Cloudera Certified Developer for Apache Hadoop (CCDH) 認定 CCD-410 試験問題:

1. What data does a Reducer reduce method process?

A) All data for a given key, regardless of which mapper(s) produced it.
B) All data produced by a single mapper.
C) All data for a given value, regardless of which mapper(s) produced it.
D) All the data in a single input file.

2. Determine which best describes when the reduce method is first called in a MapReduce job?

A) Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. The reduce method is called as soon as the intermediate key-value pairs start to arrive.
B) Reduce methods and map methods all start at the beginning of a job, in order to provide optimal performance for map-only or reduce-only jobs.
C) Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. The programmer can configure in the job what percentage of the intermediate data should arrive before the reduce method begins.
D) Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. The reduce method is called only after all intermediate data has been copied and sorted.

3. Which best describes what the map method accepts and emits?

A) It accepts a single key-value pairs as input and can emit any number of key-value pair as output, including zero.
B) It accepts a list key-value pairs as input and can emit only one key-value pair as output.
C) It accepts a single key-value pair as input and emits a single key and list of corresponding values as output.
D) It accepts a single key-value pairs as input and can emit only one key-value pair as output.

4. You have user profile records in your OLPT database, that you want to join with web logs you have already ingested into the Hadoop file system. How will you obtain these user records?

A) HDFS command
B) Hive LOAD DATA command
C) Ingest with Flume agents
D) Sqoop import
E) Pig LOAD command
F) Ingest with Hadoop Streaming

5. What is the disadvantage of using multiple reducers with the default HashPartitioner and distributing your workload across you cluster?

A) There are no concerns with this approach. It is always advisable to use multiple reduces.
B) You will longer be able to take advantage of a Combiner.
C) By using multiple reducers with the default HashPartitioner, output files may not be in globally sorted order.
D) You will not be able to compress the intermediate data.

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