elasticsearch/docs/reference/getting-started.asciidoc

[chapter]
[[getting-started]]
= Quick start

This guide helps beginners learn how to:

* Install and run {es} in a test environment
* Add data to {es}
* Search and sort data
* Extract fields from unstructured content during a search

[discrete]
[[run-elasticsearch]]
=== Step 1. Run {es}

The simplest way to set up {es} is to create a managed deployment with {ess} on
{ecloud}. If you prefer to manage your own test environment, you can install and
run {es} using Docker.

include::{es-repo-dir}/tab-widgets/code.asciidoc[]
include::{es-repo-dir}/tab-widgets/quick-start-install-widget.asciidoc[]

[discrete]
[[send-requests-to-elasticsearch]]
=== Step 2. Send requests to {es}

You send data and other requests to {es} using REST APIs. This lets you interact
with {es} using any client that sends HTTP requests, such as
https://curl.se[curl]. You can also use {kib}'s console to send requests to
{es}.

include::{es-repo-dir}/tab-widgets/api-call-widget.asciidoc[]

[discrete]
[[add-data]]
=== Step 3. Add data

You add data to {es} as JSON objects called documents. {es} stores these
documents in searchable indices.

For time series data, such as logs and metrics, you typically add documents to a
data stream made up of multiple auto-generated backing indices.

A data stream requires an index template that matches its name. {es} uses this
template to configure the stream's backing indices. Documents sent to a data
stream must have a `@timestamp` field.

[discrete]
[[add-single-document]]
==== Add a single document

Submit the following indexing request to add a single log entry to the
`logs-my_app-default` data stream. Since `logs-my_app-default` doesn't exist, the
request automatically creates it using the built-in `logs-*-*` index template.

[source,console]
----
POST logs-my_app-default/_doc
{
  "@timestamp": "2099-05-06T16:21:15.000Z",
  "event": {
    "original": "192.0.2.42 - - [06/May/2099:16:21:15 +0000] \"GET /images/bg.jpg HTTP/1.0\" 200 24736"
  }
}
----
// TEST[s/_doc/_doc?refresh=wait_for/]

The response includes metadata that {es} generates for the document:

* The backing `_index` that contains the document. {es} automatically generates
  the names of backing indices.
* A unique `_id` for the document within the index.

[source,console-result]
----
{
  "_index": ".ds-logs-my_app-default-2099-05-06-000001",
  "_id": "gl5MJXMBMk1dGnErnBW8",
  "_version": 1,
  "result": "created",
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  },
  "_seq_no": 0,
  "_primary_term": 1
}
----
// TESTRESPONSE[s/"_index": ".ds-logs-my_app-default-2099-05-06-000001"/"_index": $body._index/]
// TESTRESPONSE[s/"_id": "gl5MJXMBMk1dGnErnBW8"/"_id": $body._id/]

[discrete]
[[add-multiple-documents]]
==== Add multiple documents

To add multiple documents in one request, use the bulk API. Bulk data must be
newline-delimited JSON (NDJSON). Each line must end in a newline character
(`\n`), including the last line.

[source,console]
----
PUT logs-my_app-default/_bulk
{ "create": { } }
{ "@timestamp": "2099-05-07T16:24:32.000Z", "event": { "original": "192.0.2.242 - - [07/May/2020:16:24:32 -0500] \"GET /images/hm_nbg.jpg HTTP/1.0\" 304 0" } }
{ "create": { } }
{ "@timestamp": "2099-05-08T16:25:42.000Z", "event": { "original": "192.0.2.255 - - [08/May/2099:16:25:42 +0000] \"GET /favicon.ico HTTP/1.0\" 200 3638" } }
----
// TEST[continued]
// TEST[s/_bulk/_bulk?refresh=wait_for/]

[discrete]
[[qs-search-data]]
=== Step 4. Search data

Indexed documents are available for search in near real-time. To search your
data stream, use the search API.

The following search matches all log entries in `logs-my_app-default` and
sorts them by `@timestamp` in descending order.

[source,console]
----
GET logs-my_app-default/_search
{
  "query": {
    "match_all": { }
  },
  "sort": [
    {
      "@timestamp": "desc"
    }
  ]
}
----
// TEST[continued]

By default, the `hits` section of the response includes up to the first 10
documents that match the search. The `_source` of each hit contains the original
JSON object submitted during indexing.

