Scala Logging: is LazyLogging blocking or non-blocking?












0















I recently read this article that makes me wonder whether using LazyLogging would create a performance bottleneck.



My question: is Scala Logging's LazyLogging trait blocking or non-blocking?



We log and process a lot of messages and use Akka. So does having just lazy loggers help or hurt when it comes to performance?






scala







share|improve this question

























  • scala-logging is not related to Akka, btw, they are different libraries.

    – Vladimir Matveev
    Nov 14 '18 at 21:12
















0















I recently read this article that makes me wonder whether using LazyLogging would create a performance bottleneck.



My question: is Scala Logging's LazyLogging trait blocking or non-blocking?



We log and process a lot of messages and use Akka. So does having just lazy loggers help or hurt when it comes to performance?






scala







share|improve this question

























  • scala-logging is not related to Akka, btw, they are different libraries.

    – Vladimir Matveev
    Nov 14 '18 at 21:12














0












0








0








I recently read this article that makes me wonder whether using LazyLogging would create a performance bottleneck.



My question: is Scala Logging's LazyLogging trait blocking or non-blocking?



We log and process a lot of messages and use Akka. So does having just lazy loggers help or hurt when it comes to performance?






scala







share|improve this question
















I recently read this article that makes me wonder whether using LazyLogging would create a performance bottleneck.



My question: is Scala Logging's LazyLogging trait blocking or non-blocking?



We log and process a lot of messages and use Akka. So does having just lazy loggers help or hurt when it comes to performance?






scala




scala






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 14 '18 at 23:11









Jeffrey Chung

13.8k62140




13.8k62140










asked Nov 14 '18 at 21:08









AchilleusAchilleus

660418




660418













  • scala-logging is not related to Akka, btw, they are different libraries.

    – Vladimir Matveev
    Nov 14 '18 at 21:12



















  • scala-logging is not related to Akka, btw, they are different libraries.

    – Vladimir Matveev
    Nov 14 '18 at 21:12

















scala-logging is not related to Akka, btw, they are different libraries.

– Vladimir Matveev
Nov 14 '18 at 21:12





scala-logging is not related to Akka, btw, they are different libraries.

– Vladimir Matveev
Nov 14 '18 at 21:12












1 Answer
1






active

oldest

votes


















2














The scala-logging library relies on the SLF4J library, which is an API frontend for various logging libraries. Therefore, whether logging is synchronous or not is completely defined by the actual logging framework that you use. The most prominent and modern ones are Logback and Log4J 2, but there are other, usually older alternatives, like commons-logging, log4j1 or even java.util.Logging (JUL).



So, depending on your backend configuration, your log invocations might be either synchronous or not. For example, Logback has AsyncAppender which acts as an asynchronous frontend for other, potentially blocking appenders; it is also possible for specific appenders to be async as well, e.g. if it is an appender which writes to an external logging aggregation system.






share|improve this answer
























  • Thanks for your response. Does this affect the latency significantly? Using AsyncAppender over synchronous ones? Also are there any drawbacks using AsyncAppender?

    – Achilleus
    Nov 14 '18 at 22:13











  • That's pretty much explained in that documentation page - asynchronicity implies potential issues with flushing and also with overloading the processing queue. There is no universal answer - if it is critical for your application not to block even on logs, and your output sinks for logs can be blocking in synchronous mode (e.g. network socket, slow disk, etc), then you most likely have to use some kind of async appender. Otherwise, you'll have to benchmark and find whether it is okay for your application to block on logging statements or not.

    – Vladimir Matveev
    Nov 14 '18 at 22:31











  • Thanks for your help. Will read up more on that.

    – Achilleus
    Nov 14 '18 at 22:34











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1 Answer
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oldest

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The scala-logging library relies on the SLF4J library, which is an API frontend for various logging libraries. Therefore, whether logging is synchronous or not is completely defined by the actual logging framework that you use. The most prominent and modern ones are Logback and Log4J 2, but there are other, usually older alternatives, like commons-logging, log4j1 or even java.util.Logging (JUL).



So, depending on your backend configuration, your log invocations might be either synchronous or not. For example, Logback has AsyncAppender which acts as an asynchronous frontend for other, potentially blocking appenders; it is also possible for specific appenders to be async as well, e.g. if it is an appender which writes to an external logging aggregation system.






share|improve this answer
























  • Thanks for your response. Does this affect the latency significantly? Using AsyncAppender over synchronous ones? Also are there any drawbacks using AsyncAppender?

    – Achilleus
    Nov 14 '18 at 22:13











  • That's pretty much explained in that documentation page - asynchronicity implies potential issues with flushing and also with overloading the processing queue. There is no universal answer - if it is critical for your application not to block even on logs, and your output sinks for logs can be blocking in synchronous mode (e.g. network socket, slow disk, etc), then you most likely have to use some kind of async appender. Otherwise, you'll have to benchmark and find whether it is okay for your application to block on logging statements or not.

    – Vladimir Matveev
    Nov 14 '18 at 22:31











  • Thanks for your help. Will read up more on that.

    – Achilleus
    Nov 14 '18 at 22:34
















2














The scala-logging library relies on the SLF4J library, which is an API frontend for various logging libraries. Therefore, whether logging is synchronous or not is completely defined by the actual logging framework that you use. The most prominent and modern ones are Logback and Log4J 2, but there are other, usually older alternatives, like commons-logging, log4j1 or even java.util.Logging (JUL).



