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| |
| <div class="section"><h2>Asynchronous Loggers for Low-Latency Logging<a name="Asynchronous_Loggers_for_Low-Latency_Logging"></a></h2> |
| <p> |
| Asynchronous logging can improve your application's |
| performance by executing the I/O operations |
| in a separate thread. |
| Log4j 2 makes a number of improvements in this area. |
| </p> |
| <ul> |
| <li> |
| <b>Asynchronous Loggers</b> |
| are a new addition to Log4j 2. |
| Their aim is to return from the call |
| to Logger.log to the application as |
| soon as possible. You can choose |
| between making all Loggers asynchronous |
| or using a mixture of synchronous |
| and asynchronous Loggers. Making all |
| Loggers asynchronous will give |
| the best performance, while mixing |
| gives you more flexibility. |
| </li> |
| <li><b>LMAX Disruptor technology</b>. Asynchronous Loggers |
| internally use the <a href="#UnderTheHood">Disruptor</a>, |
| a lock-free inter-thread |
| communication library, instead of queues, resulting in higher |
| throughput and lower latency.</li> |
| <li> |
| <b>Asynchronous Appenders</b> |
| already existed in Log4j 1.x, but have |
| been enhanced to flush to disk |
| at the end of a batch (when the queue is empty). |
| This produces the same result as configuring |
| "immediateFlush=true", that is, all |
| received log events are always available on disk, |
| but is more efficient because it does not need to |
| touch the disk on each and every log event. |
| (Async Appenders use ArrayBlockingQueue internally and |
| do not need the disruptor jar on the classpath.) |
| </li> |
| <li>(For synchronous and asynchronous use) |
| <b>Random Access File Appenders</b> |
| are an alternative to Buffered File |
| Appenders. Under the hood, these |
| new appenders use a ByteBuffer + RandomAccessFile instead |
| of a BufferedOutputStream. In our testing |
| this was about 20-200% faster. |
| These appenders can also be used |
| with synchronous loggers |
| and will give the same performance benefits. |
| Random Access File Appenders do not need the disruptor jar on the classpath. |
| </li> |
| </ul> |
| <a name="Trade-offs"></a> |
| <div class="section"><h3>Trade-offs<a name="Trade-offs"></a></h3> |
| <p> |
| Although asynchronous logging can give significant performance |
| benefits, there are situations where you may want to |
| choose synchronous logging. |
| This section describes some of the trade-offs of |
| asynchronous logging. |
| </p> |
| <p> |
| <b>Benefits</b> |
| </p> |
| <ul> |
| <li>Higher <a href="#Performance">throughput</a>. |
| With an asynchronous logger |
| your application can log messages at 6 - 68 times |
| the rate of a synchronous logger. |
| </li> |
| <li> |
| Lower logging <a href="#Latency">latency</a>. |
| Latency is the time it takes for a call to Logger.log to return. |
| Asynchronous Loggers have consistently lower latency |
| than synchronous loggers or even queue-based asynchronous appenders. |
| Applications interested in low latency often care |
| not only about average latency, but also about worst-case latency. |
| Our performance comparison shows that Asynchronous |
| Loggers also do better when comparing the maximum latency |
| of 99% or even 99.99% of observations with other logging methods. |
| </li> |
| <li>Prevent or dampen latency spikes during bursts of events. |
| If the queue size is configured large enough to handle |
| spikes, asynchronous logging will help prevent your |
| application from falling behind (as much) during |
| sudden bursts of activity. |
| </li> |
| </ul> |
| <b>Drawbacks</b> |
| <ul> |
| <li>Error handling. If a problem happens during the logging |
| process and an exception is thrown, it is less easy for an |
| asynchronous logger or appender to signal this problem to the |
| application. This can partly be alleviated by configuring an |
| <tt>ExceptionHandler</tt>, but this may |
| still not cover all cases. For this |
| reason, if logging is part of your business logic, |
| for example if |
| you are using Log4j as an audit logging framework, |
| we would |
| recommend to synchronously log those audit messages. |
| (Note that you |
| can still <a href="#MixedSync-Async">combine</a> them |
| and use asynchronous logging for debug/trace |
| logging in addition to synchronous |
| logging for the audit trail.) |
| </li> |
| </ul> |
| </div> |
| <a name="AllAsync"></a> |
| <div class="section"><h3>Making All Loggers Asynchronous<a name="Making_All_Loggers_Asynchronous"></a></h3> |
| <p><i>Requires disruptor-3.0.0.jar or higher on the classpath.</i></p> |
| <p> |
| This is simplest to configure and gives the best performance. |
| To make all loggers asynchronous, |
| add the disruptor jar to the classpath |
| and set the system property <tt>Log4jContextSelector</tt> |
| to |
| <tt>org.apache.logging.log4j.core.async.AsyncLoggerContextSelector</tt>. |
| </p> |
| <p> |
| By default, <a href="#Location">location</a> is not passed to the I/O thread by |