[source,console-result]
----
{
  "took": 2,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": {
      "value": 3,
      "relation": "eq"
    },
    "max_score": null,
    "hits": [
      {
        "_index": ".ds-logs-my_app-default-2099-05-06-000001",
        "_id": "PdjWongB9KPnaVm2IyaL",
        "_score": null,
        "_source": {
          "@timestamp": "2099-05-08T16:25:42.000Z",
          "event": {
            "original": "192.0.2.255 - - [08/May/2099:16:25:42 +0000] \"GET /favicon.ico HTTP/1.0\" 200 3638"
          }
        },
        "sort": [
          4081940742000
        ]
      },
      ...
    ]
  }
}
----
// TESTRESPONSE[s/"took": 2/"took": $body.took/]
// TESTRESPONSE[s/"_index": ".ds-logs-my_app-default-2099-05-06-000001"/"_index": $body.hits.hits.0._index/]
// TESTRESPONSE[s/"_id": "PdjWongB9KPnaVm2IyaL"/"_id": $body.hits.hits.0._id/]
// TESTRESPONSE[s/\.\.\./$body.hits.hits.1,$body.hits.hits.2/]

[discrete]
[[get-specific-fields]]
==== Get specific fields

Parsing the entire `_source` is unwieldy for large documents. To exclude it from
the response, set the `_source` parameter to `false`. Instead, use the `fields`
parameter to retrieve the fields you want.

[source,console]
----
GET logs-my_app-default/_search
{
  "query": {
    "match_all": { }
  },
  "fields": [
    "@timestamp"
  ],
  "_source": false,
  "sort": [
    {
      "@timestamp": "desc"
    }
  ]
}
----
// TEST[continued]
// TEST[s/_search/_search?filter_path=hits.hits&size=1/]

The response contains each hit's `fields` values as a flat array.

[source,console-result]
----
{
  ...
  "hits": {
    ...
    "hits": [
      {
        "_index": ".ds-logs-my_app-default-2099-05-06-000001",
        "_id": "PdjWongB9KPnaVm2IyaL",
        "_score": null,
        "fields": {
          "@timestamp": [
            "2099-05-08T16:25:42.000Z"
          ]
        },
        "sort": [
          4081940742000
        ]
      },
      ...
    ]
  }
}
----
// TESTRESPONSE[s/\.\.\.//]
// TESTRESPONSE[s/"_index": ".ds-logs-my_app-default-2099-05-06-000001"/"_index": $body.hits.hits.0._index/]
// TESTRESPONSE[s/"_id": "PdjWongB9KPnaVm2IyaL"/"_id": $body.hits.hits.0._id/]
// TESTRESPONSE[s/4081940742000\n        \]\n      \},\n/4081940742000\]}/]

[discrete]
[[search-date-range]]
==== Search a date range

To search across a specific time or IP range, use a `range` query.

[source,console]
----
GET logs-my_app-default/_search
{
  "query": {
    "range": {
      "@timestamp": {
        "gte": "2099-05-05",
        "lt": "2099-05-08"
      }
    }
  },
  "fields": [
    "@timestamp"
  ],
  "_source": false,
  "sort": [
    {
      "@timestamp": "desc"
    }
  ]
}
----
// TEST[continued]

You can use date math to define relative time ranges. The following query
searches for data from the past day, which won't match any log entries in
`logs-my_app-default`.

[source,console]
----
GET logs-my_app-default/_search
{
  "query": {
    "range": {
      "@timestamp": {
        "gte": "now-1d/d",
        "lt": "now/d"
      }
    }
  },
  "fields": [
    "@timestamp"
  ],
  "_source": false,
  "sort": [
    {
      "@timestamp": "desc"
    }
  ]
}
----
// TEST[continued]

[discrete]
[[extract-fields]]
==== Extract fields from unstructured content

You can extract <<runtime-search-request,runtime fields>> from unstructured
content, such as log messages, during a search.

Use the following search to extract the `source.ip` runtime field from
`event.original`. To include it in the response, add `source.ip` to the `fields`
parameter.

