dat
dat (Data Access Toolkit) is a fast, lightweight Postgres library for Go.
-
Focused on Postgres. See
Insect,Upsert,SelectDoc,QueryJSON -
Built on a solid foundation sqlx
// child DB is *sqlx.DB DB.DB.Queryx(`SELECT * FROM users`)
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SQL and backtick friendly
DB.SQL(`SELECT * FROM people LIMIT 10`).QueryStructs(&people)
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JSON Document retrieval (single trip to Postgres, requires Postgres 9.3+)
DB.SelectDoc("id", "user_name", "avatar"). Many("recent_comments", `SELECT id, title FROM comments WHERE id = users.id LIMIT 10`). Many("recent_posts", `SELECT id, title FROM posts WHERE author_id = users.id LIMIT 10`). One("account", `SELECT balance FROM accounts WHERE user_id = users.id`). From("users"). Where("id = $1", 4). QueryStruct(&obj) // obj must be agreeable with json.Unmarshal()
results in
{ "id": 4, "user_name": "mario", "avatar": "https://imgur.com/a23x.jpg", "recent_comments": [{"id": 1, "title": "..."}], "recent_posts": [{"id": 1, "title": "..."}], "account": { "balance": 42.00 } } -
JSON marshalable bytes (requires Postgres 9.3+)
var b []byte b, _ = DB.SQL(`SELECT id, user_name, created_at FROM users WHERE user_name = $1 `, "mario", ).QueryJSON() // straight into map var obj map[string]interface{} DB.SQL(`SELECT id, user_name, created_at FROM users WHERE user_name = $1 `, "mario", ).QueryObject(&obj)
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Ordinal placeholders
DB.SQL(`SELECT * FROM people WHERE state = $1`, "CA").Exec()
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SQL-like API
err := DB. Select("id, user_name"). From("users"). Where("id = $1", id). QueryStruct(&user)
-
Redis caching
// cache result for 30 seconds key := "user:" + strconv.Itoa(user.id) err := DB. Select("id, user_name"). From("users"). Where("id = $1", user.id). Cache(key, 30 * time.Second, false). QueryStruct(&user)
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Nested transactions
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Per query timeout with database cancellation logic
pg_cancel_backend -
SQL and slow query logging
-
Performant
- ordinal placeholder logic is optimized to be nearly as fast as using
? datcan interpolate queries locally resulting in performance increase over plain database/sql and sqlx. Benchmarks
- ordinal placeholder logic is optimized to be nearly as fast as using
Getting Started
Get it
dat.v1 uses glide package dependency manager. Earlier builds relied on gopkg.in which at the time was as good a solution as any. Will move to dep once it is stable.
glide get gopkg.in/mgutz/dat.v1/sqlx-runner
Use it
import (
"database/sql"
_ "github.com/lib/pq"
"gopkg.in/mgutz/dat.v1"
"gopkg.in/mgutz/dat.v1/sqlx-runner"
)
// global database (pooling provided by SQL driver)
var DB *runner.DB
func init() {
// create a normal database connection through database/sql
db, err := sql.Open("postgres", "dbname=dat_test user=dat password=!test host=localhost sslmode=disable")
if err != nil {
panic(err)
}
// ensures the database can be pinged with an exponential backoff (15 min)
runner.MustPing(db)
// set to reasonable values for production
db.SetMaxIdleConns(4)
db.SetMaxOpenConns(16)
// set this to enable interpolation
dat.EnableInterpolation = true
// set to check things like sessions closing.
// Should be disabled in production/release builds.
dat.Strict = false
// Log any query over 10ms as warnings. (optional)
runner.LogQueriesThreshold = 10 * time.Millisecond
DB = runner.NewDB(db, "postgres")
}
type Post struct {
ID int64 `db:"id"`
Title string `db:"title"`
Body string `db:"body"`
UserID int64 `db:"user_id"`
State string `db:"state"`
UpdatedAt dat.NullTime `db:"updated_at"`
CreatedAt dat.NullTime `db:"created_at"`
}
func main() {
var post Post
err := DB.
Select("id, title").
From("posts").
Where("id = $1", 13).
QueryStruct(&post)
fmt.Println("Title", post.Title)
}
Feature highlights
Use Builders or SQL
Query Builder
var posts []*Post
err := DB.
Select("title", "body").
From("posts").
Where("created_at > $1", someTime).
OrderBy("id ASC").
Limit(10).
QueryStructs(&posts)
Plain SQL
err = DB.SQL(`
SELECT title, body
FROM posts WHERE created_at > $1
ORDER BY id ASC LIMIT 10`,
someTime,
).QueryStructs(&posts)
Note: dat does not trim the SQL string, thus any extra whitespace is transmitted to the database.
