VR Universe Exploration With HadoopUDFs

Introduction

Welcome to the futuristic world of Virtual Reality (VR), where technology and imagination merge to create immersive experiences like never before. You are a VR Game Host, responsible for designing and maintaining captivating virtual environments that transport players to realms beyond their wildest dreams.

Your latest project is to create a VR game that simulates the vast expanse of the universe, allowing players to explore distant galaxies, uncover cosmic mysteries, and unravel the secrets of the cosmos. However, to achieve this ambitious endeavor, you need to harness the power of Big Data and leverage the capabilities of the Hadoop ecosystem.

In this lab, you will delve into the world of Hadoop User Defined Functions (UDFs), a powerful feature that allows you to extend the functionality of Hive, the data warehouse component of Hadoop. By mastering UDFs, you can create custom functions tailored to your game's unique requirements, enabling you to process and analyze astronomical data with unprecedented efficiency and accuracy.

Skills Graph

Set Up the Environment

In this step, you will set up the necessary environment to work with Hadoop and Hive. First, ensure that you have switched to the hadoop user by running the following command in your terminal:

su - hadoop

Next, navigate to the /home/hadoop directory, which will be your default working directory:

cd /home/hadoop

Create a new directory called udfs to store your User Defined Functions:

mkdir udfs
cd udfs

Create a Simple UDF

In this step, you will create a simple User Defined Function (UDF) that calculates the distance between two celestial objects based on their coordinates. This function will be essential for accurately rendering the positions and movements of celestial bodies in your VR game.

First, create a new file called DistanceCalculator.java in the udfs directory:

nano DistanceCalculator.java

Copy and paste the following code into the file:

import org.apache.hadoop.hive.ql.exec.UDF;

public class DistanceCalculator extends UDF {
    public double evaluate(double x1, double y1, double z1,
                           double x2, double y2, double z2) {
        double dx = x1 - x2;
        double dy = y1 - y2;
        double dz = z1 - z2;
        double distance = Math.sqrt(dx * dx + dy * dy + dz * dz);
        return distance;
    }
}

This Java code defines a UDF called DistanceCalculator that takes six DoubleWritable parameters representing the coordinates of two celestial objects (x1, y1, z1 and x2, y2, z2). The evaluate method calculates the Euclidean distance between the two objects and returns the result as a DoubleWritable.

Save the file and exit the text editor.

Next, compile the Java code using the following command:

javac -source 8 -target 8 -classpath /home/hadoop/hadoop/share/hadoop/common/*:/usr/local/hive/lib/* DistanceCalculator.java

This command compiles the DistanceCalculator.java file and creates a DistanceCalculator.class bytecode file.

Finally, create a JAR file containing the compiled class:

jar cf distance_calculator.jar DistanceCalculator.class

This command creates a JAR file named distance_calculator.jar containing the DistanceCalculator.class bytecode.

Register the UDF in Hive

Now that you have created the DistanceCalculator UDF, you need to register it in Hive so that you can use it to process astronomical data.

First, start the Hive shell by running the following command:

hive

Once in the Hive shell, create a temporary function using the DistanceCalculator UDF:

ADD JAR /home/hadoop/udfs/distance_calculator.jar;
CREATE TEMPORARY FUNCTION distance_calculator AS 'DistanceCalculator';

The ADD JAR command adds the JAR file containing the compiled UDF to the Hive environment, and the CREATE TEMPORARY FUNCTION command creates a temporary function called distance_calculator that references the DistanceCalculator class.

You can now use the distance_calculator function in your Hive queries. For example, let's create a sample table called celestial_objects and calculate the distance between two objects:

CREATE TABLE celestial_objects (
  name STRING,
  x DOUBLE,
  y DOUBLE,
  z DOUBLE
);

This query creates a table celestial_objects with columns for the name and coordinates of celestial objects.

INSERT INTO celestial_objects VALUES
  ('Earth', 0.0, 0.0, 0.0),
  ('Moon', 384400.0, 0.0, 0.0),
  ('Mars', 227940000.0, 0.0, 0.0);

It then inserts sample data for Earth, the Moon, and Mars.

SELECT
  o1.name AS object1,
  o2.name AS object2,
  distance_calculator(o1.x, o1.y, o1.z, o2.x, o2.y, o2.z) AS distance
FROM celestial_objects o1
CROSS JOIN celestial_objects o2
WHERE o1.name < o2.name;

Finally, it performs a cross join between all pairs of objects and calculates the distance between them using the distance_calculator UDF.

The output should look similar to:

object1 object2 distance
Earth   Moon    384400.0
Mars    Moon    2.275556E8
Earth   Moon    384400.0
...

Create a Permanent UDF

While temporary functions are useful for testing and exploration, they are lost when you exit the Hive shell. To make your UDF permanently available, you need to create a permanent function.

First, exit the Hive shell by running the following command:

quit;

Next, create a new file called create_udf.hql in the udfs directory:

nano create_udf.hql

Copy and paste the following code into the file:

CREATE FUNCTION distance_calculator AS 'DistanceCalculator' USING JAR 'hdfs:///home/hadoop/udfs/distance_calculator.jar';

This Hive query creates a permanent function called distance_calculator that references the DistanceCalculator class in the distance_calculator.jar file stored in the Hadoop Distributed File System (HDFS).

Save the file and exit the text editor.

Next, create the distance_calculator.jar file in HDFS by running the following command:

hadoop fs -mkdir -p /home/hadoop/udfs
hadoop fs -put distance_calculator.jar /home/hadoop/udfs/

This command copies the distance_calculator.jar file from the local filesystem to the /home/hadoop/udfs/ directory in HDFS.

Finally, execute the create_udf.hql script in Hive:

hive -f create_udf.hql

This command runs the Hive script, creating the permanent distance_calculator function.

You can now use the distance_calculator function in your Hive queries, even after exiting and restarting the Hive shell.

Summary

In this lab, you learned how to create and use User Defined Functions (UDFs) in Hadoop Hive, a powerful feature that allows you to extend the functionality of the data warehouse component of Hadoop. By designing a futuristic VR game that simulates the exploration of the cosmos, you gained hands-on experience in creating a custom UDF to calculate the distance between celestial objects based on their coordinates.

Through this lab, you not only mastered the process of developing, compiling, and registering UDFs in Hive but also gained valuable insights into how UDFs can be leveraged to process and analyze astronomical data with unprecedented efficiency and accuracy. The skills you acquired will be invaluable as you continue to push the boundaries of virtual reality experiences, immersing players in captivating and realistic cosmic adventures.