# Spark Batch Processing - Caching, DataFrame, Dataset, SparkSQL, and Bucketing in Iceberg (Day 2 Lab)

> In this Spark lab session, we cover caching, DataFrame, Dataset, and SparkSQL, and explore how bucketing works in Iceberg for efficient data management.

- Web page: https://julie.techexpert.io/lesson/spark-batch-day-2-lab-v2
- Program: [Data Engineering Boot Camp V2 Combined Track](https://julie.techexpert.io/program/data-engineering-boot-camp-v2-combined-track)
- Module: Week 4: Batch Pipelines with Apache Spark V2
- Access: Requires enrollment in Data Engineering Boot Camp V2 Combined Track
- Length: 1 h 3 min video
- Skills: SQL, Data Modeling, ETL/ELT, Apache Spark, Docker, Apache Iceberg
- Academy: Julies academy to catch all other programs

## About this lesson

In this Spark lab session, we cover caching, DataFrame, Dataset, and SparkSQL, and explore how bucketing works in Iceberg for efficient data management.

## Navigation

- Previous lesson: [Spark Batch Processing - Caching, UDFs, DataFrames, Datasets, SparkSQL, and Parquet (Day 2 Lecture) ](https://julie.techexpert.io/lesson/spark-batch-day-2-lecture-v2.md)
- Next lesson: [Analytics Data Quality - Hands-On Exercises and Validating Real-World Datasets (Day 1 Lab)](https://julie.techexpert.io/lesson/analytics-data-quality-day-1-lab-v2.md)