The Databricks Associate-Developer-Apache-Spark exam covers a range of topics such as Spark architecture, Spark SQL, Spark Streaming, machine learning with MLlib, graph processing with GraphX, and more. It assesses one's ability to develop and deploy Spark applications using Databricks, as well as their understanding of best practices for developing reliable, scalable, and efficient Spark applications.
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The Databricks Associate-Developer-Apache-Spark exam consists of 60 multiple-choice questions that need to be answered within 90 minutes. The questions are designed to test the candidate's knowledge of Spark and Databricks. Associate-Developer-Apache-Spark exam is conducted online and can be taken from anywhere with an internet connection. The passing score for the exam is 70%.
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Databricks Associate-Developer-Apache-Spark Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Apache Spark Architecture and Components | 20% | - Cluster Mode and Execution Hierarchy - Partitioning and Fault Tolerance - Driver and Executor Roles |
| Topic 2: DataFrame and Dataset API Applications | 30% | - Column Selection and Manipulation - Joins and Transformations - Filtering, Sorting and Aggregation |
| Topic 3: Troubleshooting and Tuning | 10% | - Debugging Spark Applications - Caching and Shuffle Optimization - Spark UI and Bottlenecks |
| Topic 4: Using Spark SQL | 20% | - Window Functions - SQL Queries and Operations - Performance Optimization |
| Topic 5: Using Spark Connect and Pandas API on Spark | 10% | - Pandas API Integration - Remote Connectivity |
| Topic 6: Structured Streaming | 10% | - Stateful Processing Basics - Streaming Concepts - Watermarks and Triggers |
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