• Apache Airflow
Apache Airflow is an open source workflow management system. It provides components which allow engineers to build data pipelines between different systems. These instructions will step through tasks/adjustments to be done in each product (Astra DB, cql-proxy, Apache Airflow), ultimately resulting in Airflow being able to work with AstraDB in its directed acyclic graphs (DAG).
- You should have an Astra account
- You should Create an Astra Database
- You should Have an Astra Token
- You should Download your Secure Connect Bundle
- You should install `python3` and `pip3` (local deployment of Airflow) or Docker (docker)
This article was written for Apache Airflow version
MacOS with Python
✅ Download and install¶
Following the Apache Airflow reference documentation download and install the software.
✅ Create the keyspace
From the Astra DB dashboard, click on your database name. Scroll down to where the keyspaces are listed, and click the
Add Keyspace button to create a new keyspace. Name this keyspace
✅ Start Cql Proxy¶
DataStax’s cql-proxy is designed to function as an intermediate connection point to allow legacy Apache Cassandra applications to connect to DataStax Astra DB using its new Secure Connect Bundle. There are a few ways to install and run DataStax’s cql-proxy, as outlined in
Be sure to start
cql-proxy with the following settings:
- Using the Secure Connect Bundle downloaded in the previous section
- Binding it to the listen IP of the server instance
- Specifying the username of “token”
- Specifying the Astra Token created for the user in Astra DB as the password
You can run
cql-proxy (in the foreground) from the command line in this way, like this:
Important to note that the command shown above binds
cql-proxy to localhost (127.0.0.1), meaning it is not reachable (by Airflow) from outside the server instance.
✅ Create a new connection in Apache Airflow¶
Inside Apache Airflow, click
Connections from underneath the
Admin drop-down menu. Then click on the blue button labeled with the plus sign (
+) to add a new connection. Fill out the form as shown in Figure 2:
- Connection Id: A unique identifier for the connection in Apache Airflow, which will be referenced inside the DAG code. We will use “cassandra_cqlproxy.”
- Connection Type: Select “Cassandra” from the drop-down. If it is not present, you will have to install Airflow’s Cassandra provider.
- Host: The listen address that cql-proxy is bound to. In this case, that is “127.0.0.1.”
- Schema: The Cassandra keyspace which we created in Astra DB. We’ll set that to “airflow” in this case.
- Login: Your Astra DB client id.
- Password: Your Astra DB client secret.
- Port: The port that cql-proxy is listening on for the CQL native binary protocol, most likely 9042.
Figure 2 - Create a new Cassandra connection for Apache Airflow.
Click the blue
Save button to persist the new connection.
✅ Create a new DAG in Apache Airflow¶
A directed acyclic graph (DAG) is essentially a Python script which imports one or more libraries specific to Airflow. To create a new DAG, first locate your DAG directory. By default, Airflow looks for custom DAGs in the
For testing, there is a sample DAG out in the following GitHub repository: https://github.com/aar0np/DS_Python_stuff/blob/main/cassandra_test_dag.py
This DAG uses the following line to reference the Cassandra connection we created in the above step:
The other important aspect is that this DAG sets its unique identifier as
It also specifically creates two unique tasks:
✅ Final Test¶
To test the connection, copy the DAG mentioned above into the
/dags/ directory. Then we will invoke Airflow’s task testing functionality, by running airflow tasks test and specifying:
- The DAG’s unique identifier
- The name of the task to be run
- The execution date
If today’s date is 2022-02-08, the command looks like this:
Many messages will go by quickly. If it worked, the final messages should look something like this: