> For the complete documentation index, see [llms.txt](https://docs.quilt.bio/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.quilt.bio/version-5.0.x/catalog/searchquery.md).

# Search & query

Out of the box, Quilt provides support for queries in the ElasticSearch DSL, as well as SQL queries in Athena (details forthcoming).

### ElasticSearch

The objects in S3 buckets connected to Quilt are synchronized to an ElasticSearch cluster, which powers Quilt's search features. For custom queries, you can use the Queries tab in the Quilt catalog to directly query ElasticSearch cluster.

Quilt uses ElasticsSearch 6.7 ([docs](https://www.elastic.co/guide/en/elasticsearch/reference/6.7/index.html)).

#### Indexing

Quilt maintains a near-realtime index of the objects in your S3 bucket in ElasticSearch. Each bucket corresponds to one or more ElasticSearch indexes. As objects are mutated in S3, Quilt uses an event-driven system (via SNS and SQS) to update ElasticSearch.

There are two types of indexing in Quilt:

* *shallow* indexing includes object metadata (such as the file name and size)
* *deep* indexing includes object contents. Quilt supports deep indexing for the following file extensions:
  * .fcs (FlowJo)
  * .ipynb (Jupyter notebooks)
  * .parquet
  * .pdf
  * .html, .txt, .tsv, .csv, .md (plus many other plain-text formats)
  * .xls, .xlsx

#### Queries

![](/files/mE0xsjTysfiqUMLkWjMa)

Quilt ElasticSearch queries support the following keys:

* `index` — comma-separated list of indexes to search ([learn more](https://www.elastic.co/guide/en/elasticsearch/reference/6.8/multi-index.html))
* `filter_path` — to reducing response nesting, ([learn more](https://www.elastic.co/guide/en/elasticsearch/reference/6.8/common-options.html#common-options-response-filtering))
* `_source` — boolean that adds or removes the `_source` field, or a list of fields to return ([learn more](https://www.elastic.co/guide/en/elasticsearch/reference/6.8/search-request-source-filtering.html))
* `size` — limits the number of hits ([learn more](https://www.elastic.co/guide/en/elasticsearch/reference/6.8/search-uri-request.html))
* `from` — starting offset for pagination ([learn more](https://www.elastic.co/guide/en/elasticsearch/reference/6.8/search-uri-request.html))
* `body` — the search query body as a JSON dictionary ([learn more](https://www.elastic.co/guide/en/elasticsearch/reference/6.8/search-request-body.html))

**Saved queries**

You can provide pre-canned queries for your users by providing a configuration file at `s3://YOUR_BUCKET/.quilt/queries/config.yaml`:

```yaml
version: "1"
queries:
  query-1:
    name: My first query
    description: Optional description
    url: s3://BUCKET/.quilt/queries/query-1.json
  query-2:
    name: Second query
    url: s3://BUCKET/.quilt/queries/query-2.json
```

The Quilt catalog displays your saved queries in a drop-down for your users to select, edit, and execute.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.quilt.bio/version-5.0.x/catalog/searchquery.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.