# Athena

Quilt stores package data and metadata in S3. Metadata lives in a per-package manifest file\
in a each bucket's `.quilt/` directory.

You can therefore query package metadata wth SQL engines like AWS Athena.\
Users can write SQL queries to select packages (or files from within packages)\
using predicates based on package or object-level metadata.

Packages can be created from the resulting tabular data.\
To be able to create a package,\
the table must contain the columns `logical_key`, `physical_keys` (or `physical_key`) and `size`.\
(See also [Mental Model](https://docs.quilt.bio/mentalmodel))

![Athena page with results ready to be packaged](/files/F8UZlxBHnTeSfVzZXtZ1)

## Defining package tables and views in Athena

> This step is not required for users of Quilt enterprise, since tables and views\
> are managed by Quilt. Check the value of `UserAthenaDatabaseName` output in your\
> CloudFormation stack to know the name of the Athena database it created.

The first step in configuring Athena to query the package contents and metadata\
is to define a set of tables and views that represent the metadata fields as columns.\
The easiest way to do this is using the pre-built CloudFormation templates\
available in the [examples repository](https://github.com/quiltdata/examples/tree/master/athena_cfn/).

## Example: query object-level metadata

Suppose we wish to find all .tiff files produced by algorithm version 1.3\
with a cell index of 5.

```sql
SELECT * FROM "YOUR-BUCKET_objects-view"
WHERE substr(logical_key, -5) = '.tiff'
-- extract and query object-level metadata
AND json_extract_scalar(meta, '$.user_meta.nucmembsegmentationalgorithmversion') LIKE '1.3%'
AND json_array_contains(json_extract(meta, '$.user_meta.cellindex'), '5');
```


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# Agent Instructions: 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:

```
GET https://docs.quilt.bio/quilt-platform-catalog-user/advanced/athena.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.