| asynchronous loggers. If one of your layouts or custom |
| filters needs location information, you need to set |
| "includeLocation=true" |
| in the configuration of all relevant loggers, |
| including the root logger. |
| </p> |
| <p> |
| A configuration that does not require location might look like: |
| </p><div class="prettyprint linenums"><pre><?xml version="1.0" encoding="UTF-8"?> |
| |
| <!-- Don't forget to set system property |
| -DLog4jContextSelector=org.apache.logging.log4j.core.async.AsyncLoggerContextSelector |
| to make all loggers asynchronous. --> |
| |
| <Configuration status="WARN"> |
| <Appenders> |
| <!-- Async Loggers will auto-flush in batches, so switch off immediateFlush. --> |
| <RandomAccessFile name="RandomAccessFile" fileName="async.log" immediateFlush="false" append="false"> |
| <PatternLayout> |
| <Pattern>%d %p %c{1.} [%t] %m %ex%n</Pattern> |
| </PatternLayout> |
| </RandomAccessFile> |
| </Appenders> |
| <Loggers> |
| <Root level="info" includeLocation="false"> |
| <AppenderRef ref="RandomAccessFile"/> |
| </Root> |
| </Loggers> |
| </Configuration></pre></div> |
| |
| <p> |
| When |
| <tt>AsyncLoggerContextSelector</tt> is used to make |
| all loggers asynchronous, make sure to use normal |
| <tt><root></tt> and |
| <tt><logger></tt> elements |
| in the configuration. The |
| AsyncLoggerContextSelector |
| will ensure that all loggers are asynchronous, using a mechanism |
| that is different from what happens when you configure |
| <tt><asyncRoot></tt> or |
| <tt><asyncLogger></tt>. |
| The latter elements are intended for mixing async with sync |
| loggers. If you use both mechanisms together you will end |
| up with two |
| background threads, where your application passes the log |
| message to |
| thread A, which passes the message to thread B, |
| which then finally |
| logs the message to disk. This works, but |
| there will be an unnecessary |
| step in the middle. |
| </p> |
| |
| <p> |
| There are a few system properties |
| you can use to control |
| aspects of the asynchronous logging subsystem. |
| Some of these can be used to |
| tune logging performance. |
| </p> |
| <table border="0" class="bodyTable"><caption align="top">System Properties to configure all |
| asynchronous loggers |
| </caption> |
| <tr class="a"> |
| <th>System Property</th> |
| <th>Default Value</th> |
| <th>Description</th> |
| </tr> |
| <tr class="b"> |
| <td>AsyncLogger.ExceptionHandler</td> |
| <td> |
| <tt>null</tt> |
| </td> |
| <td> |
| Fully qualified name of a class that implements the |
| <tt>com.lmax.disruptor.ExceptionHandler</tt> |
| interface. The class needs to have a public |
| zero-argument |
| constructor. If specified, this class |
| will be notified when an |
| exception occurs while |
| logging the messages. |
| </td> |
| </tr> |
| <tr class="a"> |
| <td>AsyncLogger.RingBufferSize</td> |
| <td>256 * 1024 |
| </td> |
| <td> |
| Size (number of slots) in the RingBuffer used by the |
| asynchronous logging subsystem. |
| Make this value large enough to |
| deal with bursts |
| of activity. The minimum size is 128. |
| The |
| RingBuffer will |
| be pre-allocated at first use and will never grow |
| or shrink during the life of the system. |
| </td> |
| </tr> |
| <tr class="b"> |
| <td>AsyncLogger.WaitStrategy</td> |
| <td> |
| <tt>Sleep</tt> |
| </td> |
| <td> |
| Valid values: Block, Sleep, Yield. |
| <br /> |
| <tt>Block</tt> |
| is a strategy that uses a lock and |
| condition |
| variable for the I/O thread waiting for log events. |
| Block can be used when |
| throughput and low-latency |
| are not as important as CPU resource. |
| Recommended for resource constrained/virtualised environments. |
| <br /> |
| <tt>Sleep</tt> |
| is a strategy that initially spins, then |
| uses a Thread.yield(), and |
| eventually parks for the |
| minimum number of nanos the OS and JVM will allow |
| while the I/O thread is waiting for log events. |
| Sleep is a good compromise between performance |
| and CPU resource. |
| This strategy has very low impact on the |
| application thread, in exchange for some additional |
| latency for actually getting the message logged. |
| <br /> |
| <tt>Yield</tt> |
| is a strategy that uses a Thread.yield() for |
| waiting for log events after an initially spinning. |
| Yield is a good compromise between performance |
| and CPU resource, but may use more CPU than Sleep |
| in order to get the message logged to disk sooner. |
| </td> |
| </tr> |
| <tr class="a"> |
| <td>AsyncLogger.ThreadNameStrategy</td> |
| <td> |
| <tt>CACHED</tt> |
| </td> |
| <td> |
| Valid values: CACHED, UNCACHED. |
| <br /> |
| By default, AsyncLogger caches the thread name |
| in a threadlocal variable to improve performance. |
| Specify the <tt>UNCACHED</tt> option if your application |
| modifies the thread name at runtime (with <tt>Thread.currentThread().setName()</tt>) |
| and you want to see the new thread name reflected in the log. |
| </td> |
| </tr> |
| <tr class="b"> |
| <td>log4j.Clock</td> |
| <td> |
