-
Notifications
You must be signed in to change notification settings - Fork 4k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Check for chunk size minimum before using multipart upload with S3 #11975
Conversation
Documentation preview for 6c18920 will be available when this CircleCI job More info
|
5698fc7
to
7c8036d
Compare
|
||
def _validate_chunk_size_aws() -> None: | ||
chunk_size = MLFLOW_MULTIPART_UPLOAD_CHUNK_SIZE.get() | ||
if chunk_size <= _AWS_MIN_CHUNK_SIZE: |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
if chunk_size <= _AWS_MIN_CHUNK_SIZE: | |
if chunk_size < _AWS_MIN_CHUNK_SIZE: |
to allow 5 * 1024**2
.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Changed
|
||
def _validate_chunk_size_aws() -> None: | ||
chunk_size = MLFLOW_MULTIPART_UPLOAD_CHUNK_SIZE.get() | ||
if chunk_size <= _AWS_MIN_CHUNK_SIZE: |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
can we also validate the chunk size doesn't exceed the upper limit?
https://docs.aws.amazon.com/AmazonS3/latest/userguide/qfacts.html
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Makes sense, added
def _validate_chunk_size_aws() -> None: | ||
chunk_size = MLFLOW_MULTIPART_UPLOAD_CHUNK_SIZE.get() |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
def _validate_chunk_size_aws() -> None: | |
chunk_size = MLFLOW_MULTIPART_UPLOAD_CHUNK_SIZE.get() | |
def _validate_chunk_size_aws(chunk_size: int) -> None: |
Can we pass chunk size to this function so the code would look like this?
chunk_size = ...
_validate_chunk_size_aws(chunk_size)
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
def _validate_chunk_size_aws() -> None: | |
chunk_size = MLFLOW_MULTIPART_UPLOAD_CHUNK_SIZE.get() | |
def _validate_chunk_size_aws() -> int: |
We can return the passed-in chunk if that's convenient.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Changed to take the chunk size as a parameter. Kept None output for simpler testing / mocking setups.
S3 requires chunk sizes to be at least 5 MiB for multipart upload. This change does an assertion on chunk size env variable before commencing uploads. Add max chunk size validation, chunk_size argument, and improve testing. Fix regex match on test to match shorter error message Signed-off-by: Ian Ackerman <ian.ackerman@databricks.com>
84931f9
to
6c18920
Compare
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
LGTM!
Related Issues/PRs
#xxxWhat changes are proposed in this pull request?
S3 requires chunk sizes to be at least 5 MiB for multipart upload documentation. This change does an assertion on chunk size env variable before commencing uploads.
How is this PR tested?
Does this PR require documentation update?
Release Notes
Is this a user-facing change?
What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/artifacts
: Artifact stores and artifact loggingarea/build
: Build and test infrastructure for MLflowarea/deployments
: MLflow Deployments client APIs, server, and third-party Deployments integrationsarea/docs
: MLflow documentation pagesarea/examples
: Example codearea/model-registry
: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models
: MLmodel format, model serialization/deserialization, flavorsarea/recipes
: Recipes, Recipe APIs, Recipe configs, Recipe Templatesarea/projects
: MLproject format, project running backendsarea/scoring
: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra
: MLflow Tracking server backendarea/tracking
: Tracking Service, tracking client APIs, autologgingInterface
area/uiux
: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker
: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy
: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows
: Windows supportLanguage
language/r
: R APIs and clientslanguage/java
: Java APIs and clientslanguage/new
: Proposals for new client languagesIntegrations
integrations/azure
: Azure and Azure ML integrationsintegrations/sagemaker
: SageMaker integrationsintegrations/databricks
: Databricks integrationsHow should the PR be classified in the release notes? Choose one:
rn/none
- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/breaking-change
- The PR will be mentioned in the "Breaking Changes" sectionrn/feature
- A new user-facing feature worth mentioning in the release notesrn/bug-fix
- A user-facing bug fix worth mentioning in the release notesrn/documentation
- A user-facing documentation change worth mentioning in the release notesShould this PR be included in the next patch release?
Yes
should be selected for bug fixes, documentation updates, and other small changes.No
should be selected for new features and larger changes. If you're unsure about the release classification of this PR, leave this unchecked to let the maintainers decide.What is a minor/patch release?
Bug fixes, doc updates and new features usually go into minor releases.
Bug fixes and doc updates usually go into patch releases.