Delta Table source connector

This sample code utilizes the Unstructured Open Source Library.

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

from pyspark.sql import SparkSession

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

4. Convert JSON output into Dataframe

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.

Assistant

Responses are generated using AI and may contain mistakes.