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Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. Your cluster has 10 DataNodes, each with a single 1 TB hard drive. You utilize all your disk capacity for HDFS, reserving none for MapReduce. You implement default replication settings. What is the storage capacity of your Hadoop cluster (assuming no compression)?

A) about 10 TB
B) about 11 TB
C) about 5 TB
D) about 3 TB

2. Which statement best describes the data path of intermediate key-value pairs (i.e., output of the mappers)?

A) Intermediate key-value pairs are written to HDFS. Reducers copy the intermediate data to the local disks of the machines running the reduce tasks.
B) Intermediate key-value pairs are written to HDFS. Reducers read the intermediate data from HDFS.
C) Intermediate key-value pairs are written to the local disks of the machines running the map tasks, and then copied to the machine running the reduce tasks.
D) Intermediate key-value pairs are written to the local disks of the machines running the map tasks, and are then copied to HDFS. Reducers read the intermediate data from HDFS.

3. 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) Yes, because HDFS is optimized for fast retrieval of relatively small amounts of data.
C) No, because HDFS is optimized for write-once, streaming access for relatively large files.
D) Yes, because HDFS is optimized for random access writes.

4. In the standard word count MapReduce algorithm, why might using a combiner reduce the overall Job running time?

A) Because combiners perform local aggregation of word counts, thereby allowing the mappers to process input data faster.
B) Because combiners perform local aggregation of word counts, thereby reducing the number of key-value pairs that need to be snuff let across the network to the reducers.
C) Because combiners perform local aggregation of word counts, thereby reducing the number of mappers that need to run.
D) Because combiners perform local aggregation of word counts, and then transfer that data to reducers without writing the intermediate data to disk.

5. 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) 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.
B) 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.
C) 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.
D) There is no difference in output between the two settings.

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