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![@thi.ng/column-store](https://codeberg.org/thi.ng/umbrella/media/branch/develop/assets/banners/thing-column-store.svg?ee7af11f)\n\n[![npm version](https://img.shields.io/npm/v/@thi.ng/column-store.svg)](https://www.npmjs.com/package/@thi.ng/column-store)\n![npm downloads](https://img.shields.io/npm/dm/@thi.ng/column-store.svg)\n[![Mastodon Follow](https://img.shields.io/mastodon/follow/109331703950160316?domain=https%3A%2F%2Fmastodon.thi.ng&style=social)](https://mastodon.thi.ng/@toxi)\n\n> [!NOTE]\n\n> This is one of 217 standalone projects. LLM-free, human-made and\n> cared for software, maintained as part of the\n> [@thi.ng/umbrella](https://codeberg.org/thi.ng/umbrella/) ecosystem and\n> anti-framework.\n>\n> 🚀 Please help me to work full-time on these projects by [sponsoring\n> me](https://codeberg.org/thi.ng/umbrella/src/branch/develop/CONTRIBUTING.md#donations).\n> Thank you! ❤️\n\n- [About](#about)\n- [Column storage](#column-storage)\n  - [Column types](#column-types)\n  - [Vector column types](#vector-column-types)\n  - [Serialization options](#serialization-options)\n  - [Custom column types](#custom-column-types)\n  - [Cardinality](#cardinality)\n    - [Differences between tuple and vector column types](#differences-between-tuple-and-vector-column-types)\n  - [Default values](#default-values)\n  - [Flags](#flags)\n    - [FLAG_BITMAP](#flag_bitmap)\n    - [FLAG_DICT](#flag_dict)\n    - [FLAG_UNIQUE](#flag_unique)\n    - [FLAG_RLE](#flag_rle)\n    - [Custom flags](#custom-flags)\n- [Query engine](#query-engine)\n  - [Query execution](#query-execution)\n    - [Optimized row iteration](#optimized-row-iteration)\n  - [Built-in operators](#built-in-operators)\n    - [OR](#or)\n    - [AND](#and)\n    - [Negation](#negation)\n    - [Predicate-based matchers](#predicate-based-matchers)\n    - [Row ranges](#row-ranges)\n    - [Value ranges](#value-ranges)\n  - [Nested queries](#nested-queries)\n  - [Result order and pagination](#result-order-and-pagination)\n  - [Custom operators](#custom-operators)\n  - [Result aggregation](#result-aggregation)\n  - [Query ranges](#query-ranges)\n- [Status](#status)\n- [Installation](#installation)\n- [Dependencies](#dependencies)\n- [API](#api)\n  - [Basic usage](#basic-usage)\n- [Authors](#authors)\n- [License](#license)\n\n## About\n\nIn-memory column store database with customizable column types, extensible query engine with support for nested queries, bitfield indexing for query acceleration, JSON serialization with optional RLE compression.\n\n## Column storage\n\nAs the name indicates, data is stored in different columns, where each column\nmanages its own schema, value validation, backing storage, indexing,\nserialization etc.\n\nFrom a user's POV, columns are not (usually) used directly, but accessed via a\ntable, which provides row-based access to compound data records and acts as\nfacade to the various configured columns. Data records are added as JS objects\nto a table, which then pulls out related values, validates them and the\ndelegates them to the individual columns for encoding & storage.\n\nAn example table definition looks like this (explanation of column types in next\nsection below):\n\n```ts tangle:export/readme-types.ts\nimport { Table, FLAG_DICT, FLAG_UNIQUE } from \"@thi.ng/column-store\";\n\n// schema for a single row item\ninterface Item {\n    id: number;\n    name: string;\n    aliases?: string[];\n    latlon: number[] | Float32Array;\n    tags: string[];\n}\n\n// define a table with the given columns\nconst table = new Table<Item>({\n\n    // column of single numeric values\n    // (default cardinality makes values required)\n    id: { type: \"num\" },\n\n    // column of required string values\n    name: { type: \"str\" },\n\n    // optional tuples of max. 3 string values\n    // (if no value is given, the column stores null)\n    aliases: { type: \"str\", cardinality: [0, 3] },\n\n    // required fixed size tuples (aka vectors) of numbers\n    latlon: { type: \"f32vec\", cardinality: [2, 2] },\n\n    // optional tuples of max. 10 strings, with default\n    // the given flags (explained further below) are triggering:\n    // - dictionary-based encoding\n    // - unique values (per tuple)\n    tags: {\n        type: \"str\",\n        cardinality: [0, 10],\n        default: [\"todo\"],\n        flags: FLAG_DICT | FLAG_UNIQUE\n    }\n});\n\n// add data\ntable.addRow({\n    id: 1,\n    name: \"karsten\",\n    aliases: [\"toxi\"],\n    latlon: [47.421, 10.984],\n    tags: [\"person\", \"opensource\"],\n});\n```\n\n> [!IMPORTANT]\n> Columns can be named freely, with the exception that the `__` name prefix is\n> reserved for internal use. For example, `foo` is allowed, but `__foo` is a\n> reserved name.\n\n### Column types\n\nThe current built-in column types only support numeric or string values, though\nsupport for other JSON-serializable types is planned. For better memory\nutilization, numeric data can (and should) be stored in typed array columns.\n\nSome column types support storing multiple values per row as tuples. See\n[cardinality section](#cardinality) below for further detail.\n\nNote: Booleans and `BigInt`s are still unsupported, but being worked on...\n\n| **Column type** | **Description**     | **Tuples supported** | **RLE serialization** |\n|-----------------|---------------------|----------------------|-----------------------|\n| `num`           | JS numbers          | ✅                    | ✅ <sup>(1)</sup>      |\n| `str`           | JS strings (UTF-16) | ✅                    | ✅ <sup>(1)</sup>      |\n| `u8`            | 8bit unsigned int   | ❌                    | ✅                     |\n| `i8`            | 8bit signed int     | ❌                    | ✅                     |\n| `u16`           | 16bit unsigned int  | ❌                    | ✅                     |\n| `i16`           | 16bit signed int    | ❌                    | ✅                     |\n| `u32`           | 32bit unsigned int  | ❌                    | ✅                     |\n| `i32`           | 32bit signed int    | ❌                    | ✅                     |\n| `f32`           | 32bit float         | ❌                    | ✅ <sup>(2)</sup>      |\n| `f64`           | 64bit float         | ❌                    | ✅ <sup>(2)</sup>      |\n\n- <sup>(1)</sup> only if max. cardinality is 1, [further information](#flag_rle)\n- <sup>(2)</sup> simple RLE only, [further information](#flag_rle)\n\n### Vector column types\n\nColumns storing fixed size n-dimensional vectors can be created vis the `vec`\nsuffix for any of the typedarray based column types, i.e. `u8vec`, `i16vec`,\n`f32vec` etc.\n\nThe `cardinality` column config (in the form `[min,max]`) is interpreted as follows:\n\n- if `min` is zero, the value is optional, but a `default` value MUST be defined\n  for the column. Otherwise the `min` value MUST be the same as `max`.\n- `max` defines the actual vector size\n\nTherefore, using a 3D vector as example, the only two possible `cardinality`\nconfigs are: `[0,3]` (with default given) or `[3,3]`.\n\nWhen [querying](#query-engine) vector columns using the standard\n`(n)or`/`(n)and` operators, always the entire vector is matched (by value).