You are developing a combiner that takes as input Text keys, IntWritable values, and emits Text keys, IntWritable values. Which interface should your class implement?
A. Combiner
B. Mapper
C. Reducer
D. Reducer
E. Combiner
How are keys and values presented and passed to the reducers during a standard sort and shuffle phase of MapReduce?
A. Keys are presented to reducer in sorted order; values for a given key are not sorted.
B. Keys are presented to reducer in sorted order; values for a given key are sorted in ascending order.
C. Keys are presented to a reducer in random order; values for a given key are not sorted.
D. Keys are presented to a reducer in random order; values for a given key are sorted in ascending order.
Assuming default settings, which best describes the order of data provided to a reducer's reduce method:
A. The keys given to a reducer aren't in a predictable order, but the values associated with those keys always are.
B. Both the keys and values passed to a reducer always appear in sorted order.
C. Neither keys nor values are in any predictable order.
D. The keys given to a reducer are in sorted order but the values associated with each key are in no predictable order
You wrote a map function that throws a runtime exception when it encounters a control character in input data. The input supplied to your mapper contains twelve such characters totals, spread across five file splits. The first four file splits each have two control characters and the last split has four control characters.
Indentify the number of failed task attempts you can expect when you run the job with mapred.max.map.attempts set to 4:
A. You will have forty-eight failed task attempts
B. You will have seventeen failed task attempts
C. You will have five failed task attempts
D. You will have twelve failed task attempts
E. You will have twenty failed task attempts
You have just executed a MapReduce job. Where is intermediate data written to after being emitted from the Mapper's map method?
A. Intermediate data in streamed across the network from Mapper to the Reduce and is never written to disk.
B. Into in-memory buffers on the TaskTracker node running the Mapper that spill over and are written into HDFS.
C. Into in-memory buffers that spill over to the local file system of the TaskTracker node running the Mapper.
D. Into in-memory buffers that spill over to the local file system (outside HDFS) of the TaskTracker node running the Reducer
E. Into in-memory buffers on the TaskTracker node running the Reducer that spill over and are written into HDFS.
You have the following key-value pairs as output from your Map task:
(the, 1) (fox, 1) (faster, 1) (than, 1) (the, 1) (dog, 1)
How many keys will be passed to the Reducer's reduce method?
A. Six
B. Five
C. Four
D. Two
E. One
F. Three
What data does a Reducer reduce method process?
A. All the data in a single input file.
B. All data produced by a single mapper.
C. All data for a given key, regardless of which mapper(s) produced it.
D. All data for a given value, regardless of which mapper(s) produced it.
All keys used for intermediate output from mappers must:
A. Implement a splittable compression algorithm.
B. Be a subclass of FileInputFormat.
C. Implement WritableComparable.
D. Override isSplitable.
E. Implement a comparator for speedy sorting.
You use the hadoop fs put command to write a 300 MB file using and HDFS block size of 64 MB. Just after this command has finished writing 200 MB of this file, what would another user see when trying to access this life?
A. They would see Hadoop throw an ConcurrentFileAccessException when they try to access this file.
B. They would see the current state of the file, up to the last bit written by the command.
C. They would see the current of the file through the last completed block.
D. They would see no content until the whole file written and closed.
You write MapReduce job to process 100 files in HDFS. Your MapReduce algorithm uses TextInputFormat: the mapper applies a regular expression over input values and emits key- values pairs with the key consisting of the matching text, and the value containing the filename and byte offset. Determine the difference between setting the number of reduces to one and settings the number of reducers to zero.
A. There is no difference in output between the two settings.
B. With zero reducers, no reducer runs and the job throws an exception. With one reducer, instances of matching patterns are stored in a single file on HDFS.
C. With zero reducers, all instances of matching patterns are gathered together in one file on HDFS. With one reducer, instances of matching patterns are stored in multiple files on HDFS.
D. With zero reducers, instances of matching patterns are stored in multiple files on HDFS. With one reducer, all instances of matching patterns are gathered together in one file on HDFS.
