Data Science & AI Workbench enables you to easily connect to HP Vertica, a distributed analytics database that stores data in column format.Before you can do so, you’ll need to conda install the vertica-python package, which contains the Python adapter for Vertica databases:
Any packages you install from the command line are available during the current session only. If you want them to persist, add them to the project’s anaconda-project.yml file. For more information, see Project configurations.
You can then use code such as this to import the library and connect to Vertica from within a notebook session:
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import vertica_pythonimport json# Get credentials from Kubernetes. The credentials were setup as a dictionarycredentials = Nonewith open('/var/run/secrets/user_credentials/vertica_credentials') as f: credentials = json.load(f)# Verify the credentials were pulled correctlyif credentials: # Set up connection dictionary based on secrets obtained above connection_info = { 'host': credentials.get('hostname'), 'port': 5433, 'user': credentials.get('username'), 'password': credentials.get('password'), 'database': 'VMart' } # Use a with statement that auto closes the connection once out of the loop with vertica_python.connect(**connection_info) as connection: cursor = connection.cursor() # Set up example query for the sample dataset that is being used example_query = ( "SELECT DISTINCT s.product_key, p.product_description " "FROM store.store_sales_fact s, public.product_dimension p " "WHERE s.product_key = p.product_key " "AND s.product_version = p.product_version AND s.store_key IN (" " SELECT store_key " " FROM store.store_dimension " " WHERE store_state = 'MA') " "ORDER BY s.product_key LIMIT 50;" ) # Execute the query cursor.execute(example_query) # Iterate through the cursor and print each row for row in cursor.iterate(): print(row)
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