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Read a Delta table

This recipe reads a Unity Catalog table using the Databricks SQL Connector.

Code snippet​

app.py
import streamlit as st
from databricks import sql
from databricks.sdk.core import Config


cfg = Config()  # Set the DATABRICKS_HOST environment variable when running locally


@st.cache_resource(ttl="1h") # connection is cached
def get_connection(http_path):
    return sql.connect(
        server_hostname=cfg.host,
        http_path=http_path,
        credentials_provider=lambda: cfg.authenticate,
    )

def read_table(table_name, conn):
    with conn.cursor() as cursor:
        query = f"SELECT * FROM {table_name}"
        cursor.execute(query)
        return cursor.fetchall_arrow().to_pandas()

http_path_input = st.text_input(
    "Enter your Databricks HTTP Path:", placeholder="/sql/1.0/warehouses/xxxxxx"
)

table_name = st.text_input(
    "Specify a Unity Catalog table name:", placeholder="catalog.schema.table"
)

if http_path_input and table_name:
    conn = get_connection(http_path_input)
    df = read_table(table_name, conn)
    st.dataframe(df)
info

This sample uses Streamlit's st.cache_resource with a 1-hour TTL (time-to-live) to cache the database connection across users, sessions, and reruns. The cached connection will automatically expire after 1 hour, ensuring connections don't become stale. Use Streamlit's caching decorators and TTL parameter to implement a caching strategy that works for your use case.

Resources​

Permissions​

Your app service principal needs the following permissions:

  • SELECT on the Unity Catalog table
  • CAN USE on the SQL warehouse

See Unity Catalog privileges and securable objects for more information.

Dependencies​

requirements.txt
databricks-sdk
databricks-sql-connector
streamlit