Oracle Analyze Index

This article is for IBM system architect Mr. Wang Wenjie (valen_won@hotmail.com) in its blog park Zhiding Bowen thinking EXADATA (link original address: http://www.cnblogs.com/wenjiewang/archive/2012/10/07/ 2714406.html) mentioned some of the views on the Exadata from the technical point of view gives my personal opinion of some different, of course, I have limited level, it is inevitable that omissions or mistakes. ...

According to a report published last month by IDC (International Data Company), sales of large data technology and services are expected to grow from $3.2 billion trillion in 2010 to $16.9 billion in 2015, with an annual growth rate of 7 times times the average it market. The McKinsey Global Institute points out that data is becoming a factor in products such as physical capital and human capital. Companies that can take advantage of big data will defy the data. Data capital will be as important as brand capital. Business is already adapting to big data, and the data revolution is disrupting already-established industries and business models. No matter ...

The greatest fascination with large data is the new business value that comes from technical analysis and excavation. SQL on Hadoop is a critical direction. CSDN Cloud specifically invited Liang to write this article, to the 7 of the latest technology to do in-depth elaboration. The article is longer, but I believe there must be a harvest. December 5, 2013-6th, "application-driven architecture and technology" as the theme of the seventh session of China Large Data technology conference (DA data Marvell Conference 2013,BDTC 2013) before the meeting, ...

Through the introduction of the core Distributed File System HDFS, MapReduce processing process of the Hadoop distributed computing platform, as well as the Data Warehouse tool hive and the distributed database HBase, it covers all the technical cores of the Hadoop distributed platform. Through this stage research summary, from the internal mechanism angle detailed analysis, HDFS, MapReduce, Hbase, Hive is how to run, as well as based on the Hadoop Data Warehouse construction and the distributed database interior concrete realization. If there are deficiencies, follow-up and ...

Through the introduction of the core Distributed File System HDFS, MapReduce processing process of the Hadoop distributed computing platform, as well as the Data Warehouse tool hive and the distributed database HBase, it covers all the technical cores of the Hadoop distributed platform. Through this stage research summary, from the internal mechanism angle detailed analysis, HDFS, MapReduce, Hbase, Hive is how to run, as well as based on the Hadoop Data Warehouse construction and the distributed database interior concrete realization. If there are deficiencies, follow-up ...

This paper is an excerpt from the book "The Authoritative Guide to Hadoop", published by Tsinghua University Press, which is the author of Tom White, the School of Data Science and engineering, East China Normal University. This book begins with the origins of Hadoop, and integrates theory and practice to introduce Hadoop as an ideal tool for high-performance processing of massive datasets. The book consists of 16 chapters, 3 appendices, covering topics including: Haddoop;mapreduce;hadoop Distributed file system; Hadoop I/O, MapReduce application Open ...

1, the existence of a huge leap in the background infrastructure, data storage technology, network technology, the rapid development of the era of large data to prepare the material base. The Internet of Things is essentially more portals and nodes of data acquisition, and cloud computing fosters the business model of service and centralized construction to reduce unit computing and storage costs. The mobile internet is even more interesting: the first feature is the identity, at the right time, the right place, the right information to the right person, you need to know who your partner is, what he likes, he is now what state, no such accurate identity information, everything ...

1, the existence of a huge leap in the background infrastructure, data storage technology, network technology, the rapid development of the era of large data to prepare the material base. The Internet of Things is essentially more portals and nodes of data acquisition, and cloud computing fosters the business model of service and centralized construction to reduce unit computing and storage costs. The mobile internet is even more interesting: the first feature is the identity, at the right time, the right place, the right information to the right person, you need to know who your partner is, what he likes, he is now what state, no such accurate identity information, everything ...

Key drivers of large data growth include the dramatic growth of mobile devices and social networks, the digitization of paper-based documents and the growth of scientific data. 　　"Their archive files are growing at a high speed because they don't know what needs to be saved and which don't need to be saved," said Rob Peglar, US chief technology officer at EMC's Isilon company. Companies in various industries are investing a lot of money in big data analysis. One industry is the medical industry that analyzes patient data for diagnosis and treatment. Peglar said that in the financial services industry, data are qualitatively ...

In 2017, the double eleven refreshed the record again. The transaction created a peak of 325,000 pens/second and a peak payment of 256,000 pens/second. Such transactions and payment records will form a real-time order feed data stream, which will be imported into the active service system of the data operation platform.