CrateDB, Machine Learning, and Hydroelectric Power: Part Two
A real-life example of applied machine learning to prevent critical events in a hydroelectric power plant. Part two of the series.
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Machine Learning and CrateDB, Part Three: Experiment Design & Linear Regression
In the third part of this miniseries, I show you how to predict the number of Twitter followers a user has using regression analysis.
Machine Learning and CrateDB, Part Two: Getting Started With Jupyter
In part two of this miniseries, learn how to get started with machine learning using CrateDB and Jupyter Notebook.
Machine Learning and CrateDB, Part One
Part one of a miniseries that introduces you to the fundamentals of machine learning and shows you how to get started with some hands-on coding.
On Writing Beautiful Tests
Testing and thinking about modes of failure as you design code will help you to write more robust software, which is, in turn, easier to maintain. It also makes your code easier to refactor and easier to modify.
When is a SQL Subquery 260x Faster than a Left Join?
Learn why SQL subquery performance was 260x faster than a left join when querying 4.6 millions rows of ecommerce cross-sell data in a CrateDB database.
Geolocation 101: How To Get A User's Location
Blog post on the basics of how to get a web user's location, place a pin on a map, and show them museums nearby using JavaScript.
Berlin and Geo Shapes in CrateDB
In our last blogpost about Crate's spatial and geographic features we announced the support for the geo_point data type and related operations. Since that post, we have greatly improved our geographic features...
Analyzing Germany's weather with Crate.io
A blog post about my experiments importing 236 million rows of data of the german weather service, DWD, into Crate.
Using Spring Data Crate With Your Java REST Application
In this tutorial post will demonstrate how to integrate Spring Data Crate with your Java application based on a very simple Spring Boot REST application...