| <tt>SystemClock</tt> |
| </td> |
| <td> |
| Implementation of the |
| <tt>org.apache.logging.log4j.core.helpers.Clock</tt> |
| interface that is used for timestamping the log |
| events when all loggers are asynchronous. |
| <br /> |
| By default, <tt>System.currentTimeMillis</tt> |
| is called on every log event. |
| <br /> |
| <tt>CachedClock</tt> |
| is an optimization where |
| time stamps are generated from a clock that |
| updates its internal time in a background thread once |
| every millisecond, or every 1024 log events, |
| whichever comes first. This |
| reduces logging latency a little, at the cost of |
| some precision in the logged time stamps. |
| Unless you are logging many |
| events, you may see "jumps" |
| of 10-16 milliseconds between log time stamps. |
| <br /> |
| You can also specify a fully qualified class name |
| of a custom class that implements the |
| <tt>Clock</tt> |
| interface. |
| </td> |
| </tr> |
| |
| </table> |
| </div> |
| <a name="MixedSync-Async"></a> |
| <div class="section"><h3>Mixing Synchronous and Asynchronous Loggers<a name="Mixing_Synchronous_and_Asynchronous_Loggers"></a></h3> |
| <p><i>Requires disruptor-3.0.0.jar or higher on the classpath. |
| There is no need to set system property "Log4jContextSelector" to any value.</i></p> |
| <p> |
| Synchronous and asynchronous loggers can be combined in |
| configuration. This gives you more flexibility at the cost |
| of a |
| slight loss in performance (compared to making |
| all loggers asynchronous). Use the |
| <tt><asyncRoot></tt> |
| or |
| <tt><asyncLogger></tt> |
| configuration elements to specify the loggers that need to |
| be |
| asynchronous. The same configuration file can also |
| contain |
| <tt><root></tt> |
| and |
| <tt><logger></tt> |
| elements for the synchronous loggers. |
| </p> |
| <p> |
| By default, <a href="#Location">location</a> is not passed to the I/O thread by |
| asynchronous loggers. If one of your layouts or custom |
| filters needs location information, you need to set |
| "includeLocation=true" |
| in the configuration of all relevant loggers, |
| including the root logger. |
| </p> |
| <p> |
| A configuration that mixes asynchronous loggers might look like: |
| </p><div class="prettyprint linenums"><pre><?xml version="1.0" encoding="UTF-8"?> |
| |
| <!-- No need to set system property "Log4jContextSelector" to any value |
| when using <asyncLogger> or <asyncRoot>. --> |
| |
| <Configuration status="WARN"> |
| <Appenders> |
| <!-- Async Loggers will auto-flush in batches, so switch off immediateFlush. --> |
| <RandomAccessFile name="RandomAccessFile" fileName="asyncWithLocation.log" |
| immediateFlush="false" append="false"> |
| <PatternLayout> |
| <Pattern>%d %p %class{1.} [%t] %location %m %ex%n</Pattern> |
| </PatternLayout> |
| </RandomAccessFile> |
| </Appenders> |
| <Loggers> |
| <!-- pattern layout actually uses location, so we need to include it --> |
| <AsyncLogger name="com.foo.Bar" level="trace" includeLocation="true"> |
| <AppenderRef ref="RandomAccessFile"/> |
| </AsyncLogger> |
| <Root level="info" includeLocation="true"> |
| <AppenderRef ref="RandomAccessFile"/> |
| </Root> |
| </Loggers> |
| </Configuration></pre></div> |
| |
| <p> |
| There are a few system properties |
| you can use to control |
| aspects of the asynchronous logging subsystem. |
| Some of these can be used to |
| tune logging performance. |
| </p> |
| <table border="0" class="bodyTable"><caption align="top">System Properties to configure mixed |
| asynchronous and normal loggers |
| </caption> |
| <tr class="a"> |
| <th>System Property</th> |
| <th>Default Value</th> |
| <th>Description</th> |
| </tr> |
| <tr class="b"> |
| <td>AsyncLoggerConfig.ExceptionHandler</td> |
| <td> |
| <tt>null</tt> |
| </td> |
| <td> |
| Fully qualified name of a class that implements the |
| <tt>com.lmax.disruptor.ExceptionHandler</tt> |
| interface. The class needs to have a public |
| zero-argument |
| constructor. If specified, this class |
| will be notified when an |
| exception occurs while |
| logging the messages. |
| </td> |
| </tr> |
| <tr class="a"> |
| <td>AsyncLoggerConfig.RingBufferSize</td> |
| <td>256 * 1024 |
| </td> |
| <td> |
| Size (number of slots) in the RingBuffer used by the |
| asynchronous logging subsystem. |
| Make this value large enough to |
| deal with bursts |
| of activity. The minimum size is 128. |
| The RingBuffer will |
| be pre-allocated at first use and will never grow |
| or shrink during the life of the system. |
| </td> |
| </tr> |
| <tr class="b"> |
| <td>AsyncLoggerConfig.WaitStrategy</td> |
| <td> |
| <tt>Sleep</tt> |
| </td> |
| <td> |
| Valid values: Block, Sleep, Yield. |
| <br /> |
| <tt>Block</tt> |
| is a strategy that uses a lock and |
| condition |
| variable for the I/O thread waiting for log events. |
| Block can be used when |
| throughput and low-latency |
| are not as important as CPU resource. |
| Recommended for resource constrained/virtualised environments. |
| <br /> |
| <tt>Sleep</tt> |
