Which of the following business applications is not suitable for Hive?

Question

Options

• AReal-time online data analysis
• BData mining (user behavior analysis, interest division, regional display)
• CData summary (number of user clicks per day/week, click ranking)
• DNon-real-time analysis (log analysis, statistical analysis)

• A
  78% (25)
• B
  3% (1)
• C
  6% (2)
• D
  13% (4)

Explanation

A (Real-time online data analysis) is the correct answer because Hive is built on top of Hadoop MapReduce, which introduces significant latency - queries typically take minutes to complete, making it fundamentally unsuitable for real-time or low-latency use cases like live dashboards or transactional systems.

Options B, C, and D are all valid Hive use cases: data mining (B) and data summary/aggregation (C) involve batch processing of large datasets where Hive's SQL-like HQL excels, and non-real-time analysis (D) like log parsing is exactly Hive's primary design target - processing massive historical datasets on a schedule rather than on-demand.

Memory tip: Think of Hive as a warehouse, not a cash register - it's great for analyzing bulk historical data in the back office, but it can't serve customers in real time at the front counter. If a question mentions "real-time," "online," or "low latency," Hive is the wrong tool; look to systems like HBase, Kafka, or Spark Streaming instead.

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