Chapter 9.9, Problem 9.6ARQ

Explanation of Solution

Three V’s of Big Data:

Big data are generally large data sets, which have a data collection having huge size.

• Big data sets have the following three properties which are referred as 3V’s of Big data, they are:
  • Volume: The data sets in big data have huge volume.
  • Velocity: The data sets in big data have rapid velocity.
  • Variety: The data sets present in big data are not similar; they contain a huge variety of datasets.

General goal of Map Reduce:

• As big data are huge, fast and varied, they cannot be easily processed using traditional techniques.
• The general goal of Map Reduce is to break down big data sets into smaller data sets and process them separately.
• The steps involved are:
  • Break down the big data sets into smaller sets.
  • Through these split up data, independently running parallel processors are searched.
  • The results are integrated and combined.

Use of Map Reduce for figure 9-24:

Figure 9-24(present in the textbook) compares the search trends for the terms Web2.0 and Hadoop.

Map Reduce can be implemented in the following steps:

• Map Phase:
  • The data set having logs of Google searches is broken down and the independent processors are instructed to search for and count keywords that begin with W and H.
  • Each of the log segments are mapped into independent processors are words are arranged alphabetically...