clickhouse-js-node-rowbinary
About clickhouse-js-node-rowbinary
A skill for Node.js developers generating ClickHouse RowBinary codecs in JavaScript or TypeScript, for decoding bytes into values or encoding values into bytes. It covers format selection, reader and writer design principles, and type handling, including when JSON or Native may be more suitable.
Key features
- 01Generate RowBinary readers and writers
- 02Compare JSON and Native use cases
- 03Little-endian read and write guidance
- 04Type-specialized code generation principles
- 05Streaming and per-type references
Use cases
- 01Decode ClickHouse RowBinary responses
- 02Encode data for ClickHouse
- 03Build codecs for fixed-width numeric columns
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ clickhouse/ agent-skills --skill clickhouse-js-node-rowbinaryAfter installing, type/clickhouse-js-node-rowbinaryin Claude Code to confirm it loaded.
Bundled files
References and scripts installed along with SKILL.md.
.gitignoreAGENTS.mdCHANGELOG.mdeval_result_composer.mdeval_result_haiku.mdeval_result_sonnet.mdeval_result.mdEXAMPLES.mdpackage-lock.jsonpackage.jsonreader.mdREADME.mdcase-studies/iot-rowbinary-vs-json.mdledger-rowbinary-vs-json.mdlogs-json-wins.mdwasm-vs-js.mdsrc/examples/carts.tsevents.tsiot.tsledger.tslogs.tsobservability.tsorders.tsprofiles.tstelemetry.tssrc/readers/aggregateFunction.tsbool.tscolumnar.tscompile.tscomposite.tsDetails
From the project READMEClickHouse 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. Streaming vs whole-buffer, row-objects vs columnar, fixed vs runtime schema, and the per-type reader reference. - Encoding JS values into a
RowBinarypayload to send to ClickHouse → writer.md. TheSink/writeXbuilding blocks,writeRowsstreaming, 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
DataViewread.
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
DataViewaccessors passing a literaltruefor thelittleEndianflag. -
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/writeXfunctions 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/yieldboundary 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.