Hadoop: Data Processing and Modelling by Garry Turkington & Tanmay Deshpande & Sandeep Karanth

Author:Garry Turkington & Tanmay Deshpande & Sandeep Karanth [Turkington, Garry]
Language: eng
Format: azw3
Publisher: Packt Publishing
Published: 2016-08-31T04:00:00+00:00

We can check the loaded data, as shown here:

hive> select * from census; OK 1 Tanmay 10000 2 Sneha 12000 3 Sakalya 14000 4 Ramesh 3000 5 Rahul 4000 6 Rajesh 18000 7 Ram 3000 Time taken: 0.052 seconds, Fetched: 7 row(s)

Let's write a UDF to segregate people based on their income group. To do so, we will need to create a maven project, and add the following dependency in it:

<dependency> <groupId>org.apache.hive</groupId> <artifactId>hive-exec</artifactId> <version>1.2.1</version> </dependency>

Here is the Java class that provides logic for the income group function. To write a UDF, we need to extend the UDF class from hive-exec jar:

packagecom.demo.hive.udfs; importorg.apache.hadoop.hive.ql.exec.UDF; importorg.apache.hadoop.io.IntWritable; importorg.apache.hadoop.io.Text; public class IncomeClassifier extends UDF { public Text evaluate(IntWritable income) { Text incomeGroup = new Text(); if (income.get() <= 5000) { incomeGroup.set("lower"); } else if (income.get() >= 5001 &&income.get() <= 15000) { incomeGroup.set("middle"); } else if (income.get() >= 15001) { incomeGroup.set("upper"); } returnincomeGroup; } }

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