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How to become Databricks Associate Developer Apache Spark certified
To create applications that run on the Databricks platform. You'll learn how to use the Spark shell to interact with the data stored in Databricks, the Databricks DataFrame API, and the Databricks Query Language (DQL). You'll also gain exposure to a variety of machine learning and data mining algorithms that can be used to solve real-world problems.
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Databricks Associate-Developer-Apache-Spark Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Troubleshooting and Tuning | 10% | - Spark UI and Bottlenecks - Caching and Shuffle Optimization - Debugging Spark Applications |
| Topic 2: Using Spark SQL | 20% | - Performance Optimization - Window Functions - SQL Queries and Operations |
| Topic 3: Structured Streaming | 10% | - Watermarks and Triggers - Streaming Concepts - Stateful Processing Basics |
| Topic 4: Using Spark Connect and Pandas API on Spark | 10% | - Remote Connectivity - Pandas API Integration |
| Topic 5: DataFrame and Dataset API Applications | 30% | - Filtering, Sorting and Aggregation - Joins and Transformations - Column Selection and Manipulation |
| Topic 6: Apache Spark Architecture and Components | 20% | - Driver and Executor Roles - Cluster Mode and Execution Hierarchy - Partitioning and Fault Tolerance |
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