Ambari Cloudera

Back-end development work related to big data for more than a year, with the development of the Hadoop community, and constantly trying new things, this article focuses on the next Ambari, the new http://www.aliyun.com/zixun/aggregation/ 　　14417.html ">apache project, designed to facilitate rapid configuration and deployment of Hadoop ecosystem-related components of the environment, and provide maintenance and monitoring capabilities. As a novice, I ...

Hadoop is a large data distributed system infrastructure developed by the Apache Foundation, the earliest version of which was the 2003 original Yahoo! Doug cutting is based on Google's published academic paper. Users can easily develop and run applications that process massive amounts of data in Hadoop without knowing the underlying details of the distribution. The features of low cost, high reliability, high scalability, high efficiency and high fault tolerance make Hadoop the most popular large data analysis system, yet its HDFs and mapred ...

Today, I attended 3 keynotes,42 sessions of 8, and a lot of vendors to discuss technology, is really a big bang day. Hadoop has been around for 7 years since its inception, and this year has seen many new changes: 1, Hadoop is recognized as a set of industry data standard open source software, in a distributed environment to provide a large number of data processing capacity (Gartner). Almost all major manufacturers revolve around Hadoop development tools, Open-source software, commercial tools, and technical services. This year, large IT companies, such as ...

Top Ten Open Source technologies: Apache HBase: This large data management platform is built on Google's powerful bigtable management engine. As a database with open source, Java coding, and distributed multiple advantages, HBase was originally designed for the Hadoop platform, and this powerful data management tool is also used by Facebook to manage the vast data of the messaging platform. Apache Storm: A distributed real-time computing system for processing high-speed, large data streams. Storm for Apache Had ...

Big data has grown rapidly in all walks of life, and many organizations have been forced to look for new and creative ways to manage and control such a large amount of data, not only to manage and control data, but to analyze and tap the value to facilitate business development. Looking at big data, there have been a lot of disruptive technologies in the past few years, such as Hadoop, Mongdb, Spark, Impala, etc., and understanding these cutting-edge technologies will also help you better grasp the trend of large data development. It is true that in order to understand something, one must first understand the person concerned with the thing. So, ...

Big data has grown rapidly in all walks of life, and many organizations have been forced to look for new and creative ways to manage and control such a large amount of data, not only to manage and control data, but to analyze and tap the value to facilitate business development. Looking at big data, there have been a lot of disruptive technologies in the past few years, such as Hadoop, Mongdb, Spark, Impala, etc., and understanding these cutting-edge technologies will also help you better grasp the trend of large data development. It is true that in order to understand something, one must first understand the person concerned with the thing. So, ...

This time, we share the 13 most commonly used open source tools in the Hadoop ecosystem, including resource scheduling, stream computing, and various business-oriented scenarios. First, we look at resource management.

If you have a lot of data in your hands, then all you have to do is choose an ideal version of the Hadoop release. The old rarity, once a service for Internet empires such as Google and Yahoo, has built up a reputation for popularity and popularity and has begun to evolve into an ordinary corporate environment. There are two reasons for this: one, the larger the size of the data companies need to manage, and Hadoop is the perfect platform to accomplish this task-especially in the context of the mixed mix of traditional stale data and new unstructured data;

Big data and Hadoop are moving in a step-by-step way to bring changes to the enterprise's data management architecture. This is a gold rush, featuring franchisees, enterprise-class software vendors and cloud service vendors, each of whom wants to build a new empire on the Virgin land. Although the Open-source Apache Hadoop project itself already contains a variety of core modules-such as Hadoop Common, Hadoop Distributed File Systems (HDFS), Hadoop yarn, and Hadoop mapreduce--...

Hadoop is a large data distributed system infrastructure developed by the Apache Foundation, the earliest version of which was the 2003 original Yahoo! Dougcutting based on Google's published academic paper. Users can easily develop and run applications that process massive amounts of data in Hadoop without knowing the underlying details of the distribution. The features of low cost, high reliability, high scalability, high efficiency and high fault tolerance make Hadoop the most popular large data analysis system, yet its HDFs and mapreduc ...