How To Create A Data Warehouse In Mysql

When it comes to big data, it has to do with Alibaba. The world's leading E-commerce enterprise, the amount of data processed every day is unmatched by any other company, it is also transforming into a real data company--mysql is an important weapon in the transformation of Alibaba. 　　A database architect who interviewed Ali, who believes Ali has the best performance of open source MySQL, beyond any relational database and NoSQL. In the 2009, Oracle acquired the copyright of MySQL by acquiring Sun, and the industry began to question the use of Oracle ...

Cloud computing and data warehousing are a reasonable couple. Cloud storage can be scaled on demand, and the cloud can contribute a large number of servers to a specific task. The common function of Data Warehouse is the local data analysis tool, which is limited by calculation and storage resources, and is limited by the designer's ability to consider the new data source integration. If we can overcome some of the challenges of data migration, the problem can be solved by moving a data warehouse and its data analysis tools from dedicated servers in the datacenter to cloud-based file systems and databases. Cloud data management is often involved in loading and maintaining text in Distributed File systems ...

We have all heard the following predictions: By 2020, the amount of data stored electronically in the world will reach 35ZB, which is 40 times times the world's reserves in 2009. At the end of 2010, according to IDC, global data volumes have reached 1.2 million PB, or 1.2ZB. If you burn the data on a DVD, you can stack the DVDs from the Earth to the moon and back (about 240,000 miles one way). For those who are apt to worry about the sky, such a large number may be unknown, indicating the coming of the end of the world. To ...

Big data is changing the IT world completely. So, what kind of data can be discussed? According to IDC, global data will increase 50 times times over the next decade. In 2011 alone, we will see large data creation of 1.8ZB (i.e. 1.8 trillion GB). This is equivalent to every American writing 3 tweets a minute, and still writing for 26,976 years. Over the next decade, the number of servers managing the Data warehouse will increase by 10 times times to cater for 50 times times larger data growth. There is no doubt that large data will challenge the enterprise's storage architecture and data ...

Large data will challenge the enterprise's storage architecture and data center infrastructure, and will trigger the ripple effect of cloud computing, data Warehouse, data mining, business intelligence and so on. In 2011, companies will use more TB (1TB=1000GB) Datasets for business intelligence and Business Analytics, and by 2020 global data usage is expected to rise 44 times-fold to 35.2ZB (1zb=10 billion TB). The challenges of large data for the vast number of data information, how the complex application of these data into the current data warehousing, business intelligence and data analysis technology ...

It's really tempting to get business on big Data technology, and Apache Hadoop makes the temptation more violent. Hadoop is a large scale scalable data storage platform that forms the foundation of most large data projects. Hadoop is powerful, but it requires the company to invest a lot of learning energy and other resources. If you get the right application, Hadoop can actually improve your company's business, but the application of this hadoop is fraught with thorns. On the other side, many businesses (not Google, of course) ...

It's really tempting to get business on big Data technology, and Apache Hadoop makes the temptation more violent. Hadoop is a large scale scalable data storage platform that forms the foundation of most large data projects. Hadoop is powerful, but it requires the company to invest a lot of learning energy and other resources. If you get the right application, Hadoop can actually improve your company's business, but the application of this hadoop is fraught with thorns. On the other side, many businesses (not Google, of course) ...

Hive is a http://www.aliyun.com/zixun/aggregation/8302.html "> Data Warehouse infrastructure built on Hadoop." It provides a range of tools for data extraction, transformation, and loading, a mechanism for storing, querying, and analyzing large-scale data stored in Hadoop. Hive defines a simple class SQL query language, called QL, that allows users who are familiar with SQL to query data. Act as a part of

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 ...

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 ...