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Examine the following Hive statements:

Assuming the statements above execute successfully, which one of the following statements is true?

A. Hive reformats File1 into a structure that Hive can access and moves into to/user/joe/x/

B. The file named File1 is moved to to/user/joe/x/

C. The contents of File1 are parsed as comma-delimited rows and loaded into /user/joe/x/

D. The contents of File1 are parsed as comma-delimited rows and stored in a database

In the reducer, the MapReduce API provides you with an iterator over Writable values. What does calling the next () method return?

A. It returns a reference to a different Writable object time.

B. It returns a reference to a Writable object from an object pool.

C. It returns a reference to the same Writable object each time, but populated with different data.

D. It returns a reference to a Writable object. The API leaves unspecified whether this is a reused object or a new object.

E. It returns a reference to the same Writable object if the next value is the same as the previous value, or a new Writable object otherwise.

Which two of the following statements are true about Pig's approach toward data? Choose 2 answers

A. Accepts only data that has a key/value pair structure

B. Accepts data whether it has metadata or not

C. Accepts only data that is defined by metadata tables stored in a database

D. Accepts tab-delimited text data only

E. Accepts any data: structured or unstructured

You need to create a job that does frequency analysis on input data. You will do this by writing a Mapper that uses TextInputFormat and splits each value (a line of text from an input file) into individual characters. For each one of these characters, you will emit the character as a key and an InputWritable as the value. As this will produce proportionally more intermediate data than input data, which two resources should you expect to be bottlenecks?

A. Processor and network I/O

B. Disk I/O and network I/O

C. Processor and RAM

D. Processor and disk I/O

You want to perform analysis on a large collection of images. You want to store this data in HDFS and process it with MapReduce but you also want to give your data analysts and data scientists the ability to process the data directly from HDFS with an interpreted high- level programming language like Python. Which format should you use to store this data in HDFS?

A. SequenceFiles

B. Avro

C. JSON

D. HTML

E. XML

F. CSV