> For the complete documentation index, see [llms.txt](https://docs.bdb.ai/data-pipeline-4/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.bdb.ai/data-pipeline-4/getting-started/homepage/create/creating-a-new-job/task-components/writers/s3-writer.md).

# S3 Writer

This task is used to write the data in Amazon S3 bucket.

## Configuring the Meta Information tab fields <a href="#configuring-the-over-all-meta-information-tab-fields" id="configuring-the-over-all-meta-information-tab-fields"></a>

Drag the S3 writer task to the Workspace and click on it to open the related configuration tabs for the same. The ***Meta Information*** tab opens by default.

* **Bucket Name (\*):** Enter S3 Bucket name.
* **Region (\*):** Provide S3 region.
* **Access Key (\*):** Access key shared by AWS to login
* **Secret Key (\*):** Secret key shared by AWS to login
* **Table (\*):** Mention the Table or object name which is to be read
* **File Type (\*):** Select a file type from the drop-down menu (CSV, JSON, PARQUET, AVRO are the supported file types).
* **Save Mode:** Select the Save mode from the drop down.
  * Append
* **Schema File Name:** Upload spark schema file in JSON format.

<figure><img src="https://3157314867-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FvmyGSlDvDj86v7eh3RHM%2Fuploads%2FzKpDU10pAUyBES69nRJj%2Fimage.png?alt=media&amp;token=6b3d3a87-4ae1-4e4f-a106-263ea71dd0ce" alt=""><figcaption><p><em><strong>S3 Writer Task</strong></em></p></figcaption></figure>

{% hint style="info" %}
*<mark style="color:green;">Please Note:</mark> Please click the **Save Task In Storage** icon to save the configuration for the dragged writer task.*
{% endhint %}