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最新的 CCDH CCD-333 免費考試真題:

1. 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.

2. In a MapReduce job, you want each of you input files processed by a single map task. How do you configure a MapReduce job so that a single map task processes each input file regardless of how many blocks the input file occupies?

A) Write a custom FileInputFormat and override the method isSplittable to always return false.
B) Set the number of mappers equal to the number of input files you want to process.
C) Increase the parameter that controls minimum split size in the job configuration.
D) Write a custom MapRunner that iterates over all key-value pairs in the entire file.

3. Does the MapReduce programming model provide a way for reducers to communicate with each other?

A) No, each reducer runs independently and in isolation.
B) Yes, reducers can communicate with each other by dispatching intermediate key value pairs that get shuffled to another reduce
C) Yes, reducers running on the same machine can communicate with each other through shared memory, but not reducers on different machines.
D) Yes, all reducers can communicate with each other by passing information through the jobconf object.

4. You need to create a GUI application to help your company's sales people add and edit customer information. Would HDFS be appropriate for this customer information file?

A) No, because HDFS can only be accessed by MapReduce applications.
B) No, because HDFS is optimized for write-once, streaming access for relatively large files.
C) Yes, because HDFS is optimized for random access writes.
D) Yes, because HDFS is optimized for fast retrieval of relatively small amounts of data.

5. To process input key-value pairs, your mapper needs to load a 512 MB data file in memory. What is the best way to accomplish this?

A) Place the data file in theDistributedCacheand read the data into memory in the configure method of the mapper.
B) Place the data file in theDistributedCacheand read the data into memory in the map method of the mapper.
C) Place the datafile in the DataCache and read the data into memory in the configure method ofthe mapper.
D) Serialize the data file, insert it in the Jobconf object, and read the data into memory in the configure method of the mapper.

問題與答案：