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The Ultimate Cheat Sheet On Hadoop

Top 20 frequently asked questions to test your Hadoop knowledge given in the below Hadoop cheat sheet. Try finding your own answers and match the answers given here.




Question #1 

You have written a MapReduce job that will process 500 million input records and generate 500 million key-value pairs. The data is not uniformly distributed. Your MapReduce job will create a significant amount of intermediate data that it needs to transfer between mappers and reducers which is a potential bottleneck. A custom implementation of which of the following interfaces is most likely to reduce the amount of intermediate data transferred across the network?



A. Writable
B. WritableComparable
C. InputFormat
D. OutputFormat
E. Combiner
F. Partitioner
Ans: e




Question #2 

Where is Hive metastore stored by default ?


A. In HDFS
B. In client machine in the form of a flat file.
C. In client machine in a derby database
D. In lib directory of HADOOP_HOME, and requires HADOOP_CLASSPATH to be modified.
Ans: c




Question…

Data Analytics Key Role of NOSQL


Traditional database theory dictates that you design the data set before entering any data. A data lake, also called an enterprise data lake or enterprise data hub, turns that model on its head, says Chris Curran, principal and chief technologist in PricewaterhouseCoopers’ U.S. advisory practice. 

“It says we’ll take these data sources and dump them all into a big Hadoop repository, and we won’t try to design a data model beforehand,” he says. Instead, it provides tools for people to analyze the data, along with a high-level definition of what data exists in the lake. “People build the views into the data as they go along.

It’s a very incremental, organic model for building a large-scale database,” Curran says. On the downside, the people who use it must be highly skilled

Speed of NOSQL

Alternatives to traditional SQL-based relational databases, called NoSQL (short for “Not Only SQL”) databases, are rapidly gaining popularity as tools for use in specific kinds of analytic applications, and that momentum will continue to grow, says Curran.
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