Generate Database Schema Sql Server

1.1: Increase the secondary data file from SQL SERVER 2005, the database does not default to generate NDF data files, generally have a main data file (MDF) is enough, but some large databases, because of information, and query frequently, so in order to improve the speed of query, You can store some of the records in a table or some of the tables in a different data file. Because the CPU and memory speed is much larger than the hard disk read and write speed, so you can put different data files on different physical hard drive, so that the execution of the query, ...

After more than eight years of practice, from Taobao's collection business to today to support all of Alipay's core business, and in the annual "Double Eleven Singles Day" continue to create a world record for the transaction database peak processing capacity.

Social media, E-commerce, mobile communications, and machine-machine data exchange make terabytes or even petabytes of data that the enterprise IT department must store and process.   Mastering fragmentation best practices is a very important step in the cloud planning process when users process data for cloud computing databases. Fragmentation is the process of splitting a table into a manageable size disk file. Some highly resilient key-value data stores, such as Amazon simple DB, Google App engine ...

HBase is a distributed, column-oriented, open source database based on Google's article "Bigtable: A Distributed Storage System for Structured Data" by Fay Chang. Just as Bigtable takes advantage of the distributed data storage provided by Google's File System, HBase provides Bigtable-like capabilities over Hadoop. HBase Implements Bigtable Papers on Columns ...

Enterprises in the process of information often use a number of systems such as enterprise resource planning (Enterprise Resource planing,erp), Customer relationship management (customers relationship MANAGEMENT,CRM), etc. The database data used by these systems are independent, which increases the difficulty of managing costs and maintenance. Private cloud and database consolidation can reduce system costs and complexity, improve flexibility and quality of service; Private cloud can be implemented for servers, storage, applications, or IT services ...

The REST service can help developers to provide services to end users with a simple and unified interface. However, in the application scenario of data analysis, some mature data analysis tools (such as Tableau, Excel, etc.) require the user to provide an ODBC data source, in which case the REST service does not meet the user's need for data usage. This article provides a detailed overview of how to develop a custom ODBC driver based on the existing rest service from an implementation perspective. The article focuses on the introduction of ODBC ...

Today, some of the most successful companies gain a strong business advantage by capturing, analyzing, and leveraging a large variety of "big data" that is fast moving. This article describes three usage models that can help you implement a flexible, efficient, large data infrastructure to gain a competitive advantage in your business. This article also describes Intel's many innovations in chips, systems, and software to help you deploy these and other large data solutions with optimal performance, cost, and energy efficiency. Big Data opportunities People often compare big data to tsunamis. Currently, the global 5 billion mobile phone users and nearly 1 billion of Facebo ...

In large data technology, Apache Hadoop and MapReduce are the most user-focused. But it's not easy to manage a Hadoop Distributed file system, or to write MapReduce tasks in Java. 　　 　　Then Apache hive may help you solve the problem. The Hive Data Warehouse tool is also a project of the Apache Foundation, one of the key components of the Hadoop ecosystem, which provides contextual query statements, i.e. hive queries ...

The appearance of MapReduce is to break through the limitations of the database. Tools such as Giraph, Hama and Impala are designed to break through the limits of MapReduce. 　　While the operation of the above scenarios is based on Hadoop, graphics, documents, columns, and other NoSQL databases are also an integral part of large data. 　　Which large data tool meets your needs? The problem is really not easy to answer in the context of the rapid growth in the number of solutions available today. Apache Hado ...

& 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 ...