In practice, SQL is easier to write with backticks. Indeed, the reason this library exists is most SQL builders introduce a DSL to insulate the user from SQL.
Query builders shine when dealing with data transfer objects, structs.
Fetch Data Simply
Query then scan result to struct(s)
var post Post
err := DB.
Select("id, title, body").
From("posts").
Where("id = $1", id).
QueryStruct(&post)
var posts []*Post
err = DB.
Select("id, title, body").
From("posts").
Where("id > $1", 100).
QueryStructs(&posts)
Query scalar values or a slice of values
var n int64
DB.SQL("SELECT count(*) FROM posts WHERE title=$1", title).QueryScalar(&n)
var ids []int64
DB.SQL("SELECT id FROM posts", title).QuerySlice(&ids)
Field Mapping
dat DOES NOT map fields automatically like sqlx. You must explicitly set db struct tags in your types.
Embedded fields are mapped breadth-first.
type Realm struct {
RealmUUID string `db:"realm_uuid"`
}
type Group struct {
GroupUUID string `db:"group_uuid"`
*Realm
}
g := &Group{Realm: &Realm{"11"}, GroupUUID: "22"}
sql, args := InsertInto("groups").Columns("group_uuid", "realm_uuid").Record(g).ToSQL()
expected := `
INSERT INTO groups ("group_uuid", "realm_uuid")
VALUES ($1, $2)
`
Blacklist and Whitelist
Control which columns get inserted or updated when processing external data
// userData came in from http.Handler, prevent them from setting protected fields
DB.InsertInto("payments").
Blacklist("id", "updated_at", "created_at").
Record(userData).
Returning("id").
QueryScalar(&userData.ID)
// ensure session user can only update his information
DB.Update("users").
SetWhitelist(user, "user_name", "avatar", "quote").
Where("id = $1", session.UserID).
Exec()
IN queries
applicable when dat.EnableInterpolation == true
Simpler IN queries which expand correctly
ids := []int64{10,20,30,40,50}
b := DB.SQL("SELECT * FROM posts WHERE id IN $1", ids)
b.MustInterpolate() == "SELECT * FROM posts WHERE id IN (10,20,30,40,50)"
Tracing SQL
dat uses logxi for logging. By default, logxi logs all warnings and errors to the console. dat logs the SQL and its arguments on any error. In addition, dat logs slow queries as warnings if runner.LogQueriesThreshold > 0
To trace all SQL, set environment variable
LOGXI=dat* yourapp
CRUD
Create
Use Returning and QueryStruct to insert and update struct fields in one trip
var post Post
err := DB.
InsertInto("posts").
Columns("title", "state").
Values("My Post", "draft").
Returning("id", "created_at", "updated_at").
QueryStruct(&post)
Use Blacklist and Whitelist to control which record (input struct) fields are inserted.
post := Post{Title: "Go is awesome", State: "open"}
err := DB.
InsertInto("posts").
Blacklist("id", "user_id", "created_at", "updated_at").
Record(&post).
Returning("id", "created_at", "updated_at").
QueryStruct(&post)
// use wildcard to include all columns
err := DB.
InsertInto("posts").
Whitelist("*").
Record(&post).
Returning("id", "created_at", "updated_at").
QueryStruct(&post)
Insert Multiple Records
// create builder
b := DB.InsertInto("posts").Columns("title")
// add some new posts
for i := 0; i < 3; i++ {
b.Record(&Post{Title: fmt.Sprintf("Article %s", i)})
}
// OR (this is more efficient as it does not do any reflection)
for i := 0; i < 3; i++ {
b.Values(fmt.Sprintf("Article %s", i))
}
// execute statement
_, err := b.Exec()
Inserts if not exists or select in one-trip to database
sql, args := DB.
Insect("tab").
Columns("b", "c").
Values(1, 2).
Where("d = $1", 3).
Returning("id", "f", "g").
ToSQL()
sql == `
WITH
sel AS (SELECT id, f, g FROM tab WHERE (d = $1)),
ins AS (
INSERT INTO "tab"("b","c")
SELECT $2,$3
WHERE NOT EXISTS (SELECT 1 FROM sel)
RETURNING "id","f","g"
)
SELECT * FROM ins UNION ALL SELECT * FROM sel
`
Read
var other Post
err = DB.
Select("id, title").
From("posts").
Where("id = $1", post.ID).
QueryStruct(&other)
published := `
WHERE user_id = $1
AND state = 'published'
`
var posts []*Post
err = DB.
Select("id, title").
From("posts").
Scope(published, 100).
