Today we are going to walk through some of the preliminary data shaping steps in data science using SQL in Postgres.
I want to work on optimizing all my queries all day long because it will definitely be worth the time and effort. That's a statement that has hopefully never been said. So when it comes to query optimizing, how should you pick your battles?
Recently I ran across grand sweeping statements that suggest containers are not ready for prime time as a vehicle for deploying your databases. The definition of "futile" is something like "serving no useful purpose; completely ineffective". See why I say this below, but in short, you probably are already, for all intents and purposes, running your database in a "container". Therefore, your resistance is futile.
As a GIS newbie, I've been trying to use local open data for my own learning projects. I've recently relocated to Tampa, Florida, and was browsing through the City of Tampa open data portal and saw that they have a Public Art map. That sounded like a cool dataset to work with but I couldn't find the data source anywhere in the portal. I reached out to the nice folks on the city's GIS team and they gave me an ArcGIS-hosted URL.
Learn how to use Kubernetes taints, pod tolerations, and node affinity for designing and deploying production PostgreSQL topologies.
When Linux detects that the system is using too much memory, it will identify processes for termination and, well, assassinate them. The OOM killer has a noble role in ensuring a system does not run out of memory, but this can lead to unintended consequences.
How can you get PostgreSQL to use FIPS 140-2 crypto? The answer, to some extent, depends on how rigorously you need to be able to prove your answer. If the proof required is more than a casual check, the process is not well documented as far as I can tell. Therefore I will attempt to address that deficiency here.
Deploy PostgreSQL clusters on Kubernetes with GitOps and the Postgres Operator!
The recent selection of Postgres as the "Database of the Year" for the third time in four years is by no means an overnight success story, but is well deserved recognition for a database decades in the making. As organizations look for the relational database of the future, Postgres is ready and waiting. We are proud to be among the leading contributors and supporters of this important movement.
Today we are going to finish up by showing how to use that stored model to make predictions on new data. By the way, I did all of the Postgres work for the entire blog series in Crunchy Bridge. I wanted to focus on the data and code and not on how to run PostgreSQL.
Crunchy Data is pleased to announce the publication of the Crunchy Data PostgreSQL Security Technical Implementation Guide (STIG) by the United States Defense Information Systems Agency (DISA). PostgreSQL was the first open source database to provide a published STIG, and Crunchy Data is proud to update and improve the STIG as PostgreSQL continues to advance and evolve.
This new guide is the result of ongoing collaboration with DISA and provides security guidance for PostgreSQL 9.6 through 12
Greetings friends! We have finally come to the point in the Postgres for Data Science series where we are not doing data preparation. Today we are going to do modeling and prediction of fire occurrence given weather parameters… IN OUR DATABASE!
There are a lot of ways to load data into a PostgreSQL/PostGIS database and it's no different with spatial data. If you're new to PostGIS, you've come to the right place. In this blog post, I'll outline a few free, open source tools you can use for your spatial data import needs.