Running Pandas Jobs using Airflow

Airflow

Apache Airflow is an open-source platform for authoring, scheduling and monitoring data and computing workflows. It was first developed by Airbnb and is now under the Apache Software Foundation. Airflow uses Python to create workflows that can be easily scheduled and monitored. Airflow can help you move data from one source to a destination, filter datasets, apply data policies, manipulation, monitoring and even call microservices to trigger database management tasks. It can be used for batch jobs, organizing, monitoring, and executing workflows automatically. Airflow has been used by many companies for various use cases such as ETL pipelines, machine learning workflows, data warehousing, and more.

Pandas

Pandas is an open-source Python package that is most widely used for data science/data analysis and machine learning tasks. It provides support for multi-dimensional arrays and data manipulation. Pandas strengthens Python by giving the popular programming language the capability to work with spreadsheet-like data enabling fast loading, aligning, manipulating, and merging, in addition to other key functions. It is prized for providing highly optimized performance when backend source code is written in C or Python. Pandas has become popular because it provides a powerful set of commands and features that are used to easily analyze data. It can be used to perform various tasks like filtering data according to certain conditions, or segmenting and segregating data according to preference. It can efficiently handle large datasets and provides spreadsheet functionality.

Open source orchestrators like Airflow are one of the primary means by which companies leverage Pandas in production. Airflow offers a mechanism to schedule and monitor these jobs as part of more complex workflow graphs. Kaspian has a native operator for Airflow; this operator makes it easy to either swap to or get started with running Pandas jobs that utilize Kaspian's flexible compute layer.

Learn more about Kaspian and see how our flexible compute layer for the modern data cloud is already reshaping the way companies in industries like retail, manufacturing and logistics are thinking about data engineering and analytics.