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Elastic Search mappings from JSON Schema","homepage":"https://github.com/kristianmandrup/json-schema-to-es-mapping#readme","keywords":["elastic","search","elasticsearch","elastic-search","json","json-schema","schema","convert","build","builder","generator"],"repository":{"type":"git","url":"git+https://github.com/kristianmandrup/json-schema-to-es-mapping.git"},"author":{"name":"Kristian Mandrup","email":"kmandrup@gmail.com"},"bugs":{"url":"https://github.com/kristianmandrup/json-schema-to-es-mapping/issues","email":"kmandrup@gmail.com"},"license":"MIT","readme":"# JSON Schema to ElasticSearch mappings\n\nConvert JSON schema to [ElasticSearch mappings](https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping.html)\n\nA mapping type has:\n\n_Meta-fields_\n\nMeta-fields are used to customize how a document’s metadata associated is treated. Examples of meta-fields include the document’s `_index`, `_type`, `_id`, and `_source` fields.\n\n_Fields or properties_\n\nA mapping `type` contains a list of fields or properties pertinent to the document.\n\n_Field datatypes_\n\nEach field has a data `type` which can be:\n\n- a simple type like `text`, `keyword`, `date`, `long`, `double`, `boolean` or `ip`\n- a type which supports the hierarchical nature of JSON such as `object` or `nested`\n- a specialised type like `geo_point`, `geo_shape`, or `completion`\n\nIt is often useful to index the same field in different ways for different purposes. For instance, a `string` field could be indexed as a `text` field for full-text search, and as a `keyword` field for sorting or aggregations. Alternatively, you could index a string field with the `standard` analyzer, the `english` analyzer, and the `french` analyzer.\n\nThis is the purpose of multi-fields. Most datatypes support multi-fields via the `fields` parameter.\n\n## Quick start\n\n- npm: `npm install json-schema-to-es-mapping -S`\n- yarn: `yarn add json-schema-to-es-mapping`\n\nThe easiest way to get started is to use `buildMappingsFor` to create a mappings object for a named index given a JSON schema.\n\n```js\nconst mappings = buildMappingsFor(\"people\", schema);\n```\n\nExample:\n\n```js\nconst schema = {\n $schema: \"http://json-schema.org/draft-07/schema#\",\n $id: \"http://example.com/person.schema.json\",\n title: \"Person\",\n description: \"A person\",\n type: \"object\",\n properties: {\n name: {\n description: \"Name of the person\",\n type: \"string\"\n },\n age: {\n description: \"Age of person\",\n type: \"number\"\n }\n },\n required: [\"name\"]\n};\n\nconst { buildMappingsFor } = require(\"json-schema-to-es-mapping\");\nconst mappings = buildMappingsFor(\"people\", schema);\nconsole.log({ mappings });\n```\n\nThis will by default give the following mappings result:\n\n```json\n{\n \"mappings\": {\n \"people\": {\n \"properties\": {\n \"name\": {\n \"type\": \"text\"\n },\n \"age\": {\n \"type\": \"integer\"\n }\n }\n }\n }\n}\n```\n\nThe function `buildMappingsFor` uses the `build` function to return the properties map and simply wraps them with a `mappings` object for the named index.\n\n## Supported mappings\n\nCurrently all Elastic Search core data types are supported (except for `binary`).\n\n- string\n- numeric\n- boolean\n- date\n- range (numeric, date)\n\n### Numeric\n\nYou can assist the numeric type mapper by supplying a `numType` for the field entry, such as `numType: \"double\"`\n\nSee ES [number](https://www.elastic.co/guide/en/elasticsearch/reference/current/number.html#number) reference for list of valid `numType`s (except for `scaled_float`)\n\n### Ranges\n\n- Numeric\n- Date\n\n#### Numeric ranges\n\nTo make a numeric field entry be mapped to an ES numeric range:\n\n- Set `range: true`\n- Set a minimum range value, either `minimum` or `exlusiveMinimum`\n- Set a maximum range value, either `maximum` or `exlusiveMaximum`\n\nIf you leave out the `range: true` it will be resolved as a number, using the min and max values and the `multipleOf` (precision). These properties will in combination be used to determine the exact numeric type (`byte`, `short`, ... `double`) to be used in the Elastic Search numeric type mapping.