Data Transformation with Spark SQL in Databricks

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업데이트됨 2026. 5.

Build end-to-end data pipelines - from cleaning and aggregation to streaming and orchestration.

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Ready to handle real-world data at scale? This course teaches you to transform large datasets using Spark SQL and PySpark in Databricks. Learn to shape and clean data, run aggregations with optimized joins, and apply window functions for advanced analytics. You'll also set up file-based streaming with fault-tolerant checkpoints and persist results as Delta tables. By the end, you'll be orchestrating multi-step production pipelines with Databricks Workflows and Lakeflow Declarative Pipelines.

선수 조건

Introduction to Databricks SQL Introduction to PySpark

Loading and Shaping Data

In this chapter, you'll learn how to work with Databricks notebooks, load CSV data into Spark DataFrames, and shape data using PySpark and SQL.

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.css-nklxlk{color:var(--wf-brand--main, #03EF62);}19백만 명의 학습자와 함께 오늘 Data Transformation with Spark SQL in Databricks을 시작하세요!

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19백만 명의 학습자와 함께 오늘 Data Transformation with Spark SQL in Databricks을 시작하세요!