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Hadoop
Hadoop Mapreduce
Quiz 1
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Q.1
The Mapper implementation processes one line at a time via _________ method.
a) map
b) reduce
c) mapper
d) reducer
Q.2
Point out the correct statement.
a) Mapper maps input key/value pairs to a set of intermediate key/value pairs
b) Applications typically implement the Mapper and Reducer interfaces to provide the map and reduce methods
c) Mapper and Reducer interfaces form the core of the job
d) None of the mentioned
Q.3
The Hadoop MapReduce framework spawns one map task for each __________ generated by the InputFormat for the job.
a) OutputSplit
b) InputSplit
c) InputSplitStream
d) All of the mentioned
Q.4
Users can control which keys (and hence records) go to which Reducer by implementing a custom?
a) Partitioner
b) OutputSplit
c) Reporter
d) All of the mentioned
Q.5
Point out the wrong statement.
a) The Mapper outputs are sorted and then partitioned per Reducer
b) The total number of partitions is the same as the number of reduce tasks for the job
c) The intermediate, sorted outputs are always stored in a simple (key-len, key, value-len, value) format
d) None of the mentioned
Q.6
Applications can use the ____________ to report progress and set application-level status messages.
a) Partitioner
b) OutputSplit
c) Reporter
d) All of the mentioned
Q.7
The right level of parallelism for maps seems to be around _________ maps per-node.
a) 1-10
b) 10-100
c) 100-150
d) 150-200
Q.8
The number of reduces for the job is set by the user via _________
a) JobConf.setNumTasks(int)
b) JobConf.setNumReduceTasks(int)
c) JobConf.setNumMapTasks(int)
d) All of the mentioned
Q.9
The framework groups Reducer inputs by key in _________ stage.
a) sort
b) shuffle
c) reduce
d) none of the mentioned
Q.10
The output of the reduce task is typically written to the FileSystem via _____________
a) OutputCollector.collect
b) OutputCollector.get
c) OutputCollector.receive
d) OutputCollector.put
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