\n\n#### Date ranges\n\nTo make an entry detect as a date range, the same applies as for a number range but the entry must also resolve to a date type (see `types/util.js` function `isDate(obj)` for details)\n\n## Recent feature additions\n\nNow also resolves:\n\n- Array items that are themselves object types\n- References to object definitions (ie. `$ref`)\n- [Parent-child mapping](https://www.elastic.co/guide/en/elasticsearch/guide/current/parent-child-mapping.html)\n\n## Limitations and coming features\n\nSupport for Geo location mapping will likely be included in the near future. \n\nPlease Let me know any other features you'd like to include for a more feature complete library!\n\nInitial work to support these features have been started in the [dev](https://github.com/kristianmandrup/json-schema-to-es-mapping/tree/dev) branch and should land soon (0.4.0).\n\n## Fine grained control\n\nFor more fine-grained control, use the `build` function directly.\n\n```js\nconst { build } = require(\"json-schema-to-es-mapping\");\nconst { properties, results } = build(schema);\nconsole.log({ properties, results });\n```\n\nWill output the following Elastic Search Mapping schema:\n\n```json\n{\n \"name\": {\n \"type\": \"text\"\n },\n \"age\": {\n \"type\": \"float\"\n }\n}\n```\n\nThe `results` will in this (simple) case give the same results as the `mappings`:\n\n```js\n{\n name: { type: \"keyword\" },\n age: { type: \"float\" }\n}\n```\n\n## Event driven approach\n\nYou can use the Event driven approach with the `onResult` and other calback handlers, to generate a more context specific mapping for Elastic Search context, given your requirements.\n\n```js\nconst received = [];\nconst onResult = result => {\n console.log(\"received\", result);\n received.push(result);\n};\n\n// potentially use to call resolve callback of Promise\nconst onComplete = fullResult => {\n console.log(\"ES mapping done :)\", {\n fullResult, // 'internal\" results\n received // list built by onResult\n });\n};\n\n// potentially use to call reject callback of Promise\nconst onError = errMsg => {\n console.error(\"ES mapping error\", errMsg);\n throw errMsg;\n};\n\n// potentially use to call reject callback of Promise\nconst onThrow = err => throw err;\nconst config = { onResult, onComplete, onError, onThrow };\n```\n\nThe `onResult` handler will populate the `received` array with the following:\n\n```js\n[\n { parentName: \"Person\", key: \"name\", resultKey: \"name\", type: \"text\" },\n {\n parentName: \"Person\",\n key: \"age\",\n resultKey: \"age\",\n type: \"float\"\n }\n];\n```\n\nYou will also get notified on:\n\n- successful completion of JSON schema mapping via `onComplete` callback\n- aborted due to processing error via `onError` callback\n- aborted due to throwing exception via `onThrow` callback\n\nThe Event driven approach is entirely optional, but can be used for a more \"stream like\" approach. This approach works well with async promises (ie. `reject` and `resolve` callbacks).\n\nOn each result received you can then issue a command to the Elastic Search server (f.ex via the REST interface) to add a new mapping that reflects the result received.\n\n[Put mapping](https://www.elastic.co/guide/en/elasticsearch/reference/current/indices-put-mapping.html)\n\n```bash\nPUT person/_mapping/_doc\n{\n \"properties\": {\n \"age\": {\n \"type\": \"float\"\n }\n }\n}\n```\n\nAlternatively only submit the ES index mappings after `onComplete` is triggered, to make sure the full JSON schema could be processed, so that you don't end up with partial schema mappings.\n\n## Nested schemas\n\nFor a nested schema of the form:\n\n```js\n{\n $schema: \"http://json-schema.org/draft-07/schema#\",\n $id: \"http://example.com/person.schema.json\",\n title: \"Person\",\n description: \"A person\",\n type: \"object\",\n properties: {\n name: {\n description: \"Name of the person\",\n type: \"string\"\n },\n dog: {\n type: \"object\",\n typeName: \"Animal\",\n properties: {\n name: {\n description: \"Name of the dog\",\n type: \"string\",\n required: true\n },\n age: {\n description: \"Age of dog\",\n type: \"number\"\n }\n }\n }\n },\n required: [\"name\"]\n};\n```\n\n`buildMappingsFor` will in this case generate an Elastic Search mapping as follows:\n\n```js\nmappings: {\n people: {\n properties: {\n name: {\n type: \"keyword\"\n },\n dog: {\n properties: {\n name: {\n type: \"keyword\"\n },\n age: {\n type: \"float\"\n }\n }\n }\n }\n }\n}\n```\n\nNote that the `dog` object results in a nested mapping (see ElasticSearch resources below)\n\nThe `results` will in this case give:\n\n```js\n{\n name: { type: 'keyword' },\n dog_name: { type: 'keyword' },\n dog_age: { type: 'float' },\n dog: {\n name: { type: 'keyword' },\n age: { type: 'float' }\n }\n}\n```\n\nNotice how the dog properties are provided both in flat and nested form. Depending on your requirements, you might want to store the Elastic Search data in a more flat form than in your general application domain model.\n\n### Customizing the result\n\nYou can pass a custom function `shouldSetResult(converter)` which controls under which converter conditions the result should be set. You can also pass:\n\n- a custom name separator `nameSeparator`\n- a `resultKey(converter)` function, to customize how result keys (names) are generated\n- a `nestedKey(converter)` function, to customize how nested result keys (names) are generated\n\nExample:\n\n```js\nconst config = {\n shouldSetResult: converter => {\n return converter.type !== \"object\";\n },\n nameSeparator: \"__\" // example: dog__age\n};\n```\n\nThis configuration will result in results discarding the nested form, thus only retaining flattened field mappings.\n\n```js\n{\n name: { type: 'keyword' },\n dog__name: { type: 'keyword' },\n dog__age: { type: 'float' },\n}\n```\n\nIf you add an `onResult` handler to receive results, it will look as follows:\n\n```js\nresults:\n [\n {\n parentName: 'Person',\n key: 'name',\n resultKey: 'name',\n type: 'keyword'\n },\n {\n parentName: 'dog',\n key: 'name',\n resultKey: 'dog__name',\n type: 'keyword'\n },\n { parentName: 'dog',\n key: 'age',\n resultKey: 'dog__age',\n type: 'float'\n },\n { parentName: 'Person',\n typeName: 'Animal',\n key: 'dog',\n resultKey: 'dog',\n properties: {\n name: { type: 'keyword' },\n age: { type: 'float' }\n }\n }\n ]\n}\n```\n\nNote the `typeName` in the result for the `dog` fields (more on this later)\n\n## Default configuration\n\nThe default configuration is as follows.\n\n```js\n{\n _meta_: {\n types: {\n string: \"keyword\",\n number: \"float\",\n object: \"object\",\n array: \"nested\",\n boolean: \"boolean\",\n date: \"date\"\n }\n },\n fields: {\n name: {\n type: \"keyword\"\n },\n content: {\n type: \"text\"\n },\n text: {\n type: \"text\"\n },\n title: {\n type: \"text\"\n },\n caption: {\n type: \"text\"\n },\n label: {\n type: \"text\"\n },\n tag: {\n type: \"keyword\",\n index: \"not_analyzed\"\n }\n }\n}\n```\n\nNote that some or all of these might benefit from being defined as multi fields, that are indexed and analyzed both as `text` and `keyword`.\n\nYou can pass in a custom configuration object (last argument) to override or extend it ;)\n\nNote that for convenience, we pass in some typical field mappings based on names. Please customize this further to your needs.\n\n## Customization\n\n- Type mappers\n- Rules\n\n### Type mappers\n\nYou can pass in custom Type mapper factories if you want to override how specific types are mapped.\n\nInternally this is managed in the `SchemaEntry` constructor in `entry.js`:\n\n```js\nthis.defaults = {\n types: {\n string: toString,\n number: toNumber,\n boolean: toBoolean,\n array: toArray,\n object: toObject,\n date: toDate,\n dateRange: toDateRange,\n numericRange: toNumericRange\n },\n typeOrder: [\n \"string\",\n \"dateRange\",\n \"numericRange\",\n \"number\",\n \"boolean\",\n \"array\",\n \"object\",\n \"date\"\n ]\n};\n\nthis.types = {\n ...this.defaults.types,\n ...(config.types || {})\n};\nthis.typeOrder = config.typeOrder || this.defaults.typeOrder;\n```\n\nTo override, simply pass in a custom `types` object and/or a custom `typeOrder` array of the precedence order they should be resolved in.