Mastering MapReduce Queries: Sorting Values in Multistep Jobs

Table of Contents

1. Introduction
2. Problem Statement
3. Data Set
4. Coding Logic
5. Mapping Games
6. Reducing Sales
7. Sorting the Values
8. Selecting the Top Five Games
9. Multi-step Job in Python
10. Conclusion

Introduction

Welcome back to the Big Data tutorial on Data Fanatics! In today's tutorial, we will be exploring how to define a multi-step job and sort values. Specifically, we will focus on finding the top 5 games with the best global sales using a given dataset.

Problem Statement

Our task is to analyze the "Video Game Sales and Ratings" dataset and calculate the total global sales for each game. After obtaining these values, we will then select the top five games Based on their global sales.

Data Set

To complete this analysis, we will be using the "Video Game Sales and Ratings" dataset. This dataset contains information on various games, including their names, platforms, and global sales.

Coding Logic

To solve this problem, we will follow a step-by-step approach. First, we will map the games by extracting the game name and global sales. Then, we will reduce the sales by summing them for each game. Next, we will sort the values in descending order based on the sum of global sales. Finally, we will select the top five games with the highest global sales.

Mapping Games

In this step, we will map the games by extracting the game name and global sales from the dataset. We will split the lines and store them in a temporary variable. The index value for the game name is 0, and the index value for the global sales is 9. We will yield the game name and global sales as key-value pairs.

Reducing Sales

Once we have mapped the games, we will reduce the sales by summing them for each game. Instead of using the key and sum approach, we will Create pairs of the value and key. This helps us in sorting the values later. We will sort the pairs in ascending order using the sorted function, with the reverse parameter set to True to get the values in descending order. Finally, we will yield the sorted pairs.

Sorting the Values

To sort the values, we will use the sorted function. By default, it sorts the values in ascending order, but since we want the best sales (top sales), we will set the reverse parameter to True to get the values in descending order.

Selecting the Top Five Games

In this step, we will select the top five games from the sorted pairs obtained in the previous step. We will iterate through the sorted pairs and yield only the first five pairs.

Multi-step Job in Python

To inform Python that this is a multi-step job, we need to import the mr_step library. We will define a steps function that returns the different steps. In the steps function, we return a list containing the mapper and reducer for each step. We specify the mapper and reducer functions using self to indicate they are from the Current class. Finally, we run the job and observe the results.

Conclusion

In this tutorial, we learned how to define a multi-step job and sort values using the MRJob library in Python. We applied this knowledge to find the top 5 games with the best global sales in a given dataset. By mapping the games, reducing the sales, sorting the values, and selecting the top five games, we obtained the desired results.

Now, let's move forward and Delve deeper into each step to better understand the process.