Enterprise Tag

contrailscience.com_skitch_skitched_20130315_131709 One of the projects that I'm currently working on is developing a solution whereby millions of rows per hour are streamed real-time into Google BigQuery. This data is then available for immediate analysis by the business. The business likes this. It's an extremely interesting, yet challenging project. And we are always looking for ways of improving our streaming infrastructure. As I explained in a previous blog post, the data/rows that we stream to BigQuery are ad-impressions, which are generated by an ad-server (Google DFP). This was a great accomplishment in its own right, especially after optimising our architecture and adding Redis into the mix. Using Redis added robustness, and stability to our infrastructure.  But – there is always a but – we still need to denormalise the data before analysing it. In this blog post I'll talk about how you can use Google Cloud Pub/Sub to denormalize your data in real-time before performing analysis on it.

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“In our (admittedly limited) experience, Redis is so fast that the slowest part of a cache lookup is the time spent reading and writing bytes to the network” - stackoverflow.com

Can Databases Be Exciting To Work With?

It’s very rare that a project can cause an engineer to get excited about the prospect of working with a database they've never worked with previously, especially when it’s a relational one. That mainly boils down to the fact that the majority of them are clunky monstrosities that are painfully slow and cause us to grimace at the thought of having to integrate them into our applications, not to mention having to piece together gnarly and over engineered SQL statements.