Where is log4j output

The log4j library does not make any assumptions about its environment. In particular, there are no default log4j appenders. Under certain well-defined circumstances however, the static inializer of the Logger class will attempt to automatically configure log4j. The Java language guarantees that the static initializer of a class is called once and only once during the loading of a class into memory.

It is important to remember that different classloaders may load distinct copies of the same class. These copies of the same class are considered as totally unrelated by the JVM. The default initialization is very useful in environments where the exact entry point to the application depends on the runtime environment. For example, the same application can be used as a stand-alone application, as an applet, or as a servlet under the control of a web-server.

See Loader. String for the list of searched locations. You can optionaly specify a custom configurator. The value of the log4j.

The custom configurator you specify must implement the Configurator interface. The default log4j initialization is particularly useful in web-server environments. Under Tomcat 3. Log4j will find the properties file and initialize itself. This is easy to do and it works. You can also choose to set the system property log4j. For Tomcat 3. For Tomcat 4. Different web-applications will load the log4j classes through their respective classloaderss.

Thus, each image of the log4j environment will act independetly and without any mutual synchronization. For example, FileAppenders defined exactly the same way in multiple web-application configurations will all attempt to write the same file.

The results are likely to be less than satisfactory. You must make sure that log4j configurations of different web-applications do not use the same underlying system resource. Writing an initialization servlet is the most flexible way for initializing log4j. There are no constraints on the code you can place in the init method of the servlet.

Most real-world systems have to deal with multiple clients simultaneously. In a typical multithreaded implementation of such a system, different threads will handle different clients. Logging is especially well suited to trace and debug complex distributed applications.

A common approach to differentiate the logging output of one client from another is to instantiate a new separate logger for each client. This promotes the proliferation of loggers and increases the management overhead of logging. A lighter technique is to uniquely stamp each log request initiated from the same client interaction.

Martin, D. Riehle, and F. Buschmann Addison-Wesley, To uniquely stamp each request, the user pushes contextual information into the NDC, the abbreviation of Nested Diagnostic Context. The NDC class is shown below. The NDC is managed per thread as a stack of contextual information. Note that all methods of the org. NDC class are static. Assuming that NDC printing is turned on, every time a log request is made, the appropriate log4j component will include the entire NDC stack for the current thread in the log output.

This is done without the intervention of the user, who is responsible only for placing the correct information in the NDC by using the push and pop methods at a few well-defined points in the code.

In contrast, the per-client logger approach commands extensive changes in the code. To illustrate this point, let us take the example of a servlet delivering content to numerous clients.

The servlet can build the NDC at the very beginning of the request before executing other code. The contextual information can be the client's host name and other information inherent to the request, typically information contained in cookies. Hence, even if the servlet is serving multiple clients simultaneously, the logs initiated by the same code, i.

Contrast this with the complexity of passing a freshly instantiated logger to all code exercised during the client's request. Nevertheless, some sophisticated applications, such as virtual hosting web servers, must log differently depending on the virtual host context and also depending on the software component issuing the request.

Recent log4j releases support multiple hierarchy trees. This enhancement allows each virtual host to possess its own copy of the logger hierarchy. One of the often-cited arguments against logging is its computational cost.

This is a legitimate concern as even moderately sized applications can generate thousands of log requests. Much effort was spent measuring and tweaking logging performance.

Log4j claims to be fast and flexible: speed first, flexibility second. When logging is turned off entirely or just for a set of levels , the cost of a log request consists of a method invocation plus an integer comparison. However, The method invocation involves the "hidden" cost of parameter construction. This will not incur the cost of parameter construction if debugging is disabled.

On the other hand, if the logger is debug-enabled, it will incur twice the cost of evaluating whether the logger is enabled or not: once in debugEnabled and once in debug.

In log4j, logging requests are made to instances of the Logger class. Logger is a class and not an interface. This measurably reduces the cost of method invocation at the cost of some flexibility.

Certain users resort to preprocessing or compile-time techniques to compile out all log statements. This leads to perfect performance efficiency with respect to logging. However, since the resulting application binary does not contain any log statements, logging cannot be turned on for that binary.

In my opinion this is a disproportionate price to pay in exchange for a small performance gain. This is essentially the performance of walking the logger hierarchy. When logging is turned on, log4j still needs to compare the level of the log request with the level of the request logger. However, loggers may not have an assigned level; they can inherit them from the logger hierarchy.

Thus, before inheriting a level, the logger may need to search its ancestors. There has been a serious effort to make this hierarchy walk to be as fast as possible. For example, child loggers link only to their existing ancestors. In the BasicConfigurator example shown earlier, the logger named com. Bar is linked directly to the root logger, thereby circumventing the nonexistent com or com. This significantly improves the speed of the walk, especially in "sparse" hierarchies.

The typical cost of walking the hierarchy is typically 3 times slower than when logging is turned off entirely. This is the cost of formatting the log output and sending it to its target destination.