\n\n> [!IMPORTANT]\n> For performance reasons, rows retrieved from vector columns contain mutable\n> data views of the underlying column storage. That means when manipulating data\n> in these views, the underlying data in the column would be changed too. To\n> avoid index corruption, always edit only copies of this vector data and then\n> use `table.updateRow()` to properly update the column storage (incl. any\n> internal indexes).\n\n### Serialization options\n\nFor `f32`, `f64`, `f32vec` and `f64vec` column types, the optional `prec` column\noption can be provided to specify the number of fractional digits used in\nthe JSON serialization:\n\n```ts tangle:export/readme-serialize-prec.ts\nimport { Table } from \"@thi.ng/column-store\";\n\nconst table = new Table({\n    vec: { type: \"f32vec\", cardinality: [3, 3], opts: { prec: 2 } }\n});\n\ntable.addRow({ vec: [1.11111, 22.22222, 333.33333]});\n\nconsole.log(JSON.stringify(table));\n// {\n//   \"schema\":{\"vec\":{\"cardinality\":[3,3],\"flags\":0,\"type\":\"f32vec\",\"opts\":{\"prec\":2}}},\n//   \"columns\":{\"vec\":{\"values\":[1.11,22.22,333.33]}},\n//   \"length\":1\n// }\n\n```\n\n### Custom column types\n\nThe system already supports custom column type implementations via the\n[`IColumn`](https://docs.thi.ng/umbrella/column-store/interfaces/IColumn.html)\nand\n[`ColumnTypeSpec`](https://docs.thi.ng/umbrella/column-store/interfaces/ColumnTypeSpec.html)\ninterfaces.\n\nCustom column types and their implementations can be registered via\n[`registerColumnType()`](https://docs.thi.ng/umbrella/column-store/functions/registerColumnType.html).\n\n### Cardinality\n\nColumns can store zero, one or tuples of multiple values per row. Acceptable\nmin/max ranges can be defined via the\n[`cardinality`](https://docs.thi.ng/umbrella/column-store/interfaces/ColumnSpec.html#cardinality)\nkey of the column spec. The following presets are provided:\n\n| **Preset**  | **Value**        | **Description**                             |\n|-------------|------------------|---------------------------------------------|\n| `REQUIRED`  | `[1, 1]`         | Required single value (default)             |\n| `OPTIONAL`  | `[0, 1]`         | Optional single value (present or not)      |\n| `ONE_PLUS`  | `[1, (2**32)-1]` | One or more values (always expects tuples)  |\n| `ZERO_PLUS` | `[0, (2**32)-1]` | Zero or more values (always expects tuples) |\n\n#### Differences between tuple and vector column types\n\n| **Feature**                      | **Tuples**            | **Vectors** |\n|----------------------------------|-----------------------|-------------|\n| Optional (without default value) | ✅                     | ❌           |\n| Flexible size                    | ✅                     | ❌           |\n| Query ops match...               | Individual components | Full vector |\n\n### Default values\n\nDefault values can be specified for columns with a minimum cardinality of 1 or\nmore (aka required values). When a row is added or updated, any `null`ish values\nfor such columns in the row record will then be replaced with their default\nvalues. If a column with required values has no configured default value, an\nerror will be thrown when attempting to add/update an incomplete record.\n\n```ts\n// example column spec with default value\n{\n    type: \"str\",\n    cardinality: [1, 1],\n    default: \"todo\",\n}\n```\n\n**Note:** Typed array backed columns **do no** support optional values and\ntherefore require either a cardinality of `[1,1]` or `[0,1]` with a default.\n\n### Flags\n\nGenerally applicable to all column types, the following numeric flags can be\nassigned and combined (into bitmasks) to customize the storage & indexing\nbehavior.\n\n#### FLAG_BITMAP\n\n(Value: 0x01)\n\nThe column will construct & maintain additional bitfields for each unique value\nstored in the column. These bitfields record which values are stored in which\nrows and are utilized by the [query engine](#query-engine) to massively\naccelerate complex searches.