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Copy file name to clipboardExpand all lines: deploy-manage/deploy/cloud-on-k8s/configure-eck.md
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This page explains the various methods for configuring and applying ECK settings.
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For a detailed list and description of all available settings in ECK, refer to asciidocalypse://reference/cloud/cloud-on-k8s/eck-configuration-flags.md.
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For a detailed list and description of all available settings in ECK, refer to [ECK configuration flags](asciidocalypse://docs/cloud-on-k8s/docs/reference/cloud/cloud-on-k8s/eck-configuration-flags.md).
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By default, the ECK installation includes a [ConfigMap](https://kubernetes.io/docs/concepts/configuration/configmap/) with an `eck.yaml` key where you can add, remove, or update configuration settings. This ConfigMap is mounted into the operator’s container as a file, and provided to the application through the `--config` flag.
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You can update the ConfigMap directly using the command `kubectl edit configmap elastic-operator -n elastic-operator` or modify the installation manifests and reapply them with `kubectl apply -f <your-manifest-file.yaml>`.
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The following shows the default `elastic-operator` ConfigMap, for reference purposes. Refer to asciidocalypse://reference/cloud/cloud-on-k8s/eck-configuration-flags.md for a complete list of available settings.
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The following shows the default `elastic-operator` ConfigMap, for reference purposes. Refer to [ECK configuration flags](asciidocalypse://docs/cloud-on-k8s/docs/reference/cloud/cloud-on-k8s/eck-configuration-flags.md) for a complete list of available settings.
Copy file name to clipboardExpand all lines: manage-data/data-store/manage-data-from-the-command-line.md
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# Manage data from the command line
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% What needs to be done: Lift-and-shift
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Learn how to index, update, retrieve, search, and delete documents in an {{es}} cluster from the command line.
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If you are looking for a user interface for {{es}} and your data, head on over to [Kibana](/get-started/the-stack.md)! Not only are there amazing visualization and index management tools, Kibana includes realistic sample data sets to play with so that you can get to know what you *could* do with your data.
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::::
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## Before you begin [before-you-begin]
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On the **Overview** page for your new cluster in the Cloud UI, copy the {{es}} endpoint URL under **Endpoints**.
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These examples use the `elastic` user. If you didn’t copy down the password for the `elastic` user, you can [reset the password](/deploy-manage/users-roles/cluster-or-deployment-auth/built-in-users.md).
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To use these examples, you also need to have the [curl](http://curl.haxx.se/) command installed.
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## Indexing [indexing]
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To index a document into {{es}}, `POST` your document:
To show that the operation worked, {{es}} returns a JSON response that looks like `{"_index":"my_index","_type":"_doc","_id":"0KNPhW4BnhCSymaq_3SI","_version":1,"result":"created","_shards":{"total":2,"successful":2,"failed":0},"_seq_no":0,"_primary_term":1}`.
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In this example, the index `my_index` is created dynamically when the first document is inserted into it. All documents in {{es}} have a `type` and an `id`, which is echoed as `"_type":"_doc"` and `_id":"0KNPhW4BnhCSymaq_3SI` in the JSON response. If no ID is specified during indexing, a random `id` is generated.
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### Bulk indexing [bulk-indexing]
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To achieve the best possible performance, use the bulk API.
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To index some additional documents with the bulk API:
To update an existing document in {{es}}, `POST` the updated document to `http://ELASTICSEARCH_URL/my_index/_doc/ID`, where the ID is the `_id` of the document.
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For example, to update the last document indexed from the previous example with `"_id":"06NqhW4BnhCSymaqFHQn"`:
This request didn’t include `GET`, as the method is implied if you don’t specify anything else. If the document you are looking for exists, {{es}} returns `found":true` along with the document as part of the JSON response. Otherwise, the JSON response contains `"found":false`.
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## Searching [searching]
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You issue search requests for documents with one of these {{es}} endpoints:
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```bash
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https://ELASTICSEARCH_URL/_search
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https://ELASTICSEARCH_URL/INDEX_NAME/_search
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```
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Either a `GET` or a `POST` request with some URI search parameters works, or omit the method to default to `GET` request:
For performance reasons, `?pretty=true` is not recommended in production. You can verify the performance difference yourself by checking the `took` field in the JSON response which tells you how long Elasticsearch took to evaluate the search in milliseconds. When we tested these examples ourselves, the difference was `"took" : 4` against `"took" : 18`, a substantial difference.
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For a full explanation of how the request body is structured, check [Elasticsearch Request Body documentation](https://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-body.html). You can also execute multiple queries in one request with the [Multi Search API](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-msearch).
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## Deleting [deleting]
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You delete documents from {{es}} by sending `DELETE` requests.
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To delete a single document by ID from an earlier example:
Copy file name to clipboardExpand all lines: manage-data/ingest/transform-enrich/data-enrichment.md
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# Data enrichment
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You can use the [enrich processor](asciidocalypse://docs/elasticsearch/docs/reference/ingestion-tools/enrich-processor/enrich-processor.md) to add data from your existing indices to incoming documents during ingest.
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: A set of configuration options used to add the right enrich data to the right incoming documents.
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An enrich policy contains:
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* A list of one or more *source indices* which store enrich data as documents
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* The *policy type* which determines how the processor matches the enrich data to incoming documents
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* A *match field* from the source indices used to match incoming documents
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**Enrich fields* containing enrich data from the source indices you want to add to incoming documents
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Before it can be used with an enrich processor, an enrich policy must be [executed](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-enrich-execute-policy). When executed, an enrich policy uses enrich data from the policy’s source indices to create a streamlined system index called the *enrich index*. The processor uses this index to match and enrich incoming documents.
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$$$source-index$$$
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source index
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: An index which stores enrich data you’d like to add to incoming documents. You can create and manage these indices just like a regular {{es}} index. You can use multiple source indices in an enrich policy. You also can use the same source index in multiple enrich policies.
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$$$enrich-index$$$
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$$$enrich-policy$$$
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enrich index
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: A special system index tied to a specific enrich policy.
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Directly matching incoming documents to documents in source indices could be slow and resource intensive. To speed things up, the enrich processor uses an enrich index.
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Enrich indices contain enrich data from source indices but have a few special properties to help streamline them:
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* They are system indices, meaning they’re managed internally by {{es}} and only intended for use with enrich processors and the {{esql}} `ENRICH` command.
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* They always begin with `.enrich-*`.
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* They are read-only, meaning you can’t directly change them.
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* They are [force merged](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-indices-forcemerge) for fast retrieval.
When creating an enrich policy, the UI walks you through the configuration setup and selecting the fields. Before you can use the policy with an enrich processor or {{esql}} query, you must execute the policy.
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When executed, an enrich policy uses enrich data from the policy’s source indices to create a streamlined system index called the enrich index. The policy uses this index to match and enrich incoming documents.
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Check out these examples:
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*[Example: Enrich your data based on geolocation](/manage-data/ingest/transform-enrich/example-enrich-data-based-on-geolocation.md)
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*[Example: Enrich your data based on exact values](/manage-data/ingest/transform-enrich/example-enrich-data-based-on-exact-values.md)
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*[Example: Enrich your data by matching a value to a range](/manage-data/ingest/transform-enrich/example-enrich-data-by-matching-value-to-range.md)
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