Which of the following scenario may not be a good fit for HDFS in Big Data…

Concept: HDFS (Hadoop Distributed File System) follows a Write-Once, Read-Many (WORM) model: a file supports only a single active writer at a time, and once written it is not open to arbitrary in-place modification (only controlled append/truncate operations are supported). HDFS is engineered for high-throughput, sequential access to very large files, not for low-latency or frequently-updated access patterns.

Application: Checking each offered scenario against this design:

• The multiple/simultaneous-writers scenario — not supported; HDFS allows only a single writer per file at a time, and this option is phrased as an explicit mismatch statement ("HDFS is not suitable for..."), which is exactly what the question is asking for.

• The low-latency-access scenario — HDFS genuinely does not prioritize this (it favours throughput over latency), so the claim that HDFS 'is suitable' for low-latency access is itself inaccurate. But this option is phrased as a suitability claim, not as a stated mismatch, so it does not directly answer 'which scenario is described as not a good fit' the way the multiple-writers option does.

• The high-latency, batch/streaming-access scenario — this matches HDFS's actual design goal, so the claim of suitability here is accurate; it describes a genuine fit, not a mismatch.

• 'None of the above' does not apply, since one of the scenarios above is both a real limitation and explicitly phrased as one.

Cross-check: This matches the Apache Hadoop HDFS design documentation, which confirms HDFS files support exactly one writer at a time and that the system favours high throughput over low latency. Among the four scenarios offered, only the multiple-simultaneous-writers scenario is both a genuine limitation and explicitly phrased as a mismatch, making it the answer to which scenario is not a good fit for HDFS.