CCD-410 試験問題を無料オンラインアクセス

In a MapReduce job with 500 map tasks, how many map task attempts will there be?

• A.At least 500.
• B.At most 500.
• C.It depends on the number of reduces in the job.
• D.Exactly 500.
• E.Between 500 and 1000.

In a MapReduce job, the reducer receives all values associated with same key. Which statement best describes the ordering of these values?

• A.The values are arbitrary ordered, but multiple runs of the same MapReduce job will always have the same ordering.
• B.The values are in sorted order.
• C.Since the values come from mapper outputs, the reducers will receive contiguous sections of sorted values.
• D.The values are arbitrarily ordered, and the ordering may vary from run to run of the same MapReduce job.

Table metadata in Hive is:

• A.Stored as metadata on the NameNode.
• B.Stored in ZooKeeper.
• C.Stored in the Metastore.
• D.Stored along with the data in HDFS.

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.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.
• B.There is no difference in output between the two settings.
• 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.

Which process describes the lifecycle of a Mapper?

• A.The TaskTracker spawns a new Mapper to process each key-value pair.
• B.The JobTracker spawns a new Mapper to process all records in a single file.
• C.The JobTracker calls the TaskTracker's configure () method, then its map () method and finally its close () method.
• D.The TaskTracker spawns a new Mapper to process all records in a single input split.