| is a strategy that initially spins, then |
| uses a Thread.yield(), and |
| eventually parks for the |
| minimum number of nanos the OS and JVM will allow |
| while the I/O thread is waiting for log events. |
| Sleep is a good compromise between performance |
| and CPU resource. |
| This strategy has very low impact on the |
| application thread, in exchange for some additional |
| latency for actually getting the message logged. |
| <br /> |
| <tt>Yield</tt> |
| is a strategy that uses a Thread.yield() for |
| waiting for log events after an initially spinning. |
| Yield is a good compromise between performance |
| and CPU resource, but may use more CPU than Sleep |
| in order to get the message logged to disk sooner. |
| </td> |
| </tr> |
| |
| </table> |
| </div> |
| <a name="Location"></a> |
| <div class="section"><h3>Location, location, location...<a name="Location_location_location..."></a></h3> |
| <p> |
| If one of the layouts is |
| configured with a location-related attribute like |
| HTML <a href="layouts.html#HtmlLocationInfo">locationInfo</a>, |
| or one of the patterns |
| <a href="layouts.html#PatternClass">%C or $class</a>, |
| <a href="layouts.html#PatternFile">%F or %file</a>, |
| <a href="layouts.html#PatternLocation">%l or %location</a>, |
| <a href="layouts.html#PatternLine">%L or %line</a>, |
| <a href="layouts.html#PatternMethod">%M or %method</a>, |
| Log4j will take a snapshot of the |
| stack, and walk the stack trace to find the location information. |
| </p> |
| <p> |
| This is an expensive operation: 1.3 - 5 times slower for |
| synchronous loggers. Synchronous loggers wait as |
| long as possible before they take this stack snapshot. If no |
| location is required, the snapshot will never be taken. |
| </p><p> |
| 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 |
| 4 - 20 times slower than without location. |
| For this reason, asynchronous loggers and asynchronous |
| appenders do not include location information by default. |
| </p><p> |
| You can override the default behaviour in your logger |
| or asynchronous appender configuration |
| by specifying |
| <tt>includeLocation="true"</tt>. |
| </p> |
| <p> |
| </p> |
| </div> |
| <a name="Performance"></a> |
| <div class="section"><h3>Asynchronous Logging Performance<a name="Asynchronous_Logging_Performance"></a></h3> |
| <p> |
| The performance results below were all derived from running the |
| PerfTest, MTPerfTest and PerfTestDriver classes which can be found |
| in the Log4j 2 unit test source directory. |
| All tests were done using the |
| default settings (SystemClock and SleepingWaitStrategy). |
| The methodology used was the same for all tests: |
| </p> |
| <ul> |
| <li>First, warm up the JVM by logging 200,000 log messages of 500 |
| characters.</li> |
| <li>Repeat the warm-up 10 times, then wait 10 seconds for the I/O thread to catch up and buffers to drain.</li> |
| <li>Latency test: at less than saturation, measure how |
| long a call to Logger.log takes. |
| Pause for 10 microseconds * threadCount between measurements. |
| Repeat this 5 million times, and measure average latency, |
| latency of 99% of observations and 99.99% of observations.</li> |
| <li>Throughput test: measure how long it takes to execute 256 * |
| 1024 / threadCount calls to Logger.log and express the |
| result in messages per second.</li> |
| <li>Repeat the test 5 times and average the results.</li> |
| </ul> |
| <p>The results below were obtained with log4j-2.0-beta5, disruptor-3.0.0.beta3, |
| log4j-1.2.17 and logback-1.0.10.</p> |
| <div class="section"><h4>Logging Throughput<a name="Logging_Throughput"></a></h4> |
| <p> |
| The graph below compares the throughput of synchronous loggers, |
| asynchronous appenders and asynchronous loggers. This |
| is the total throughput of all threads together. |
| In the test with 64 threads, asynchronous loggers are 12 times |
| faster than asynchronous appenders, and 68 times faster than |
| synchronous loggers. |
| </p> |
| <p> |
| Asynchronous loggers' throughput increases with the number of threads, |
| whereas both synchronous loggers and asynchronous appenders |
| have more or less constant throughput regardless of the number of |
| threads that are doing the logging. |
| </p> |
| <p><img src="../images/async-vs-sync-throughput.png" alt="" /></p> |
| |
| </div><div class="section"><h4>Asynchronous Throughput Comparison with Other Logging Packages<a name="Asynchronous_Throughput_Comparison_with_Other_Logging_Packages"></a></h4> |
| <p> |
| We also compared throughput of asynchronous loggers to |
| the synchronous loggers and asynchronous appenders available |
| in other logging packages, specifically log4j-1.2.17 and |
| logback-1.0.10, with similar results. |
| For asynchronous appenders, total logging throughput of all |
| threads together remains roughly constant when adding more threads. |
| Asynchronous loggers make more effective use of the multiple cores |
| available on the machine in multi-threaded scenarios. |
| </p> |
