# Source: https://docs.unstructured.io/examplecode/codesamples/oss/table-source-connector.md

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.unstructured.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Delta Table source connector

<Note>
  This sample code utilizes the [Unstructured Open Source](/open-source/introduction/overview "Open Source") Library.
</Note>

## Objectives

1. Extract text and metadata from a PDF file using the Unstructured.io Python SDK.

2. Process and store this data in a Databricks Delta Table.

3. Retrieve data from the Delta Table using the Unstructured.io Delta Table Connector.

## Prerequisites

* Unstructured Python SDK

* Databricks account and workspace

* AWS S3 for Delta Table storage

## Processing and Storing into Databricks Delta Table

3. Initialize PySpark

```python  theme={null}
from pyspark.sql import SparkSession

spark = SparkSession.builder.appName('sparkdf').getOrCreate()

```

4. Convert JSON output into Dataframe

```python  theme={null}
import pyspark

dataframe = spark.createDataFrame(res.elements)

```

5. Store DataFrame as Delta Table

```
dataframe.write.mode("overwrite").format("delta").saveAsTable("delta_table")

```

## Conclusion

This documentation covers the essential steps for converting unstructured PDF data into structured data and storing it in a Databricks Delta Table. It also outlines how to extract this data for further use.