# Go Client
MyScale is compatible with ClickHouse, so you can use the official Clickhouse Go client (opens new window) to access MyScale from your Go applications.
# Install
go get -u github.com/ClickHouse/clickhouse-go/v2
# Examples
# Connecting to Database
To learn how to establish a connection to the cluster, please refer to the Connection Details section.
// Replace "MYSCALE_CLUSTER_URL" with the endpoint hostname of your cluster,
// which can be found in the MyScale web console.
// An example of the hostname is "msc-ad2378cf.us-east-1.aws.myscale.com"
// Here "default" is your default database, and you can replace "default"
// with the name of your target database.
conn:= clickhouse.OpenDB(&clickhouse.Options{
Addr: []string{"MYSCALE_CLUSTER_URL"},
Auth: clickhouse.Auth{
Database: "default",
Username: "YOUR_USERNAME",
Password: "YOUR_CLUSTER_PASSWORD",
},
Protocol: clickhouse.HTTP,
TLS: &tls.Config{
InsecureSkipVerify: false,
},
})
_, err := conn.Query("SELECT 1")
if err != nil {
fmt.Printf("err %s", err)
return
}
# Importing Data
Create a table with vectors:
_, err = conn.Exec("CREATE TABLE default.myscale_categorical_search" +
"(" +
" id UInt32," +
" data Array(Float32)," +
" CONSTRAINT check_length CHECK length(data) = 128," +
" date Date," +
" label Enum8('person' = 1, 'building' = 2, 'animal' = 3)" +
")" +
"ORDER BY id")
if err != nil {
fmt.Printf("err %s", err)
return
}
Assuming we have a set of data with a defined data structure:
Use Exec
function to batch write data:
scope, err := conn.Begin()
if err != nil {
fmt.Printf("err %s", err)
return
}
batch, err := scope.Prepare("INSERT INTO default.myscale_categorical_search")
if err != nil {
fmt.Printf("err %s", err)
return
}
for i := 0; i < len(data); i++ {
_, err := batch.Exec(
uint32(data[i].ID),
data[i].Data,
data[i].Date,
data[i].Label,
)
if err != nil {
fmt.Printf("err %s", err)
return
}
}
err = scope.Commit()
if err != nil {
fmt.Printf("err %s", err)
return
}
# Creating Vector Index and Search
Create a vector search index:
_, err = conn.Exec("ALTER TABLE default.myscale_categorical_search ADD VECTOR INDEX categorical_vector_idx data TYPE MSTG")
if err != nil {
fmt.Printf("err %s", err)
return
}
Search for vectors and release the result set:
rows, err := conn.Query("SELECT id, date, label, data," + "distance(data, [3.0,9,45,22,28,11,4,3,77,10,4,1,1,4,3,11,23,0," +
"0,0,26,49,6,7,5,3,3,1,11,50,8,9,11,7,15,21,12,17,21,25,121,12,4,7,4,7,4," +
"41,28,2,0,1,10,42,22,20,1,1,4,9,31,79,16,3,23,4,6,26,31,121,87,40,121,82," +
"16,12,15,41,6,10,76,48,5,3,21,42,41,50,5,17,18,64,86,54,17,6,43,62,56,84," +
"116,108,38,26,58,63,20,87,105,37,2,2,121,121,38,25,44,33,24,46,3,16,27,74," +
"121,55,9,4]) AS dist " +
"FROM default.myscale_categorical_search ORDER BY dist LIMIT 10")
if err != nil {
fmt.Printf("err %s", err)
return
}
for rows.Next() {
var (
id int
date string
label string
data []float32
dist float32
)
if err := rows.Scan(&id, &date, &label, &data, &dist); err != nil {
fmt.Printf("err %s", err)
return
}
fmt.Printf("row: id=%d, date=%s, label=%s, dist=%f\n", id, date, label, dist)
}
Output:
row: id=3, date=2024-08-11T00:00:00+08:00, label=animal, dist=252972.640625
row: id=5, date=2025-04-02T00:00:00+08:00, label=building, dist=255089.046875
row: id=9, date=2024-08-11T00:00:00+08:00, label=person, dist=255117.093750
row: id=9, date=1971-02-02T00:00:00+08:00, label=building, dist=255117.093750
row: id=2, date=2015-12-17T00:00:00+08:00, label=person, dist=255440.062500
row: id=0, date=2030-09-26T00:00:00+08:00, label=person, dist=255492.390625
row: id=1, date=1996-06-22T00:00:00+08:00, label=building, dist=255535.312500
row: id=7, date=1970-09-10T00:00:00+08:00, label=building, dist=255631.140625
row: id=4, date=1970-01-31T00:00:00+08:00, label=animal, dist=255742.671875
row: id=8, date=2007-10-26T00:00:00+08:00, label=person, dist=255818.390625
At last, close the connection:
conn.Close()