| <p> |
| <img src="../images/async-throughput-comparison.png" alt="" /> |
| </p> |
| <p>On Solaris 10 (64bit) with JDK1.7.0_06, 4-core Xeon X5570 dual CPU |
| @2.93Ghz with hyperthreading switched on (16 virtual cores):</p> |
| <table border="0" class="bodyTable"><caption align="top">Throughput per thread in messages/second |
| </caption> |
| <tr class="a"> |
| <th>Logger</th> |
| <th>1 thread</th> |
| <th>2 threads</th> |
| <th>4 threads</th> |
| <th>8 threads</th> |
| <th>16 threads</th> |
| <th>32 threads</th> |
| <th>64 threads</th> |
| </tr> |
| <tr class="b"> |
| <td>Log4j 2: Loggers all asynchronous</td> |
| <td align="right">2,652,412</td> |
| <td align="right">909,119</td> |
| <td align="right">776,993</td> |
| <td align="right">516,365</td> |
| <td align="right">239,246</td> |
| <td align="right">253,791</td> |
| <td align="right">288,997</td> |
| </tr> |
| <tr class="a"> |
| <td>Log4j 2: Loggers mixed sync/async</td> |
| <td align="right">2,454,358</td> |
| <td align="right">839,394</td> |
| <td align="right">854,578</td> |
| <td align="right">597,913</td> |
| <td align="right">261,003</td> |
| <td align="right">216,863</td> |
| <td align="right">218,937</td> |
| </tr> |
| <tr class="b"> |
| <td>Log4j 2: Async Appender</td> |
| <td align="right">1,713,429</td> |
| <td align="right">603,019</td> |
| <td align="right">331,506</td> |
| <td align="right">149,408</td> |
| <td align="right">86,107</td> |
| <td align="right">45,529</td> |
| <td align="right">23,980</td> |
| </tr> |
| <tr class="a"> |
| <td>Log4j1: Async Appender</td> |
| <td align="right">2,239,664</td> |
| <td align="right">494,470</td> |
| <td align="right">221,402</td> |
| <td align="right">109,314</td> |
| <td align="right">60,580</td> |
| <td align="right">31,706</td> |
| <td align="right">14,072</td> |
| </tr> |
| <tr class="b"> |
| <td>Logback: Async Appender</td> |
| <td align="right">2,206,907</td> |
| <td align="right">624,082</td> |
| <td align="right">307,500</td> |
| <td align="right">160,096</td> |
| <td align="right">85,701</td> |
| <td align="right">43,422</td> |
| <td align="right">21,303</td> |
| </tr> |
| <tr class="a"> |
| <td>Log4j 2: Synchronous</td> |
| <td align="right">273,536</td> |
| <td align="right">136,523</td> |
| <td align="right">67,609</td> |
| <td align="right">34,404</td> |
| <td align="right">15,373</td> |
| <td align="right">7,903</td> |
| <td align="right">4,253</td> |
| </tr> |
| <tr class="b"> |
| <td>Log4j1: Synchronous</td> |
| <td align="right">326,894</td> |
| <td align="right">105,591</td> |
| <td align="right">57,036</td> |
| <td align="right">30,511</td> |
| <td align="right">13,900</td> |
| <td align="right">7,094</td> |
| <td align="right">3,509</td> |
| </tr> |
| <tr class="a"> |
| <td>Logback: Synchronous</td> |
| <td align="right">178,063</td> |
| <td align="right">65,000</td> |
| <td align="right">34,372</td> |
| <td align="right">16,903</td> |
| <td align="right">8,334</td> |
| <td align="right">3,985</td> |
| <td align="right">1,967</td> |
| </tr> |
| |
| </table> |
| <p></p> |
| <p>On Windows 7 (64bit) with JDK1.7.0_11, 2-core Intel i5-3317u CPU |
| @1.70Ghz with hyperthreading switched on (4 virtual cores):</p> |
| <table border="0" class="bodyTable"><caption align="top">Throughput per thread in messages/second |
| </caption> |
| <tr class="a"> |
| <th>Logger</th> |
| <th>1 thread</th> |
| <th>2 threads</th> |
| <th>4 threads</th> |
| <th>8 threads</th> |
| <th>16 threads</th> |
| <th>32 threads</th> |
| </tr> |
| <tr class="b"> |
| <td>Log4j 2: Loggers all asynchronous</td> |
| <td align="right">1,715,344</td> |
| <td align="right">928,951</td> |
| <td align="right">1,045,265</td> |
| <td align="right">1,509,109</td> |
| <td align="right">1,708,989</td> |
| <td align="right">773,565</td> |
| </tr> |
| <tr class="a"> |
| <td>Log4j 2: Loggers mixed sync/async</td> |
| <td align="right">571,099</td> |
| <td align="right">1,204,774</td> |
| <td align="right">1,632,204</td> |
| <td align="right">1,368,041</td> |
| <td align="right">462,093</td> |
| <td align="right">908,529</td> |
| </tr> |
| <tr class="b"> |
| <td>Log4j 2: Async Appender</td> |
| <td align="right">1,236,548</td> |
| <td align="right">1,006,287</td> |
| <td align="right">511,571</td> |
| <td align="right">302,230</td> |
| <td align="right">160,094</td> |
| <td align="right">60,152</td> |
| </tr> |
| <tr class="a"> |
| <td>Log4j1: Async Appender</td> |
| <td align="right">1,373,195</td> |
| <td align="right">911,657</td> |
| <td align="right">636,899</td> |
| <td align="right">406,405</td> |
| <td align="right">202,777</td> |
| <td align="right">162,964</td> |
| </tr> |
| <tr class="b"> |
| <td>Logback: Async Appender</td> |
| <td align="right">1,979,515</td> |
| <td align="right">783,722</td> |
| <td align="right">582,935</td> |
| <td align="right">289,905</td> |
| <td align="right">172,463</td> |
| <td align="right">133,435</td> |
| </tr> |
| <tr class="a"> |
| <td>Log4j 2: Synchronous</td> |
| <td align="right">281,250</td> |
| <td align="right">225,731</td> |