[source,console]
----
GET logs-my_app-default/_search
{
  "runtime_mappings": {
    "source.ip": {
      "type": "ip",
      "script": """
        String sourceip=grok('%{IPORHOST:sourceip} .*').extract(doc[ "event.original" ].value)?.sourceip;
        if (sourceip != null) emit(sourceip);
      """
    }
  },
  "query": {
    "range": {
      "@timestamp": {
        "gte": "2099-05-05",
        "lt": "2099-05-08"
      }
    }
  },
  "fields": [
    "@timestamp",
    "source.ip"
  ],
  "_source": false,
  "sort": [
    {
      "@timestamp": "desc"
    }
  ]
}
----
// TEST[continued]

[discrete]
[[combine-queries]]
==== Combine queries

You can use the `bool` query to combine multiple queries. The following search
combines two `range` queries: one on `@timestamp` and one on the `source.ip`
runtime field.

[source,console]
----
GET logs-my_app-default/_search
{
  "runtime_mappings": {
    "source.ip": {
      "type": "ip",
      "script": """
        String sourceip=grok('%{IPORHOST:sourceip} .*').extract(doc[ "event.original" ].value)?.sourceip;
        if (sourceip != null) emit(sourceip);
      """
    }
  },
  "query": {
    "bool": {
      "filter": [
        {
          "range": {
            "@timestamp": {
              "gte": "2099-05-05",
              "lt": "2099-05-08"
            }
          }
        },
        {
          "range": {
            "source.ip": {
              "gte": "192.0.2.0",
              "lte": "192.0.2.240"
            }
          }
        }
      ]
    }
  },
  "fields": [
    "@timestamp",
    "source.ip"
  ],
  "_source": false,
  "sort": [
    {
      "@timestamp": "desc"
    }
  ]
}
----
// TEST[continued]

[discrete]
[[aggregate-data]]
==== Aggregate data

Use aggregations to summarize data as metrics, statistics, or other analytics.

The following search uses an aggregation to calculate the
`average_response_size` using the `http.response.body.bytes` runtime field. The
aggregation only runs on documents that match the `query`.

[source,console]
----
GET logs-my_app-default/_search
{
  "runtime_mappings": {
    "http.response.body.bytes": {
      "type": "long",
      "script": """
        String bytes=grok('%{COMMONAPACHELOG}').extract(doc[ "event.original" ].value)?.bytes;
        if (bytes != null) emit(Integer.parseInt(bytes));
      """
    }
  },
  "aggs": {
    "average_response_size":{
      "avg": {
        "field": "http.response.body.bytes"
      }
    }
  },
  "query": {
    "bool": {
      "filter": [
        {
          "range": {
            "@timestamp": {
              "gte": "2099-05-05",
              "lt": "2099-05-08"
            }
          }
        }
      ]
    }
  },
  "fields": [
    "@timestamp",
    "http.response.body.bytes"
  ],
  "_source": false,
  "sort": [
    {
      "@timestamp": "desc"
    }
  ]
}
----
// TEST[continued]

The response’s `aggregations` object contains aggregation results.

[source,console-result]
----
{
  ...
  "aggregations" : {
    "average_response_size" : {
      "value" : 12368.0
    }
  }
}
----
// TESTRESPONSE[s/\.\.\./"took": "$body.took", "timed_out": false, "_shards": "$body._shards", "hits": "$body.hits",/]

[discrete]
[[explore-more-search-options]]
==== Explore more search options

To keep exploring, index more data to your data stream and check out <<common-search-options>>.

[discrete]
[[clean-up]]
=== Step 5. Clean up

When you're done, delete your test data stream and its backing indices.

[source,console]
----
DELETE _data_stream/logs-my_app-default
----
// TEST[continued]

You can also delete your test deployment.

include::{es-repo-dir}/tab-widgets/quick-start-cleanup-widget.asciidoc[]

[discrete]
[[whats-next]]
=== What's next?

* Get the most out of your time series data by setting up data tiers and
{ilm-init}. See <<use-elasticsearch-for-time-series-data>>.

* Use {fleet} and {agent} to collect logs and metrics directly from your data
sources and send them to {es}. See the
{fleet-guide}/fleet-quick-start.html[{fleet} quick start guide].

* Use {kib} to explore, visualize, and manage your {es} data. See the
{kibana-ref}/get-started.html[{kib} quick start guide].