Case Study: MyFitnessPal delivers "Verified Foods" and a 10x faster data pipeline with Databricks

MyFitnessPal - Customer Case Study

MyFitnessPal, a large health and fitness platform with millions of user-generated food entries, needed to launch a “Verified Foods” feature to harmonize noisy, crowdsourced nutrition data. The verification algorithms had to run on terabyte-scale data and the team’s legacy non-distributed Java/Hadoop pipelines were too slow and inflexible—processing took weeks and couldn’t scale to meet product timelines.

MyFitnessPal rebuilt the pipeline on Apache Spark using the Databricks platform—leveraging zero-management Spark clusters, an interactive notebook workspace, and an automated job scheduler—to move from exploration to production rapidly. The new solution delivered the Verified Foods feature and cut processing time by tenfold (weeks to hours), enabled four times more projects through higher team productivity, and improved analytics, code reuse, and operational scalability.

MyFitnesspal

Chul Lee

Director of Data Engineering & Science