---
title: Index and search basics
description: This quickstart provides a hands-on introduction to the fundamental concepts of Elasticsearch: indices, documents, and field type mappings. You'll learn...
url: https://www.elastic.co/elastic/docs-builder/docs/3016/solutions/search/get-started/index-basics
products:
- Elastic Cloud Enterprise
- Elastic Cloud Hosted
- Elastic Cloud Serverless
- Elastic Cloud on Kubernetes
- Elasticsearch
applies_to:
- Elastic Cloud Serverless: Generally available
- Elastic Stack: Generally available
---
# Index and search basics
This quickstart provides a hands-on introduction to the fundamental concepts of Elasticsearch: [indices, documents, and field type mappings](https://www.elastic.co/elastic/docs-builder/docs/3016/manage-data/data-store/index-basics). You'll learn how to create an index, add documents, work with dynamic and explicit mappings, and perform your first basic searches.
The code examples are in [Console](https://www.elastic.co/elastic/docs-builder/docs/3016/explore-analyze/query-filter/tools/console) syntax by default.
You can [convert into other programming languages](/elastic/docs-builder/docs/3016/explore-analyze/query-filter/tools/console#import-export-console-requests) in the Console UI.
## Requirements
You can follow this guide using any Elasticsearch deployment.
To see all deployment options, refer to [Deploy > Choosing your deployment type](/elastic/docs-builder/docs/3016/deploy-manage/deploy#choosing-your-deployment-type).
To get started quickly, spin up a cluster [locally in Docker](https://www.elastic.co/elastic/docs-builder/docs/3016/deploy-manage/deploy/self-managed/local-development-installation-quickstart).
## Add data to Elasticsearch
This quickstart uses Elasticsearch APIs, but there are many other ways to [add data to Elasticsearch](https://www.elastic.co/elastic/docs-builder/docs/3016/solutions/search/ingest-for-search).
You add data to Elasticsearch as JSON objects called documents.
Elasticsearch stores these documents in searchable indices.
Create a new index named `books`:
```json
```
The following response indicates the index was created successfully.
```json
{
"acknowledged": true,
"shards_acknowledged": true,
"index": "books"
}
```
Use the following request to add a single document to the `books` index.
If the index doesn't already exist, this request will automatically create it.
```json
{
"name": "Snow Crash",
"author": "Neal Stephenson",
"release_date": "1992-06-01",
"page_count": 470
}
```
The response includes metadata that Elasticsearch generates for the document, including a unique `_id` for the document within the index.
```json
{
"_index": "books",
"_id": "O0lG2IsBaSa7VYx_rEia",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 2,
"failed": 0
},
"_seq_no": 0,
"_primary_term": 1
}
```
Use the [`_bulk` endpoint](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-bulk) to add multiple documents in a single request.
Bulk data must be formatted as newline-delimited JSON (NDJSON).
```json
{ "index" : { "_index" : "books" } }
{"name": "Revelation Space", "author": "Alastair Reynolds", "release_date": "2000-03-15", "page_count": 585}
{ "index" : { "_index" : "books" } }
{"name": "1984", "author": "George Orwell", "release_date": "1985-06-01", "page_count": 328}
{ "index" : { "_index" : "books" } }
{"name": "Fahrenheit 451", "author": "Ray Bradbury", "release_date": "1953-10-15", "page_count": 227}
{ "index" : { "_index" : "books" } }
{"name": "Brave New World", "author": "Aldous Huxley", "release_date": "1932-06-01", "page_count": 268}
{ "index" : { "_index" : "books" } }
{"name": "The Handmaids Tale", "author": "Margaret Atwood", "release_date": "1985-06-01", "page_count": 311}
```
You should receive a response indicating there were no errors.
```json
{
"errors": false,
"took": 29,
"items": [
{
"index": {
"_index": "books",
"_id": "QklI2IsBaSa7VYx_Qkh-",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 2,
"failed": 0
},
"_seq_no": 1,
"_primary_term": 1,
"status": 201
}
},
{
"index": {
"_index": "books",
"_id": "Q0lI2IsBaSa7VYx_Qkh-",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 2,
"failed": 0
},
"_seq_no": 2,
"_primary_term": 1,
"status": 201
}
},
{
"index": {
"_index": "books",
"_id": "RElI2IsBaSa7VYx_Qkh-",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 2,
"failed": 0
},
"_seq_no": 3,
"_primary_term": 1,
"status": 201
}
},
{
"index": {
"_index": "books",
"_id": "RUlI2IsBaSa7VYx_Qkh-",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 2,
"failed": 0
},
"_seq_no": 4,
"_primary_term": 1,
"status": 201
}
},
{
"index": {
"_index": "books",
"_id": "RklI2IsBaSa7VYx_Qkh-",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 2,
"failed": 0
},
"_seq_no": 5,
"_primary_term": 1,
"status": 201
}
}
]
}
```
[Mappings](/elastic/docs-builder/docs/3016/manage-data/data-store/index-basics#elasticsearch-intro-documents-fields-mappings) define how data is stored and indexed in Elasticsearch, like a schema in a relational database.If you use dynamic mapping, Elasticsearch automatically creates mappings for new fields.