| <td align="right">129,015</td> |
| <td align="right">66,590</td> |
| <td align="right">34,401</td> |
| <td align="right">17,347</td> |
| </tr> |
| <tr class="b"> |
| <td>Log4j1: Synchronous</td> |
| <td align="right">147,824</td> |
| <td align="right">72,383</td> |
| <td align="right">32,865</td> |
| <td align="right">18,025</td> |
| <td align="right">8,937</td> |
| <td align="right">4,440</td> |
| </tr> |
| <tr class="a"> |
| <td>Logback: Synchronous</td> |
| <td align="right">149,811</td> |
| <td align="right">66,301</td> |
| <td align="right">32,341</td> |
| <td align="right">16,962</td> |
| <td align="right">8,431</td> |
| <td align="right">3,610</td> |
| </tr> |
| |
| </table> |
| |
| </div><div class="section"><h4>Throughput of Logging With Location (includeLocation="true")<a name="Throughput_of_Logging_With_Location_includeLocationtrue"></a></h4> |
| <p>On Solaris 10 (64bit) with JDK1.7.0_06, 4-core Xeon X5570 dual CPU |
| @2.93Ghz with hyperthreading switched off (8 virtual cores):</p> |
| <table border="0" class="bodyTable"><caption align="top">Throughput in log messages/second |
| per thread</caption> |
| <tr class="a"> |
| <th>Logger (Log4j 2)</th> |
| <th>1 thread</th> |
| <th>2 threads</th> |
| <th>4 threads</th> |
| <th>8 threads</th> |
| </tr> |
| <tr class="b"> |
| <td>Loggers all asynchronous</td> |
| <td align="right">75,862</td> |
| <td align="right">88,775</td> |
| <td align="right">80,240</td> |
| <td align="right">68,077</td> |
| </tr> |
| <tr class="a"> |
| <td>Loggers mixed sync/async</td> |
| <td align="right">61,993</td> |
| <td align="right">66,164</td> |
| <td align="right">55,735</td> |
| <td align="right">52,843</td> |
| </tr> |
| <tr class="b"> |
| <td>Async Appender</td> |
| <td align="right">47,033</td> |
| <td align="right">52,426</td> |
| <td align="right">50,882</td> |
| <td align="right">36,905</td> |
| </tr> |
| <tr class="a"> |
| <td>Synchronous</td> |
| <td align="right">31,054</td> |
| <td align="right">33,175</td> |
| <td align="right">29,791</td> |
| <td align="right">23,628</td> |
| </tr> |
| |
| </table> |
| <p>As expected, logging location information |
| has a large performance impact. Asynchronous loggers are 4 - 20 |
| times slower, while synchronous loggers are 1.3 - 5 times slower. |
| However, if you do need location information, |
| asynchronous logging will still be faster than synchronous logging.</p> |
| |
| <a name="Latency"></a> |
| </div><div class="section"><h4>Latency<a name="Latency"></a></h4> |
| <p>Latency tests are done by logging at |
| less than saturation, measuring how long a call to Logger.log |
| takes to return. After each call to Logger.log, the test waits |
| for 10 microseconds * threadCount before continuing. |
| Each thread logs 5 million messages. |
| </p> |
| <p>All the latency measurements below are results of tests run |
| on Solaris 10 (64bit) with JDK1.7.0_06, 4-core Xeon X5570 dual CPU |
| @2.93Ghz with hyperthreading switched on (16 virtual cores).</p> |
| <p><img src="../images/async-latency-histogram-64-threads.png" alt="" /></p> |
| <p>Note that this is log-scale, not linear. |
| The above graph compares the latency distributions of |
| an asynchronous logger and a Log4j 1.2.17 Async Appender. |
| This shows the latency of one thread |
| during a test where 64 threads are logging in parallel. |
| The test was run once for the async logger and once for the |
| async appender.</p> |
| <table border="0" class="bodyTable"><caption align="top">Latency of a call to Logger.log() in nanoseconds</caption> |
| <tr class="a"> |
| <th></th> |
| <th colspan="2">Average latency</th> |
| <th colspan="2">99% observations |
| less than</th> |
| <th colspan="2">99.99% |
| observations less than</th> |
| </tr> |
| <tr class="b"> |
| <th></th> |
| <th>1 thread</th> |
| <th>64 threads</th> |
| <th>1 thread</th> |
| <th>64 threads</th> |
| <th>1 thread</th> |
| <th>64 threads</th> |
| </tr> |
| <tr class="a"> |
| <td>Log4j 2: Loggers all async</td> |
| <td align="right">677</td> |
| <td align="right">4,135</td> |
| <td align="right">1,638</td> |
| <td align="right">4,096</td> |
| <td align="right">8,192</td> |
| <td align="right">16,128</td> |
| </tr> |
| <tr class="b"> |
| <td>Log4j 2: Loggers mixed |
| sync/async</td> |
| <td align="right">648</td> |
| <td align="right">4,873</td> |
| <td align="right">1,228</td> |
| <td align="right">4,096</td> |
| <td align="right">8,192</td> |
| <td align="right">16,384</td> |
| </tr> |
| <tr class="a"> |
| <td>Log4j 2: Async Appender</td> |
| <td align="right">2,423</td> |
| <td align="right">2,117,722</td> |
| <td align="right">4,096</td> |
| <td align="right">67,108,864</td> |
| <td align="right">16,384</td> |
| <td align="right">268,435,456</td> |
| </tr> |
| <tr class="b"> |
| <td>Log4j1: Async Appender</td> |
| <td align="right">1,562</td> |
| <td align="right">1,781,404</td> |
| <td align="right">4,096</td> |
| <td align="right">109,051,904</td> |
| <td align="right">16,384</td> |
| <td align="right">268,435,456</td> |
