Commons logging file appender

Include the jar in your project. Define log4j. Use the logger in the class: import org. Log; import org. As of log4j1. See bug Bharat Sinha Bharat Sinha That is only if you use log4j as the backend for commons logging. I tried this , but it not works! It seem to be that org. We can use log4j and apache commons logging together. Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password.

Post as a guest Name. Email Required, but never shown. The Overflow Blog. Stack Gives Back Safety in numbers: crowdsourcing data on nefarious IP addresses. Featured on Meta. New post summary designs on greatest hits now, everywhere else eventually. Linked The two steps listed below enable the JUL integration. This allows for routing logging messages from JUL to the Logbback appenders. If org. So far Sling used to configure the appenders based on OSGi config.

This provides a very limited set of configuration options. To make use of other Logback features you can override the OSGi config from within the Logback config file.

OSGi config based appenders are named based on the file name. In this case the logging module creates an appender based on the Logback config instead of the OSGi config. This can be used to move the application from OSGi based configs to Logback based configs. With Slf4j API 1. Without var args you need to construct an object array log. To make use of this API and still be able to use your bundle on Sling systems which package older version of the API jar, follow the below steps.

This setup allows your bundles to make use of the var args feature while making logging calls, but the bundles can still be deployed on older systems which provide only the 1. Log Tracer provides support for enabling the logs for specific category at specific level and only for specific request. It provides a very fine level of control via config provided as part of HTTP request around how the logging should be performed for given category.

The filter also allow configuration to extract data from request cookie, header and parameters. Download the bundle from here or use following Maven dependency. This fragment is required to make use of Groovy based event evaluation support provided by Logback. This enables programatic filtering of the log messages and is useful to get desired logs without flooding the system.

For example Oak logs the JCR operations being performed via a particular session. However if you need logging only from session created in a particular thread then that can be done in following way. Logback exposes a variable e which is of type ILoggingEvent. It provides access to current logging event. Above logback config would route all log messages from org. Further only those log messages would be logged where the threadName contains JobHandler. Depending on the requirement the expression can be customised.

Currently the bundle is not released and has to be build from here. This bundle does not depend on any other Sling bundle and can be easily used in any OSGi framework. To get complete log support working you need to deploy following bundles. You need to specify the location of logback. Become a Sponsor Buy Stuff. Home Documentation Development.

This document is for the new November 4. Refer to Logging 3. Sets the initial logging level of the root logger. Sets the log file to which log messages are written. If this property is empty or missing, log messages are written to System. Starting in Log4j 2.

The CassandraAppender writes its output to an Apache Cassandra database. A keyspace and table must be configured ahead of time, and the columns of that table are mapped in a configuration file. Each column can specify either a StringLayout e. ThreadContextMap or org. A conversion type compatible with java. Date will use the log event timestamp converted to that type e. Date to fill a timestamp column type in Cassandra. As one might expect, the ConsoleAppender writes its output to either System.

A Layout must be provided to format the LogEvent. The FailoverAppender wraps a set of appenders. If the primary Appender fails the secondary appenders will be tried in order until one succeeds or there are no more secondaries to try. While FileAppenders from different Configurations cannot be shared, the FileManagers can be if the Manager is accessible.

For example, two web applications in a servlet container can have their own configuration and safely write to the same file if Log4j is in a ClassLoader that is common to both of them. When set to true - the default, each write will be followed by a flush.

This will guarantee that the data is passed to the operating system for writing; it does not guarantee that the data is actually written to a physical device such as a disk drive. Note that if this flag is set to false, and the logging activity is sparse, there may be an indefinite delay in the data eventually making it to the operating system, because it is held up in a buffer. This can cause surprising effects such as the logs not appearing in the tail output of a file immediately after writing to the log.

Flushing after every write is only useful when using this appender with synchronous loggers. Asynchronous loggers and appenders will automatically flush at the end of a batch of events, even if immediateFlush is set to false. This also guarantees the data is passed to the operating system but is more efficient. Changing file's owner may be restricted for security reason and Operation not permitted IOException thrown.

