Oracle Database Error Logs

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The secret of Chief engineer: How LinkedIn's big data backstage works

Editor's note: Jay Kreps, a chief engineer from LinkedIn, says that logs exist almost at the time of the computer's creation, and there is a wide range of uses in addition to distributed computing or abstract distributed computing models. In this paper, he describes the principles of the log and the use of the log as a separate service to achieve data integration, real-time data processing and distributed system design. Article content is very dry, worth learning. Here's the original: I joined the LinkedIn company at an exciting time six years ago. From that time ...

The secret of Chief engineer: How LinkedIn's big data backstage works

Editor's note: Jay Kreps, a chief engineer from LinkedIn, says that logs exist almost at the time of the computer's creation, and there is a wide range of uses in addition to distributed computing or abstract distributed computing models. In this paper, he describes the principles of the log and the use of the log as a separate service to achieve data integration, real-time data processing and distributed system design. Article content is very dry, worth learning. Here's the original: I joined the LinkedIn company at an exciting time six years ago. From that time ...

Oracletool 3.0.0 Publishing Database management tools

Oracletool is an interactive web-based Oracle database management tool that uses http://www.aliyun.com/zixun/aggregation/17117.html > Web server to run as a CGI script. This feature is based on a non-web tool that does not need to be installed on the client machine or on the database, and can be used as a Web browser once the installation is successful. Oracletool 3.0.0 This version changed ...

LinkedIn large data Platform depth analysis (i)

I joined the LinkedIn company at an exciting time six years ago. From that point on, we cracked down on a single, centralized database and started switching to a special distributed System suite. This is an exciting thing: the Distributed graphics database, the distributed search backend, the Hadoop installation, and the first and second generation key value data stores that we build, deploy, and still run until today. The most rewarding thing we've learned from all of this is that the core of many of the things we build contains a simple idea: log. Sometimes ...

LinkedIn large data Platform depth analysis (i)

I joined the LinkedIn company at an exciting time six years ago. From that point on, we cracked down on a single, centralized database and started switching to a special distributed System suite. This is an exciting thing: the Distributed graphics database, the distributed search backend, the Hadoop installation, and the first and second generation key value data stores that we build, deploy, and still run until today. The most rewarding thing we've learned from all of this is that the core of many of the things we build contains a simple idea: log. Sometimes ...

On several databases used in the work

Several years of work down, also used several kinds of database, accurate point is "database management system", relational database, there are nosql. Relational database: 1.MySQL: Open source, high performance, low cost, high reliability (these features tend to make him the preferred database for many companies and projects), for a large scale Web application, we are familiar with such as Wikipedia, Google, and Facebook are the use of MySQL. But the current Oracle takeover of MySQL may give us the prospect of using MySQL for free ...

The framework and characteristics of IBM SPSS analytical Decision Management cluster environment

This article describes in detail how to deploy and configure ibm®spss®collaboration and deployment Services in a clustered environment. Ibm®spss®collaboration and Deployment Services Repository can be deployed not only on a stand-alone environment, but also on the cluster's application server, where the same is deployed on each application server in a clustered environment.

Translating large data into large value practical strategies

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 ...

Cloud Man Technology CEO Wu Zhuhua: Opportunity and challenge of real-time and large-data processing

In "2013 Zhongguancun Big Data Day" Big Data Wisdom City Forum, cloud Human Science and Technology CEO Wu Zhuhua brings to the theme "about intelligent city thinking-real-time large data processing opportunities and challenges" speech. He believes that the opportunities for large data in various industries are as follows: Financial securities (high-frequency transactions, quantitative transactions), telecommunications services (support systems, unified tents, business intelligence), Energy (Power plant power grid Monitoring, information collection and analysis of electricity), Internet and electricity business (user behavior analysis, commodity model analysis, credit analysis), other industries such as Intelligent city, Internet of things. Wu Zhuhua ...

Hadoop technology in telecom operators Internet log processing application architecture

Hadoop technology in telecom operators online log processing application architecture Fang Jianguo First, the telecom operators Internet log processing status Today, so popular in the mobile Internet, every day will produce a lot of Internet log, these Internet log due to the huge amount of data generated Can only be retained for 3 days, because of storage space and other reasons are discarded. At present, telecom operators may only have a lot of useful information on customer behavior missing from the analysis of customer behavior mainly based on CDRs (call logs). For example, two people with similar phone conversations may be completely different types of customers ...

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