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From "Sangjin Lee" <sjl...@gmail.com>
Subject Re: [AsyncHttpClient] data collection & instrumentation
Date Tue, 22 Jan 2008 22:42:45 GMT
The modified patch is there on JIRA.  Some follow-up discussions...
I think the current implementation works well, but one thing that's
difficult to do is to collecting timing data.  For example, some of the most
important instrumentation data are things like average response time (from
request start to request complete) and average connect time (from connect
start to connect complete).

Currently the context object that's available to monitoring listeners is the
request object, along with the timestamp of the event itself.  To be able to
compute a response time for a given request, one would need to take the
timestamp from the request start event, associate it with the request, and
store it on the listener.  When the request complete event fires, then one
would need to look up the stored data using the request object as a key to
retrieve the timestamp for the request start event, compute the delta, and
store the delta.

While all this is possible, it has a number of issues, not the least of
which is that one would need to maintain a map of request to start time (as
well as request to connect time).  This would bloat memory as well as other
implications.

A substantially easier solution would be to provide the request start time
and connect start time as part of the information that's passed to the
monitoring listener.  Then listeners could simply compute the diff to get
the elapsed time very easily with no need to maintain maps of any kind.
 This could be either part of the request object itself, or if desirable,
one could consider a separate context or event object that contains this
information.  What do you think?

Thanks,
Sangjin

On Jan 22, 2008 1:33 PM, Sangjin Lee <sjlee0@gmail.com> wrote:

> I took a look at the patch on GERONIMO-3761, and it looks great.  Thanks.
>  I have modified your patch for several things, though, and I'm nearly ready
> to add it to the JIRA report.  Comments about the changes...
> - I rewrote the EventQueue class to use an Executor.  Since the Executor
> implementation provided by the JDK is basically a thread pool associated
> with a task queue, it provides an identical functionality to what was in
> EventQueue.  I think that it is good to use the constructs from
> java.util.concurrent.* whenever it makes sense, and I believe this is one
> of them.
>
> - This change also enables us to remove "synchronized" from
> notifyMonitoringListener().  The notify method will be called very often and
> concurrently, and reducing the lock contention will be important.  Using an
> Executor makes it possible to eliminate synchronization, at least at that
> level.
>
> - I associated a shared thread pool (Executor) for all dispatchers.  I
> think it is desirable for dispatchers to share this thread pool rather than
> each instance of dispatchers creating and maintaining its own thread.
>
> - Renamed EventQueue to EventDispatcher.
>
> - I also moved the monitoring listener list to EventDispatcher.  I also
> used CopyOnWriteArrayList as the implementation for the list.
>  CopyOnWriteArrayList is an ideal choice for this as it is thread safe and
> lock-free.  Also, our use case is heavy read-access but very infrequent
> write-access, which CopyOnWriteArrayList is suitable for.
>
> - I moved the connection_failed notification to before the getSession()
> call.  The getSession() call here always throws an exception (by design),
> and thus notification needs to be done before calling getSession().
>
> - I rewrote the CountingMonitor to use AtomicIntegers.  This should be
> slightly safer.
>
> - I changed the timestamp calls from System.currentTimeMillis() to
> System.nanoTime()/1000000.  The nanoTime() call is more high-res, as
> currentTimeMillis() may be tens of milliseconds accurate on some platforms,
> and thus not suitable for these measurements.
>
> I also have some more follow-up questions, which I'll post soon.
>
> Thanks,
> Sangjin
>
>
> On Jan 17, 2008 10:51 AM, Sangjin Lee <sjlee0@gmail.com> wrote:
>
> > I like your idea of using the event listener as the main way of doing
> > this.  Basically no or multiple listeners would be invoked on a different
> > thread when events occur.
> > The event listener APIs would define those key methods which would
> > contain all the necessary information about the events in an immutable
> > fashion.
> >
> > We could provide a simple adapter that is no op so people can override
> > necessary methods easily.  Also, we could provide one implementation which
> > is a counting listener that does the basic metrics collection.
> >
> > What do you think?
> >
> > Thanks,
> > Sangjin
> >
> > On Jan 17, 2008 2:58 AM, Rick McGuire < rickmcg@gmail.com> wrote:
> >
> > > Thunderbird is playing very strange games with me this morning,
> > > somehow
> > > deleting the original post.   Anyway, here are my comments on this.
> > >
> > > > I'd like to propose changes to enable some basic stat collection
> > > > and/or instrumentation to have visibility into performance of AHC.
> > > >  For a given *AsyncHttpClient*, one might want to know metrics like
> > > >
> > > > - total request count
> > > > - total success count
> > > > - total exception count
> > > > - total timeout count
> > > > - connection attempt count
> > > > - connection failure count
> > > > - connect time average
> > > > - connection close count
> > > > - average response time (as measured from the invocation time to
> > > > having the response ready)
> > > > - and others?
> > > Collection of metric information would, I think, be a good thing.
> > > However, I think we should separate the consolidation of the
> > > information
> > > from the collection.  That is, the client should just have different
> > > types of events for data collection, and the event listener would be
> > > responsible for presenting the information appropriately.
> > >
> > > For example, to create the list above, I'd see the following set of
> > > events needed:
> > >
> > > - request made
> > > - request completed
> > > - request failed
> > > - request timeout
> > > - connection attempt started
> > > - connection failed
> > > - connection closed
> > >
> > > All events would be timestamped, which would allow metrics like
> > > "average
> > > request time" to be calculated.  This set of events would mean the
> > > client would not need to maintain any metric accumulators, and if the
> > > event information is done correctly, would even allow more fine
> > > grained
> > > monitoring (e.g., average connection time for requests to domain
> > > "foo.bar.com").
> > >
> > >
> > > >
> > > > Collecting these metrics should have little effect on the overall
> > > > performance.  There would be an API to access these stats.
> > > >
> > > > I was initially thinking of an IoFilter to consolidate these hooks,
> > > > but I realize some of these metrics are not readily available to an
> > > > IoFilter (e.g. connect-related numbers).  It might be unavoidable to
> > > > spread the instrumentation in a couple of places (IoHandler,
> > > > ConnectFutureListener, etc.).
> > > >
> > > > Taking this one step further, one might think of callbacks or
> > > > listeners for various key events such as connect complete, request
> > > > sent, etc., so callers can provide instrumenting/logging code via
> > > > event notification.  However, I think this should be used
> > > judiciously
> > > > as such injected code may cause havoc.
> > > I think listeners would be the way to go.  This would allow multiple
> > > monitoring types to be attached to the pipe to gather data as needed.
> > > Perhaps the approached used with the javamail API might be of use
> > > here.
> > > The javamail Store APIs have a number of listener events that are
> > > broadcast (new mail arrived, message delete, folder created, etc.).
> > > Because there are similar concerns of havoc, the events get posted to
> > > a
> > > queue, and are dispatched on to a separate thread.  The queue is only
> > > created (and the associated thread) are only created when there are
> > > listeners available to handle the events.  This allows the events to
> > > very low overhead when there are no interested parties and prevents
> > > the
> > > listeners from interfering with normal javamail operations by being
> > > processed on a different thread.
> > >
> > >
> > > >
> > > > Thoughts?  Suggestions?
> > >
> >
> >
>

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