Underlying files system shall support file owner attribute view. Apache Flume is a distributed, reliable, and available system for efficiently collecting, aggregating, and moving large amounts of log data from many different sources to a centralized data store.

Usage as an embedded agent will cause the messages to be directly passed to the Flume Channel and then control will be immediately returned to the application. All interaction with remote agents will occur asynchronously. Setting the "type" attribute to "Embedded" will force the use of the embedded agent. In addition, configuring agent properties in the appender configuration will also cause the embedded agent to be used. One or more Property elements that are used to configure the Flume Agent.

The properties must be configured without the agent name the appender name is used for this and no sources can be configured. Interceptors can be specified for the source using "sources. All other Flume configuration properties are allowed. Specifying both Agent and Property elements will result in an error. A sample FlumeAppender configuration that is configured with a primary and a secondary agent, compresses the body, and formats the body using the RFCLayout:.

A sample FlumeAppender configuration that is configured with a primary and a secondary agent, compresses the body, formats the body using the RFCLayout, and persists encrypted events to disk:. A sample FlumeAppender configuration that is configured with a primary and a secondary agent, compresses the body, formats the body using RFCLayout and passes the events to an embedded Flume Agent.

A sample FlumeAppender configuration that is configured with a primary and a secondary agent using Flume configuration properties, compresses the body, formats the body using RFCLayout and passes the events to an embedded Flume Agent. See the enableJndiJdbc system property. Whichever approach you take, it must be backed by a connection pool. Otherwise, logging performance will suffer greatly. If batch statements are supported by the configured JDBC driver and a bufferSize is configured to be a positive number, then log events will be batched.

Note that as of Log4j 2. To get off the ground quickly during development, an alternative to using a connection source based on JNDI is to use the non-pooling DriverManager connection source. This connection source uses a JDBC connection string, a user name, and a password. Optionally, you can also use properties. You must use exactly one of the following nested elements:. Use this attribute to insert a literal value in this column.

This is especially useful for databases that don't support identity columns. Use this attribute to insert an expression with a parameter marker '? The value will be included directly in the insert SQL, without any quoting which means that if you want this to be a string, your value should contain single quotes around it like this:. This let you insert rows for custom values in a database table based on a Log4j MapMessage instead of values from LogEvents.

See the enableJndiJms system property. Note that in Log4j 2. However, configurations written for 2. As of Log4j 2. It requires the API and a provider implementation be on the classpath.

It also requires a decorated entity configured to persist to the table desired. The entity should either extend org. BasicLogEventEntity if you mostly want to use the default mappings and provide at least an Id property, or org. AbstractLogEventWrapperEntity if you want to significantly customize the mappings.

See the Javadoc for these two classes for more information. You can also consult the source code of these two classes as an example of how to implement the entity. Here is a sample configuration for the JPAAppender. The first XML sample is the Log4j configuration file, the second is the persistence.

EclipseLink is assumed here, but any JPA 2. You should always create a separate persistence unit for logging, for two reasons. Also, for performance reasons the logging entity should be isolated in its own persistence unit away from all other entities and you should use a non-JTA data source. Will set the Content-Type header according to the layout. Additional headers can be specified with embedded Property elements. The KafkaAppender logs events to an Apache Kafka topic.

Each log event is sent as a Kafka record. This appender is synchronous by default and will block until the record has been acknowledged by the Kafka server, timeout for this can be set with the timeout.

This appender requires the Kafka client library. Note that you need to use a version of the Kafka client library matching the Kafka server used. Note: Make sure to not let org. New since 2. Be aware that this is a new addition, and although it has been tested on several platforms, it does not have as much track record as the other file appenders. The MemoryMappedFileAppender maps a part of the specified file into memory and writes log events to this memory, relying on the operating system's virtual memory manager to synchronize the changes to the storage device.