QueryStructs(&posts)
Update
Use Returning to fetch columns updated by triggers. For example, an update trigger on "updated_at" column
err = DB.
Update("posts").
Set("title", "My New Title").
Set("body", "markdown text here").
Where("id = $1", post.ID).
Returning("updated_at").
QueryScalar(&post.UpdatedAt)
Upsert - Update or Insert
sql, args := DB.
Upsert("tab").
Columns("b", "c").
Values(1, 2).
Where("d=$1", 4).
Returning("f", "g").
ToSQL()
expected := `
WITH
upd AS (
UPDATE tab
SET "b" = $1, "c" = $2
WHERE (d=$3)
RETURNING "f","g"
), ins AS (
INSERT INTO "tab"("b","c")
SELECT $1,$2
WHERE NOT EXISTS (SELECT 1 FROM upd)
RETURNING "f","g"
)
SELECT * FROM ins UNION ALL SELECT * FROM upd
`
applicable when dat.EnableInterpolation == true
To reset columns to their default DDL value, use DEFAULT. For example, to reset payment\_type
res, err := DB.
Update("payments").
Set("payment_type", dat.DEFAULT).
Where("id = $1", 1).
Exec()
Use SetBlacklist and SetWhitelist to control which fields are updated.
// create blacklists for each of your structs
blacklist := []string{"id", "created_at"}
p := paymentStructFromHandler
err := DB.
Update("payments").
SetBlacklist(p, blacklist...)
Where("id = $1", p.ID).
Exec()
Use a map of attributes
attrsMap := map[string]interface{}{"name": "Gopher", "language": "Go"}
result, err := DB.
Update("developers").
SetMap(attrsMap).
Where("language = $1", "Ruby").
Exec()
Delete
result, err = DB.
DeleteFrom("posts").
Where("id = $1", otherPost.ID).
Exec()
Joins
Define JOINs in argument to From
err = DB.
Select("u.*, p.*").
From(`
users u
INNER JOIN posts p on (p.author_id = u.id)
`).
WHERE("p.state = 'published'").
QueryStructs(&liveAuthors)
Scopes
Scopes predefine JOIN and WHERE conditions. Scopes may be used with DeleteFrom, Select and Update.
As an example, a "published" scope might define published posts by user.
publishedPosts := `
INNER JOIN users u on (p.author_id = u.id)
WHERE
p.state == 'published' AND
p.deleted_at IS NULL AND
u.user_name = $1
`
unpublishedPosts := `
INNER JOIN users u on (p.author_id = u.id)
WHERE
p.state != 'published' AND
p.deleted_at IS NULL AND
u.user_name = $1
`
err = DB.
Select("p.*"). // must qualify columns
From("posts p").
Scope(publishedPosts, "mgutz").
QueryStructs(&posts)
Creating Connections
All queries are made in the context of a connection which is acquired from the underlying SQL driver's pool
For one-off operations, use DB directly
err := DB.SQL(sql).QueryStruct(&post)
For multiple operations, create a Tx transaction. defer Tx.AutoCommit() or defer Tx.AutoRollback() MUST be called
func PostsIndex(rw http.ResponseWriter, r *http.Request) {
tx, _ := DB.Begin()
defer tx.AutoRollback()
// Do queries with the session
var post Post
err := tx.Select("id, title").
From("posts").
Where("id = $1", post.ID).
QueryStruct(&post)
)
if err != nil {
// `defer AutoRollback()` is used, no need to rollback on error
r.WriteHeader(500)
return
}
// do more queries with transaction ...
// MUST commit or AutoRollback() will rollback
tx.Commit()
}
DB and Tx implement runner.Connection interface to keep code DRY
func getUsers(conn runner.Connection) ([]*dto.Users, error) {
sql := `
SELECT *
FROM users
`
var users []*dto.Users
err := conn.SQL(sql).QueryStructs(&users)
if err != nil {
return err
}
return users
}
Nested Transactions
Nested transaction logic is as follows:
-
If
Commitis called in a nested transaction, the operation results in no operation (NOOP). Only the top levelCommitcommits the transaction to the database. -
If
Rollbackis called in a nested transaction, then the entire transaction is rolled back.Tx.IsRollbackedis set to true. -
Either
defer Tx.AutoCommit()ordefer Tx.AutoRollback()MUST BE CALLED for each correspondingBegin. The internal state of nested transactions is tracked in these two methods.