\n\n#### Custom Type mapper example (object)\n\nCreate a `toObject` file loally in your project that contains your overrides\n\n```js\nconst { types } = require(\"json-schema-to-es-mapping\");\nconst { MappingObject, toObject, util } = types;\n\nclass MyMappingObject extends MappingObject {\n // ...override\n\n createMappingResult() {\n return this.hasProperties\n ? this.buildObjectValueMapping()\n : this.defaultObjectValueMapping;\n }\n\n buildObjectValueMapping() {\n const { buildProperties } = this.config;\n return buildProperties(this.objectValue, this.mappingConfig);\n }\n}\n\nmodule.exports = function toObject(obj) {\n return util.isObject(obj) && new MyMappingObject(obj).convert();\n};\n```\n\nImport the `toObject` function and pass it in the `types` object of the `config` object passed to the `build` function.\n\n```js\n// custom implementation\nconst toObject = require(\"./toObject\");\n\nconst myConfig = {\n types: {\n toObject\n }\n};\n\n// will now use the custom toObject for mapping JSON schema object to ES object\nbuild(schema, myConfig);\n```\n\nDepending on your requirements, you can post-process the generated mapping to better suit your specific needs and strategies for handling nested/complex data relationships.\n\n## Elastic search types\n\n- [Elasticsearch: mapping types](https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-types.html)\n\nCore:\n\n- String (`text`, `keyword`)\n- Numeric (`long`, `integer`, `short`, `byte`, `double`, `float`, `half_float`, `scaled_float`)\n- Date (`date`)\n- Boolean (`boolean`)\n- Binary (`binary`)\n- Range (`integer_range`, `float_range`, `long_range`, `double_range`, `date_range`)\n\n## Type mappings\n\nThe default type mappings are as follows:\n\n- `boolean` -> `boolean`\n- `object` -> `object`\n- `array` -> `nested`\n- `string` -> `keyword`\n- `number` -> `integer`\n- `date` -> `date`\n\nFor `array` it will use `type` of first [array item](https://cswr.github.io/JsonSchema/spec/arrays/) if [basic type](https://cswr.github.io/JsonSchema/spec/basic_types/) and the type for all array items are the same.\n\n```js\n{\n \"type\": \"array\",\n \"items\":{\n \"type\": \"integer\"\n }\n}\n```\n\nIf array item types are note \"uniform\" it will throw an error.\n\nFor the following array JSON schema entry the mapper will currently set the mapping type to `string` (by default). Please use the customization options outlined to define a more appropriate mapping strategy if needed.\n\n```js\n{\n \"type\": \"array\",\n \"items\" : [{\n \"type\": \"string\"\n // ...\n },\n {\n \"type\": \"string\"\n // ...\n },\n ]\n}\n```\n\nYou can override the default type mappings by passing a `types` entry with type mappings in the `_meta_` entry of `config`\n\n```js\nconst config = {\n _meta_: {\n types: {\n number: \"long\", // use \"integer\" for numbers\n string: \"text\" // use \"text\" for strings\n }\n }\n};\n```\n\n### Rules\n\nYou can pass an extra configuration object with specific rules for ES mapping properties that will be merged into the resulting mapping.\n\n```js\nconst config = {\n _meta_: {\n types: {\n number: \"long\", // use \"integer\" for numbers\n string: \"text\" // use \"text\" for strings\n }\n },\n fields: {\n created: {\n // add extra indexing field meta data for Elastic search\n format: \"strict_date_optional_time||epoch_millis\"\n // ...\n },\n firstName: {\n type: \"keyword\" // make sure firstName will be a keyword field (exact match) in ES mapping\n }\n }\n};\n\nconst { build } = require(\"json-schema-to-es-mapping\");\nconst mapping = build(schema, config);\n```\n\nAlso note that you can pass in many of the functions used internally, so that the internal mechanics themselves can easily be customized as needed or used as building blocks.\n\n### Elastic Search nested objects and data\n\n- [Elasticsearch: Nested datatype](https://www.elastic.co/guide/en/elasticsearch/reference/current/nested.html)\n- [Elasticsearch: Nested Objects](https://www.elastic.co/guide/en/elasticsearch/guide/current/nested-objects.html)\n- [Elasticsearch data schema for nested objects](https://stackoverflow.com/questions/43488166/elasticsearch-data-schema-for-nested-objects)\n- [Elasticsearch : Advanced search and nested objects](http://obtao.com/blog/2014/04/elasticsearch-advanced-search-and-nested-objects/)\n\n## Advanced customization\n\nTo override the default mappings for certain fields, you can pass in a fields mapping entry in the `config` object as follows:\n\n```js\nconst config = {\n fields: {\n timestamp: {\n type: \"date\",\n format: \"dateOptionalTime\"\n }\n // ... more custom field mappings\n }\n};\n```\n\nFor a more scalable customization, pass an `entryFor` function which returns custom mappings\ndepending on the entry being processed.