
            ID:  cris2.ID,
            Age: nullable.Int(29),
        })
        if err != nil {
            // This will also cause an automatic rollback and then panic again
            // so that we don't hide the panic inside the KissSQL library
            panic(err.Error())
        }

        // Commits the transaction
        return nil
    })
    if err != nil {
        panic(err.Error())
    }

    fmt.Printf("Users: %#v\n", users)
}

Benchmark Comparison

The results of the benchmark are good: they show that KSQL is in practical terms, as fast as sqlx which was our goal from the start.

To understand the benchmark below you must know that all tests are performed using Postgres 12.1 and that we are comparing the following tools:

  • KSQL using the adapter that wraps database/sql
  • KSQL using the adapter that wraps pgx
  • database/sql
  • sqlx
  • pgx (with pgxpool)
  • gorm
  • sqlc
  • sqlboiler

For each of these tools we are running 3 different queries:

The insert-one query looks like:

INSERT INTO users (name, age) VALUES ($1, $2) RETURNING id

The single-row query looks like:

SELECT id, name, age FROM users OFFSET $1 LIMIT 1

The multiple-rows query looks like:

SELECT id, name, age FROM users OFFSET $1 LIMIT 10

Keep in mind that some of the tools tested (like GORM) actually build the queries internally so the actual code used for the benchmark might differ a little bit from the example ones above.

Without further ado, here are the results:

$ make bench TIME=5s
find . -name go.mod -execdir go mod tidy \;
sqlc generate
go test -bench=. -benchtime=5s
goos: linux
goarch: amd64
pkg: github.com/vingarcia/ksql/benchmarks
cpu: Intel(R) Core(TM) i7-10750H CPU @ 2.60GHz
BenchmarkInsert/ksql/sql-adapter/insert-one-12              9513        625637 ns/op
BenchmarkInsert/ksql/pgx-adapter/insert-one-12             10000        541374 ns/op
BenchmarkInsert/sql/insert-one-12                           9369        618969 ns/op
BenchmarkInsert/sql/prep-stmt/insert-one-12                10000        551131 ns/op
BenchmarkInsert/sqlx/insert-one-12                          9328        629889 ns/op
BenchmarkInsert/pgxpool/insert-one-12                      10000        542283 ns/op
BenchmarkInsert/gorm/insert-one-12                          8716        675421 ns/op
BenchmarkInsert/sqlc/insert-one-12                          9446        629378 ns/op
BenchmarkInsert/sqlc/prep-stmt/insert-one-12               10000        553632 ns/op
BenchmarkInsert/sqlboiler/insert-one-12                     9595        633391 ns/op
BenchmarkQuery/ksql/sql-adapter/single-row-12              40746        146739 ns/op
BenchmarkQuery/ksql/sql-adapter/multiple-rows-12           37886        156191 ns/op
BenchmarkQuery/ksql/pgx-adapter/single-row-12              79155         71939 ns/op
BenchmarkQuery/ksql/pgx-adapter/multiple-rows-12           73729         83560 ns/op
BenchmarkQuery/sql/single-row-12                           42253        143241 ns/op
BenchmarkQuery/sql/multiple-rows-12                        40456        149423 ns/op
BenchmarkQuery/sql/prep-stmt/single-row-12                 83389         72348 ns/op
BenchmarkQuery/sql/prep-stmt/multiple-rows-12              77712         76644 ns/op
BenchmarkQuery/sqlx/single-row-12                          41792        145506 ns/op
BenchmarkQuery/sqlx/multiple-rows-12                       39500        151435 ns/op
BenchmarkQuery/pgxpool/single-row-12                       85870         69418 ns/op
BenchmarkQuery/pgxpool/multiple-rows-12                    79922         73978 ns/op
BenchmarkQuery/gorm/single-row-12                          77432         78407 ns/op
BenchmarkQuery/gorm/multiple-rows-12                       61074         96030 ns/op
BenchmarkQuery/sqlc/single-row-12                          42672        145121 ns/op
BenchmarkQuery/sqlc/multiple-rows-12                       40122        149068 ns/op
BenchmarkQuery/sqlc/prep-stmt/single-row-12                81829         73210 ns/op
BenchmarkQuery/sqlc/prep-stmt/multiple-rows-12             74799         78834 ns/op
BenchmarkQuery/sqlboiler/single-row-12                     64158         93305 ns/op
BenchmarkQuery/sqlboiler/multiple-rows-12                  64686         92270 ns/op
PASS
ok      github.com/vingarcia/ksql/benchmarks    200.547s
Benchmark executed at: 2022-07-26
Benchmark executed on commit: 3d34bae47e90ff84d87ba47a2fad81d21390c5ec

Running the KSQL tests (for contributors)

The tests use docker-test for setting up all the supported databases, which means that:

  • You need to have docker installed
  • You must be able to run docker without sudo, i.e. if you are not root you should add yourself to the docker group, e.g.:
  $ sudo usermod <your_username> -aG docker

And then restart your login session (or just reboot)

After that you can just run the tests by using:

make test

But it is recommended to first download the required images using:

docker pull postgres:14.0
docker pull mysql:8.0.27
docker pull mcr.microsoft.com/mssql/server:2017-latest

Otherwise the first attempt to run the tests will spend a long time downloading these images and then fail because the TestMain() function is configured to kill the containers after 20 seconds.

TODO List

  • Add support for serializing structs as other formats such as YAML
  • Update ksqltest.FillStructWith to work with ksql:"..,json" tagged attributes
  • Create a way for users to submit user defined dialects
  • Improve error messages (ongoing)
  • Add support for the Patch function to work with maps for partial updates
  • Add support for the Insert function to work with maps
  • Add support for a ksql.Array(params ...interface{}) for allowing queries like this: db.Query(ctx, &user, "SELECT * FROM user WHERE id in (?)", ksql.Array(1,2,3))
  • Improve docs about ksql.Mock

Optimization Oportunities

  • Test if using a pointer on the field info is faster or not
  • Consider passing the cached structInfo as argument for all the functions that use it, so that we don't need to get it more than once in the same call.
  • Use a cache to store often used queries (like pgx)
  • Preload the insert method for all dialects inside ksql.NewTable()
  • Use prepared statements for the helper functions, Update, Insert and Delete.

Features for a possible V2

  • Change the .Transaction(db ksql.Provider) to a .Transaction(ctx context.Context)
  • Make the .Query() method to return a type Query interface { One(); All(); Chunks(); }
  • Have an Update() method that updates without ignoring NULLs as Patch() does
  • Rename NewTable() to just Table() so it feels right to declare it inline when convenient