clickhouse-core-workflow-b

name	clickhouse-core-workflow-b
description	Insert, query, and aggregate data in ClickHouse with real SQL patterns. Use when writing analytical queries, inserting data at scale, building dashboards, or implementing materialized views for pre-aggregation. Trigger with "clickhouse query", "clickhouse insert", "clickhouse aggregate", "clickhouse materialized view", "clickhouse SQL".
allowed-tools	Read, Write, Edit, Bash(npm:*)
version	1.7.0
license	MIT
author	Jeremy Longshore <[e-mail]>
tags	["saas","database","analytics","clickhouse","olap"]
compatibility	Designed for Claude Code

ClickHouse Insert & Query (Core Workflow B)

Overview

Move data into ClickHouse efficiently, then answer analytical questions with aggregations, funnels, retention, window functions, and materialized views. This skill covers the read/write half of the core workflow: the fast-path insert patterns that avoid "too many parts", the parameterized query API for Node.js, and pre-aggregation via materialized views. The high-frequency patterns live inline below; the deep query library and advanced engine patterns are broken out into references/ so you can drill in only when you need them.

Prerequisites

• Tables already created — run clickhouse-core-workflow-a first if not.
• @clickhouse/client installed and connected (CLICKHOUSE_HOST, CLICKHOUSE_USER, CLICKHOUSE_PASSWORD in the environment).
• A target database/table (examples use analytics.events).

Instructions

Step 1: Bulk insert (the fast path)

Batch rows and let the client buffer. ClickHouse writes a new "part" per INSERT, so many tiny inserts are the number-one performance mistake.

import { createClient } from '@clickhouse/client';

const client = createClient({
  url: process.env.CLICKHOUSE_HOST!,
  username: process.env.CLICKHOUSE_USER ?? 'default',
  password: process.env.CLICKHOUSE_PASSWORD ?? '',
});

// Insert many rows efficiently — @clickhouse/client buffers internally
await client.insert({
  table: 'analytics.events',
  values: events,   // Array of objects matching table columns
  format: 'JSONEachRow',
});