Skip to main content

Custom Log4J Appenders

 1.   Definitions


1.       com.habanoz.logging. CombinedDailyAndRollingFileAppender

This appender combines functions of log4j DailyRollingFileAppender and RollingFileAppender.
Files are rotated according to max file parameter. If rolling date reaches, all indexed files are renamed to have date pattern.

Rolling Algorithm can be depicted as follows:

file.log                                                                                   (name of log file.corresponds to File param.)
if(maxFileSize) {                                                             (corresponds to MaxFileSize param.)
 file.log -> file.log.1
 file.log.1 -> file.log.2
 ..
 file.log.max-1 -> file.log.max      (max determined by MaxBackupIndex param)
}

if(date passed) {                                  (determined by DatePattern param.)
  file.log -> file.log.date
  file.log.1 -> file.log.date.1
  file.log.2 -> file.log.date.2
  ..
  file.log.max-> file.log.date.max
}


Example log4j Configuration:
log4j.appender.defaultLog=com.habanoz.logging.CombinedDailyAndRollingFileAppender
log4j.appender.defaultLog.File=catchAll.1.log
log4j.appender.defaultLog.MaxFileSize=500MB
log4j.appender.defaultLog.MaxBackupIndex=20
log4j.appender.defaultLog.DatePattern=.yyyy-MM-dd
log4j.appender.defaultLog.layout=org.apache.log4j.PatternLayout
log4j.appender.defaultLog.layout.ConversionPattern=%d{${datestamp}} [%t] [%c] %-5p %m%n



2.        com.habanoz.logging. CreationDateNamedRollingFileAppender

This appender is basically the same as RollingFileAppender. File is created with a name containing date string. If max file size is reached,
file is closed and a new file is created, having the same date pattern added to its name.

Logic can be depicted as follows:

file.date.log                                     (file comes from File param.)

if(maxFile) {                                     (maxFile comes from MaxFileSize param.)
        close file.date.log
   open new file.
}


Example log4j Configuration:
log4j.appender.defaultLog.2=com.habanoz.logging.CreationDateNamedRollingFileAppender
log4j.appender.defaultLog.2.File=catchAll.1.log
log4j.appender.defaultLog.2.MaxFileSize=500MB
log4j.appender.defaultLog.2.layout=org.apache.log4j.PatternLayout
log4j.appender.defaultLog.2.layout.ConversionPattern=%d{${datestamp}} [%t] [%c] %-5p %m%n

  
3.       com.habanoz.logging. LastAccessDateNamedRollingFileAppender

This appender is basically the same as RollingFileAppender. Logic is changed to rename files with date pattern,
instead of rotating according to maxBackUpIndex.Log file is created. If max file size is reached it is closed and renamed with creation time.

Logic can be depicted as follows:

file.log                                                    (file comes from File param.)

if(maxFile)  {                                                                       (maxFile comes from MaxFileSize param.)
        file.log -> file.YYYY-MM-dd HH-MM-ss.log                     (last-access time is used.)
        open new file.
}

Example log4j Configuration:
log4j.appender.defaultLog.3=com.habanoz.logging.LastAccessDateNamedRollingFileAppender
log4j.appender.defaultLog.3.File=catchAll.3.log
log4j.appender.defaultLog.3.MaxFileSize=500MB
log4j.appender.defaultLog.3.layout=org.apache.log4j.PatternLayout
log4j.appender.defaultLog.3.layout.ConversionPattern=%d{${datestamp}} [%t] %-5p %m%n


2.   Conclusion


Java files can be downloaded from this link.

Comments

Popular posts from this blog

Obfuscating Spring Boot Projects Using Maven Proguard Plugin

Introduction Obfuscation is the act of reorganizing bytecode such that it becomes hard to decompile. Many developers rely on obfuscation to save their sensitive code from undesired eyes. Publishing jars without obfuscation may hinder competitiveness because rivals may take advantage of easily decompilable nature of java binaries. Objective Spring Boot applications make use of public interfaces, annotations which makes applications harder to obfuscate. Additionally, maven Spring Boot plugin creates a fat jar which contains all dependent jars. It is not viable to obfuscate the whole fat jar. Thus obfuscating Spring Boot applications is different than obfuscating regular java applications and requires a suitable strategy. Audience Those who use Spring Boot and Maven and wish to obfuscate their application using Proguard are the target audience for this article. Sample Application As the sample application, I will use elastic search synch application from my G...

Hadoop Installation Document - Standalone Mode

This document shows my experience on following apache document titled “Hadoop:Setting up a Single Node Cluster”[1] which is for Hadoop version 3.0.0-Alpha2 [2]. A. Prepare the guest environment Install VirtualBox. Create a virtual 64 bit Linux machine. Name it “ubuntul_hadoop_master”. Give it 500MB memory. Create a VMDK disc which is dynamically allocated up to 30GB. In network settings in first tab you should see Adapter 1 enabled and attached to “NAT”. In second table enable adapter 2 and attach to “Host Only Adaptor”. First adapter is required for internet connection. Second one is required for letting outside connect to a guest service. In storage settings, attach a Linux iso file to IDE channel. Use any distribution you like. Because of small installation size, I choose minimal Ubuntu iso [1]. In package selection menu, I only left standard packages selected.  Login to system.  Setup JDK. $ sudo apt-get install openjdk-8-jdk Install ssh and pdsh, if...

How To Use Keras Trained CNN Models

Introduction Keras is a popular deep learning api. It can run on top of Tensorflow , CNTK and Theano frameworks. Keras provides an easy to use interface which makes deep learning practice straight forward. It is widely used thus resources are easily accessible. Objective This article aims to give an introductory information about using a Keras trained CNN model for inference. This article does not contain information about CNN training. Audience This article assumes introductory information about python and Convolutional Neural Networks. For those who lack information may first begin with information from following resources. For python use  Python For Beginners For Convolutional Neural Networks use  CS231n Convolutional Neural Networks for Visual Recognition Software Installation Keras is a high level API. It requires a back-end framework to be installed. In this article, Tensorflow is used. Keras can transparently select CPU or GPU for processing. If use ...