| </tr> |
| <tr class="a"> |
| <td>Logback: Async Appender</td> |
| <td align="right">2,123</td> |
| <td align="right">2,079,020</td> |
| <td align="right">3,276</td> |
| <td align="right">67,108,864</td> |
| <td align="right">14,745</td> |
| <td align="right">268,435,456</td> |
| </tr> |
| |
| </table> |
| <p> |
| The latency comparison graph below is also log-scale, |
| and shows the average latency of asynchronous loggers and |
| ArrayBlockingQueue-based asynchronous appenders |
| in scenarios with more and more threads running in parallel. |
| Up to 8 threads asynchronous appenders have comparable |
| average latency, two or three times that of asynchronous loggers. |
| With more threads, the average latency of |
| asynchronous appenders is orders of magnitude larger than |
| asynchronous loggers. |
| </p> |
| <p><img src="../images/async-average-latency.png" alt="" /></p> |
| <p> |
| Applications interested in low latency often care not only about |
| average latency, but also about worst-case latency. |
| The graph below shows that asynchronous loggers also do |
| better when comparing the maximum latency of 99.99% of |
| observations with other logging methods. |
| When increasing the number of threads |
| the vast majority of latency measurements for asynchronous |
| loggers stay in the 10-20 microseconds range |
| where Asynchronous Appenders start experiencing many |
| latency spikes in the 100 millisecond range, a difference of |
| four orders of magnitude. |
| </p> |
| <p> |
| <img src="../images/async-max-latency-99.99pct.png" alt="" /> |
| </p> |
| |
| <a name="RandomAccessFileAppenderPerformance"></a> |
| </div><div class="section"><h4>FileAppender vs. RandomAccessFileAppender<a name="FileAppender_vs._RandomAccessFileAppender"></a></h4> |
| <p>The appender comparison below was done with <i>synchronous loggers</i>. |
| </p> |
| <p>On Windows 7 (64bit) with JDK1.7.0_11, 2-core Intel i5-3317u CPU |
| @1.70Ghz with hyperthreading switched on (4 virtual cores):</p> |
| <table border="0" class="bodyTable"><caption align="top">Throughput per thread in messages/second |
| </caption> |
| <tr class="a"> |
| <th>Appender</th> |
| <th>1 thread</th> |
| <th>2 threads</th> |
| <th>4 threads</th> |
| <th>8 threads</th> |
| </tr> |
| <tr class="b"> |
| <td>RandomAccessFileAppender</td> |
| <td align="right">250,438</td> |
| <td align="right">169,939</td> |
| <td align="right">109,074</td> |
| <td align="right">58,845</td> |
| </tr> |
| <tr class="a"> |
| <td>FileAppender</td> |
| <td align="right">186,695</td> |
| <td align="right">118,587</td> |
| <td align="right">57,012</td> |
| <td align="right">28,846</td> |
| </tr> |
| <tr class="b"> |
| <td>RollingRandomAccessFileAppender</td> |
| <td align="right">278,369</td> |
| <td align="right">213,176</td> |
| <td align="right">125,300</td> |
| <td align="right">63,103</td> |
| </tr> |
| <tr class="a"> |
| <td>RollingFileAppender</td> |
| <td align="right">182,518</td> |
| <td align="right">114,690</td> |
| <td align="right">55,147</td> |
| <td align="right">28,153</td> |
| </tr> |
| |
| </table> |
| <p>On Solaris 10 (64bit) with JDK1.7.0_06, 4-core dual Xeon X5570 CPU |
| @2.93GHz with hyperthreading switched off (8 virtual cores):</p> |
| <table border="0" class="bodyTable"><caption align="top">Throughput per thread in messages/second |
| </caption> |
| <tr class="a"> |
| <th>Appender</th> |
| <th>1 thread</th> |
| <th>2 threads</th> |
| <th>4 threads</th> |
| <th>8 threads</th> |
| </tr> |
| <tr class="b"> |
| <td>RandomAccessFileAppender</td> |
| <td align="right">240,760</td> |
| <td align="right">128,713</td> |
| <td align="right">66,555</td> |
| <td align="right">30,544</td> |
| </tr> |
| <tr class="a"> |
| <td>FileAppender</td> |
| <td align="right">172,517</td> |
| <td align="right">106,587</td> |
| <td align="right">55,885</td> |
| <td align="right">25,675</td> |
| </tr> |
| <tr class="b"> |
| <td>RollingRandomAccessFileAppender</td> |
| <td align="right">228,491</td> |
| <td align="right">135,355</td> |
| <td align="right">69,277</td> |
| <td align="right">32,484</td> |
| </tr> |
| <tr class="a"> |
| <td>RollingFileAppender</td> |
| <td align="right">186,422</td> |
| <td align="right">97,737</td> |
| <td align="right">55,766</td> |
| <td align="right">25,097</td> |
| </tr> |
| |
| </table> |
| </div></div> |
| <!-- <a name="PerformanceTuning" /> |
| <subsection name="Async Logger Performance Tuning"> |
| <p>While the default settings should give good results out |
| of the box, you may want to change settings to improve |
| your logging throughput and/or latency. |
| We suggest the following steps for tuning your logging performance:</p> |
| <ol> |
| <li>Create a base line by running the performance tests in your environment.</li> |
| <li>Change a parameter (e.g. WaitStrategy or RingBufferSize) and |
| run the tests again. Check performance results.</li> |
| <li>Repeat (2) until you find a parameter combination that gives acceptable performance.</li> |
| </ol> |