\n\n#### FLAG_DICT\n\n(Value: 0x02)\n\nDictionary encoded storage. Recommended for (non-numeric) data with a relatively\nsmall (though not necessarily fixed) set of possible values. Instead of storing\nvalues directly, only numeric IDs will be stored. The original (de-duplicated)\nvalues are stored in a dictionary alongside the column data.\n\nNote: Not supported by typedarray-backed column types.\n\n#### FLAG_UNIQUE\n\n(Value: 0x04)\n\nOnly applicable for tuple-based columns to enforce Set-like semantics (per row),\ni.e. values of each tuple will be deduplicated (e.g. for tagging).\n\nNote: Not supported by typedarray-backed column types.\n\n#### FLAG_RLE\n\n(Value: 0x08)\n\nThis flag enables [Run-length encoding](https://thi.ng/rle-pack) in the\nJSON serialization of a column, potentially leading to dramatic file size\nsavings, esp. for dictionary-based data.\n\nTwo modes of RLE compression are supported, depending on column type:\n\n- Simple RLE merely stores arrays in `[value1, count1, value2, count2...]` form\n- Binary RLE uses more advanced bitwise encoding, but is only available for\n  typedarray and vector columns\n\nTuple-based columns do not support RLE and will throw an error at creation time\nwhen trying to use this flag.\n\n#### Custom flags\n\nThe lower 16bit of the 32bit `flags` integer are reserved for built-ins and\nfuture extension of this package. However, the upper 16 bits can be freely used\nfor custom flags, i.e. in conjunction with [custom column\ntypes](#custom-column-types).\n\n## Query engine\n\nThe query engine is highly extensible and can be used for executing arbitrarily\ncomplex queries via chaining of [query operators](#built-in-operators) and\n[nested sub-queries](#nested-queries).\n\n### Query execution\n\nThe system allows predefining queries, which are then only evaluated and produce\nup-to-date results via the standard JS iterable mechanism (i.e. queries\nimplement `[Symbol.iterator]`).\n\n```ts\n// predefine query\nconst query = table.query().or(\"name\", [\"alice\", \"bob\"]);\n\n// actually (re)execute query\nfor(let result of query) { ... }\n\n// ..or collect result into an array using slice operator\nconst results = [...query];\n```\n\nAlternatively, queries can also be eagerly executed via\n[`.exec()`](https://docs.thi.ng/umbrella/column-store/classes/Query.html#exec).\nThis will also include metadata alongside the results, useful for paging\nresults.\n\n```ts\n// predefine query\nconst query = table.query().or(\"name\", [\"alice\", \"bob\"]).limit(10);\n\nconst results = query.exec();\n// {\n//   results: [{...}, ...],\n//   total: 123,\n//   offset: 0,\n//   limit: 10\n// }\n```\n\n#### Optimized row iteration\n\nThe query engine works by applying a number of [query\nterms](https://docs.thi.ng/umbrella/column-store/interfaces/QueryTerm.html) in\nseries.\n\n##### Term intersection\n\nBy default, each query term is intersecting (aka logical AND) its own results\nwith the results of the previous step(s), thereby narrowing down the result set.\nAlternatively, each term's result set can also be combined via set-union (aka\nlogical OR), [discussed further below](#term-union).\n\nWhen using the default intersection behavior (AND), for each query term, only\nthe rows already marked (aka pre-selected by predecessor query terms) are\nvisited. When a query term does not manage to select any rows, the query is\nterminated. Internally, this selecting and intersecting of partial query results\nis done via bitfields only. There's no creation of interim result arrays, nor\nany full decoding/construction of interim row records. The latter only happens\nfor the final result rows and/or when using the [`matchRow()` or\n`matchPartialRow()`](#predicate-based-matchers) query operators.