Q. The Hadoop MapReduce framework spawns one map task for each __________ generated by the InputFormat for the job.

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Q. Users can control which keys (and hence records) go to which Reducer by implementing a custom?

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Q. Applications can use the ____________ to report progress and set application-level status messages.

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Q. The right level of parallelism for maps seems to be around _________ maps per-node.

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Q. The number of reduces for the job is set by the user via _________

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Q. The framework groups Reducer inputs by key in _________ stage.

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Q. The output of the reduce task is typically written to the FileSystem via _____________

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Q. Which of the following is the default Partitioner for Mapreduce?

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Q. Which of the following partitions the key space?

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Q. ____________ is a generalization of the facility provided by the MapReduce framework to collect data output by the Mapper or the Reducer.

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Q. __________ is the primary interface for a user to describe a MapReduce job to the Hadoop framework for execution.

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Q. The ___________ executes the Mapper/ Reducer task as a child process in a separate jvm.

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Q. Maximum virtual memory of the launched child-task is specified using _________

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Q. Which of the following parameter is the threshold for the accounting and serialization buffers?

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Q. ______________ is percentage of memory relative to the maximum heap size in which map outputs may be retained during the reduce.

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Q. ____________ specifies the number of segments on disk to be merged at the same time.

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Q. Map output larger than ___________ percent of the memory allocated to copying map outputs.

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Q. Jobs can enable task JVMs to be reused by specifying the job configuration _________

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Q. During the execution of a streaming job, the names of the _______ parameters are transformed.

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Q. The standard output (stdout) and error (stderr) streams of the task are read by the TaskTracker and logged to _________

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