map reduce program to count Frequency of particular entity in a column of a table

[#1]

We have a marketing report in form of tabular data set which schema looks like this:

event	timestamp	distinct_id	initial_referring_domain	ColumnX	ColumnY
Page Viewed	1472688038	489687	www.abc.com	Sample Data	Sample Data
Page Viewed	1472688052	118805	www.abc.com	Sample Data	Sample Data
Request Information Click	1472688056	192674	www.abc.com	Sample Data	Sample Data
Page Viewed	1472688087	204231	ww.123.com	Sample Data	Sample Data
Page Viewed	1472688161	76081	www.abc.com	Sample Data	Sample Data
Page Viewed	1472688219	186081	www.abc.com	Sample Data	Sample Data
Page Viewed	1472688236	83259	www.google.co.in	Sample Data	Sample Data
Page Viewed	1472688310	61410	www.tuv.in	Sample Data	Sample Data

We need to write a map reduce program in order to find out the highest frequency of Initial_referring source site in order to find out which website most effective ad platform.

Approach

1. Remove rows having duplicate entities in distinct_id column.
2. Count frequency of each entity in initial_referring column.
3. Publish the result of frequency of each identity.

I am able to do this problem in Hive and pig but was not able to get the correct result in MapReduce program.

Any reference or piece of similar code can help.

[#2]

@Praveen Singh

Assuming that when you say "tabular", your file is comma/tab/pipe/etc.. delimited. A simple word-count program should suffice.

A nice posting with ways to achieve this using any of Hive, Pig, R, Spark, MapReduce (java), MapReduce(Python) may be found in the below link. The page formatting is not great, but the content is informative

https://www.linkedin.com/pulse/word-count-program-using-r-spark-map-reduce-pig-hive-python-sahu

As always, if you find this post useful, don't forget to "accept" the answer.