Transitioning to another SQL database? This blog post is for you. Shifting from one SQL dialect to another can be a journey full of surprises. While the basic syntax (SELECT FROM WHERE) is similar, there are important differences, that will make your queries slow, fast, fail or worse: fail silently!
In this blog post I’ll guide you through the intricate pathways of databases I have come across during my work as a data scientist: Postgres, MySQL, SQLite, Hive and Presto (AWS Athena). We’ll start with a brief introduction into the databases and some differences. Then we jump into three pitfalls you have to be aware of.
You have built a great streamlit app. So far, you only ran it locally on your computer on localhost:8501. Now you would like to share your app with others, but wonder how. This blogpost introduces you to one option: Heroku. Heroku is a platform as a service that allows you to deploy your apps (not just streamlit apps, but also jvm apps, ruby apps etc.). This post will guide you through the deployment of a streamlit app on Heroku.
Search engines rely on models, which rank the matching results for a given user query. These models optimize the order of items. They learn how to rank items in a result list, therefore the name Learning-to-Rank (LTR) models.
You have kafka as your message broker up and running and you may wonder: In which format should I send my data around? Maybe the string format pops up in your mind. Why not just put all fields into a long string and separate them with a comma?
In this blogpost you will get a basic understanding about message brokers. We will look at two very popular message brokers, Kafka and RabbitMQ, and learn, how they handle messages.