Databricks Certified Associate Developer for Apache Spark 4
About this course
This is a COMPLETE Apache Spark 4.0 Bootcamp you need in 2026 to become a PRO Spark Developer. Whether you're a beginner or a working professional looking to upskill, this course will guide step by step with a hands-on, practical, and engaging lectures (doodle illustrations).GAIN STRONG HANDS-ON WITH:Spark Architecture & Components - Understand how Driver, Executors, and Cluster Manager work together behind the scenes. Learn DAG execution, lazy evaluation, Catalyst optimizer, stages, tasks & how to monitor everything using Spark UI.PySpark DataFrames & Manipulation - Master filtering, grouping, joins, window functions, exploding arrays, nested JSON handling, pivoting, advanced aggregations and complex transformations. SparkSQL - Run SQL queries directly on CSV, JSON, Parquet, Delta & more. Work with temp views, save modes, partitioning, date-time functions & Unix epoch conversions like a pro.Memory Management & Garbage Collection - Understand how executor memory pool works and why Driver/Executor OOM errors happen. Learn storage levels (MEMORY_ONLY, DISK_ONLY), caching strategies & Spark Garbage Collection in depth.Performance Tuning & Optimization - Learn partitioning, repartition, coalesce, AQE, broadcast joins, bucketing, shuffle optimization and Salting techniques to boost your Spark application's performance.Structured Streaming - Build real-time pipelines with watermarking & exactly-once guarantees. Implement tumbling, sliding & session windows along with triggers and ForEachBatch operations.Spark Connect & Deployment Modes - Understand Spark Connect and how it changes client-server communication. Learn local, client & cluster deployment modes and how to choose the right one for real-world projects.<
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- What the provider tells you
- 38/45
- Who stands behind it
- 8/35
- How complete the listing is
- 16/20
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What you'll learn
- understand Spark architecture and components
- master PySpark DataFrames and advanced manipulation techniques
- run SQL queries on various file formats using SparkSQL
- grasp memory management strategies and garbage collection concepts
- perform performance tuning and optimization techniques
- build real-time streaming pipelines with structured streaming
- learn about Spark Connect and different deployment modes
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