The documents you've added so far have used dynamic mapping, because you didn't specify a mapping while creating the index.To see how dynamic mapping works, add a new document to the `books` index with a field that isn't available in the existing documents.
```json
{
"name": "The Great Gatsby",
"author": "F. Scott Fitzgerald",
"release_date": "1925-04-10",
"page_count": 180,
"language": "EN" <1>
}
```
View the mapping for the `books` index with the [get mapping API](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-indices-get-mapping).
The new field `language` has been added to the mapping with a `text` data type.
```json
```
The following response displays the mappings that were created by Elasticsearch.
```json
{
"books": {
"mappings": {
"properties": {
"author": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"name": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"language": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"page_count": {
"type": "long"
},
"release_date": {
"type": "date"
}
}
}
}
}
```
Create an index named `my-explicit-mappings-books` and specify the mappings yourself.
Pass each field's properties as a JSON object.
This object should contain the [field data type](https://docs-v3-preview.elastic.dev/elastic/docs-builder/docs/3016/reference/elasticsearch/mapping-reference/field-data-types) and any additional [mapping parameters](https://docs-v3-preview.elastic.dev/elastic/docs-builder/docs/3016/reference/elasticsearch/mapping-reference/mapping-parameters).
```json
{
"mappings": {
"dynamic": false, <1>
"properties": { <2>
"name": { "type": "text" },
"author": { "type": "text" },
"release_date": { "type": "date", "format": "yyyy-MM-dd" },
"page_count": { "type": "integer" }
}
}
}
```
The following response indicates a successful operation.
```json
{
"acknowledged": true,
"shards_acknowledged": true,
"index": "my-explicit-mappings-books"
}
```
Explicit mappings are defined at index creation, and documents must conform to these mappings.
You can also use the [update mapping API](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-indices-put-mapping).
When an index has the `dynamic` flag set to `true`, you can add new fields to documents without updating the mapping, which allows you to combine explicit and dynamic mappings.
Learn more about [managing and updating mappings](/elastic/docs-builder/docs/3016/manage-data/data-store/mapping#mapping-manage-update).
## Search your data
Indexed documents are available for search in near real-time, using the [`_search` API](https://www.elastic.co/elastic/docs-builder/docs/3016/solutions/search/querying-for-search).
Use the following request to search all documents in the `books` index:
```json
```
```json
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 7,
"relation": "eq"
},
"max_score": 1,
"hits": [
{
"_index": "books",
"_id": "CwICQpIBO6vvGGiC_3Ls",
"_score": 1,
"_source": {
"name": "Brave New World",
"author": "Aldous Huxley",
"release_date": "1932-06-01",
"page_count": 268
}
},
... (truncated)
]
}
}
```
Use the [`match` query](https://docs-v3-preview.elastic.dev/elastic/docs-builder/docs/3016/reference/query-languages/query-dsl/query-dsl-match-query) to search for documents that contain a specific value in a specific field. This is the standard query for full-text searches.Use the following request to search the `books` index for documents containing `brave` in the `name` field:
```json
{
"query": {
"match": {
"name": "brave"
}
}
}
```
This example uses [Query DSL](https://www.elastic.co/elastic/docs-builder/docs/3016/explore-analyze/query-filter/languages/querydsl), which is the primary query language for Elasticsearch.
```json
{
"took": 9,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 0.6931471,
"hits": [
{
"_index": "books",
"_id": "CwICQpIBO6vvGGiC_3Ls",
"_score": 0.6931471,
"_source": {
"name": "Brave New World",
"author": "Aldous Huxley",
"release_date": "1932-06-01",
"page_count": 268
}
}
]
}
}
```
## Delete your indices
If you want to delete an index to start from scratch at any point, use the [delete index API](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-indices-delete).
For example, use the following request to delete the indices created in this quickstart:
```json
```
Deleting an index permanently deletes its documents, shards, and metadata.
## Next steps
This quickstart introduced the basics of creating indices, adding data, and performing basic searches with Elasticsearch.
To try out similar steps from the Elasticsearch Python client, go to [Build your first search query with Python](https://www.elastic.co/elastic/docs-builder/docs/3016/solutions/search/get-started/keyword-search-python).
The following resources will help you understand Elasticsearch concepts better and dive into the basics of query languages for searching data:
- [Fundamentals of Elasticsearch](https://www.elastic.co/elastic/docs-builder/docs/3016/manage-data/data-store)
- [Search and filter with Query DSL](https://docs-v3-preview.elastic.dev/elastic/docs-builder/docs/3016/reference/query-languages/query-dsl/full-text-filter-tutorial)
- [Search using ES|QL](https://docs-v3-preview.elastic.dev/elastic/docs-builder/docs/3016/reference/query-languages/esql/esql-search-tutorial)