Instead of making system calls to write to disk, this appender can simply change the program's local memory, which is orders of magnitude faster. Also, in most operating systems the memory region mapped actually is the kernel's page cache file cache , meaning that no copies need to be created in user space. There is some overhead with mapping a file region into memory, especially very large regions half a gigabyte or more. The default region size is 32 MB, which should strike a reasonable balance between the frequency and the duration of remap operations.

TODO: performance test remapping various sizes. When set to true, each write will be followed by a call to MappedByteBuffer. This will guarantee the data is written to the storage device. The default for this parameter is false. This means that the data is written to the storage device even if the Java process crashes, but there may be data loss if the operating system crashes.

Note that manually forcing a sync on every log event loses most of the performance benefits of using a memory mapped file. This also guarantees the data is written to disk but is more efficient. We recommend you review the source code for the MongoDB and CouchDB providers as a guide for creating your own provider. The module log4j-mongodb2 aliases the old configuration element MongoDb to MongoDb2. The OutputStreamAppender provides the base for many of the other Appenders such as the File and Socket appenders that write the event to an Output Stream.

It cannot be directly configured. Support for immediateFlush and buffering is provided by the OutputStreamAppender. This can be used to mask sensitive information such as passwords or to inject information into each event. The RewriteAppender must be configured with a RewritePolicy. The RewriteAppender should be configured after any Appenders it references to allow it to shut down properly.

RewritePolicy is an interface that allows implementations to inspect and possibly modify LogEvents before they are passed to Appender. RewritePolicy declares a single method named rewrite that must be implemented. The method is passed the LogEvent and can return the same event or create a new one. The following configuration shows a RewriteAppender configured to add a product key and its value to the MapMessage.

PropertiesRewritePolicy will add properties configured on the policy to the ThreadContext Map being logged. The properties will not be added to the actual ThreadContext Map.

The property values may contain variables that will be evaluated when the configuration is processed as well as when the event is logged. The following configuration shows a RewriteAppender configured to add a product key and its value to the MapMessage:.

You can use this policy to make loggers in third party code less chatty by changing event levels. You configure a LoggerNameLevelRewritePolicy with a logger name prefix and a pairs of levels, where a pair defines a source level and a target level.

The triggering policy determines if a rollover should be performed while the RolloverStrategy defines how the rollover should be done. Since log4j Since 2. The CompositeTriggeringPolicy combines multiple triggering policies and returns true if any of the configured policies return true.

The CompositeTriggeringPolicy is configured simply by wrapping other policies in a Policies element. The CronTriggeringPolicy triggers rollover based on a cron expression. This policy is controlled by a timer and is asynchronous to processing log events, so it is possible that log events from the previous or next time period may appear at the beginning or end of the log file.

The filePattern attribute of the Appender should contain a timestamp otherwise the target file will be overwritten on each rollover. The OnStartupTriggeringPolicy policy causes a rollover if the log file is older than the current JVM's start time and the minimum file size is met or exceeded.

The SizeBasedTriggeringPolicy causes a rollover once the file has reached the specified size. The size may also contain a fractional value such as 1. The size is evaluated using the Java root Locale so a period must always be used for the fractional unit. When used without a time based triggering policy the SizeBased Triggering Policy will cause the timestamp value to change. This policy accepts an interval attribute which indicates how frequently the rollover should occur based on the time pattern and a modulate boolean attribute.

If the pattern contains an integer it will be incremented on each rollover. If the file pattern ends with ". The pattern may also contain lookup references that can be resolved at runtime such as is shown in the example below. The default rollover strategy supports three variations for incrementing the counter. To illustrate how it works, suppose that the min attribute is set to 1, the max attribute is set to 3, the file name is "foo.

By way of contrast, when the fileIndex attribute is set to "min" but all the other settings are the same the "fixed window" strategy will be performed. Finally, as of release 2. The DirectWriteRolloverStrategy causes log events to be written directly to files represented by the file pattern.

With this strategy file renames are not performed. If the size-based triggering policy causes multiple files to be written during the specified time period they will be numbered starting at one and continually incremented until a time-based rollover occurs. Warning: If the file pattern has a suffix indicating compression should take place the current file will not be compressed when the application is shut down.

