Today we’ll be looking at sorting and reducing an array of a complex data type. I’m using Databricks to do Spark, but I’m sure the code is compatible. I’ll be using Spark SQL to show the steps. I’ve tried to keep the data as simple as possible. The example should apply to scenarios that are more complex.
Last week we had some problems with the Google Ads bot. It was not able to crawl a bunch of URLs while the browser had no problem getting through. The only difference was the User-Agent. This send us on a debugging journey through Cloudflare, gateways and micro-sites. To assist us, we’ve created a small bash script to visit an URL and show some debug info.
At Wehkamp we use AWS Lambda to classify images on S3. The Lambda is triggered when a new image is uploaded to the S3 bucket. Currently we have over 6.400.000 images in the bucket. Now we would like to run the Lambda for all images of the bucket. In this blog I’ll show how we did this with a Python 3.6 script.
At Wehkamp we’ve been using machine learning for a while now. We’re training models in Databricks (Spark) and Keras. This produces a Keras file that we use to make the actual predictions. Training is one thing, but getting them to production is quite another!
The main problem we’ve faced was that it was too big to actually fit into a lambda. This blogs shows how we’ve dealt with that problem.
We live in a day and age in which we can choose a data-store that matches the characteristics of our apps and (micro) services. Lately we’ve been looking into Redis as a high performing store for last viewed items. In this blog I’ll look show how to create a POC with the redis-cli and then implement it using .NET Core. We’ll be using the sorted set structure.
What’s the buzz all about? Well, originally it started out as a small children’s game, but now and again I see it being used to detect weak developers in job interviews (I think there are better ways to do this). The assignment has a view nice properties. In this blog I would like to look at some implementations and discuss the pro’s and con’s of each implementation.
I love how we can use appsettings.json files to configure applications in the .NET Core platform. The JSON-format feels a lot less bloated than the old XML appSettings config I used to work with. In this blog I’ll explore how to load a dictionary-style settings class as an IOption. This can be very useful when working with dependency injection.