# Databricks and Advanced Spark Day2 Lab

> In this Lab, Zach dives into performance tuning and incremental data processing using a substantial dataset of around 50 gigabytes of tweets. He demonstrates the importance of partitioning. He explores the impact of repartitioning strategies on performance. He encourages everyone to experiment with…

- Web page: https://www.dataexpert.io/lesson/databricksandadvancedsparkday2lab-feb26
- Program: [Winter 2026 Data Engineering Boot Camp](https://www.dataexpert.io/program/databricks-engineering-boot-camp-starting-february-9th-2026-7319)
- Access: Requires enrollment in Winter 2026 Data Engineering Boot Camp
- Length: 50 min video
- Skills: Python, Apache Spark, Databricks
- Academy: DataExpert.io Academy

## About this lesson

In this Lab, Zach dives into performance tuning and incremental data processing using a substantial dataset of around 50 gigabytes of tweets. He demonstrates the importance of partitioning. He explores the impact of repartitioning strategies on performance. He encourages everyone to experiment with their own partitioning strategies and to utilize the Spark UI for performance analysis.

## Navigation

- Previous lesson: [Databricks and Advanced Spark Day2 Lecture](https://www.dataexpert.io/lesson/databricksandadvancedsparkday2lecture-feb26.md)
- Next lesson: [Managing Unstructured Data Day1 Lecture](https://www.dataexpert.io/lesson/managingunstructureddataday1lecture-feb26.md)
