H13-711_V3.5 · Question #265
Which of the following scenarios is Spark suitable for? (Multiple choice)
The correct answer is A. Graph computing B. Interactive query C. Batch processing D. Real-time stream processing. Apache Spark is a unified analytics engine designed to handle all four workloads in a single framework. It supports graph computing via GraphX (its built-in graph processing library), interactive queries via Spark SQL and its REPL/notebook interface (e.g., Databricks, Jupyter)…
Question
Which of the following scenarios is Spark suitable for? (Multiple choice)
Options
- AGraph computing
- BInteractive query
- CBatch processing
- DReal-time stream processing
How the community answered
(25 responses)- A100% (25)
Explanation
Apache Spark is a unified analytics engine designed to handle all four workloads in a single framework. It supports graph computing via GraphX (its built-in graph processing library), interactive queries via Spark SQL and its REPL/notebook interface (e.g., Databricks, Jupyter), and batch processing as its foundational use case - replacing Hadoop MapReduce with in-memory execution for dramatically faster throughput. It also handles real-time stream processing through Spark Streaming (micro-batch) and Structured Streaming (continuous processing). Since all four options are correct, there are no wrong distractors - the exam is testing whether you know Spark's breadth rather than trying to trick you with one capability it lacks.
Memory tip: Think of Spark as a "4-in-1" engine - Graph, Query, Batch, Stream. The keyword is unified: Spark was explicitly built to replace specialized tools (Pregel for graphs, Hive for queries, MapReduce for batch, Storm for streaming) with one consistent API.
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