Here again, a serious effort was made to make layouts formatters perform as quickly as possible. The same is true for appenders. The typical cost of actually logging is about to microseconds.

Although log4j has many features, its first design goal was speed. Some log4j components have been rewritten many times to improve performance. Nevertheless, contributors frequently come up with new optimizations. You should be pleased to know that when configured with the SimpleLayout performance tests have shown log4j to log as quickly as System.

Log4j is a popular logging package written in Java. One of its distinctive features is the notion of inheritance in loggers. Using a logger hierarchy it is possible to control which log statements are output at arbitrary granularity. This helps reduce the volume of logged output and minimize the cost of logging. One of the advantages of the log4j API is its manageability. Once the log statements have been inserted into the code, they can be controlled with configuration files.

They can be selectively enabled or disabled, and sent to different and multiple output targets in user-chosen formats. The log4j package is designed so that log statements can remain in shipped code without incurring a heavy performance cost. Last Published: Version: 1. About log4j 1. Abstract This document describes the log4j API, its unique features and design rationale. Introduction Almost every large application includes its own logging or tracing API.

Kernighan and Rob Pike put it in their truly excellent book "The Practice of Programming" As personal choice, we tend not to use debuggers beyond getting a stack trace or the value of a variable or two. One reason is that it is easy to get lost in details of complicated data structures and control flow; we find stepping through a program less productive than thinking harder and adding output statements and self-checking code at critical places.

Clicking over statements takes longer than scanning the output of judiciously-placed displays. It takes less time to decide where to put print statements than to single-step to the critical section of code, even assuming we know where that is. More important, debugging statements stay with the program; debugging sessions are transient. Loggers, Appenders and Layouts Log4j has three main components: loggers , appenders and layouts.

Logger names are case-sensitive and they follow the hierarchical naming rule: Named Hierarchy A logger is said to be an ancestor of another logger if its name followed by a dot is a prefix of the descendant logger name. A logger is said to be a parent of a child logger if there are no ancestors between itself and the descendant logger. The ScriptPatternSelector executes a script as descibed in the Scripts section of the Configuration chapter. The script is passed all the properties configured in the Properties section of the configuration, the StrSubstitutor used by the Confguration in the "substitutor" variables, and the log event in the "logEvent" variable, and is expected to return the value of the PatternMatch key that should be used, or null if the default pattern should be used.

The SerializedLayout accepts no parameters. This layout is deprecated since version 2. Java Serialization has inherent security weaknesses, using this layout is no longer recommended. Appends a series of Event elements as defined in the log4j. Markers are represented by a Marker element within the Event element.

The Marker element appears only when a marker is used in the log message. The name of the marker's parent will be provided in the parent attribute of the Marker element. By default, the XML layout is not compact a. Message content may contain, of course, end-of-lines. Additional runtime dependencies are required for using XmlLayout. If true, the appender includes the location information in the generated YAML.

Additional runtime dependencies are required for using YamlLayout. This is an expensive operation: 1. Synchronous loggers wait as long as possible before they take this stack snapshot.

If no location is required, the snapshot will never be taken. However, asynchronous loggers need to make this decision before passing the log message to another thread; the location information will be lost after that point. The performance impact of taking a stack trace snapshot is even higher for asynchronous loggers: logging with location is times slower than without location.

For this reason, asynchronous loggers and asynchronous appenders do not include location information by default. Layouts An Appender uses a Layout to format a LogEvent into a form that meets the needs of whatever will be consuming the log event. To log CSV records, you can use the usual Logger methods info , debug , and so on: logger. Main", "method" : "main", "file" : "Main. Exception java. IllegalArgumentException: IllegalArgument at org.

NullPointerException: null pointer at org. RuntimeException" extendedStackTrace: - class: "logtest. Main" method: "main" file: "Main. See CSVFormat. Sets the output quote policy of the format to the specified value. Whether to include full stacktrace of logged Throwables optional, default to true.

If set to false, only the class name and message of the Throwable will be included. Whether to include NULL byte as delimiter after each event optional, default to false. Cannot be used with compression. The pattern to use to format the String. If not supplied only the text derived from the logging message will be used. See PatternLayout for information on the pattern strings. A comma separated list of ThreadContext attributes to exclude when formatting the event.

If threadContextIncludes are also specified this attribute will be ignored. A comma separated list of ThreadContext attributes to include when formatting the event. If threadContextExcludes are also specified this attribute will override them. ThreadContext fields specified here that have no value will be omitted.

The value must be a valid Charset. If not specified, this layout uses UTF The date format of the logging event. For other valid values, refer to the date pattern of PatternLayout. The timezone id of the logging event. If not specified, this layout uses the java. Like date pattern of PatternLayout, you can use timezone id from java. The character set to use when converting to a byte array. If not specified, UTF-8 will be used.

