Querying Data Using Map-reduce in MongoDB
MongoDB’s Map-reduce stands strong as the number one choice for big data analytics. Learn about condensing a large volume of document data into a small set of aggregated results by creating versatile map and reduce functions in JavaScript.
What you'll learn
Working with large volumes of document data for analytics requires the power and flexibility of MongoDB’s Map-reduce feature. In this course, Querying Data Using Map-reduce in MongoDB, you’ll gain the ability to get yourself fully equipped to confidently apply the Map-reduce pattern to any data set no matter how large it could be. First, you’ll discover the requirement for Map-reduce among other aggregation capabilities of MongoDB. Next, you’ll explore how to create a custom JavaScript map function and a reduce function that are needed to perform map and reduce operations. Finally, you’ll learn how to use these custom functions to perform a Map-reduce operation on a MongoDB data set to aggregate results across documents. When you’re finished with this course, you’ll have the skills and knowledge of working with the Map-reduce function in MongoDB that will help you leverage the power of MongoDB’s aggregation feature for data crunching requirements in your next project.
Table of contents
- Version Check 0m
- Introduction 4m
- Aggregation Mechanisms in MongoDB 4m
- Demo: Creating the Database and Loading the Data 5m
- Demo: Using Single Purpose Aggregation Operations 2m
- Demo: Using the Aggregation Pipeline 4m
- Lack of Flexibility and Power for Complex Operations 3m
- The map() and reduce() Methods in JavaScript Array 2m
- Linking JS Array Map and Reduce to Document Aggregation 2m
- Summary 1m
- Introduction 1m
- Map-reduce Process Decomposed 6m
- Transform the Custom Map Function to Process a Collection of Documents 4m
- Demo: Converting the Map Function to Process a Collection of Documents 3m
- Transform the Custom Reduce Function to Further Process Results from the Map Phase 5m
- Demo: Converting the Reduce Function to Process the Documents from the Map Phase 2m
- Summary 1m
About the author
Buddhini is an EdTech Enabler/ Author / Instructor / Lecturer / Trainer and a Senior Java Engineer who is passionate about learning and exploring new technology as well as sharing her knowledge with others in the most learner friendly and effective manner. Buddhini always looks for challenging work and opportunities to learn and develop herself as well as to teach what she knows, to other technology enthusiasts. With her 19 years of experience in the IT/Software Development industry, Buddhini h... more