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Set default connection timeout #12016

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@harupy harupy commented May 15, 2024

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Install mlflow from this PR

pip install git+https://github.com/mlflow/mlflow.git@refs/pull/12016/merge

Checkout with GitHub CLI

gh pr checkout 12016

Related Issues/PRs

What changes are proposed in this pull request?

Address #11969 (comment)

How is this PR tested?

  • Existing unit/integration tests
  • New unit/integration tests
  • Manual tests

Does this PR require documentation update?

  • No. You can skip the rest of this section.
  • Yes. I've updated:
    • Examples
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  • Yes. Give a description of this change to be included in the release notes for MLflow users.

What component(s), interfaces, languages, and integrations does this PR affect?

Components

  • area/artifacts: Artifact stores and artifact logging
  • area/build: Build and test infrastructure for MLflow
  • area/deployments: MLflow Deployments client APIs, server, and third-party Deployments integrations
  • area/docs: MLflow documentation pages
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  • rn/none - No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" section
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Signed-off-by: harupy <[email protected]>
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github-actions bot commented May 15, 2024

Documentation preview for 47bd07f will be available when this CircleCI job
completes successfully.

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@github-actions github-actions bot added the rn/none List under Small Changes in Changelogs. label May 15, 2024
Signed-off-by: harupy <[email protected]>
Comment on lines 253 to 254
read request. Default to (60, None) which means 60 seconds for connect and no timeout
for read.
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Suggested change
read request. Default to (60, None) which means 60 seconds for connect and no timeout
for read.
read request. Default to (30, None) which means 30 seconds for connect and no timeout
for read.

Signed-off-by: harupy <[email protected]>
@@ -235,7 +235,7 @@ def cloud_storage_http_request(
backoff_factor=2,
backoff_jitter=1.0,
retry_codes=_TRANSIENT_FAILURE_RESPONSE_CODES,
timeout=None,
timeout=(30, None),
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This seems reasonable. Let's test with a massive model using MPU (Mixtral) on s3 and ADLS to verify.

@harupy harupy requested a review from dbczumar May 16, 2024 05:49
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@harupy A couple questions:

  1. Are we sure this works? @smurching informed that @dakinggg tried something similar, but it didn't resolve the issue that he was facing with ADLS during fine tuning. (@dakinggg can you comment further here?)

  2. What's our retry policy when there's a connection timeout? We need to make sure we're retrying :)

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harupy commented May 16, 2024

@dbczumar

  1. No, we aren't. We need to test this. We can close this PR if we've already tried this and it didn't work :)
  2. Can we do retries retry with exponential backoff on requests.exceptions.ConnectTimeout?
for _ in range(max_attempts):
    try:
        ...
    except requests.exceptions.ConnectTimeout:
        ...

@dbczumar
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  1. Can you work with @dakinggg to test this further / explore alternatives if this doesn't work?
  2. Absolutely - we must do something like this

@harupy
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harupy commented May 16, 2024

@dbczumar We already using retry logic for connection related errors:

"connect": max_retries,

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@harupy @dbczumar

Unfortunately reproducing is quite difficult (we had to run many training runs in order to repro, and never managed to get a standalone uploading script to repro). It also seemed to interact with load (i.e. was possibly worse during the day). I think we were hoping that as part of mitigating this on the mlflow side, we could carry on @smurching attempt to reproduce in a standalone script.

That being said, it did seem that adding the explicit request.close() (mosaicml/composer#3276) was important. The request timeout in this PR was not verified to work on its own (although seems like a good idea). The socket.setdefaulttimeout from mosaicml/composer#3265 was also not verified to work on its own, however this one may be a little dangerous since its a global default. Not entirely sure there.

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