@Aljoscha Shading takes a few minutes for a full build; you can see this quite easily by looking at the compile step in the misc profile <https://api.travis-ci.org/v3/job/572560060/log.txt>; all modules that longer than a fraction of a section are usually caused by shading lots of classes. Note that I cannot tell you how much of this is spent on relocations, and how much on writing the jar.

Personally, I'd very much like us to move all shading to flink-shaded; this would finally allows us to use newer maven versions without needing cumbersome workarounds for flink-dist. However, this isn't a trivial affair in some cases; IIRC calcite could be difficult to handle.

On another note, this would also simplify switching the main repo to another build system, since you would no longer had to deal with relocations, just packaging + merging NOTICE files.

@BowenLi I disagree, flink-shaded does not include any tests,  API compatibility checks, checkstyle, layered shading (e.g., flink-runtime and flink-dist, where both relocate dependencies and one is bundled by the other), and, most importantly, CI (and really, without CI being covered in a PoC there's nothing to discuss).

On 16/08/2019 15:13, Aljoscha Krettek wrote:
Speaking of flink-shaded, do we have any idea what the impact of shading is on 
the build time? We could get rid of shading completely in the Flink main 
repository by moving everything that we shade to flink-shaded.


On 16. Aug 2019, at 14:58, Bowen Li <bowenl...@gmail.com> wrote:

+1 to Till's points on #2 and #5, especially the potential non-disruptive,
gradual migration approach if we decide to go that route.

To add on, I want to point it out that we can actually start with
flink-shaded project [1] which is a perfect candidate for PoC. It's of much
smaller size, totally isolated from and not interfered with flink project
[2], and it actually covers most of our practical feature requirements for
a build tool - all making it an ideal experimental field.

[1] https://github.com/apache/flink-shaded
[2] https://github.com/apache/flink

On Fri, Aug 16, 2019 at 4:52 AM Till Rohrmann <trohrm...@apache.org> wrote:

For the sake of keeping the discussion focused and not cluttering the
discussion thread I would suggest to split the detailed reporting for
reusing JVMs to a separate thread and cross linking it from here.


On Fri, Aug 16, 2019 at 1:36 PM Chesnay Schepler <ches...@apache.org>


TL;DR: table-planner is a good candidate for enabling fork reuse right
away, while flink-tests has the potential for huge savings, but we have
to figure out some issues first.

Build link: https://travis-ci.org/zentol/flink/builds/572659220

4/8 profiles failed.

No speedup in libraries, python, blink_planner, 7 minutes saved in
libraries (table-planner).

The kafka and connectors profiles both fail in kafka tests due to
producer leaks, and no speed up could be confirmed so far:

java.lang.AssertionError: Detected producer leak. Thread name:
kafka-producer-network-thread | producer-239
        at org.junit.Assert.fail(Assert.java:88)



The tests profile failed due to various errors in migration tests:

junit.framework.AssertionFailedError: Did not see the expected
results within time limit.

*However*, a normal tests run takes 40 minutes, while this one above
failed after 19 minutes and is only missing the migration tests (which
currently need 6-7 minutes). So we could save somewhere between 15 to 20
minutes here.

Finally, the misc profiles fails in YARN:

        at org.apache.flink.yarn.YARNITCase.setup(YARNITCase.java:64)

No significant speedup could be observed in other modules; for
flink-yarn-tests we can maybe get a minute or 2 out of it.

On 16/08/2019 10:43, Chesnay Schepler wrote:
There appears to be a general agreement that 1) should be looked into;
I've setup a branch with fork reuse being enabled for all tests; will
report back the results.

On 15/08/2019 09:38, Chesnay Schepler wrote:
Hello everyone,

improving our build times is a hot topic at the moment so let's
discuss the different ways how they could be reduced.

       Current state:

First up, let's look at some numbers:

1 full build currently consumes 5h of build time total ("total
time"), and in the ideal case takes about 1h20m ("run time") to
complete from start to finish. The run time may fluctuate of course
depending on the current Travis load. This applies both to builds on
the Apache and flink-ci Travis.

At the time of writing, the current queue time for PR jobs (reminder:
running on flink-ci) is about 30 minutes (which basically means that
we are processing builds at the rate that they come in), however we
are in an admittedly quiet period right now.
2 weeks ago the queue times on flink-ci peaked at around 5-6h as
everyone was scrambling to get their changes merged in time for the
feature freeze.

(Note: Recently optimizations where added to ci-bot where pending
builds are canceled if a new commit was pushed to the PR or the PR
was closed, which should prove especially useful during the rush
hours we see before feature-freezes.)

       Past approaches

Over the years we have done rather few things to improve this
situation (hence our current predicament).

Beyond the sporadic speedup of some tests, the only notable reduction
in total build times was the introduction of cron jobs, which
consolidated the per-commit matrix from 4 configurations (different
scala/hadoop versions) to 1.

The separation into multiple build profiles was only a work-around
for the 50m limit on Travis. Running tests in parallel has the
obvious potential of reducing run time, but we're currently hitting a
hard limit since a few modules (flink-tests, flink-runtime,
flink-table-planner-blink) are so loaded with tests that they nearly
consume an entire profile by themselves (and thus no further
splitting is possible).

The rework that introduced stages, at the time of introduction, did
also not provide a speed up, although this changed slightly once more
profiles were added and some optimizations to the caching have been

Very recently we modified the surefire-plugin configuration for
flink-table-planner-blink to reuse JVM forks for IT cases, providing
a significant speedup (18 minutes!). So far we have not seen any
negative consequences.


This is a list of /all /suggestions for reducing run/total times that
I have seen recently (in other words, they aren't necessarily mine
nor may I agree with all of them).

1. Enable JVM reuse for IT cases in more modules.
     * We've seen significant speedups in the blink planner, and this
       should be applicable for all modules. However, I presume
       a reason why we disabled JVM reuse (information on this would
2. Custom differential build scripts
     * Setup custom scripts for determining which modules might be
       affected by change, and manipulate the splits accordingly. This
       approach is conceptually quite straight-forward, but has limits
       since it has to be pessimistic; i.e. a change in flink-core
       _must_ result in testing all modules.
3. Only run smoke tests when PR is opened, run heavy tests on demand.
     * With the introduction of the ci-bot we now have significantly
       more options on how to handle PR builds. One option could be to
       only run basic tests when the PR is created (which may be only
       modified modules, or all unit tests, or another low-cost
       scheme), and then have a committer trigger other builds (full
       test run, e2e tests, etc...) on demand.
4. Move more tests into cron builds
     * The budget version of 3); move certain tests that are either
       expensive (like some runtime tests that take minutes) or in
       rarely modified modules (like gelly) into cron jobs.
5. Gradle
     * Gradle was brought up a few times for it's built-in support for
       differential builds; basically providing 2) without the
       of maintaining additional scripts.
     * To date no PoC was provided that shows it working in our CI
       environment (i.e., handling splits & caching etc).
     * This is the most disruptive change by a fair margin, as it
       affect the entire project, developers and potentially users (f
       they build from source).
6. CI service
     * Our current artifact caching setup on Travis is basically a
       hack; we're basically abusing the Travis cache, which is meant
       for long-term caching, to ship build artifacts across jobs.
       brittle at times due to timing/visibility issues and on
       the cleanup processes can interfere with running builds. It is
       also not as effective as it could be.
     * There are CI services that provide build artifact caching out
       the box, which could be useful for us.
     * To date, no PoC for using another CI service has been provided.

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