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Look no further if you're looking for a comprehensive set of realistic, high-quality questions to help you prepare for the Databricks Certified Developer for Apache Spark 3.0 exam in Python.
These up-to-date practise exams will give you the knowledge and confidence you need to pass the exam with flying colours. All 120 questions were written from the ground up, based on the actual topic distribution and tone of the exam. The questions cover all of the exam themes, including Python and Apache Spark 3.0 specifics. Most questions include detailed explanations, allowing you to learn from your mistakes, as well as links to Spark documentation and expert web content, which will help you understand how Spark works even better.
Syllabus :
1. Spark Architecture Conceptual understanding (ca. 17 %)
- Spark driver, execution hierarchy, DAGs, execution modes, deployment modes, memory management, cluster configurations, fault tolerance, partitioning, narrow vs. wide transformations, executors, Python vs. Scala, Spark vs. Hadoop
2. Spark Architecture Applied understanding (ca. 11%)
- Memory management, configurations, lazy evaluation, action vs. transformation, shuffles, broadcasting, fault tolerance, accumulators, adaptive query execution, Spark UI, partitioning
3. Spark DataFrame API Applications (ca. 72%)
- Selecting/dropping columns, renaming columns, aggregating rows, filtering DataFrames, different types of joins, partitioning/coalescing, reading and writing DataFrames in different formats, string functions, math functions, UDFs, Spark configurations, caching, collect/take
