Problem trying to download very large data sets
Chris Jones reports that attempts to move very large data files from Metacat to
Morpho often apparently 'hang' after several hundred kilobytes has been transferred.
#1 Updated by Dan Higgins over 17 years ago
I created a new data package containing one of the PISCO large CODAR data files
(~47MB). Submitting it to Metacat seemed to work fine (~10 secs of so from
within the NCEAS local net). Examination of the directory where data is stored
on ecoinfo indicates that the entire file was copied. Thus the upload of very
large files seems to work OK.
Download, however, is where the problem seems to occur. I deleted the local copy
and then attempted to Synchronize from Metacat. The process seems to start but
then hangs (with the CPU at near 100%) after 3-25MB have been sent. (Estimate
based on size of file in cache). I waited 15-20 minutes and no recovery seemed
Could this be a problem with MetaCat or Apache?
#4 Updated by Dan Higgins over 17 years ago
This problem with large data sets is apparently linked to the alternate
HTTPClient package being used in Morpho. If one removes that code to sets the
protocol handler and just uses the default http handler from Sun for downloads,
there is no problem downloading large data files! (Of course, there is a problem
uploading large files!)
There appears to have been no updates to the HTTPClient code since May 2001, so
there is no a newer version.
Also, same problems are seen with Java 1.3 and 1.4
#5 Updated by Dan Higgins over 17 years ago
A test using Morpho 1.1 indicates that the downloading of a large test dataset
(a single 45MB Pisco data set) works fine with the current HTTPClient, but the
same dataset hangs while trying to download with Morpho 1.2. An investigation
which examined the differeces between the two versions showed that the sychonize
code in the newer version runs inside a SwingWorker threan. If one removes that
thread and simply runs the synch code 'in-line' the download works OK!!!!
It would thus appear that there is a thread problem with the HTTPClient code
(since the same problem does not occur if one uses Sun's version). One 'fix'
would be to simply not run the metacat downloads in a separate thread, but that
leaves Morpho 'unresponsive' during downloads. This is not a big problem if
working within NCEAS but with a T1 connection from the ourside, one might have
to wait a number of minutes to download a 50 MB data file.
#6 Updated by Dan Higgins over 17 years ago
Some further investigation seems to confirm that we have a 'thread' problem in
the HTTPClient package. Downloading a large data package seemed to hang at
different places during the download. It finally occurred to me that this might
be due to the backgound timer that checks for network connections by 'pinging'
And, sure enough, if one disables the periodic checks for network availablity,
then the download of large data file works!!!!!!!!!!!!!!!
So a quick fix (hack) is to simply check for network availabiity at start up and
not continually poll during a session.
Of course it would be better to figure out where the threading problem is inside
HTTPClient, but that may take some time. [Note that since the system works with
Sun's http handler, I assume there is no inherent reason that we cannot have two
threads connecting to metacat at the same time.]
This problem indicates that any attempt to have two threads talking to metacat
at the same time will probably cause a problem. Morpho threading allows, for
example, one to start a query while data is being downloaded. This probably will
not work right while this threading bug exists in HTTPClient.
#7 Updated by Dan Higgins about 17 years ago
added a flag in the Morpho class that keeps track of when a connection to
metacat is busy. The doPing method here checks that flag. Synchronized
'getMetacatInputStream' method in Morpho class to avoid threading problems with
HTTPClient. Also added flags in MetacatDataStore methods to turn off the
'doPing' method while any streams from metacat are open.
Thus, problem with downloading large data sets has been eliminated, although the
root cause of threading problem has not been determined.