\n\nWhen a column has an associated bitfield index (enabled via\n[`FLAG_BITMAP`](#flag_bitmap)), some query operators (see below) are optimized\neven further, entirely avoiding the need to visit any individual rows.\n\nThe diagram below illustrates the application of the following 3-operator query\nand the resulting stepwise narrowing of the result set:\n\n```ts\ntable.query()\n    .matchColumn(\"id\", inRange(100, 110))\n    .matchColumn(\"age\", inRange(20, 50))\n    .matchColumn(\"name\", startsWith(\"a\"))\n```\n\n![Diagram showing a list of rows with object values and three columns\nillustrating the narrowing effect of query operators with their partial\nresults](https://codeberg.org/thi.ng/umbrella/media/branch/develop/assets/column-store/query-narrowing.png)\n\n##### Term union\n\nWith the default intersection behavior alone, certain complex query types are\nnot possible, e.g. queries selecting alternative matches on multiple columns\n(e.g. `WHERE A = 100 OR B = 10`). For these cases to succeed, individual term\nresult sets need to be merged via set-union (aka logical OR).\n\nThis alternative merge behavior can be triggered (per term) by supplying an\noptional argument to any of the [built-in query operators](#built-in-operators)\nlisted below, for example:\n\n```ts\n// 2-step query representing the condition `WHERE A = 100 OR B = 10`\n// with the B-terms results merged via OR (set-union)\nquery.where(\"a\", 100).where(\"b\", 10, \"or\");\n```\n\nReminder: Query terms are executed in given order and the default behavior of\neach term is to merge its results via intersection with the existing results,\nthus mixed AND/OR merges are possible.\n\n### Built-in operators\n\nBy default, individual query terms operate on a single column, but can also can\nalso apply to multiple. Terms are supplied either as array given to the\n[`Query`](https://docs.thi.ng/umbrella/column-store/classes/Query.html)\nconstructor, via the fluent API of the `Query` class and/or via\n[`.addTerm()`](https://docs.thi.ng/umbrella/column-store/classes/Query.html#addterm).\n\n#### OR\n\nOptionally optimized via [`FLAG_BITMAP`](#flag_bitmap) presence on column. One\nor more values can be provided.\n\n```ts\nquery.or(\"column-name\", \"option\");\n\nquery.or(\"column-name\", [\"option1\", \"option2\",...]);\n```\n\n#### AND\n\nOptionally optimized via [`FLAG_BITMAP`](#flag_bitmap) presence on column. One\nor more values can be provided.\n\n```ts\nquery.and(\"column-name\", \"option\");\n\nquery.and(\"column-name\", [\"option1\", \"option2\",...]);\n```\n\n#### Negation\n\nOptionally optimized via [`FLAG_BITMAP`](#flag_bitmap) presence on column.\nNegation is available via `nand` & `nor`. For negation of single values either\ncan be used, otherwise the behavior is:\n\n- [`nand`](https://docs.thi.ng/umbrella/column-store/classes/Query.html#nand):\n  select rows same as [`and`](#and), then negate results\n- [`nor`](https://docs.thi.ng/umbrella/column-store/classes/Query.html#nor):\n  select rows same as [`or`](#or), then negate results\n\n#### Predicate-based matchers\n\n> [!NOTE]\n> For best performance and to minimize/avoid potential decoding and construction\n> of interim row objects, prefer `matchColumn` or `matchPartialRow` over\n> `matchRow` if at all possible. Oftentimes, query predicates requiring multiple\n> column values can be easily refactored into separate query terms.