clickhouse/agent-skills

clickhouse-js-node-rowbinary

Generate TypeScript/JavaScript code that reads/decodes AND writes/encodes ClickHouse RowBinary streams for the ClickHouse HTTP server.

Voir la source

Mode d’emploi

  1. Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
  2. Consultez le document original pour les outils, identifiants et environnements requis.
  3. Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/clickhouse/agent-skills --skill clickhouse-js-node-rowbinary

Avant de commencer

  • L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
  • Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Document Skill original

Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.

ClickHouse JS RowBinary Codec Generator for Node.js

This skill generates both directions of the wire format: readers (decode bytes → values) and writers (encode values → bytes, the mirror). A given task normally needs only one side. This file is the shared entry point — the format gate plus the principles common to both directions; the per-direction decisions, guidance, and the per-type reference tables live in two sibling files.

Pick your side — read only the one you need:

  • Decoding a `RowBinary` response** from ClickHouse into JS values →

[reader.md](reader.md). Streaming vs whole-buffer, row-objects vs columnar, fixed vs runtime schema, and the per-type reader reference.

  • Encoding JS values into a `RowBinary` payload to send to ClickHouse →

[writer.md](writer.md). The Sink/writeX building blocks, writeRows streaming, and the per-type writer reference.

The per-type code is real, split by direction under src/readers/ and src/writers/.

First: is RowBinary even the right format?

RowBinary exists for throughput, but it is not automatically the fastest path — match the format to the shape of the data before committing to a bespoke parser.

Prefer a `JSON format (e.g. JSONEachRow) when** the result is mostly strings / JSON-like values that you consume wholesale — randomly accessing essentially every field, running string/regexp methods on them, treating values as text. V8's native JSON.parse is heavily optimized C++ and builds JS strings and objects faster than a JS-level RowBinary decoder can; pair it with HTTP response compression (gzip / zstd`, which crushes JSON's repetitive keys) and the wire cost shrinks too.

RowBinary clearly wins when the result is dominated by:

  • Wide numerics — Int128/Int256/UInt128/UInt256,

Decimal128/Decimal256.

  • Binary / fixed-width blobs — IPv4, IPv6, UUID, FixedString.
  • High-volume fixed-width numeric columns generally, where each value is a

single DataView read.

Prefer the `Native` format when columnar load and client-side analytics are the main goal (fold/scan/filter columns, feed typed arrays to a Worker or WASM). Native is column-major, so it loads straight into one typed array per column with no transpose.

For help choosing and consuming a JSON* format (or CSV / TSV) instead, use the `clickhouse-js-node-coding` skill.

Core guidance (both directions)

These principles apply whether you are generating a reader or a writer; the side-specific operational guidance is in reader.md / writer.md.

  • Little-endian only. RowBinary is little-endian; target x86/ARM. Read and

write every multi-byte number with DataView accessors passing a literal true for the littleEndian flag.

  • Correct first, then optimize. First emit a correct codec built from the

plain per-type API. Only after it's correct (and tested) specialize it. Don't bake performance assumptions in before correctness.

  • Monomorphize generic/composite types. Emit specialized, inlined code per

type combination instead of passing functions as arguments where the type is known ahead of time.

  • Inline the leaf ops. The per-type readX/writeX functions are the

correct, composable reference; the generated codec should INLINE their bodies, not call them, so the row loop is straight-line with no per-field indirection (and so the fixed-width coalescing can fold the offset arithmetic together).

  • Annotate the type per column. Inlining erases the type structure, so put a

short comment above each column's encode/decode block naming the ClickHouse type it handles.

  • Shared scratch is not reentrant. Some hot methods reuse a module-level

scratch buffer as a write-then-read pair — correct only because the access is fully synchronous. An async/yield boundary between populating and reading it corrupts the value.

  • TypeScript by default. Generate TypeScript code and helpers unless the user

explicitly asks for plain JavaScript.

Worked examples

Six end-to-end examples with real speedup are catalogued in EXAMPLES.md.

Out of scope

  • JSON / CSV / TSV / Parquet parsing → use clickhouse-js-node-coding.
  • Connection errors, hangs, type mismatches → use

clickhouse-js-node-troubleshooting.

  • Browser / Web Worker / Edge → @clickhouse/client-web.

Still Stuck?

Tâches connexes

du même dépôt

Autres Skills

Tous les Skills
clickhouse
Officiel

chdb-datastore

Use when the user has tabular data (pandas DataFrame, parquet, csv, Arrow, json) and wants to filter, group, aggregate, join, or speed up slow pandas. Provides chDB DataStore — same pandas API, ClickHouse engine underneath. Also handles reading from S3, MySQL, PostgreSQL, MongoDB, ClickHouse Cloud, Iceberg, Delta Lake as DataFrames and joining across sources. TRIGGER when: user mentions DataFrame, parquet, csv, "fast pandas", "speed up pandas", or cross-source DataFrame joins; user imports chdb.

installations
2
GitHub Stars
557
Mis à jour
21 oct.
clickhouse
Officiel

clickhouse-managed-postgres-rca

MUST USE when investigating performance issues on a ClickHouse-managed Postgres instance. Provides an evidence-based RCA workflow that scrapes the Prometheus endpoint for system signal, pulls per-digest evidence from the Slow Query Patterns API, and recommends (does not apply) a fix.

installations
2
GitHub Stars
557
Mis à jour
21 oct.
clickhouse
Officiel

infra-postgres

Sets up and manages Postgres using the clickhousectl CLI — runs a local Docker-backed Postgres for development, and creates and operates managed ClickHouse Cloud Postgres services (connections, TLS, runtime config, read replicas, failover, point-in-time restore). Use when the user wants a Postgres or PostgreSQL database for their application, a local Postgres dev environment, psql access, or a managed/production Postgres in ClickHouse Cloud, or mentions moving a local Postgres to production. Als

installations
2
GitHub Stars
557
Mis à jour
21 oct.
clickhouse
Officiel

clickhouse-js-node-coding

Write idiomatic application code with the ClickHouse Node.js client (@clickhouse/client). Use this skill whenever a user is building against the Node.js client — configuring the client, pinging, inserting rows in JSON or raw formats, selecting and parsing results, binding query parameters, managing sessions and temporary tables, working with data types or customizing JSON parsing. Do NOT use for browser/Web client code.

installations
2
GitHub Stars
557
Mis à jour
21 oct.