best database for large data

Ultra-Large system features: 1, the number of users are generally more than million, and some more than tens of millions of data, the database generally more than 1TB; First, IntroductionUltra-large systems are characterized by:1, the number of users are generally more than million, and some more than tens of millions

In Java Development, I often encounter requirements for exporting database data to excel. For example, in my project, the customer requires that all query results be exported to excel, this is easy to implement for a small amount of data (tens of thousands of records), but for a large amount of

First, IntroductionUltra-large systems are characterized by: 1, the number of users are generally more than million, and some more than tens of millions of data, the database generally more than 1TB; 2, the system must provide real-time response functions, the system needs to operate without downtime, the system requires a high availability and scalability. In or

Optimization of large database tables: Use the tered tables and the tered Index) Two-dimensional tables and two-dimensional indexes are a technology provided by oracle. The basic idea is to share several tables with the same data items that are frequently used together through data blocks). The common fields of each ta

Recently, as one of the many external vendors, the company needs to rely on a large platform system (hereinafter referred to as BIG-S) to provide some services to specific users.As a WEB application developed by an external manufacturer (hereinafter referred to as SMALL-S), it is necessary to extract the basic data from the Big-s, including the user, organization structure, code table ... Part of the field

SOURCE Link: Spark streaming: The upstart of large-scale streaming data processingSummary: Spark Streaming is the upstart of large-scale streaming data processing, which decomposes streaming calculations into a series of short batch jobs. This paper expounds the architecture and programming model of spark streaming, an

code implementation on efficiency. As shown below, the Pandas object's row count is implemented differently, and the efficiency of the operation varies greatly. While time may seem trivial, when the number of runs reaches millions, the runtime is simply not negligible: So the next few articles will be sorted out slag in the large-scale data on the practice of some of the problems encountered, the article

The log file in the SAP SQLServer database is too large.The server is a windows server 2008 R2 64-bit English version, and the database is an SQL server 2008 English version. The sap dev (SAP Test System) and its database are installed on the server. Because my colleagues copied six groups to test the system, client 6 wants to delete the group and release some di

Configuring larger memory for the database can improve database performance effectively. Because the database is running, a region is marked in memory as the data cache. Typically, when a user accesses a database, the data is firs

management model. Currently, there are three major business units: normal temperature, low temperature, and ice cream. Previously, various business departments had established their respective information systems, which were very fragmented. Even in the same business unit, due to rapid business development, many systems were constantly built, they are also separated. Therefore, Yang Xiaobo said: "This isolated system makes it difficult for the Group to grasp the operation status of each busines

Label:Reproduced in: http://www.itxuexiwang.com/a/shujukujishu/redis/2016/0216/124.html?1455853509 The partner feature on the Mint App uses a lot of in-memory database Redis, and as the volume of data grows fast, Redis expands quickly and is close to the size of a single Redis instance. A single giant Redis instance has the following disadvantages: 1. First, a machine with a