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Cloudera CCD-333 Exam Syllabus Topics:

Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. What is the behavior of the default partitioner?

A) The default partitioner implements a round robin strategy, shuffling the key value pairs to each reducer in turn. This ensures an even partition of the key space.
B) The default partitioner computes the hash of the key and divides that value modulo the number of reducers. The result determines the reducer assigned to process the key-value pair.
C) The default partitioner assigns key value pairs to reducers based on an internal random number generator.
D) The default partitioner computes the hash of the key. Hash values between specific ranges are associated with different buckets, and each bucket is assigned to a specific reducer.
E) The default partitioner computes the hash of the value and takes the mod of that value with the number of reducers. The result determines the reducer assigned to process the key value pair.

2. In the reducer, the MapReduce API provides you with an iterator over Writable values. Calling the next () method:

A) Returns a reference to a different Writable object each time.
B) Returns a reference to the same writable object if the next value is the same as the previous value, or a new writable object otherwise.
C) Returns a reference to a Writable object. The API leaves unspecified whether this is a reused object or a new object.
D) Returns a reference to the same writable object each time, but populated with different data.
E) Returns a reference to a Writable object from an object pool.

3. You write a MapReduce job to process 100 files in HDFS. Your MapReduce algorithm uses TextInputFormat and the IdentityReducer: the mapper applies a regular expression over input values and emits key-value 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 reducers to zero.

A) There is no difference in output between the two settings.
B) With zero reducers, all instances of matching patterns are gathered together in one file on HDFS. With one reducer, instances of matching patterns stored in multiple files on HDFS.
C) 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.
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.

4. For each input key-value pair, mappers can emit:

A) As many intermediate key value pairs as desired, as long as all the keys have the same type and all the values have the same type.
B) As many intermediate key-value pairs as desired, but they cannot be of the same type as the input key-value pair.
C) One intermediate key value pair, but of the same type.
D) One intermediate key value pair, of a different type.
E) As many intermediate key-value pairs as desired. There are no restrictions on the types of those key-value pairs (i.e., they can be heterogeneous).

5. What is the standard configuration of slave nodes in a Hadoop cluster?

A) Each slave node runs a TaskTracker and a DataNode daemon.
B) Each slave node runs a TaskTracker, but only a fraction of the slave nodes run DataNode daemons.
C) Each slave node runs a DataNode daemon, but only a fraction of the slave nodes run TaskTrackers.
D) Each slave node runs a JobTracker and a DataNode daemon.
E) Each slave node either runs a TaskTracker or a DataNode daemon, but not both.

Solutions: