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Issue #953: add MAKEFLAGS="-j4"
to RStudio Dockerfiles for parallel compilation
#1395
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0097a87
📝 CodeRabbit Chat: Add MAKEFLAGS="-j2" to RStudio Dockerfiles for par…
coderabbitai[bot] 88208f8
📝 CodeRabbit Chat: Restore and update four RStudio Dockerfiles with M…
coderabbitai[bot] c87b0f0
📝 CodeRabbit Chat: Restore four RStudio Dockerfiles and add MAKEFLAGS…
coderabbitai[bot] adae6bf
📝 CodeRabbit Chat: Restore four Dockerfiles and add MAKEFLAGS environ…
coderabbitai[bot] a8eb8ee
Update Dockerfile.cpu
jiridanek 0d299d5
Update Dockerfile.cuda
jiridanek 94e9442
Update Dockerfile.cpu
jiridanek 6ef483d
Update Dockerfile.cuda
jiridanek 394d58a
Update Dockerfiles: adjust MAKEFLAGS to use 4 threads
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@coderabbitai the benefits on dockerfile buildtime are small, suggest ways to speed up
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@jiridanek Looking at the RStudio Dockerfile, I can suggest several optimization strategies that would likely provide more significant build time improvements than the MAKEFLAGS change:
Layer Caching Optimizations
1. Consolidate Package Operations
2. Move Stable Dependencies Earlier
Build Context Optimizations
3. Use .dockerignore
# Create .dockerignore to exclude unnecessary files *.md .git/ .github/ test/ docs/ *.log
4. Multi-stage Build Improvements
Network and Download Optimizations
5. Pre-download Large Assets
6. Use Package Manager Caching
Build-time Performance
7. Parallel R Package Installation
# In install_packages.R, use parallel installation options(Ncpus = parallel::detectCores())
8. Use BuildKit Cache Mounts
Specific to This Dockerfile
9. Optimize Permission Changes
10. Use Faster Base Images
Consider using images with more packages pre-installed or create a custom base image for RStudio builds.
The most impactful optimizations would likely be:
Would you like me to create a GitHub issue to track these Docker build optimization improvements?
ᕱ⁾⁾ᕱ thoughtful about build optimization strategies
🧠 Learnings used