433 lines
10 KiB
Plaintext
433 lines
10 KiB
Plaintext
[[modules-scripting-using]]
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== How to use scripts
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Wherever scripting is supported in the Elasticsearch API, the syntax follows
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the same pattern:
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[source,js]
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-------------------------------------
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"script": {
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"lang": "...", <1>
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"source" | "id": "...", <2>
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"params": { ... } <3>
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}
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-------------------------------------
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// NOTCONSOLE
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<1> The language the script is written in, which defaults to `painless`.
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<2> The script itself which may be specified as `source` for an inline script or `id` for a stored script.
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<3> Any named parameters that should be passed into the script.
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For example, the following script is used in a search request to return a
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<<request-body-search-script-fields, scripted field>>:
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[source,console]
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-------------------------------------
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PUT my-index-000001/_doc/1
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{
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"my_field": 5
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}
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GET my-index-000001/_search
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{
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"script_fields": {
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"my_doubled_field": {
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"script": {
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"lang": "expression",
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"source": "doc['my_field'] * multiplier",
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"params": {
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"multiplier": 2
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}
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}
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}
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}
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}
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-------------------------------------
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[discrete]
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=== Script parameters
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`lang`::
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Specifies the language the script is written in. Defaults to `painless`.
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`source`, `id`::
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Specifies the source of the script. An `inline` script is specified
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`source` as in the example above. A `stored` script is specified `id`
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and is retrieved from the cluster state (see <<modules-scripting-stored-scripts,Stored Scripts>>).
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`params`::
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Specifies any named parameters that are passed into the script as
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variables.
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[IMPORTANT]
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[[prefer-params]]
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.Prefer parameters
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========================================
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The first time Elasticsearch sees a new script, it compiles it and stores the
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compiled version in a cache. Compilation can be a heavy process.
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If you need to pass variables into the script, you should pass them in as
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named `params` instead of hard-coding values into the script itself. For
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example, if you want to be able to multiply a field value by different
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multipliers, don't hard-code the multiplier into the script:
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[source,js]
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----------------------
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"source": "doc['my_field'] * 2"
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----------------------
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// NOTCONSOLE
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Instead, pass it in as a named parameter:
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[source,js]
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----------------------
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"source": "doc['my_field'] * multiplier",
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"params": {
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"multiplier": 2
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}
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----------------------
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// NOTCONSOLE
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The first version has to be recompiled every time the multiplier changes. The
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second version is only compiled once.
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If you compile too many unique scripts within a small amount of time,
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Elasticsearch will reject the new dynamic scripts with a
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`circuit_breaking_exception` error. By default, up to 75 scripts per
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5 minutes will be compiled for most contexts and 375 scripts per 5 minutes
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for `ingest` contexts. You can change these settings dynamically by setting
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`script.context.$CONTEXT.max_compilations_rate` e.g.,
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`script.context.field.max_compilations_rate=100/10m`.
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========================================
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[discrete]
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[[modules-scripting-short-script-form]]
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=== Short script form
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A short script form can be used for brevity. In the short form, `script` is represented
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by a string instead of an object. This string contains the source of the script.
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Short form:
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[source,js]
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----------------------
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"script": "ctx._source.likes++"
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----------------------
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// NOTCONSOLE
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The same script in the normal form:
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[source,js]
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----------------------
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"script": {
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"source": "ctx._source.likes++"
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}
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----------------------
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// NOTCONSOLE
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[discrete]
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[[modules-scripting-stored-scripts]]
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=== Stored scripts
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Scripts may be stored in and retrieved from the cluster state using the
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`_scripts` end-point.
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If the {es} {security-features} are enabled, you must have the following
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privileges to create, retrieve, and delete stored scripts:
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* cluster: `all` or `manage`
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For more information, see <<security-privileges>>.
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[discrete]
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==== Request examples
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The following are examples of using a stored script that lives at
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`/_scripts/{id}`.
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First, create the script called `calculate-score` in the cluster state:
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[source,console]
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-----------------------------------
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POST _scripts/calculate-score
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{
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"script": {
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"lang": "painless",
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"source": "Math.log(_score * 2) + params.my_modifier"
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}
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}
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-----------------------------------
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// TEST[setup:twitter]
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You may also specify a context as part of the url path to compile a
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stored script against that specific context in the form of
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`/_scripts/{id}/{context}`:
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[source,console]
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-----------------------------------
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POST _scripts/calculate-score/score
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{
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"script": {
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"lang": "painless",
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"source": "Math.log(_score * 2) + params.my_modifier"
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}
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}
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-----------------------------------
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// TEST[setup:twitter]
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This same script can be retrieved with:
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[source,console]
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-----------------------------------
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GET _scripts/calculate-score
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-----------------------------------
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// TEST[continued]
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Stored scripts can be used by specifying the `id` parameters as follows:
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[source,console]
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--------------------------------------------------
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GET twitter/_search
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{
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"query": {
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"script_score": {
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"query": {
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"match": {
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"message": "some message"
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}
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},
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"script": {
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"id": "calculate-score",
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"params": {
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"my_modifier": 2
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}
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}
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}
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}
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}
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--------------------------------------------------
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// TEST[continued]
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And deleted with:
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[source,console]
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-----------------------------------
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DELETE _scripts/calculate-score
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-----------------------------------
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// TEST[continued]
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[discrete]
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[[modules-scripting-search-templates]]
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=== Search templates
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You can also use the `_scripts` API to store **search templates**. Search
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templates save specific <<search-search,search requests>> with placeholder
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values, called template parameters.
