Data Schema Diagram

One of the big data is that large data is longer than analysis, not causation. But this may be a pseudo proposition. How to infer causal relationship from related relationship is the real problem of big data. The problem, known as causal inference (causal inference), is the foundation of Apple's iphone 6 speech recognition and Google's unmanned car technology. Daniel of this field, American Academy of Engineering, Uda Pearl (Judea http://www.aliyun.com/z ...)

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 ...

Several articles in the series cover the deployment of Hadoop, distributed storage and computing systems, and Hadoop clusters, the Zookeeper cluster, and HBase distributed deployments. When the number of Hadoop clusters reaches 1000+, the cluster's own information will increase dramatically. Apache developed an open source data collection and analysis system, Chhuwa, to process Hadoop cluster data. Chukwa has several very attractive features: it has a clear architecture and is easy to deploy; it has a wide range of data types to be collected and is scalable; and ...

Large data architectures and platforms are new things and are evolving at an extraordinary rate. The business and open source development team publishes new features of its platform almost every month. Today's large data clusters will be very different from the data clusters we see in the future. Security tools to adapt to this new difficulty will also change. In the life cycle of large data, the industry is still at an early stage, but the sooner companies start coping with the security of large data, the easier it is to work. If security becomes an important requirement in the development of large data clusters, the cluster is not easily corrupted by hackers. In addition, the company can also ...

Cloud storage is a concept that extends and develops in the concept of cloud computing (Cloud Computing). Its goal is to combine application software with storage devices to transform storage devices into storage services through application software. In short, cloud storage is not storage, it's a service. This service can provide virtual storage on demand on the network, also known as data storage as a service (Storage, DaaS). The customer pays for the storage capacity that is actually required to purchase. Any reference to the amount of fixed capacity added ...

MongoDB company formerly known as 10gen, founded in 2007, in 2013 received a sum of 231 million U.S. dollars in financing, the company's market value has been increased to 1 billion U.S. dollar level, this height is well-known open source company Red Hat (founded in 1993) 20 's struggle results. High-performance, easy to expand has been the foothold of the MongoDB, while the specification of documents and interfaces to make it more popular with users, this point from the analysis of the results of Db-engines's score is not difficult to see-just 1 years, MongoDB finished the 7th ...

Uncover 10 effective tips for completing software as a service (SaaS) application in a budget on time to achieve a satisfactory return on investment. Software provided in the form of online services rather than desktop applications continues to grow exponentially. I have been involved in the development of many company SaaS projects. Based on these experiences, I have summed up 10 ...

The analysis of data is the core of large data processing. The traditional data analysis is mainly aimed at the structured data, and the general process is as follows: firstly, the database is used to store the structured data, then the Data Warehouse is constructed, and then the corresponding cubes are constructed and the on-line analysis is processed according to the need. This process is very efficient when dealing with relatively small structured data. However, for large data, the analysis technology faces 3 intuitive problems: large-capacity data, multi-format data and analysis speed, which makes the standard storage technology can not store large data, so it is necessary to introduce a more reasonable analysis platform for large data analysis. Eyes ...

& http: //www.aliyun.com/zixun/aggregation/37954.html "> The ApacheSqoop (SQL-to-Hadoop) project is designed to facilitate efficient big data exchange between RDBMS and Hadoop. Users can access Sqoop's With help, it is easy to import data from relational databases into Hadoop and its related systems (such as HBase and Hive); at the same time ...

Two years ago OpenStack based on the NASA Nova project and the Rackspace Swift Project merger, OpenStack has become a new star in the Cloud computing field, following the release of the Essex version in April 2012, At the end of September this year OpenStack 6th edition Folsom officially released, this article briefly analyzes the OpenStack Folsom architecture. Folsom Logical structure diagram Object Store Swift structure is distributed so that you can ...