Furthermore, if the time changes such that the file pattern no longer matches the current file it will not be compressed at startup either. Below is a sample configuration that uses a RollingFileAppender with both the time and size based triggering policies, will create up to 7 archives on the same day that are stored in a directory based on the current year and month, and will compress each archive using gzip:.

This second example shows a rollover strategy that will keep up to 20 files before removing them. Below is a sample configuration that uses a RollingFileAppender with both the time and size based triggering policies, will create up to 7 archives on the same day that are stored in a directory based on the current year and month, and will compress each archive using gzip and will roll every 6 hours when the hour is divisible by This sample configuration uses a RollingFileAppender with both the cron and size based triggering policies, and writes directly to an unlimited number of archive files.

The cron trigger causes a rollover every hour while the file size is limited to MB:. This sample configuration is the same as the previous but limits the number of files saved each hour to The Delete action lets users configure one or more conditions that select the files to delete relative to a base directory. Note that it is possible to delete any file, not just rolled over log files, so use this action with care! With the testMode parameter you can test your configuration without accidentally deleting the wrong files.

If more than one condition is specified, they all need to accept a path before it is deleted. Conditions can be nested, in which case the inner condition s are evaluated only if the outer condition accepts the path.

If conditions are not nested they may be evaluated in any order. Required if no PathConditions are specified. A ScriptCondition element specifying a script. The script is passed a number of parameters , including a list of paths found under the base path up to maxDepth and must return a list with the paths to delete.

Below is a sample configuration that uses a RollingFileAppender with the cron triggering policy configured to trigger every day at midnight. Archives are stored in a directory based on the current year and month. Below is a sample configuration that uses a RollingFileAppender with both the time and size based triggering policies, will create up to archives on the same day that are stored in a directory based on the current year and month, and will compress each archive using gzip and will roll every hour.

The script returns a list of rolled over files under the base directory dated Friday the 13th. The Delete action will delete all files returned by the script. The PosixViewAttribute action lets users configure one or more conditions that select the eligible files relative to a base directory. This will guarantee the data is written to disk but could impact performance. Below is a sample configuration that uses a RollingRandomAccessFileAppender with both the time and size based triggering policies, will create up to 7 archives on the same day that are stored in a directory based on the current year and month, and will compress each archive using gzip:.

Below is a sample configuration that uses a RollingRandomAccessFileAppender with both the time and size based triggering policies, will create up to 7 archives on the same day that are stored in a directory based on the current year and month, and will compress each archive using gzip and will roll every 6 hours when the hour is divisible by The target Appender may be an appender previously configured and may be referenced by its name or the Appender can be dynamically created as needed.

The RoutingAppender should be configured after any Appenders it references to allow it to shut down properly. You can also configure a RoutingAppender with scripts: you can run a script when the appender starts and when a route is chosen for an log event. In this example, the script causes the "ServiceWindows" route to be the default route on Windows and "ServiceOther" on all other operating systems.

Note that the List Appender is one of our test appenders, any appender can be used, it is only used as a shorthand. The Routes element accepts a single attribute named "pattern". The pattern is evaluated against all the registered Lookups and the result is used to select a Route.

Each Route may be configured with a key. If the key matches the result of evaluating the pattern then that Route will be selected. If no key is specified on a Route then that Route is the default. Only one Route can be configured as the default. The Routes element may contain a Script child element. If specified, the Script is run for each log event and returns the String Route key to use. You must specify either the pattern attribute or the Script element, but not both.

Each Route must reference an Appender. If the Route contains a ref attribute then the Route will reference an Appender that was defined in the configuration. If the Route contains an Appender definition then an Appender will be created within the context of the RoutingAppender and will be reused each time a matching Appender name is referenced through a Route.

In this example, the script runs for each log event and picks a route based on the presence of a Marker named "AUDIT". The RoutingAppender can be configured with a PurgePolicy whose purpose is to stop and remove dormant Appenders that have been dynamically created by the RoutingAppender.