If true, the appender appends an end-of-line after each record. If set, overrides the default end-of-line string. Defaults to null i. If true, the appender includes the JSON header and footer, and comma between records. If true, the thread context map is included as a list of map entry objects, where each entry has a "key" attribute whose value is the key and a "value" attribute whose value is the value.

Defaults to false, in which case the thread context map is included as a simple map of key-value pairs. If true, include full stacktrace of any logged Throwable optional, default to true. If true, the timeMillis attribute is included in the Json payload instead of the instant.

Whether to format the stacktrace as a string, and not a nested object optional, defaults to false. The character set to use when converting the syslog String to a byte array. The String must be a valid Charset. If not specified, this layout uses the platform default character set. A composite pattern string of one or more conversion patterns from the table below. Cannot be specified with a PatternSelector. A component that analyzes information in the LogEvent and determines which pattern should be used to format the event.

The pattern and patternSelector parameters are mutually exclusive. Allows portions of the resulting String to be replaced. If configured, the replace element must specify the regular expression to match and the substitution. This performs a function similar to the RegexReplacement converter but applies to the whole message while the converter only applies to the String its pattern generates.

If true it is by default exceptions are always written even if the pattern contains no exception conversions. This means that if you do not include a way to output exceptions in your pattern, the default exception formatter will be added to the end of the pattern.

Setting this to false disables this behavior and allows you to exclude exceptions from your pattern output. A Java-compliant regular expression to match in the resulting string. See Pattern. F file. Outputs the file name where the logging request was issued. Outputs location information of the caller which generated the logging event. L line. Outputs the line number from where the logging request was issued.

Outputs the application supplied message associated with the logging event. M method. Outputs the method name where the logging request was issued. Outputs the platform dependent line separator character or characters. N nano. Outputs the number of milliseconds elapsed since the JVM was started until the creation of the logging event.

If you are not aware of them, please take a few minutes to get used to them as the log levels are crucial for logging. We explain everything from what they are to how to choose the right one and how to make use of them to get meaningful insights. Log4j informed us that there is no configuration present. There are multiple ways we can configure our Log4j logging. We can do it programmatically — for example by including a static initialization block:.

The above code configures Log4j to output the logs to the console in the default format. The output of running our example application would look as follows:. The most common way would be to either use a properties file or an XML file.

We can change our code and include the log4j. That way we told Log4j that we create the root logger, that will be used by default. We also gave our logger a name — MAIN. Next, we configure the logger, by setting its output to console and by using the pattern layout.

We will talk about it more later in the blog post. The output of running the above code would be as follows:. If we wish, we can also change the log4j. The same configuration using XML format would look as follows:. If we would now change the log4j. So how does Log4j know which file to use? When it starts it looks for the log4j. That means that we can overwrite the Log4j configuration from the classpath by providing the -Dlog4j. For example, if we include a file called other. And then run out code with -Dlog4j.

We already used appenders in our examples… well, really just one — the ConsoleAppender. Its sole purpose is to write the log events to the console. Of course, with a large number of log events and systems running in different environments writing pure text data to the standard output may not be the best idea, unless you are running in containers.

Here are a few common examples of Log4j appenders:. For example, you can send logs to the console and to a file. The following log4j. The MAIN logger is the one that we already saw — the one that sends the data to the console. In our case, the log files should be called awesome.

If there are more files they will be removed from the file system as soon as log4j sees them. After running the code with the above configuration the console would print the following content:. The nice thing about Appenders is that they can have their level which should be taken into consideration when logging. What if we wanted to change that for all the classes in the com.

We would only have to modify our log4j. Look at the last line in the above configuration file. Our example application code looks like this:. With the above Log4j configuration the output of the logging looks as follows:.

As you can see, only the WARN level log was included. That is exactly what we wanted. Finally, the part of the Log4j logging framework that controls the way our data is structured in our log file — the layout. In most cases, you will encounter the PatternLayout.

The idea behind this layout is that you can provide a variety of formatting options to define the structure of the logs.

Some of the examples are:. For more information on the available options head over to the official Log4j Javadocs for the PatternLayout. When using the PatternLayout we can configure which option we would like to use. We could use a pattern like this:. The full log4j. The output that is written to the console after running our example code looks as follows:.

It is surrounded by a certain context. To provide such context, per-thread, Log4j provides the so-called Nested Diagnostic Context. That way we can bound a given thread with additional information, for example, a session identifier, just like in our example application :. When using a pattern that includes x variable additional information will be included in each logline for the given thread.

In our case the output will look like this:. You can see that the information about the session identifier is in the logline. Just for reference, the log4j. The second type of contextual information that we can include in our log events is mapped diagnostic context. Using the MDC class we can provide additional key-value related information.

Similar to nested diagnostic context, the mapped diagnostic context is thread-bound. We have two context fields — the user and the step.

To display all of the mapped diagnostic context information associated with the log event we just use the X variable in our pattern definition. For example:. Launching the above code along with the configuration would result in the following output:.