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Use REPL context attributes if available to avoid calling JVM methods #5132

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merged 22 commits into from Dec 22, 2021

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harupy
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@harupy harupy commented Dec 1, 2021

What changes are proposed in this pull request?

Use REPL context attributes if available to avoid calling JVM methods.

How is this patch tested?

Install mlflow from this branch on Databricks and confirmed we can run mlflow code in multiprocessing.

Does this PR change the documentation?

  • No. You can skip the rest of this section.
  • Yes. Make sure the changed pages / sections render correctly by following the steps below.
  1. Check the status of the ci/circleci: build_doc check. If it's successful, proceed to the
    next step, otherwise fix it.
  2. Click Details on the right to open the job page of CircleCI.
  3. Click the Artifacts tab.
  4. Click docs/build/html/index.html.
  5. Find the changed pages / sections and make sure they render correctly.

Release Notes

Is this a user-facing change?

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

(Details in 1-2 sentences. You can just refer to another PR with a description if this PR is part of a larger change.)

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/docs: MLflow documentation pages
  • area/examples: Example code
  • area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
  • area/models: MLmodel format, model serialization/deserialization, flavors
  • area/projects: MLproject format, project running backends
  • area/scoring: MLflow Model server, model deployment tools, Spark UDFs
  • area/server-infra: MLflow Tracking server backend
  • area/tracking: Tracking Service, tracking client APIs, autologging

Interface

  • area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
  • area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
  • area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
  • area/windows: Windows support

Language

  • language/r: R APIs and clients
  • language/java: Java APIs and clients
  • language/new: Proposals for new client languages

Integrations

  • integrations/azure: Azure and Azure ML integrations
  • integrations/sagemaker: SageMaker integrations
  • integrations/databricks: Databricks integrations

How should the PR be classified in the release notes? Choose one:

  • rn/breaking-change - The PR will be mentioned in the "Breaking Changes" section
  • 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
  • rn/feature - A new user-facing feature worth mentioning in the release notes
  • rn/bug-fix - A user-facing bug fix worth mentioning in the release notes
  • rn/documentation - A user-facing documentation change worth mentioning in the release notes

Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
@github-actions github-actions bot added the rn/none List under Small Changes in Changelogs. label Dec 1, 2021
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
_env_var_prefix = "DATABRICKS_"


def _use_env_var_if_exists(env_var, *, if_exists=lambda x: os.environ[x]):
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Introduced this decorator to make it easier to preserve the existing logic for older runtime versions.

"""

def decorator(f):
@functools.wraps(f)
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nice use of the decorator factory here. +1

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really clever, elegant, and simplified solution.

Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
@harupy harupy changed the title Get databricks metadata from environment variables and jupyter command metadata [WIP] Get databricks metadata from environment variables and jupyter command metadata Dec 1, 2021
@@ -50,6 +79,7 @@ def _get_context_tag(context_tag_key):
return None


@_use_env_var_if_exists(_env_var_prefix + "ACL_PATH_OF_ACL_ROOT")
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Can we prefix these environment variables with DATABRICKS?

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We probably don't need ACL_PATH_OF_ACL_ROOT, since this is used for is_in_databricks_notebook / get_notebook_id. We can rely on DATABRICKS_NOTEBOOK_ID for those.

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@dbczumar Thanks for the comment! _env_var_prefix adds DATABRICKS_ or am I missing something?

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Doh. Sorry - missed that.

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We probably don't need ACL_PATH_OF_ACL_ROOT, since this is used for is_in_databricks_notebook / get_notebook_id. We can rely on DATABRICKS_NOTEBOOK_ID for those.

Makes sense!

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LGTM once #5132 (comment) is addressed. Thanks Haru!

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harupy commented Dec 1, 2021

@BenWilson2 @dbczumar Thanks for the review, I still need to update the code for dynamic metadata (e.g. command run id).

Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
@@ -133,6 +166,7 @@ def get_notebook_id():
return None


@_use_env_var_if_exists(_ENV_VAR_PREFIX + "NOTEBOOK_PATH")
def get_notebook_path():
"""Should only be called if is_in_databricks_notebook is true"""
path = _get_property_from_spark_context("spark.databricks.notebook.path")
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does this work with ephemeral notebooks within and without jobs?

harupy and others added 7 commits December 2, 2021 15:56
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
@harupy harupy changed the title [WIP] Get databricks metadata from environment variables and jupyter command metadata Get databricks metadata from environment variables and jupyter command metadata Dec 6, 2021
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
@harupy harupy changed the title Get databricks metadata from environment variables and jupyter command metadata Use REPL context attributes if available to avoid calling JVM methods Dec 14, 2021
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
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re-LGTM! Thanks @harupy !

Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
@harupy harupy force-pushed the use-env-var-command-metadata branch from 30473e2 to 5ac0475 Compare December 16, 2021 07:56
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
@harupy harupy merged commit 852f567 into mlflow:master Dec 22, 2021
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