@ananthakrishna raikar :
Certainly! Streamlit can be used to connect to Databricks Delta tables and SQL endpoints through the use of the Databricks SQL Endpoint JDBC/ODBC driver.
Here's a sample code snippet to connect Streamlit with Databricks Delta:
import streamlit as st
import pandas as pd
import sqlalchemy
# Set up a connection to the Databricks SQL Endpoint using SQLAlchemy
# Replace with your own values for the JDBC/ODBC driver and endpoint URL
engine = sqlalchemy.create_engine("databricks+odbc://<Driver Name>:<Host Name>:<Port Number>?Authentication=<Auth Type>")
# Define a function to execute SQL queries and return the results as a Pandas dataframe
def run_query(query):
with engine.connect() as con:
rs = con.execute(query)
df = pd.DataFrame(rs.fetchall(), columns=rs.keys())
return df
# Example query to retrieve data from a Delta table
query = "SELECT * FROM my_delta_table"
# Call the function to execute the query and display the results in Streamlit
result_df = run_query(query)
st.dataframe(result_df)
Make sure to replace the values in the engine variable with your own JDBC/ODBC driver name, host name, port number, and authentication type.
Also, note that Databricks Delta tables can be accessed through the Databricks Delta JDBC driver, while Databricks SQL endpoints can be accessed through the Databricks SQL Endpoint JDBC/ODBC driver.
