# Databricks and AWS s3

**URL:** <https://discourse.greatexpectations.io/t/databricks-and-aws-s3/400>\
**Category:** Archive\
**Tags:** databricks, s3\
**Created:** [September 21, 2020, 9:18pm UTC](https://discourse.greatexpectations.io/t/databricks-and-aws-s3/400 "2020-09-21T21:18:40Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![anthony](https://yyz1.discourse-cdn.com/flex031/user_avatar/discourse.greatexpectations.io/anthony/32/68_2.png) [@anthony](https://discourse.greatexpectations.io/u/anthony)\
**Post date:** [September 21, 2020, 9:18pm UTC](https://discourse.greatexpectations.io/t/databricks-and-aws-s3/400/1 "2020-09-21T21:18:40Z")

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We have noticed that there is some confusion around writing to s3 from a Databricks environment (e.g. writing to metadata stores / data docs). That is understandable as it’s a bit involved to set up access to s3 from within Databricks. Please see the Databricks documentation to [mount S3 buckets with DBFS](https://docs.databricks.com/data/data-sources/aws/amazon-s3.html#mount-s3-buckets-with-dbfs). Once the bucket is mounted, you can [access files in your s3 bucket as if they were local files](https://docs.databricks.com/data/data-sources/aws/amazon-s3.html#access-files-in-your-s3-bucket-as-if-they-were-local-files).

You can refer to these documents for tips on setting up Great Expectations from within a Databricks environment:

- [Deploying Great Expectations in a hosted environment without file system or CLI](https://docs.greatexpectations.io/en/latest/guides/workflows_patterns/deployment_hosted_environments.html)
- [How to instantiate a Data Context on Databricks Spark cluster](https://docs.greatexpectations.io/en/latest/guides/how_to_guides/configuring_data_contexts/how_to_instantiate_a_data_context_on_a_databricks_spark_cluster.html)

We have not yet tested this, but some of our users have had success with Databricks → s3 so please comment here with any concerns or success stories!