Tag: Cloudera

Feed: Cloudera Engineering Blog. Author: Bikas Saha. Apache Spark is one of the most popular engines for distributed data processing on Big Data clusters. Spark jobs come in all shapes, sizes and cluster form factors. Ranging from 10’s to 1000’s of nodes and executors, seconds to hours or even days for job duration, megabytes to petabytes of data and simple data scans to complicated analytical workloads. Throw in a growing number of streaming workloads to huge body of batch and machine learning jobs — and we can see the significant amount of infrastructure expenditure on running Spark jobs. Costs that ... Read More

Feed: All - O'Reilly Media. Author: Mike Loukides. San Francisco (source: O'Reilly) Visit the O'Reilly online learning platform for presentations from the Strata Data Conference in San Francisco 2019. The Strata Data Conference in San Francisco was filled with speakers talking about opportunity. But those opportunities were balanced against risks—risks that loom large as we discover more powerful ways to apply data using machine learning and artificial intelligence. It's a necessary tension we'll need to understand as we continue on the journey into the age of data. Cloudera's merger with HortonWorks demonstrates some of the opportunities. They "drank their own ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Yoey Thamas. According to the “Future of Jobs 2018” report, it is said that with advancement in machines and artificial intelligence it is likely that these technologies will replace 75 million jobs by 2020. Data scientist remains to be one of the trending careers, and those interested in pursuing data science as a career must first have the right skill set to land a job in this field.   As more companies become data-driven, professionals skilled in data science must keep updating their skills based on the current industry’s demand. A ... Read More

Feed: Cloudera Engineering Blog. Author: Shelby Khan. This was originally published on the Fast Forward Labs blog We are excited to release Learning with Limited Labeled Data, the latest report and prototype from Cloudera Fast Forward Labs. Being able to learn with limited labeled data relaxes the stringent labeled data requirement for supervised machine learning. Our report focuses on active learning, a technique that relies on collaboration between machines and humans to label smartly. Active learning makes it possible to build applications using a small set of labeled data, and enables enterprises to leverage their large pools of unlabeled data. In ... Read More

Feed: CDH – Cloudera Engineering Blog. Author: Michael Wilson. Cloudera Altus Director helps you deploy, scale, and manage Cloudera clusters on AWS, Microsoft Azure, or Google Cloud Platform. Altus Director both enables and enforces the best practices of big data deployments and cloud infrastructure. Altus Director’s enterprise-grade features deliver a mechanism for establishing production-ready clusters in the cloud for big data workloads and applications in a simple, reliable, automated fashion. In this post, you will learn about new functionality and changes in release 6.2. Cloudera Altus Director Overview For those new to Altus Director, let’s revisit what it does. On-demand ... Read More

Feed: Cloudera Engineering Blog. Author: Romain Rigaux. Self-service exploratory analytics is one of the most common use cases we see by our customers running on Cloudera’s Data Warehouse solution. With the recent release of Cloudera 6.2, we continue to improve the end user query experience with Hue, focusing on easier SQL query troubleshooting and increased compatibility with Hive. Read on to learn more and try it out in one-click at demo.gethue.com. Easier SelfService Query Troubleshooting Hue has great assistance for finding tables in the Data Catalog and getting recommendations on how to write (better) queries with the smart autocomplete, providing ... Read More

Feed: All - O'Reilly Media. Author: Mike Olson. This is a keynote highlight from the Strata Data Conference in San Francisco 2019. Watch the full version of this keynote on the O'Reilly online learning platform. You can also see other highlights from the event. Article image: Skyscraper (source: Pixabay). Mike Olson co-founded Cloudera in 2008 and served as its CEO until 2013, when he took on his current role of chief strategy officer (CSO.) As CSO, Mike is responsible for Cloudera’s product strategy, open source leadership, engineering alignment, and direct engagement with customers. Prior to Cloudera Mike was CEO of ... Read More

Feed: All - O'Reilly Media. Author: Mac Slocum. San Francisco skyline - Strata Data Conference 2019 People from across the data world are coming together in San Francisco for the Strata Data Conference. Below you'll find links to highlights from the event. The journey to the data-driven enterprise from the edge to AI Amy O'Connor explains how Cloudera applies an "edge to AI" approach to collect, process, and analyze data. Streamlining your data assets: A strategy for the journey to AI Dinesh Nirmal shares a data asset framework that incorporates current business structures and the elements you need for an ... Read More

Feed: All - O'Reilly Media. Author: Amy O'Connor. This is a keynote highlight from the Strata Data Conference in San Francisco 2019. Watch the full version of this keynote on the O'Reilly online learning platform. You can also see other highlights from the event. Article image: Fractal (source: Pixabay). Amy O’Connor is a Big Data evangelist and Telecommunications specialist at Cloudera, the leading Big Data vendor. She advises customers globally as they introduce Big Data solutions and adopt enterprise-wide Big Data delivery capabilities. Amy was recently named by Information Management as one of the “10 Big Data Experts to Know” ... Read More

Feed: Planet big data. Author: Praveen Sripati. In one of the previous blog, we looked at Canary deployment and how it can be done with Istio (service mesh). Initially a small percent of the traffic (may be 1%) is sent to the new version and the remaining (99%) is sent to the old version. As performance metrics are met, errors are within limit for the new version then the amount of traffic to the new version is increased incrementally till all the traffic goes to the new version.We have seen how to do the same manually (again from the previous ... Read More