Describe the Nature and Use of MapReduce and Apache Hadoop DATA-SCIENCE-FOUNDATIONS Practice Questions (Page 2)

Questions 6–10

1. 6application · medium

   A company stores 10 TB of log files in HDFS for batch analysis. They want to ensure that if a few machines fail, the data remains available. Which HDFS feature directly provides this protection?

   • ANameNode's metadata caching.
   • BYARN's resource scheduling.
   • CMapReduce's speculative execution.
   • DBlock replication across DataNodes.
   Reveal Solution Discussion Select an answer first
2. 7application · medium

   A company stores sensor data in HDFS. The data is written once and read many times for analysis. Which HDFS characteristic is most important for this workload?

   • AHigh write throughput for frequent updates.
   • BHigh throughput streaming reads of large files.
   • CIn-memory caching of all data.
   • DLow-latency random access to individual records.
   Reveal Solution Discussion Select an answer first
4. 8application · medium

   A company runs a MapReduce job to count the number of times each IP address appears in a web server log. The mapper emits (IP, 1). The job produces correct counts, but the output is not sorted by IP. What is the most likely reason?

   • AThe input split size is too large.
   • BThe mapper is not emitting IP as the key.
   • CThe job uses multiple reducers, and the output from each reducer is not globally sorted.
   • DThe reducer is not summing the counts.
   Reveal Solution Discussion Select an answer first
5. 9expert · medium

   A Hadoop cluster is used for both batch processing and interactive SQL queries. The batch jobs are long-running and consume most of the cluster's resources, causing the interactive queries to time out. The administrator wants to ensure that interactive queries get resources promptly. Which approach is most effective?

   • ADisable speculative execution.
   • BRun all jobs in a single queue.
   • CIncrease the replication factor for interactive data.
   • DUse YARN capacity scheduler with separate queues for batch and interactive workloads.
   Reveal Solution Discussion Select an answer first
6. 10foundation · easy

   In a MapReduce job, what is the correct order of the data flow phases?

   • AInput splitting → Shuffle and sort → Map → Reduce → Output
   • BMap → Input splitting → Reduce → Shuffle and sort → Output
   • CInput splitting → Map → Shuffle and sort → Reduce → Output
   • DInput splitting → Map → Reduce → Shuffle and sort → Output
   Reveal Solution Discussion Select an answer first