| <p>Use the following command to run the performance tests:</p> |
| <blockquote> |
| <tt>java -cp log4j-async-2.0-tests.jar:log4j-async-2.0.jar:disruptor-3.0.0.jar:log4j-api-2.0.jar:log4j-core-2.0.jar \<br /> |
| [-DWaitStrategy=Sleep] [-DRingBufferSize=262144] org.apache.logging.log4j.async.perftest.PerfTestDriver [path-to-java] [repeats]</tt> |
| <br /><br /> |
| [<b>WaitStrategy</b>] is an optional system property with valid values "Block", "Sleep", or "Yield". |
| Details are documented under "System Properties to configure ... loggers". |
| <br /> |
| [<b>RingBufferSize</b>] is an optional system property with an integer value of at least 128. |
| Details are documented under "System Properties to configure ... loggers". |
| <br /> |
| [<b>path-to-java</b>] is an optional parameter that is the full |
| path to the "java" executable. Specify this if just running |
| "java" in the current directory does not specify the version of |
| java that you want to test with. |
| <br /> |
| [<b>repeats</b>] is an optional parameter that specifies how often |
| each test is repeated. The default is 5. |
| </blockquote> |
| |
| <p>For reference, below are some of the numbers we used to |
| determine the default settings. (Solaris 10 (64bit), 2.93GHz Xeon X5570 with JDK1.7.0_06):</p> |
| <table> |
| <tr> |
| <th>Logger</th> |
| <th>WaitStrategy</th> |
| <th>1 thread</th> |
| <th>2 threads</th> |
| <th>4 threads</th> |
| <th>8 threads</th> |
| </tr> |
| <tr> |
| <td rowspan="3" valign="top">All Async System Clock</td> |
| <td align="center">Block</td> |
| <td align="right">1,717,261</td> |
| <td align="right">727,075</td> |
| <td align="right">263,760</td> |
| <td align="right">150,533</td> |
| </tr> |
| <tr> |
| <td align="center">Sleep</td> |
| <td align="right">1,568,623</td> |
| <td align="right">948,653</td> |
| <td align="right">629,951</td> |
| <td align="right">651,340</td> |
| </tr> |
| <tr> |
| <td align="center">Yield</td> |
| <td align="right">1,618,103</td> |
| <td align="right">884,314</td> |
| <td align="right">628,008</td> |
| <td align="right">675,879</td> |
| </tr> |
| <tr> |
| <td rowspan="3" valign="top">All Async Cached Clock</td> |
| <td align="center">Block</td> |
| <td align="right">2,771,734</td> |
| <td align="right">642,899</td> |
| <td align="right">331,003</td> |
| <td align="right">172,877</td> |
| </tr> |
| <tr> |
| <td align="center">Sleep</td> |
| <td align="right">2,393,901</td> |
| <td align="right">1,211,425</td> |
| <td align="right">770,416</td> |
| <td align="right">632,361</td> |
| </tr> |
| <tr> |
| <td align="center">Yield</td> |
| <td align="right">2,331,763</td> |
| <td align="right">1,132,529</td> |
| <td align="right">684,109</td> |
| <td align="right">671,957</td> |
| </tr> |
| <tr> |
| <td rowspan="3" valign="top">Mixed Async</td> |
| <td align="center">Block</td> |
| <td align="right">1,347,853</td> |
| <td align="right">443,652</td> |
| <td align="right">251,433</td> |
| <td align="right">136,152</td> |
| </tr> |
| <tr> |
| <td align="center">Sleep</td> |
| <td align="right">1,371,511</td> |
| <td align="right">567,829</td> |
| <td align="right">407,676</td> |
| <td align="right">408,071</td> |
| </tr> |
| <tr> |
| <td align="center">Yield</td> |
| <td align="right">1,360,267</td> |
| <td align="right">675,570</td> |
| <td align="right">389,609</td> |
| <td align="right">391,969</td> |
| </tr> |
| <caption align="top">Throughput in log messages/second per thread</caption> |
| </table> |
| </subsection> --> |
| <a name="UnderTheHood"></a> |
| <div class="section"><h3>Under The Hood<a name="Under_The_Hood"></a></h3> |
| <p> |
| Asynchronous Loggers are implemented using the |
| <a class="externalLink" href="http://lmax-exchange.github.com/disruptor/">LMAX Disruptor</a> |
| inter-thread messaging library. From the LMAX web site: |
| </p> |
| <blockquote> |
| <p>... using queues to pass |
| data between stages of the system was |
| introducing latency, so we |
| focused on optimising this area. |
| The Disruptor is the result of our research and |
| testing. We found that cache misses at the |
| CPU-level, and locks requiring kernel |
| arbitration are both extremely costly, so we created a |
| framework which has "mechanical sympathy" for |
| the hardware it's running on, and that's lock-free. |
| </p> |
| </blockquote> |
| |
| <p> |
| LMAX Disruptor internal performance comparisons with |
| <tt>java.util.concurrent.ArrayBlockingQueue</tt> |
| can be found |
| <a class="externalLink" href="https://github.com/LMAX-Exchange/disruptor/wiki/Performance-Results"> |
| here</a>. |
| </p> |
| </div> |
| </div> |
| |
| |
| </td> |
| </tr> |
| </table> |
| </div> |
| |
| <div class="footer"> |
| <p>Copyright © 1999-2014 <a class="external" href="http://www.apache.org">Apache Software Foundation</a>. All Rights Reserved.</p> |
| <p>Apache Logging, Apache Log4j, Log4j, Apache, the Apache feather logo, and the Apache Logging project logo are trademarks of The Apache Software Foundation.</p> |
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