This is a sample app on how to show how easy it is to build a new application using Databricks Connect and Plotly.
From DBR 13 onwards, Databricks Connect is now built on open-source Spark Connect. Spark Connect introduces a decoupled client-server architecture for Apache Spark™ that allows remote connectivity to Spark clusters using the DataFrame API and unresolved logical plans as the protocol. With this new architecture based on Spark Connect, Databricks Connect becomes a thin client that is simple and easy to use! It can be embedded everywhere to connect to Databricks: in IDEs, Notebooks and any application, allowing customers and partners alike to build new (interactive) user experiences based on their Databricks Lakehouse!
All you need to get started is a Databricks cluster and this simple Python
application. The dataset used in this application is the standard Databricks samples
dataset.
To get started, create a new virtual environment and install the reuired dependencies
pip instal -r requirements.txt
from databricks.connect.session import DatabricksSession as SparkSession
from databricks.sdk import WorkspaceClient
config = WorkspaceClient(profile="PROFILE", cluster_id="CLUSTER_ID").config
spark = SparkSession.builder.sdkConfig(config).getOrCreate()In the app.py file configure the values for HOST, CLUSTER and TOKEN with
correct values that identify your Databricks workspace, cluster ID and your personal
access token.
Run the plotly app
python app.py
This sample application is meant for illustration purposes only. The application uses the follwing third-party dependencies:
- Plotly / Dash - https://github.com/plotly/dash - The MIT License (MIT)
- Tailwind CSS - https://github.com/tailwindlabs/tailwindcss - - The MIT License (MIT)