\n\n- [`matchColumn`](https://docs.thi.ng/umbrella/column-store/classes/Query.html#matchcolumn):\n  apply predicate to column value\n- [`matchPartialRow`](https://docs.thi.ng/umbrella/column-store/classes/Query.html#matchpartialrow):\n  apply predicate to partial row (only selected columns)\n- [`matchRow`](https://docs.thi.ng/umbrella/column-store/classes/Query.html#matchrow):\n  apply predicate to full row\n\n#### Row ranges\n\nThe\n[`rowRange`](https://docs.thi.ng/umbrella/column-store/classes/Query.html#rowrange)\noperator selects the given `start` (inclusive) .. `end` (exclusive) range of row\nindices.\n\n```ts\n// select first ten rows\nquery.rowRange(0, 10);\n```\n\n#### Value ranges\n\nThe\n[`valueRange`](https://docs.thi.ng/umbrella/column-store/classes/Query.html#valuerange)\noperator selects rows based on a given column's `start` .. `end` vaulue range\n(both inclusive) of row indices.\n\n```ts\n// select rows where ID is in closed [100,109] interval\nquery.valueRange(\"id\", 100, 109);\n```\n\n### Nested queries\n\nAll of the above query operators accept sub-queries. Alternatively,\n[`.nest()`](https://docs.thi.ng/umbrella/column-store/classes/Query.html#nest)\ncan be used to add a sub-query term.\n\nNote that **only the query terms of sub-queries are used for nesting**. Any\nlimits, offsets or sort criteria configured for sub-queries are ignored!\nFurthermore, a sub-query MUST refer to the same table as the main query,\notherwise an error will be thrown.\n\n```ts\n// find flights for alice which weren't from given airports and longer than 1000km\ntable.query()\n    .where(\"name\", \"alice\")\n    .nor(\n        // sub-query\n        table.query()\n            .or(\"departure\", [\"LHR\", \"LGW\", \"LTN\"])\n            .matchColumn(\"distance\", (x) => x > 1000)\n    )\n```\n\n### Result order and pagination\n\n- [`sortBy()`](https://docs.thi.ng/umbrella/column-store/classes/Query.html#sortby)\n  allows query results to be ordered (ascending or descending) via an arbitrary\n  number of sort columns or criteria, applied in the given order.\n- [`limit()`](https://docs.thi.ng/umbrella/column-store/classes/Query.html#limit)\n  provides basic pagination of query results by specifying a max. number of\n  results and start offset\n\n### Custom operators\n\nCustom query operators can be registered via\n[`registerQueryOp()`](https://docs.thi.ng/umbrella/column-store/functions/registerQueryOp.html).\n\n### Result aggregation\n\nTODO\n\n### Query ranges\n\nTODO\n\n## Status\n\n**BETA** - possibly breaking changes forthcoming\n\n[Search or submit any issues for this package](https://codeberg.org/thi.ng/umbrella/issues?q=%5Bcolumn-store%5D)\n\n## Installation\n\n```bash\nyarn add @thi.ng/column-store\n```\n\nESM import:\n\n```ts\nimport * as cs from \"@thi.ng/column-store\";\n```\n\nBrowser ESM import:\n\n```html\n<script type=\"module\" src=\"https://esm.run/@thi.ng/column-store\"></script>\n```\n\n[JSDelivr documentation](https://www.jsdelivr.com/)\n\nFor Node.js REPL:\n\n```js\nconst cs = await import(\"@thi.ng/column-store\");\n```\n\nPackage sizes (brotli'd, pre-treeshake): ESM: 6.70 KB\n\n## Dependencies\n\n- [@thi.ng/api](https://codeberg.org/thi.ng/umbrella/src/branch/develop/packages/api)\n- [@thi.ng/bidir-index](https://codeberg.org/thi.ng/umbrella/src/branch/develop/packages/bidir-index)\n- [@thi.ng/checks](https://codeberg.org/thi.ng/umbrella/src/branch/develop/packages/checks)\n- [@thi.ng/compare](https://codeberg.org/thi.ng/umbrella/src/branch/develop/packages/compare)\n- [@thi.ng/errors](https://codeberg.org/thi.ng/umbrella/src/branch/develop/packages/errors)\n- [@thi.ng/rle-pack](https://codeberg.org/thi.ng/umbrella/src/branch/develop/packages/rle-pack)\n\nNote: @thi.ng/api is in _most_ cases a type-only import (not used at runtime)\n\n## API\n\n[Generated API docs](https://docs.thi.ng/umbrella/column-store/)\n\n### Basic usage\n\n```ts tangle:export/readme-1.ts\nimport {\n    