[Solved] Consider this Hadoop code snippet to read small files and combine them into a SequenceFile format: from pydoop import hdfs with hdfs.open('/input/file1') as f1, hdfs.open('/input/file2') as f2:... | Hadoop

Hadoop - Performance Tuning

Consider this Hadoop code snippet to read small files and combine them into a SequenceFile format:

from pydoop import hdfs
with hdfs.open('/input/file1') as f1, hdfs.open('/input/file2') as f2:
    data1 = f1.read()
    data2 = f2.read()
# Combine data1 and data2 into a SequenceFile here

What is the main benefit of using SequenceFile for small files?

AIt compresses files but slows down reading

BIt merges small files into a single large file improving read efficiency

CIt splits large files into smaller chunks automatically

DIt encrypts files for security

Step-by-Step Solution

Solution:

Step 1: Understand SequenceFile purpose
SequenceFile is a Hadoop file format that stores data as key-value pairs and merges many small files into one large file.
Step 2: Identify benefit for small files
Merging small files into a SequenceFile reduces overhead and improves read performance in Hadoop jobs.
Final Answer:
It merges small files into a single large file improving read efficiency -> Option B
Quick Check:
SequenceFile merges small files for faster reading [OK]

Quick Trick: SequenceFile merges small files to speed up Hadoop reads [OK]

Common Mistakes:

Thinking SequenceFile splits files
Assuming it only compresses without merging
Confusing encryption with file format

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More Hadoop Quizzes

Consider this Hadoop code snippet to read small files and combine them into a SequenceFile format:

Step 1: Understand SequenceFile purpose

Step 2: Identify benefit for small files

Final Answer:

Quick Check:

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