Ken RimplePodcast: Play in new window | Download (Duration: 26:38 — 30.5MB) | Embed
Ken and Joel wrap up the year with a bit of conversation about smart watches, whether you’re a user of tools or conversationalist with your code, and a number of other little ditties.
If you’re used to writing jQuery scripts and trying them from your browser, you’ll probably be surprised to know that over the past few years, tools have cropped up to make the old browser language more enterpris-ey. This multi-part tutorial series shows you how the world of Javascript tooling has invaded and provided ways to handle dependency management, build processing, and application assembly in a whole new way.
Podcast: Play in new window | Download (Duration: 18:32 — 21.2MB) | Embed
This week we give you some light viewing for the week – a Letterman interview circa 1983 or so with the famous Rear Admiral Grace Hopper, and a really interesting demonstration by recently passed Douglas Englebart (search him above to find other DevNews articles on him) dubbed the Mother of all Demos (1968). Super cool stuff. Also, we discuss a nice little SQL tutorial website for PostgreSQL, the “Smartest Person in the Room complex”, our new Data I/O screencasts, and a few blog entries from Chariot’s developers.
Podcast: Play in new window | Download (Duration: 59:47 — 137.9MB) | Embed
In this talk, Hive and Cassandra author (and Hive committer and PMC member) Edward Capriolo will discuss common big-data software challenges and how they can be solved using both batch and stream processing. Technology focus will primarily be on Apache Kafka for publish-subscribe messaging, Storm for stream processing, and Apache Cassandra as a NoSQL data store.
We’ve been detained… Sorry to all of our fans out there, we’ve been unavoidably detained by the MCP from Tron until Friday. We’ll have a show then, and we’ll be off for a week over the Christmas Break, to return on the following Monday. Ken Rimple
Podcast: Play in new window | Download (Duration: 32:10 — 105.0MB) | Embed
As Mahout rolls towards a 1.0 release, Mahout committer and co-founder Grant Ingersoll, will provide an overview of what’s happening with the machine learning project and what to look forward to next.
Podcast: Play in new window | Download (Duration: 44:57 — 94.0MB) | Embed
Predictive modeling is one of the figureheads of big data. Machine Learning Theory asserts that the more data the better, and empirical observations suggest that the more granular data, the better the performance (provided you have modern algorithms and big data) but the paradox of predictive modeling is that when you need models the most, even all the data is not enough.
Podcast: Play in new window | Download (Duration: 55:18 — 143.1MB) | Embed
Vert.x is an asynchronous, event-driven application platform similar in style to Node.js, except it runs on the JVM. It supports several JVM languages, including Javascript, and uses a multi-reactor event loop to handle a very high number of concurrent connections. Learn about it in this screencast from Data I/O 2013.
Podcast: Play in new window | Download (Duration: 57:36 — 200.3MB) | Embed
This talk will address valuable lessons learned with the current versions of HBase. There are inherent architectural features that warrant for careful evaluation of the data schema and how to scale out a cluster. The audience will get a best practices summary of where there are limitations in the design of HBase and how to avoid those. In particular, we will discuss issues like proper memory tuning (for reads and writes), optimal flush file sizing, compaction tuning, and the number of write ahead logs required. Further, there is a discussion of the theoretical write performance, in comparison to those observed on real clusters. A collection of cheat sheets and example calculation for cluster sizing rounds out the talk towards the end.
Podcast: Play in new window | Download (Duration: 53:02 — 142.2MB) | Embed
Is Amazon’s new managed, lower cost, petabyte scale warehousing solution a game changer? We’ll review the costs and discuss what does (or does not) make Amazon Redshift reliable, scalable and effective. We’ll dive into the technical details behind the query and storage engines and we’ll expose what works well and what does not. This talk should benefit both those that are and are not already part of the Amazon Web Services ecosystem.