H13-723_V2.0 · Question #7
In FusionInsight HD, what are the computing frameworks that can be used in real-time processing scenarios? (multiple choice)
The correct answer is A. Spark Streaming B. Streaming. Spark Streaming (A) and Streaming (B) are correct because both are designed to process data continuously as it arrives - Spark Streaming processes data in micro-batches using the Spark engine, while FusionInsight HD's Streaming component (based on Apache Storm) handles true…
Question
In FusionInsight HD, what are the computing frameworks that can be used in real-time processing scenarios? (multiple choice)
Options
- ASpark Streaming
- BStreaming
- CMapReduoe
- DHDFS
How the community answered
(13 responses)- A77% (10)
- C8% (1)
- D15% (2)
Explanation
Spark Streaming (A) and Streaming (B) are correct because both are designed to process data continuously as it arrives - Spark Streaming processes data in micro-batches using the Spark engine, while FusionInsight HD's Streaming component (based on Apache Storm) handles true event-driven real-time computation. Both are purpose-built for low-latency, continuous data ingestion scenarios.
MapReduce (C) is wrong because it is a batch processing framework - it reads input, processes it in large chunks, and writes output, making it unsuitable for real-time or near-real-time requirements. HDFS (D) is not a computing framework at all; it is the Hadoop Distributed File System, a storage layer used to persist data, not to process it.
Memory tip: Think "Real-time = Stream" - both correct answers contain the word "Stream" (Spark Streaming, Streaming). If it has "Stream," it's real-time; MapReduce is for massive batches, and HDFS just stores.
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