Table,\n    FLAG_BITMAP,\n    FLAG_DICT,\n    FLAG_UNIQUE,\n} from \"@thi.ng/column-store\";\n\ninterface Item {\n    id: number;\n    type: string;\n    tags: string[];\n}\n\nconst table = new Table<Item>({\n    // ID column stores 8bit ints (typed array)\n    id: { type: \"u8\" },\n    // Type column stores indexed strings\n    type: { type: \"str\", flags: FLAG_DICT },\n    // Tags column stores array of strings (max. 10) with set-semantics\n    // and bitmap optimized for query acceleration\n    tags: {\n        type: \"str\",\n        // min/max number of values per row (default is: [1,1])\n        cardinality: [0, 10],\n        // flag to define column behavior (flags explained above)\n        flags: FLAG_DICT | FLAG_UNIQUE | FLAG_BITMAP,\n        // default value(s) assigned if missing when row is added\n        default: [\"unsorted\"],\n    },\n});\n\n// add data/rows\ntable.addRows([\n    { id: 100, type: \"img\", tags: [\"a\", \"a\", \"c\", \"b\"] },\n    { id: 101, type: \"video\", tags: [\"a\", \"d\", \"b\"] },\n    { id: 102, type: \"img\" },\n    { id: 103, type: \"video\" },\n    { id: 104, type: \"img\", tags: [\"b\", \"c\", \"d\"] },\n]);\n\n// pre-define a query, here to select images which have an `unsorted` tag...\n// the fluent API shown is merely syntax sugar for creating/appending query terms.\n// queries can have an arbitrary number of terms (which are executed in series)\nconst unsortedImages = table.query().where(\"type\", \"img\").and(\"tags\", \"unsorted\");\n\n// queries are iterables and only execute when the iterator is consumed\n// each query result includes a `__row` ID\nconsole.log([...unsortedImages]);\n// [ { id: 102, type: \"img\", tags: [ \"unsorted\" ], __row: 2 } ]\n\n// select items with `a` OR `b` tags, intersect with those which have `c` AND `d` tags\nconst complexTagQuery = table.query().or(\"tags\", [\"a\", \"b\"]).and(\"tags\", [\"c\", \"d\"]);\nconsole.log([...complexTagQuery]);\n// [ { id: 104, type: \"img\", tags: [ \"b\", \"c\", \"d\" ], __row: 4 } ]\n\n// query using custom predicates\nconsole.log([...table.query().matchColumn(\"id\", (id) => id > 102)]);\n// [\n//    { id: 103, type: \"img\", tags: [ \"unsorted\" ], __row: 3 },\n//    { id: 104, type: \"img\", tags: [ \"b\", \"c\", \"d\" ], __row: 4 }\n// ]\n\n// serialize table to JSON\nconsole.log(JSON.stringify(table, null, \"\\t\"));\n```\n\nSerialized table (can be loaded again via `Table.load()`):\n\n```json\n{\n    \"schema\": {\n        \"id\": { \"cardinality\": [1, 1], \"flags\": 0, \"type\": \"u8\" },\n        \"type\": { \"cardinality\": [1, 1], \"flags\": 1, \"type\": \"str\" },\n        \"tags\": { \"cardinality\": [0, 10], \"flags\": 7, \"type\": \"str\", \"default\": [\"unsorted\"] }\n    },\n    \"columns\": {\n        \"id\": {\n            \"values\": [100, 101, 102, 103, 104]\n        },\n        \"type\": {\n            \"dict\": {\n                \"index\": [\"img\", \"video\"],\n                \"next\": 2\n            },\n            \"values\": [0, 1, 0, 1, 0]\n        },\n        \"tags\": {\n            \"dict\": {\n                \"index\": [\"a\", \"c\", \"b\", \"d\", \"unsorted\"],\n                \"next\": 5\n            },\n            \"values\": [[0, 1, 2], [0, 3, 2], [4], [4], [2, 1, 3]]\n        }\n    },\n    \"length\": 5\n}\n```\n\n## Authors\n\n- [Karsten Schmidt](https://thi.ng)\n\nIf this project contributes to an academic publication, please cite it as:\n\n```bibtex\n@misc{thing-column-store,\n  title = \"@thi.ng/column-store\",\n  author = \"Karsten Schmidt\",\n  note = \"https://thi.ng/column-store\",\n  year = 2025\n}\n```\n\n## License\n\n&copy; 2025 - 2026 Karsten Schmidt // Apache License 2.0\n","readmeFilename":"README.md"}