From clickhouse-pack
Creates ClickHouse MergeTree table for events, inserts JSONEachRow data via @clickhouse/client, and runs analytical GROUP BY queries. For new projects, MergeTree learning, or connection tests.
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin clickhouse-packThis skill is limited to using the following tools:
Create a MergeTree table, insert rows with JSONEachRow, and run your first
Designs ClickHouse schemas with MergeTree engines, ORDER BY sort keys, partitioning, and codecs for analytical workloads and query optimization.
Provides ClickHouse table design patterns with MergeTree engines, query optimization techniques, and best practices for high-performance analytics and data engineering.
Provides ClickHouse patterns for MergeTree table design, query optimization, aggregations, data ingestion, and analytics. Useful for OLAP workloads, schema design, performance tuning, and migrations from PostgreSQL/MySQL.
Share bugs, ideas, or general feedback.
Create a MergeTree table, insert rows with JSONEachRow, and run your first
analytical query -- all using the official @clickhouse/client.
@clickhouse/client installed and connected (see clickhouse-install-auth)import { createClient } from '@clickhouse/client';
const client = createClient({
url: process.env.CLICKHOUSE_HOST ?? 'http://localhost:8123',
username: process.env.CLICKHOUSE_USER ?? 'default',
password: process.env.CLICKHOUSE_PASSWORD ?? '',
});
await client.command({
query: `
CREATE TABLE IF NOT EXISTS events (
event_id UUID DEFAULT generateUUIDv4(),
event_type LowCardinality(String),
user_id UInt64,
payload String,
created_at DateTime DEFAULT now()
)
ENGINE = MergeTree()
ORDER BY (event_type, created_at)
PARTITION BY toYYYYMM(created_at)
TTL created_at + INTERVAL 90 DAY
`,
});
console.log('Table "events" created.');
Key concepts:
MergeTree() -- the foundational ClickHouse engine for analyticsORDER BY -- defines the primary index (sort key); pick columns you filter/group onPARTITION BY -- splits data into parts by month for efficient pruningTTL -- automatic data expirationLowCardinality(String) -- dictionary-encoded string, ideal for columns with < 10K distinct valuesawait client.insert({
table: 'events',
values: [
{ event_type: 'page_view', user_id: 1001, payload: '{"url":"/home"}' },
{ event_type: 'click', user_id: 1001, payload: '{"button":"signup"}' },
{ event_type: 'page_view', user_id: 1002, payload: '{"url":"/pricing"}' },
{ event_type: 'purchase', user_id: 1002, payload: '{"amount":49.99}' },
{ event_type: 'page_view', user_id: 1003, payload: '{"url":"/docs"}' },
],
format: 'JSONEachRow',
});
console.log('Inserted 5 events.');
// Count events by type
const rs = await client.query({
query: `
SELECT
event_type,
count() AS total,
uniqExact(user_id) AS unique_users
FROM events
GROUP BY event_type
ORDER BY total DESC
`,
format: 'JSONEachRow',
});
const rows = await rs.json<{
event_type: string;
total: string; // ClickHouse returns numbers as strings in JSON
unique_users: string;
}>();
for (const row of rows) {
console.log(`${row.event_type}: ${row.total} events, ${row.unique_users} users`);
}
Expected output:
page_view: 3 events, 3 users
click: 1 events, 1 users
purchase: 1 events, 1 users
// Check table size and row count
const stats = await client.query({
query: `
SELECT
table,
formatReadableSize(sum(bytes_on_disk)) AS disk_size,
sum(rows) AS row_count,
count() AS part_count
FROM system.parts
WHERE active AND database = currentDatabase() AND table = 'events'
GROUP BY table
`,
format: 'JSONEachRow',
});
console.log('Table stats:', await stats.json());
| Engine | Use Case |
|---|---|
MergeTree | General-purpose analytics |
ReplacingMergeTree | Upserts (dedup by ORDER BY key) |
SummingMergeTree | Auto-sum numeric columns on merge |
AggregatingMergeTree | Pre-aggregated materialized views |
CollapsingMergeTree | State changes / versioned rows |
| Type | Example | Notes |
|---|---|---|
UInt8/16/32/64 | user_id UInt64 | Unsigned integers |
Int8/16/32/64 | delta Int32 | Signed integers |
Float32/64 | price Float64 | IEEE 754 |
Decimal(P,S) | amount Decimal(18,2) | Exact decimal |
String | name String | Variable-length bytes |
DateTime | created_at DateTime | Unix timestamp (seconds) |
DateTime64(3) | ts DateTime64(3) | Millisecond precision |
UUID | id UUID | 128-bit UUID |
Array(T) | tags Array(String) | Variable-length array |
LowCardinality(T) | status LowCardinality(String) | Dictionary encoding |
| Error | Cause | Solution |
|---|---|---|
Table already exists | Re-running CREATE | Use IF NOT EXISTS |
Unknown column | Typo in column name | Check DESCRIBE TABLE events |
Type mismatch | Wrong data type in insert | Match types to schema |
Memory limit exceeded | Query too broad | Add WHERE clauses, use LIMIT |
Proceed to clickhouse-local-dev-loop for Docker-based local development.