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Welcome to this series of blog posts which covers Redis Streams with the help of a practical example. We will use a sample application to make Twitter data available for search and query in real-time. RediSearch and Redis Streams serve as the backbone of this solution that consists of several co-operating components, each of which will we covered in a dedicated blog post.

The code is available in this GitHub repo - https://github.com/abhirockzz/redis-streams-in-action

We will continue from where we left off in the previous blog post and see how to build a monitoring app to make the overall system more robust in the face of high load or failure scenarios. This is because our very often, data processing applications either slow down (due to high data volumes) or may even crash/stop due to circumstances beyond our control. If this happens with our Tweets processing application, the messages that were assigned to a specific instance will be left unprocessed. The monitoring component covered in this blog post, checks pending Tweets (using XPENDING), claims (XCLAIM), processes (store them as HASH using HSET) and finally acknowledges them (XACK).

Welcome to this series of blog posts which covers Redis Streams with the help of a practical example. We will use a sample application to make Twitter data available for search and query in real-time. RediSearch and Redis Streams serve as the backbone of this solution that consists of several co-operating components, each of which will we covered in a dedicated blog post.

The code is available in this GitHub repo - https://github.com/abhirockzz/redis-streams-in-action

This blog post will cover a Java based Tweets processor application whose role is to pick up tweets from Redis Streams and store them (as a HASH) so that they can be queried using RediSearch (the accurate term for this is “indexing documents” in RediSearch). You will deploy the application to Azure, validate it, run a few RediSearch queries to search tweets. Finally, there is a section where we will walk through the code to understand “how things work”.

Welcome to this series of blog posts which covers Redis Streams with the help of a practical example. We will use a sample application to make Twitter data available for search and query in real-time. RediSearch and Redis Streams serve as the backbone of this solution that consists of several co-operating components, each of which will we covered in a dedicated blog post.

The code is available in this GitHub repo - https://github.com/abhirockzz/redis-streams-in-action

In this part, we look at the service which interacts with the Twitter Streaming API to consume tweets and move them on to the next part in the processing pipeline.

Welcome to this series of blog posts which covers Redis Streams with the help of a practical example. We will use a sample application to make Twitter data available for search and query in real-time. RediSearch and Redis Streams serve as the backbone of this solution that consists of several co-operating components, each of which will we covered in a dedicated blog post.

The code is available in this GitHub repo - https://github.com/abhirockzz/redis-streams-in-action

This is the first part which explores the use case, motivations and provides a high level overview of the Redis features used in the solution.