Use https://packagemanager.rstudio.com to install R packages faster#5220
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https://packagemanager.rstudio.com to install R packages faster
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Signed-off-by: harupy <hkawamura0130@gmail.com>
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Signed-off-by: harupy <hkawamura0130@gmail.com>
harupy
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Jan 5, 2022
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| # https://packagemanager.rstudio.com provides pre-compiled binary packages for Linux | ||
| # that can be installed significantly faster. | ||
| options(repos = c(REPO_NAME = "https://packagemanager.rstudio.com/cran/__linux__/focal/latest")) |
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The package installation (which usually takes 15~20 min) took 1.5 min with https://packagemanager.rstudio.com:
https://github.com/mlflow/mlflow/runs/4716557367?check_suite_focus=true#step:11:1
harupy
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Jan 5, 2022
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| working-directory: mlflow/R/mlflow | ||
| run: | | ||
| install.packages("devtools") | ||
| remotes::install_deps('mlflow/R/mlflow', dependencies = TRUE, upgrade = FALSE) | ||
| remotes::install_deps('.', dependencies = TRUE, upgrade = FALSE) |
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Run remotes::install_deps in mlflow/R/mlflow to allow R to find .Rprofile.
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where is .Rprofile file ?
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oh, in user home directory
Signed-off-by: harupy <hkawamura0130@gmail.com>
Signed-off-by: harupy <hkawamura0130@gmail.com>
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nice 🥳 |
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What changes are proposed in this pull request?
Use https://packagemanager.rstudio.com to install R packages faster.
Before: 15 ~ 20 minutes
After: 1.5 minutes.
How is this patch tested?
Ensure the existing checks all pass.
Does this PR change the documentation?
ci/circleci: build_doccheck. If it's successful, proceed to thenext step, otherwise fix it.
Detailson the right to open the job page of CircleCI.Artifactstab.docs/build/html/index.html.Release Notes
Is this a user-facing change?
(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 loggingarea/build: Build and test infrastructure for MLflowarea/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/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/breaking-change- The PR will be mentioned in the "Breaking Changes" sectionrn/none- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" 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 notes