# Dask

## Description

The Dask offline store provides support for reading [FileSources](/reference/data-sources/file.md).

{% hint style="warning" %}
All data is downloaded and joined using Python and therefore may not scale to production workloads.
{% endhint %}

## Example

{% code title="feature\_store.yaml" %}

```yaml
project: my_feature_repo
registry: data/registry.db
provider: local
offline_store:
  type: dask
```

{% endcode %}

The full set of configuration options is available in [DaskOfflineStoreConfig](https://rtd.feast.dev/en/latest/#feast.infra.offline_stores.dask.DaskOfflineStoreConfig).

## Functionality Matrix

The set of functionality supported by offline stores is described in detail [here](/reference/offline-stores/overview.md#functionality). Below is a matrix indicating which functionality is supported by the dask offline store.

|                                                                    | Dask |
| ------------------------------------------------------------------ | ---- |
| `get_historical_features` (point-in-time correct join)             | yes  |
| `pull_latest_from_table_or_query` (retrieve latest feature values) | yes  |
| `pull_all_from_table_or_query` (retrieve a saved dataset)          | yes  |
| `offline_write_batch` (persist dataframes to offline store)        | yes  |
| `write_logged_features` (persist logged features to offline store) | yes  |

Below is a matrix indicating which functionality is supported by `DaskRetrievalJob`.

|                                                       | Dask |
| ----------------------------------------------------- | ---- |
| export to dataframe                                   | yes  |
| export to arrow table                                 | yes  |
| export to arrow batches                               | no   |
| export to SQL                                         | no   |
| export to data lake (S3, GCS, etc.)                   | no   |
| export to data warehouse                              | no   |
| export as Spark dataframe                             | no   |
| local execution of Python-based on-demand transforms  | yes  |
| remote execution of Python-based on-demand transforms | no   |
| persist results in the offline store                  | yes  |
| preview the query plan before execution               | yes  |
| read partitioned data                                 | yes  |

To compare this set of functionality against other offline stores, please see the full [functionality matrix](/reference/offline-stores/overview.md#functionality-matrix).


---

# 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.feast.dev/reference/offline-stores/dask.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.