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Why does Hadoop's NameNode struggle with many small files, and how does SequenceFile format internally help mitigate this?

hard📝 Conceptual Q10 of 15
Hadoop - Performance Tuning
Why does Hadoop's NameNode struggle with many small files, and how does SequenceFile format internally help mitigate this?
ANameNode compresses small files; SequenceFile decompresses them for processing
BNameNode replicates small files more; SequenceFile disables replication
CNameNode stores metadata per file; SequenceFile reduces metadata by combining files into one
DNameNode merges small files automatically; SequenceFile stores them separately
Step-by-Step Solution
Solution:
  1. Step 1: Understand NameNode metadata storage

    NameNode keeps metadata for each file, so many small files increase memory usage and overhead.
  2. Step 2: How SequenceFile helps

    SequenceFile combines many small files into one large file, reducing the number of metadata entries.
  3. Final Answer:

    NameNode stores metadata per file; SequenceFile reduces metadata by combining files into one -> Option C
  4. Quick Check:

    NameNode metadata overload reduced by SequenceFile merging [OK]
Quick Trick: SequenceFile reduces NameNode metadata by merging files [OK]
Common Mistakes:
  • Thinking NameNode compresses files
  • Assuming SequenceFile disables replication
  • Believing NameNode merges files automatically

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