In this post, engineers from Wargaming.net, the online game developer and publisher, describe the design of their real-time recommendation engine built on CDH.
The scope of activities at Wargaming.net extends far beyond the development of games. We work on dozens of internal projects simultaneously, and our Data-driven Real-time Rules Engine (DDRRE) is among the most ambitious.
DDRRE is a system that analyzes large amounts of data in real time,
Recently, GoDataDriven installed a Cloudera cluster on Microsoft Azure. This two-part blog post, written by Alexander Bij and Tünde Alkemade and republished with permission, provides information about use case, implemented design, installation.
In the first post we discussed some information about the use case, the design and some basic information about Microsoft Azure. We showed some options how you can install Cloudera on Azure and what best practices we saw when installing a distributed system on Azure.
In this guest post, Deenar Toraskar, founder of risk-analytics solution provider Think Reactive and a contributor to Spark, describes why new requirements for agile, self-service, and VaR reporting help make the case for building out new analytic infrastructure on the Apache Hadoop ecosystem.
As described previously in this post, Value at Risk (VaR) is a popular risk measure used for risk management,
Thanks to Jonathan Natkins, a field engineer from StreamSets, for the guest post below about using StreamSets Data Collector—open source, GUI-driven ingest technology for developing and operating data pipelines with a minimum of code—and Cloudera Search and HUE to build a real-time search environment.
As pressure mounts on data engineers to deliver more data from more sources in less time, StreamSets Data Collector can serve as a linchpin in the data management process,
Recently, GoDataDriven installed a Cloudera Enterprise (CDH + Cloudera Manager) cluster on Microsoft Azure. This two-part series, written by Alexander Bij and Tünde Alkemade and republished with permission, includes information about use case, design, and installation.
Processing large amounts of unstructured data requires serious computing power and also maintenance effort. As load on computing power typically fluctuates due to time and seasonal influences and/or processes running on certain times,