[
https://issues.apache.org/jira/browse/WAGON-537?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Olaf Otto updated WAGON-537:
----------------------------
Description:
We are using maven for build process automation with docker. This sometimes
involves uploading and downloading artifacts with a few gigabytes in size.
Here, maven's transfer speed is consistently and reproducibly slow. For
instance, an artifact with 7,5 GB in size took almost two hours to transfer in
spite of a 100 MB/s connection with respective reproducible download speed from
the remote nexus artifact repository when using a browser to download. The same
is true when uploding such an artifact.
I have investigated the issue using JProfiler. The result shows an issue in
AbstractWagon's transfer( Resource resource, InputStream input, OutputStream
output, int requestType, long maxSize ) method used for remote artifacts and
the same issue in AbstractHttpClientWagon#writeTo(OutputStream).
Here, the input stream is read in a loop using a 4 Kb buffer. Whenever data is
received, the received data is pushed to downstream listeners via
fireTransferProgress. These listeners (or rather consumers) perform expensive
tasks.
Now, the underlying InputStream implementation used in transfer will return
calls to read(buffer, offset, length) as soon as *some* data is available. That
is, fireTransferProgress may well be invoked with an average number of bytes
less than half the buffer capacity (this varies with the underlying network and
hardware architecture). Consequently, fireTransferProgress is invoked *millions
of times* for large files. As this is a blocking operation, the time spent in
fireTransferProgress dominates and drastically slows down the transfers by at
least one order of magnitude.
!wagon-issue.png!
In our case, we found download speed reduced from a theoretical optimum of ~80
seconds to to more than 3200 seconds.
>From an architectural perspective, I would not want to make the consumers /
>listeners invoked via fireTransferProgress aware of their potential impact on
>download speed, but rather refactor the transfer method such that it uses a
>buffer strategy reducing the the number of fireTransferProgress invocations.
>This should be done with regard to the expected file size of the transfer,
>such that fireTransferProgress is invoked often enough but not to frequent.
was:
We are using maven for build process automation with docker. This sometimes
involves downloading images with a few gigabytes in size. Here, maven's
download speed is consistently and reproducibly slow. For instance, an artifact
with 7,5 GB in size took almost two hours to transfer in spite of a 100 MB/s
connection with respective reproducible download speed from the remote nexus
artifact repository when using a browser to download.
I have investigated the issue using JProfiler. The result clearly shows a
significant issue in AbstractWagon's transfer( Resource resource, InputStream
input, OutputStream output, int requestType, long maxSize ) method used for
remote artifacts.
Here, the input stream is read in a loop using a 4 Kb buffer. Whenever data is
received, the received data is pushed to downstream listeners via
fireTransferProgress. These listeners (or rather consumers) perform expensive
tasks such as checksumming or printing to console.
Now, the underlying InputStream implementation used in transfer will return
calls to read(bugger, offset, length) as soon as *some* data is available. That
is, fireTransferProgress is invoked with an average number of bytes less than
half the buffer capacity (this varies with the underlying network and hardware
architecture). Consequently, fireTransferProgress is invoked *millions of
times* for large files. As this is a blocking operation, the time spent in
fireTransferProgress dominates and drastically slows down the transfer by at
least one order of magnitude.
!wagon-issue.png!
In our case, we found download speed reduced from a theoretical optimum of ~80
seconds to to more than 3200 seconds.
>From an architectural perspective, I would not want to make the consumers /
>listeners invoked via fireTransferProgress aware of their potential impact on
>download speed, but rather refactor the transfer method such that it uses a
>buffer strategy reducing the the number of fireTransferProgress invocations.
>This should be done with regard to the expected file size of the transfer,
>such that fireTransferProgress is invoked often enough but not to frequent.
I have implemented a solution and transfer speed went up more than one order of
magnitude. I will provide a pull request asap.
Summary: Maven transfer speed of large artifacts is slow due to
unsuitable buffer strategy (was: Maven download speed of large artifacts is
slow due to unsuitable buffer strategy for remote Artifacts in AbstractWagon)
> Maven transfer speed of large artifacts is slow due to unsuitable buffer
> strategy
> ---------------------------------------------------------------------------------
>
> Key: WAGON-537
> URL: https://issues.apache.org/jira/browse/WAGON-537
> Project: Maven Wagon
> Issue Type: Improvement
> Components: wagon-provider-api
> Affects Versions: 3.2.0
> Environment: Windows 10, JDK 1.8, Nexus Artifact store > 100MB/s
> network connection.
> Reporter: Olaf Otto
> Assignee: Michael Osipov
> Priority: Major
> Labels: perfomance
> Attachments: wagon-issue.png
>
>
> We are using maven for build process automation with docker. This sometimes
> involves uploading and downloading artifacts with a few gigabytes in size.
> Here, maven's transfer speed is consistently and reproducibly slow. For
> instance, an artifact with 7,5 GB in size took almost two hours to transfer
> in spite of a 100 MB/s connection with respective reproducible download speed
> from the remote nexus artifact repository when using a browser to download.
> The same is true when uploding such an artifact.
> I have investigated the issue using JProfiler. The result shows an issue in
> AbstractWagon's transfer( Resource resource, InputStream input, OutputStream
> output, int requestType, long maxSize ) method used for remote artifacts and
> the same issue in AbstractHttpClientWagon#writeTo(OutputStream).
> Here, the input stream is read in a loop using a 4 Kb buffer. Whenever data
> is received, the received data is pushed to downstream listeners via
> fireTransferProgress. These listeners (or rather consumers) perform expensive
> tasks.
> Now, the underlying InputStream implementation used in transfer will return
> calls to read(buffer, offset, length) as soon as *some* data is available.
> That is, fireTransferProgress may well be invoked with an average number of
> bytes less than half the buffer capacity (this varies with the underlying
> network and hardware architecture). Consequently, fireTransferProgress is
> invoked *millions of times* for large files. As this is a blocking operation,
> the time spent in fireTransferProgress dominates and drastically slows down
> the transfers by at least one order of magnitude.
> !wagon-issue.png!
> In our case, we found download speed reduced from a theoretical optimum of
> ~80 seconds to to more than 3200 seconds.
> From an architectural perspective, I would not want to make the consumers /
> listeners invoked via fireTransferProgress aware of their potential impact on
> download speed, but rather refactor the transfer method such that it uses a
> buffer strategy reducing the the number of fireTransferProgress invocations.
> This should be done with regard to the expected file size of the transfer,
> such that fireTransferProgress is invoked often enough but not to frequent.
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
