Java应用日志框架 TNT4J
- 授权协议: GPL
- 开发语言: Java
- 操作系统: 跨平台
- 软件首页: https://github.com/Nastel/TNT4J
- 软件文档: https://github.com/Nastel/TNT4J
软件介绍
TNT4J是一个改进Log4J新的开源Java应用日志框架。用于应用程序活动的跟踪、相关性检查、诊断,可以跨多个应用程序,运行时,服务器,地理的位置。这个API是专门用以解决分布式,并发,多线程,多用户应用,包括活动的相关性,应用程序的状态转储,性能和用户定义的量度。
以下是它的特性:
Simple programming model to facilitate fast root-cause, log analysis
Automated timing of application activities and sub-activities (elapsed, idle time, message age)
Application state dump framework for reporting internal variables, data structures
Granular conditional logging based on application tokens, patterns, that can be shared accross applications, runtimes
Share logging context across application, thread, runtime boundaries
Inter-log correlation of log entries (correlators and tags) between multiple related applications
Intra-log correlation of related activities and sub-activities between multiple applications and threads
Event location tags such as GPS, server etc.
Message flow direction for composite applications that exchange messages (e.g. SOAP, JMS, and SQL etc.)
User defined properties such as CPU, memory logging, thread statistics per process/thread
Extensible activity, sink, error listeners for pre, post event processing
Granular context such as thread id, process id, server, application name
1. 不需要写 "logger.isDebugEnabled()"
2. can log based on filter (e.g wait time longer than certain value)
3. share logging context across apps. 调用路径信息串联起来
4. logging statistics关于日志的统计信息
计算统计
Geof H.Givens、Jennifer A.Hoeting / 王兆军、刘民千、邹长亮、杨建峰 / 人民邮电出版社 / 2009-09-01 / 59.00元
随着计算机的快速发展, 数理统计中许多涉及大计算量的有效方法也得到了广泛应用与迅猛发展, 可以说, 计算统计已是统计中一个很重要的研究方向. 本书既包含一些经典的统计计算方法, 如求解非线性方程组的牛顿方法、传统的随机模拟方法等, 又全面地介绍了近些年来发展起来的某些新方法, 如模拟退火算法、基因算法、EM算法、MCMC方法、Bootstrap方法等, 并通过某些实例, 对这些方法的应用进行......一起来看看 《计算统计》 这本书的介绍吧!
