We’re in the process of moving Radar to the new oreilly. All of the material you’re java web services up and running martin kalin pdf to finding on Radar has now moved to oreilly. New editions of Four Short Links are available at oreilly.
If you subscribe to Radar through RSS, new content is already appearing in that feed. Please drop us a line if you have questions. The top 50 Radar posts from the last 5 years Looking for something specific? You might find it in the following list of Radar’s top traffic-generating posts. Which Language Should You Learn First? Wouldn’t it be fun to build your own Google?
Comments Off on Radar has moved to oreilly. That philosophy was great, but hasn’t survived into the Web age. Unfortunately, nothing better has come along to replace it. The poster child for this blight is Evernote. I started using Evernote because it did an excellent job of solving one problem. I’d take notes at a conference or a meeting, or add someone to my phone list, and have to distribute those files by hand from my laptop to my desktop, to my tablets, to my phone, and to any and all other machines that I might use. But as time has progressed, Evernote has added many other features.
I’d rather not have, thank you. I’ve tried sharing Evernote notes with other users: they did a good job of convincing me not to use them. When I’m taking notes at a conference, the last thing I’m thinking about is selfies with the speakers. Editor’s note: This is the first post in a two-part series about the evolution of data processing, with a focus on streaming systems, unbounded data sets, and the future of big data. Streaming data processing is a big deal in big data these days, and for good reasons. Businesses crave ever more timely data, and switching to streaming is a good way to achieve lower latency. The massive, unbounded data sets that are increasingly common in modern business are more easily tamed using a system designed for such never-ending volumes of data.
Processing data as they arrive spreads workloads out more evenly over time, yielding more consistent and predictable consumption of resources. Despite this business-driven surge of interest in streaming, the majority of streaming systems in existence remain relatively immature compared to their batch brethren, which has resulted in a lot of exciting, active development in the space recently. I’m delighted by this streaming zeitgeist, to say the least. Streaming 101: This first post will cover some basic background information and clarify some terminology before diving into details about time domains and a high-level overview of common approaches to data processing, both batch and streaming. Cloud Dataflow, facilitated by a concrete example applied across a diverse set of use cases.
After that, I’ll conclude with a brief semantic comparison of existing batch and streaming systems. So, long-winded introductions out of the way, let’s get nerdy. Elasticsearch continues to grow by leaps and bounds. When it comes to actually using Elasticsearch, there are tons of metrics generated. Most of the charts in this piece group metrics either by displaying multiple metrics in one chart, or by organizing them into dashboards.
This is done to provide context for each of the metrics we’re exploring. 10 Elasticsearch metrics in one compact SPM dashboard. This dashboard image, and all images in this post, are from Sematext’s SPM Performance Monitoring tool. Now, let’s dig into each of the 10 metrics one by one and see how to interpret them. This article examines the impact of the blockchain on developers, the segmentation of blockchain applications, and the network effects factors affecting bitcoin and blockchains. The blockchain is the new database — get ready to rewrite everything The technology concept behind the blockchain is similar to that of a database, except that the way you interact with that database is different.
To my phone, which Language Should You Learn First? The segmentation of blockchain applications, and it’s difficult for operators to run distributed systems. The blockchain is the new database — let’s get nerdy. If you subscribe to Radar through RSS, one author advised a wide range of database vendors to move to Flash.