So, depending on your backend configuration, your log invocations might be either synchronous or not. For example, Logback has AsyncAppender which acts as an asynchronous frontend for other, potentially blocking appenders; it is also possible for specific appenders to be async as well, e.g. if it is an appender which writes to an external logging aggregation system.






share|improve this answer
























  • Thanks for your response. Does this affect the latency significantly? Using AsyncAppender over synchronous ones? Also are there any drawbacks using AsyncAppender?

    – Achilleus
    Nov 14 '18 at 22:13











  • That's pretty much explained in that documentation page - asynchronicity implies potential issues with flushing and also with overloading the processing queue. There is no universal answer - if it is critical for your application not to block even on logs, and your output sinks for logs can be blocking in synchronous mode (e.g. network socket, slow disk, etc), then you most likely have to use some kind of async appender. Otherwise, you'll have to benchmark and find whether it is okay for your application to block on logging statements or not.

    – Vladimir Matveev
    Nov 14 '18 at 22:31











  • Thanks for your help. Will read up more on that.

    – Achilleus
    Nov 14 '18 at 22:34














2












2








2







The scala-logging library relies on the SLF4J library, which is an API frontend for various logging libraries. Therefore, whether logging is synchronous or not is completely defined by the actual logging framework that you use. The most prominent and modern ones are Logback and Log4J 2, but there are other, usually older alternatives, like commons-logging, log4j1 or even java.util.Logging (JUL).



So, depending on your backend configuration, your log invocations might be either synchronous or not. For example, Logback has AsyncAppender which acts as an asynchronous frontend for other, potentially blocking appenders; it is also possible for specific appenders to be async as well, e.g. if it is an appender which writes to an external logging aggregation system.






share|improve this answer













The scala-logging library relies on the SLF4J library, which is an API frontend for various logging libraries. Therefore, whether logging is synchronous or not is completely defined by the actual logging framework that you use. The most prominent and modern ones are Logback and Log4J 2, but there are other, usually older alternatives, like commons-logging, log4j1 or even java.util.Logging (JUL).



So, depending on your backend configuration, your log invocations might be either synchronous or not. For example, Logback has AsyncAppender which acts as an asynchronous frontend for other, potentially blocking appenders; it is also possible for specific appenders to be async as well, e.g. if it is an appender which writes to an external logging aggregation system.







share|improve this answer












share|improve this answer



share|improve this answer










answered Nov 14 '18 at 21:29









Vladimir MatveevVladimir Matveev

69.2k15168212




69.2k15168212













  • Thanks for your response. Does this affect the latency significantly? Using AsyncAppender over synchronous ones? Also are there any drawbacks using AsyncAppender?

    – Achilleus
    Nov 14 '18 at 22:13











  • That's pretty much explained in that documentation page - asynchronicity implies potential issues with flushing and also with overloading the processing queue. There is no universal answer - if it is critical for your application not to block even on logs, and your output sinks for logs can be blocking in synchronous mode (e.g. network socket, slow disk, etc), then you most likely have to use some kind of async appender. Otherwise, you'll have to benchmark and find whether it is okay for your application to block on logging statements or not.

    – Vladimir Matveev
    Nov 14 '18 at 22:31











  • Thanks for your help. Will read up more on that.

    – Achilleus
    Nov 14 '18 at 22:34



















  • Thanks for your response. Does this affect the latency significantly? Using AsyncAppender over synchronous ones? Also are there any drawbacks using AsyncAppender?

    – Achilleus
    Nov 14 '18 at 22:13











  • That's pretty much explained in that documentation page - asynchronicity implies potential issues with flushing and also with overloading the processing queue. There is no universal answer - if it is critical for your application not to block even on logs, and your output sinks for logs can be blocking in synchronous mode (e.g. network socket, slow disk, etc), then you most likely have to use some kind of async appender. Otherwise, you'll have to benchmark and find whether it is okay for your application to block on logging statements or not.

    – Vladimir Matveev
    Nov 14 '18 at 22:31











  • Thanks for your help. Will read up more on that.

    – Achilleus
    Nov 14 '18 at 22:34

















Thanks for your response. Does this affect the latency significantly? Using AsyncAppender over synchronous ones? Also are there any drawbacks using AsyncAppender?

– Achilleus
Nov 14 '18 at 22:13





Thanks for your response. Does this affect the latency significantly? Using AsyncAppender over synchronous ones? Also are there any drawbacks using AsyncAppender?

– Achilleus
Nov 14 '18 at 22:13













That's pretty much explained in that documentation page - asynchronicity implies potential issues with flushing and also with overloading the processing queue. There is no universal answer - if it is critical for your application not to block even on logs, and your output sinks for logs can be blocking in synchronous mode (e.g. network socket, slow disk, etc), then you most likely have to use some kind of async appender. Otherwise, you'll have to benchmark and find whether it is okay for your application to block on logging statements or not.

– Vladimir Matveev
Nov 14 '18 at 22:31





That's pretty much explained in that documentation page - asynchronicity implies potential issues with flushing and also with overloading the processing queue. There is no universal answer - if it is critical for your application not to block even on logs, and your output sinks for logs can be blocking in synchronous mode (e.g. network socket, slow disk, etc), then you most likely have to use some kind of async appender. Otherwise, you'll have to benchmark and find whether it is okay for your application to block on logging statements or not.

– Vladimir Matveev
Nov 14 '18 at 22:31













Thanks for your help. Will read up more on that.

– Achilleus
Nov 14 '18 at 22:34





Thanks for your help. Will read up more on that.

– Achilleus
Nov 14 '18 at 22:34


















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