Data Schema Definition

Virtualization encounters "bottlenecks" in traditional data centers, in the process of the IT system construction, the application and storage of 1:1, 2:1, 4:1, 8:1, 12:2 and so on are the corresponding physical configuration, the static load mode can be provided to the application side of the performance, capacity is completely predictable, storage quality is guaranteed. 　　However, the lack of flexibility in this deployment, the basic use of dry manual operations, often take weeks of deployment time, easy to manage islands, and with the passage of time, storage performance is getting worse, affecting TCO. With the cloud ...

The storage system is the core infrastructure of the IT environment in the data center, and it is the final carrier of data access. Storage in cloud computing, virtualization, large data and other related technologies have undergone a huge change, block storage, file storage, object storage support for a variety of data types of reading; Centralized storage is no longer the mainstream storage architecture of data center, storage access of massive data, need extensibility, 　　Highly scalable distributed storage architecture. In the new IT development process, data center construction has entered the era of cloud computing, enterprise IT storage environment can not be simple ...

At the recent Enterprise data World Conference, participants have expressed their views on the topic of "Big Data". Karen Lopez, chief consultant from Infoadvisors, said the big numbers weren't as reliable as they seemed. Lopez said: "From the most basic question, what is the big data?" I believe that no one can really speak clearly. Lopez The Wikipedia explanation for an example, which says big numbers ...

In terms of how the organization handles data, Apache Hadoop has launched an unprecedented revolution--through free, scalable Hadoop, to create new value through new applications and extract the data from large data in a shorter period of time than in the past. The revolution is an attempt to create a Hadoop-centric data-processing model, but it also presents a challenge: How do we collaborate on the freedom of Hadoop? How do we store and process data in any format and share it with the user's wishes?

Cloud computing and large data are now hot topics, and how to combine the two together to achieve large data projects on the cloud is a new practice area. Senior data expert David Gillman, based on his own experience, lists the basic elements that need to be considered in the cloud's large data scenarios, including real-time indexing of data, free-mode search and analysis, monitoring of data, and providing real-time alerts to help users better assess and select solutions. When it comes to implementing large data projects on the cloud, David highlights three real-time elements, real-time indexing, real-time data, and real-time monitoring. Have a ...

Wave Group at the two-year "Inspur World 2014" Technology and Applications Summit, the wave of the first release of a fusion architecture strategy for the IaaS layer, "cloud computing, large data, mobile interconnection, while changing the world, but also to the data center facing new challenges." In order to adapt to the explosive growth of information processing needs, the convergence of the cloud data center will be the trend. "Software definition + hardware refactoring = Fusion architecture," said Wang Endong, executive director of Wave Group. The Fusion architecture product should first complete the hardware refactoring to truly implement the software definition. "Expected ...

Cloud computing and large data are now hot topics, and how to combine the two together to achieve large data projects on the cloud is a new practice area. Senior data expert David Gillman, based on his own experience, lists the basic elements that need to be considered in the cloud's large data scenarios, including real-time indexing of data, free-mode search and analysis, monitoring of data, and providing real-time alerts to help users better assess and select solutions. When it comes to implementing large data projects on the cloud, David highlights three real-time elements, real-time indexing, real-time data, and real-time monitoring. Have a ...

Cloud computing and large data are now hot topics, and how to combine the two together to achieve large data projects on the cloud is a new practice area. Senior data expert David Gillman, based on his own experience, lists the basic elements that need to be considered in the cloud's large data scenarios, including real-time indexing of data, free-mode search and analysis, monitoring of data, and providing real-time alerts to help users better assess and select solutions. When it comes to implementing large data projects on the cloud, David highlights three real-time elements, real-time indexing, real-time data, and real-time monitoring. Have a ...

This article is my second time reading Hadoop 0.20.2 notes, encountered many problems in the reading process, and ultimately through a variety of ways to solve most of the. 　　Hadoop the whole system is well designed, the source code is worth learning distributed students read, will be all notes one by one post, hope to facilitate reading Hadoop source code, less detours. 1 serialization core Technology The objectwritable in 0.20.2 version Hadoop supports the following types of data format serialization: Data type examples say ...

Cloud computing and large data are now hot topics, and how to combine the two together to achieve large data projects on the cloud is a new practice area. Senior data expert David Gillman, based on his own experience, lists the basic elements that need to be considered in the cloud's large data scenarios, including real-time indexing of data, free-mode search and analysis, monitoring of data, and providing real-time alerts to help users better assess and select solutions. When it comes to implementing large data projects on the cloud, David highlights three real-time elements, real-time indexing, real-time data, and real-time monitoring. Have a ...