Review the technology options available for the website product recommendations use case, compare them, and choose the right technology for the modules.
- [Instructor] We now look at the technology options…we can use for the website product recommendations…use case in this video.…We start out with the real-time stream queue…used for clickstreams and recommendations.…We will use Apache Kafka as the message queue…based on the selection criteria we have explored…in our earlier use cases.…Next, we look at the recommendation engine we can use…for coming up with real-time product recommendations…based on clickstream data.…
We will use Apache Spark for doing machine learning…and coming up with recommendations…based on the clickstream model.…The recommendation service implements custom functionality.…It provides a service to combine product…and clickstream-based recommendations.…We will use a custom built recommendation service…for this use case.…We finally look at in-memory databases that can be used…to store clickstream data and current recommendations.…
In-memory databases keep data in memory…and provide excellent response times for queries.…They can only store small amounts of data though,…
There is no coding involved. Instead you will see how big data tools can help solve some of the most complex challenges for businesses that generate, store, and analyze large amounts of data. The use cases are drawn from a variety of industries, including ecommerce and IT. Instructor Kumaran Ponnambalam shows how to analyze a problem, draw an architectural outline, choose the right technologies, and finalize the solution. After each use case, he reviews related best practices for real-time streaming, predictive analytics, parallel processing, and pipeline management. Each lesson is rich in practical techniques and insights from a developer who has experienced the benefits and shortcomings of these technologies firsthand.
- Components of a big data application
- Big data app development strategies
- Use cases: fraud detection and product recommendations
- Technology options
- Designing solutions
- Best practices