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

1. Table metadata in Hive is:

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

2. You need to perform statistical analysis in your MapReduce job and would like to call methods in the Apache Commons Math library, which is distributed as a 1.3 megabyte Java archive (JAR) file. Which is the best way to make this library available to your MapReducer job at runtime?

A) When submitting the job on the command line, specify the -libjars option followed by the JAR file path.
B) Package your code and the Apache Commands Math library into a zip file named JobJar.zip
C) Have your system administrator copy the JAR to all nodes in the cluster and set its location in the HADOOP_CLASSPATH environment variable before you submit your job.
D) Have your system administrator place the JAR file on a Web server accessible to all cluster nodes and then set the HTTP_JAR_URL environment variable to its location.

3. You have a directory named jobdata in HDFS that contains four files: _first.txt, second.txt, .third.txt and #data.txt. How many files will be processed by the FileInputFormat.setInputPaths () command when it's given a path object representing this directory?

A) Two, file names with a leading period or underscore are ignored
B) Four, all files will be processed
C) Three, the pound sign is an invalid character for HDFS file names
D) One, no special characters can prefix the name of an input file
E) None, the directory cannot be named jobdata

4. Can you use MapReduce to perform a relational join on two large tables sharing a key? Assume that the two tables are formatted as comma-separated files in HDFS.

A) Yes.
B) No, but it can be done with either Pig or Hive.
C) No, MapReduce cannot perform relational operations.
D) Yes, so long as both tables fit into memory.
E) Yes, but only if one of the tables fits into memory

5. For each intermediate key, each reducer task can emit:

A) One final key-value pair per value associated with the key; no restrictions on the type.
B) One final key-value pair per key; no restrictions on the type.
C) As many final key-value pairs as desired. There are no restrictions on the types of those key-value pairs (i.e., they can be heterogeneous).
D) As many final key-value pairs as desired, as long as all the keys have the same type and all the values have the same type.
E) As many final key-value pairs as desired, but they must have the same type as the intermediate key-value pairs.

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