Working With Jupyter Notebooks And Airflow On Hadoop

Mark Litwintschik shows us an interesting demonstration of running Jupyter Notebooks as well as automating tasks with Airflow on Hadoop:

The following will create a ~/airflow folder, setup a SQLite 3 database used to store Airflow’s state and configuration set via the Web UI, upgrade the configuration schema and create a folder for the Python-based jobs code Airflow will run.

$ cd ~
$ airflow initdb
$ airflow upgradedb
$ mkdir -p ~/airflow/dags

By default Presto’s Web UI, Spark’s Web UI and Airflow’s Web UI all use TCP port 8080. If you launch Presto after Spark then Presto will fail to start. If you start Spark after Presto then Presto will launch on 8080 and the Spark Master Server will take 8081 and keep trying higher ports until it finds one that is free. Spark will then pick an even higher port number for the Spark Worker Web UI. This overlap normally isn’t an issue as in a production setting these services would normally live on separate machines.

Read the whole thing.

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