Mapr (HP) Hadoop Developer Certification Questions and Answers (Dumps and Practice Questions)
Question : You have following sample Mapper class and its map() method.
public class ProjectionMapper extends Mapper
private Text word = new Text();
private LongWritable count = new LongWritable();
@Override
protected void map(LongWritable key, Text value, Context context)
throws IOException, InterruptedException {
String[] split = value.toString().split("\t+");
word.set(split[0]);
if (split.length > 2) {
try {
count.set(Long.parseLong(split[2]));
context.write(word, count);
} catch (NumberFormatException e) {
}
}
}
}
Now, select the correct statement based on above code.
1. Four arguments to the Mapper Class added in angle bracket are for Input key and value as well output key and value
2. Mapper class always use map() method
4. 1,2
5. 1,2,3
Correct Answer : Get Lastest Questions and Answer :
Explanation: The map() method is called once per input record, so it pays to avoid unnecessary object creation. The body of map() is
straightforward: It splits the
tab-separated input line into fields, and uses the first field as the word, and the third as the count. The map output is written using the write method in
Context. For simplicity, this code ignores lines with an occurrence field that is not a number, but there are other actions you could take, such as
incrementing a MapReduce counter to track how many lines it affects (see the getCounter() method on Context for details)
Question : Select correct statement regarding map() method
1. each call to map() method will produce List of key value pair for all the records in input split
2. each call to map() method will produce List of key value pair for all the records in a block of a file
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4. Both 1 and 2
Correct Answer : Get Lastest Questions and Answer :
Explanation: map method is called for each record of Input Split and each call emits the key value pair. Now sorting , suffling, merging and
partioning is a
Hadoop framework responsbility.
Question : We have reduce class example as below.
public class LongSumReducer
private LongWritable result = new LongWritable();
public void reduce(KEY key, Iterable
Context context) throws IOException, InterruptedException {
long sum = 0;
for (LongWritable val : values) {
sum += val.get();
}
result.set(sum);
context.write(key, result);
}
}
Select correct option
1. reduce methods emits final results as key and value. Both will be saved on hdfs.
2. reduce methods emits final results value and will be saved on hdfs.
4. 1,3
5. 2,3
Correct Answer : Get Lastest Questions and Answer :
Explanation: reduce() method signature is different from map() because it has an iterator over the values, rather than a single value. This
reflects the grouping that
the framework performs on the values for a key. In LongSumReducer, the implementation is very simple: It sums the values, then writes the total out using the
same key as the input.
Related Questions
Question : If a Task attempts is fail then JobTracker will wait to finish all the task and retry the failed task
1. true
2. false
Question : Mapper outputs zero or more key value pairs ?
1. True
2. False
Question : Which statement is correct for the Hadoop framework
1. Hadoop attempts that Mappers run on node which hold their portio of data locally.
2. Multiple Mappers run parallel
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4. 1 and 2 are correct
5. 1,2 and 3 are correct
Question : The Mapper may use or completely ignore the input key ?
1. True
2. False
Question : What would be the key when file is an input to the MapReduce job
1. The key is the byte offset into the file at which the line starts
2. the key is the line contents itself
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4. None of the above
Question :The Mappers output must be in the form of key value pairs
1. True
2. False