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Blog posts tagged "Big Data"

Implement an enterprise-ready data lakehouse architecture with Spark and Kyuubi

Here at Canonical we are excited to announce that we have shipped the first release of our solution for enterprise-ready data lakehouses, built on the combination of Apache Spark and Apache Kyuubi. Using our Charmed Apache Kyuubi in integration with Spark, you can deliver a robust, production-level, and open source data lakehouse . Our Ap

Accelerating data science with Apache Spark and GPUs

Apache Spark has always been very well known for distributing computation among multiple nodes using the assistance of partitions, and CPU cores have always performed processing within a single partition.  What’s less widely known is that it is possible to accelerate Spark with GPUs. Harnessing this power in the right situation brings imm

Apache Spark security: start with a solid foundation

Everyone agrees security matters – yet when it comes to big data analytics with Apache Spark, it’s not just another checkbox. Spark’s open source Java architecture introduces special security concerns that, if neglected, can quietly reveal sensitive information and interrupt vital functions. Unlike standard software, Spark design permits

Spark or Hadoop: the best choice for big data teams?

I always find the Olympics to be an unusual experience. I’m hardly an athletics fanatic, yet I can’t help but get swept up in the spirit of the competition. When the Olympics took place in Paris last summer, I suddenly began rooting for my country in sports I barely knew existed. I would spend random

Can it play Doom? Running an AI LAN party on a Spark cluster with ViZDoom

It’s all about AI these days, so I decided to try and answer the important question: can you make a Spark cluster run AI agents that play a game of Doom, in a multiplayer LAN party? Although I’m no data scientist, I was able to get this to work and I’ll show you how so

Migrating from Cloudera to a modern data hub architecture

In the early 2010s, Apache Hadoop captured the imagination of the tech community. A free and powerful open source platform, it gave users a way to process unimaginably large quantities of data, and offered a dazzling variety of tooling to suit nearly every use case – MapReduce for odd jobs like processing of text, audio

Why we built a Spark solution for Kubernetes

We’re super excited to announce that we have shipped the first release of our solution for big data – Charmed Spark. Charmed Spark packages a supported distribution of Apache Spark and optimises it for deployment to Kubernetes, which is where most of the industry is moving these days. Reimagining how to work with big data

Canonical announces supported solution for Apache Spark® on Kubernetes

17 October 2023 Today, Canonical announced the release of Charmed Spark – an advanced solution for Apache Spark® that provides everything users need to run Apache Spark on Kubernetes.  Apache Spark is suitable for use in diverse data processing applications including predictive analytics, data warehousing, machine learning data preparatio

Write a Spark big data job with ChatGPT

I’ve read and watched more than a few articles about ChatGPT in the last couple of months. It seems the large language model AI hype machine just can’t stop.  As somebody with a passion for music production, some of the more interesting things I’ve seen included a guy using ChatGPT to build a virtual effect

Charmed Spark beta release is out – try it today

The Canonical Data Fabric team is pleased to announce the first beta release of Charmed Spark, our solution for Apache Spark. Apache Spark is a free, open source software framework for developing distributed, parallel processing jobs. It’s popular with data engineers and data scientists alike when building data pipelines for both batch an

Big data security foundations in five steps

We’ve all read the headlines about spectacular data breaches and other security incidents, and the impact that they have had on the victim organisations. And in some ways there’s no place more vulnerable to attack than a big data environment like a data lake.

Apache Kafka service design for low latency and no data loss

Designing a production service environment around Apache Kafka that delivers low latency and zero-data loss at scale is non-trivial. Indeed, it’s the holy grail of messaging systems. In this blog post, I’ll outline some of the fundamental service design considerations that you’ll need to take into account in order to get your service arch

Kubernetes operators – the top 5 things to watch for

Software operators are steadily revolutionising how we deploy and run complex distributed systems. They offer the promise of low-intervention, self-driving software – ideally leading to service reliability gains and better uptime. For an introduction to Kubernetes operators, check out our introductory webinar or download our guide to Kube

Canonical Data Platform 2021 winter roundup

Canonical Data Platform: that was 2021 It’s that time of the year again: many folks are panic buying cans of windscreen de-icer spray and thermal underwear, bringing pine trees into the front room and preparing to enjoy an extended break with the family. So we thought to ourselves, what better time than now to take

SQL Server on Ubuntu Pro: bringing it all back home

Not going to lie, the Microsoft SQL Server is my all-time favourite Microsoft product. For a long time, SQL Server was only available for Windows, but not much is really sacred. So now Microsoft, in collaboration with Canonical, are distributing and supporting several flavours of SQL Server on Ubuntu Pro for Azure. I’m going to

In defence of pet servers

We all know the drill by now: modern compute infrastructure needs to be deterministic, disposable, commoditised and repeatable. We’re all farmers now, and our server estates must be treated like cattle – ready for slaughter at a moment’s notice. However, we must remember that the driver behind the new design rationale is primarily the unr

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