func nested(conn runner.Connection) error {
tx, err := conn.Begin()
if err != nil {
return err
}
defer tx.AutoRollback()
_, err := tx.SQL(`INSERT INTO users (email) values $1`, "[email protected]").Exec()
if err != nil {
return err
}
// prevents AutoRollback
tx.Commit()
}
func top() {
tx, err := DB.Begin()
if err != nil {
logger.Fatal("Could not create transaction")
}
defer tx.AutoRollback()
err := nested(tx)
if err != nil {
return
}
// top level commits the transaction
tx.Commit()
}
Timeouts
A timeout may be set on any Query* or Exec with the Timeout method. When a timeout is set, the query is run in a separate goroutine and should a timeout occur dat will cancel the query via Postgres' pg_cancel_backend.
err := DB.Select("SELECT pg_sleep(1)").Timeout(1 * time.Millisecond).Exec()
err == dat.ErrTimedout
Dates
Use dat.NullTime type to properly handle nullable dates from JSON and Postgres.
Constants
applicable when dat.EnableInterpolation == true
dat provides often used constants in SQL statements
dat.DEFAULT- insertsDEFAULTdat.NOW- insertsNOW()
Defining Constants
UnsafeStrings and constants will panic unless dat.EnableInterpolation == true
To define SQL constants, use UnsafeString
const CURRENT_TIMESTAMP = dat.UnsafeString("NOW()")
DB.SQL("UPDATE table SET updated_at = $1", CURRENT_TIMESTAMP)
UnsafeString is exactly that, UNSAFE. If you must use it, create a constant and NEVER use UnsafeString directly as an argument like this
DB.SQL("UPDATE table SET updated_at = $1", dat.UnsafeString(someVar))
Primitive Values
Load scalar and slice values.
var id int64
var userID string
err := DB.
Select("id", "user_id").From("posts").Limit(1).QueryScalar(&id, &userID)
var ids []int64
err = DB.Select("id").From("posts").QuerySlice(&ids)
Caching
dat implements caching backed by an in-memory or Redis store. The in-memory store is not recommended for production use. Caching can cache any struct or primitive type that can be marshaled/unmarshaled cleanly with the json package due to Redis being a string value store.
Time is especially problematic as JavaScript, Postgres and Go have different time formats. Use the type dat.NullTime if you are getting cannot parse time errors.
Caching is performed before the database driver lessening the workload on the database.
// key-value store (kvs) package
import "gopkg.in/mgutz/dat.v1/kvs"
func init() {
// Redis: namespace is the prefix for keys and should be unique
store, err := kvs.NewRedisStore("namespace:", ":6379", "passwordOrEmpty")
// Or, in-memory store provided by [go-cache](https://github.com/pmylund/go-cache)
cleanupInterval := 30 * time.Second
store = kvs.NewMemoryStore(cleanupInterval)
runner.SetCache(store)
}
// Cache states query for a year using key "namespace:states"
b, err := DB.
SQL(`SELECT * FROM states`).
Cache("states", 365 * 24 * time.Hour, false).
QueryJSON()
// Without a key, the checksum of the query is used as the cache key.
// In this example, the interpolated SQL will contain their user_name
// (if EnableInterpolation is true) effectively caching each user.
//
// cacheID == checksum("SELECT * FROM users WHERE user_name='mario'")
b, err := DB.
SQL(`SELECT * FROM users WHERE user_name = $1`, user).
Cache("", 365 * 24 * time.Hour, false).
QueryJSON()
// Prefer using known unique IDs to avoid the computation cost
// of the checksum key.
key = "user" + user.UserName
b, err := DB.
SQL(`SELECT * FROM users WHERE user_name = $1`, user).
Cache(key, 15 * time.Minute, false).
QueryJSON()
// Set invalidate to true to force setting the key
statesUpdated := true
b, err := DB.
SQL(`SELECT * FROM states`).
Cache("states", 365 * 24 * time.Hour, statesUpdated).
QueryJSON()
// Clears the entire cache
runner.Cache.FlushDB()
runner.Cache.Del("fookey")
SQL Interpolation
Interpolation is DISABLED by default. Set dat.EnableInterpolation = true to enable.
dat can interpolate locally to inline query arguments. For example, this statement
go
db.Exec(
"INSERT INTO (a, b, c, d) VALUES ($1, $2, $3, $4)",
[]interface{}[1, 2, 3, 4],
)
is sent to the database with inlined args bypassing prepared statement logic in the lib/pq layer
"INSERT INTO (a, b, c, d) VALUES (1, 2, 3, 4)"
Interpolation provides these benefits:
- Performance improvements
- Debugging/tracing is simpler with interpolated SQL
- May use safe SQL constants like
dat.NOWanddat.DEFAULT - Expand placeholders with slice values
$1 => (1, 2, 3)
Read SQL Interpolation in wiki for more details and SQL injection.