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You can use stored search templates to run searches without writing out the
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entire query. Just provide the stored template's ID and the template parameters.
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This is useful when you want to run a commonly used query quickly and without
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mistakes.
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Search templates use the http://mustache.github.io/mustache.5.html[mustache
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templating language]. See <<search-template>> for more information and examples.
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[discrete]
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[[modules-scripting-using-caching]]
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=== Script caching
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All scripts are cached by default so that they only need to be recompiled
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when updates occur. By default, scripts do not have a time-based expiration, but
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you can configure the size of this cache using the
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`script.context.$CONTEXT.cache_expire` setting.
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By default, the cache size is `100` for all contexts except the `ingest` and the
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`processor_conditional` context, where it is `200`.
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|====
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| Context | Default Cache Size
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| `ingest` | 200
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| `processor_conditional` | 200
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| default | 100
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|====
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NOTE: The size of scripts is limited to 65,535 bytes. This can be
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changed by setting `script.max_size_in_bytes` setting to increase that soft
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limit, but if scripts are really large then a
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<<modules-scripting-engine,native script engine>> should be considered.
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[[scripts-and-search-speed]]
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=== Scripts and search speed
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Scripts can't make use of {es}'s index structures or related optimizations. This
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can sometimes result in slower search speeds.
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If you often use scripts to transform indexed data, you can speed up search by
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making these changes during ingest instead. However, that often means slower
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index speeds.
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.*Example*
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[%collapsible]
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=====
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An index, `my_test_scores`, contains two `long` fields:
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* `math_score`
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* `verbal_score`
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When running searches, users often use a script to sort results by the sum of
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these two field's values.
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[source,console]
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----
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GET /my_test_scores/_search
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{
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"query": {
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"term": {
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"grad_year": "2099"
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}
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},
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"sort": [
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{
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"_script": {
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"type": "number",
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"script": {
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"source": "doc['math_score'].value + doc['verbal_score'].value"
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},
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"order": "desc"
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}
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}
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]
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}
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----
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// TEST[s/^/PUT my_test_scores\n/]
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To speed up search, you can perform this calculation during ingest and index the
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sum to a field instead.
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First, <<indices-put-mapping,add a new field>>, `total_score`, to the index. The
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`total_score` field will contain sum of the `math_score` and `verbal_score`
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field values.
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[source,console]
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----
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PUT /my_test_scores/_mapping
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{
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"properties": {
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"total_score": {
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"type": "long"
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}
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}
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}
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----
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// TEST[continued]
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Next, use an <<ingest,ingest pipeline>> containing the
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<<script-processor,`script`>> processor to calculate the sum of `math_score` and
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`verbal_score` and index it in the `total_score` field.
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[source,console]
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----
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PUT _ingest/pipeline/my_test_scores_pipeline
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{
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"description": "Calculates the total test score",
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"processors": [
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{
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"script": {
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"source": "ctx.total_score = (ctx.math_score + ctx.verbal_score)"
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}
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}
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]
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}
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----
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// TEST[continued]
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To update existing data, use this pipeline to <<docs-reindex,reindex>> any
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documents from `my_test_scores` to a new index, `my_test_scores_2`.
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[source,console]
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----
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POST /_reindex
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{
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"source": {
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"index": "my_test_scores"
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},
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"dest": {
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"index": "my_test_scores_2",
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"pipeline": "my_test_scores_pipeline"
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}
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}
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----
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// TEST[continued]
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Continue using the pipeline to index any new documents to `my_test_scores_2`.
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[source,console]
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----
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POST /my_test_scores_2/_doc/?pipeline=my_test_scores_pipeline
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{
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"student": "kimchy",
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"grad_year": "2099",
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"math_score": 800,
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"verbal_score": 800
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}
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----
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// TEST[continued]
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These changes may slow indexing but allow for faster searches. Users can now
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sort searches made on `my_test_scores_2` using the `total_score` field instead
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of using a script.
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[source,console]
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----
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GET /my_test_scores_2/_search
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{
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"query": {
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"term": {
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"grad_year": "2099"
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}
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},
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"sort": [
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{
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"total_score": {
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"order": "desc"
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}
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}
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]
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}
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----
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// TEST[continued]
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////
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[source,console]
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----
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DELETE /_ingest/pipeline/my_test_scores_pipeline
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----
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// TEST[continued]
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[source,console-result]
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----
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{
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"acknowledged": true
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}
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----
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////
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=====
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We recommend testing and benchmarking any indexing changes before deploying them
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in production.
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[discrete]
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[[modules-scripting-errors]]
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=== Script errors
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Elasticsearch returns error details when there is a compliation or runtime
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exception. The contents of this response are useful for tracking down the
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problem.
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experimental[]
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The contents of `position` are experimental and subject to change.
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