This package is written in TypeScript because Node.js typing development is already an industry standard.
It has been empirically verified that in-memory collecting rows is the most efficient and consistent way to insert into Clickhouse. To work with built-in caching, you just need to call the useCaching() method
clickhouse-ts doesn't use a lot of abstractions and dependencies, so it's fast and stable.
The Lookforsale team has been using clickhouse-ts effectively for over a year under extreme loads!
Double checking data for anomalies during in-memory caching and when inserting a finished batch.
Flexible configuration of the Clickhouse client instance and support for all features provided by Clickhouse developers.
SQL Injection Protection with sqlstring
The package has a public license and is available for download to any developer!## Installation
Starting from version 2.0.0
the caching module should be imported separately.
This is because clickcache package, like clickhouse-ts, is going to be part of my Clickhouse Node.js ecosystem.
In addition, it planned to introduce data validation, as in Joi and model generation, as in mongodb/mongoose.
npm i clickhouse-ts
npm i clickcache
- Implement http/cli-queries-with-parameters feature
- Complete in/out data validation with schemas
- Make it works with GrahpQL or something like cube.js
Basically, this client supports data insertion, but you should consider collecting your data before passing it as an argument here. Use clickcache
to prepare batches!
Starting from version 2.0.0
the caching module should be imported separately.
This is because clickcache package, like clickhouse-ts, is going to be part of my Clickhouse Node.js ecosystem.
In addition, it planned to introduce data validation, as in Joi and model generation, as in mongodb/mongoose.
Only HTTP(s) protocol is supported.
const client = new Clickhouse(
{
url: 'url',
port: 8443,
user: 'user',
password: 'password',
database: 'database',
ca: fs.readFileSync('cert.crt')
},
{
/* https://clickhouse.com/docs/en/interfaces/formats */
defaultResponseFormat: 'JSON',
clickhouseOptions: {
/* https://clickhouse.tech/docs/en/operations/settings/settings/ */
send_progress_in_http_headers: '1'
}
}
)
const response = await client.insert('table_strings', rows, {
format: 'CSVWithNames'
})
await clickhouseInstance.query<{ t: string }>('WITH now() as t SELECT t', {
format: 'TSV',
send_progress_in_http_headers: '1'
})
await clickhouseInstance.query(`
CREATE TABLE strings (
date DateTime('UTC'),
string String
) Engine = ReplacingMergeTree()
PARTITION BY toMonday(date)
ORDER BY (date, string)
`, { noFormat: true })