\n\n- `key`\n- `resultKey` (ie. potentially nested key name)\n- `parentName` name of parent entry if nested property\n- `schemaValue` (entry from JSON schema being mapped)\n\nYou could f.ex use this to provide custom mappings for specific types of date fields.\n\n```js\nconst config = {\n entryFor: ({ key }) => {\n if (key === \"date\" || key === \"timestamp\") {\n return {\n type: \"date\",\n format: \"dateOptionalTime\"\n };\n }\n }\n};\n```\n\n### resolve type maps\n\nYou can use [resolve-type-maps](https://github.com/kristianmandrup/resolve-type-maps) to define mappings to be used across your application in various schema-like contexts:\n\n- GraphQL schema\n- Data storage (tables, colletions etc)\n- Validation\n- Forms\n- Data Display\n- Indexing (including Elastic Search)\n- Mocks and fake data\n\n```js\nconst fieldMap = {\n name: {\n matches: ['title', 'caption', 'label'],\n elastic: {\n type: 'string',\n }\n }\n tag: {\n matches: ['tags'],\n elastic: {\n type: 'keyword',\n }\n\n },\n text: {\n matches: ['description', 'content'],\n elastic: {\n type: 'text',\n }\n },\n date: {\n matches: ['date', 'timestamp'],\n elastic: {\n type: 'text',\n format: 'dateOptionalTime'\n }\n }\n}\n\nconst typeMap = {\n Person: {\n matches: ['User'],\n fields: {\n dog: {\n // ...\n elastic: {\n type: 'nested',\n // ...\n }\n },\n // ...\n }\n }\n}\n```\n\nThen pass an `entryFor` function in the config object to resolve the entry to be used for the ES mapping entry.\n\n```js\nimport { createTypeMapResolver } from \"resolve-type-maps\";\n\nconst map = {\n typeMap,\n fieldMap\n};\n\nconst resolverConfig = {};\nconst functions = {\n resolveResult: (obj) => obj.elastic;\n}\n\nconst resolver = createTypeMapResolver(\n { map, functions },\n resolverConfig\n);\n\nconst config = {\n entryFor: ({ parentName, typeName }) => {\n // ensure capitalized and camelized name\n const type = classify(typeName || parentName);\n const name = converter.key;\n return resolver.resolve({ type, name });\n }\n};\n```\n\nNote that for `typeName` to be set, either set a `className` or `typeName` property on the object entry in the JSON schema (see `dog` example above) or alternatively provide a lookup function `typeNameFor(name)` on the config object passed in.\n\nFor inner workings, see [TypeMapResolver.ts](https://github.com/kristianmandrup/resolve-type-maps/blob/master/src/lib/TypeMapResolver.ts)\n\nThe above configuration should look up the elastic mapping entry to use, based on the type/field combination in the `typeMap` first and then fall back to the field name only in the `fieldMap` if not found. On a match, it will resolve by returning entry named `elastic` in the object matching.\n\n```js\n{\n Person: {\n matches: [/User/],\n fields: {\n dog: {\n // ...\n elastic: {\n type: 'nested',\n // ...\n }\n },\n }\n }\n}\n```\n\nIt should match a schema (or nested schema entry) named `Person` or `User` on the `typeMap` entry `Person`. For the nested `dog` entry it should then match on the entry `dog` under `fields` and return the entry for elastic, ie:\n\n```js\n{\n type: \"nested\";\n}\n```\n\nIf no match is made in the `typeMap`, it will follow a similar strategy by lookup a match in the `fieldMap` (as per the `maps` entry passed in the `config` object when creating the `resolver`), matching only on the field name.\n\n## ElasticSearch mapping resources\n\n- [mapping](https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping.html)\n- [removal of types](https://www.elastic.co/guide/en/elasticsearch/reference/current/removal-of-types.html)\n- [nested](https://www.elastic.co/guide/en/elasticsearch/reference/current/nested.html)\n\n## Testing\n\nUses [jest](jestjs.io/) for unit testing.\n\nCurrently not well tested. Please help add more test coverage :)\n\n## TODO\n\n### 1.0.0\n\n- Convert project to TypeScript\n- Add unit tests for ~80% test coverage\n- Improve mappings for:\n - Date range\n\n## Author\n\n2019 Kristian Mandrup (CTO@Tecla5)\n\n## License\n\nMIT\n","readmeFilename":"Readme.md"}