Issue: Docker volume mount from $HOME/.m2 wasn't working in GitHub Actions
- Container couldn't access the locally built SNAPSHOT JARs
- Maven failed with 'Could not find artifact seaweedfs-hadoop3-client:3.80.1-SNAPSHOT'
Solution: Copy Maven repository into workspace
1. In CI: Copy ~/.m2/repository/com/seaweedfs to test/java/spark/.m2/repository/com/
2. docker-compose.yml: Mount ./.m2 (relative path in workspace)
3. .gitignore: Added .m2/ to ignore copied artifacts
Why this works:
- Workspace directory (.) is successfully mounted as /workspace
- ./.m2 is inside workspace, so it gets mounted too
- Container sees artifacts at /root/.m2/repository/com/seaweedfs/...
- Maven finds the 3.80.1-SNAPSHOT JARs with our debug logging!
Next run should finally show the [DEBUG-2024] logs! 🎯
Issue: docker-compose was using ~ which may not expand correctly in CI
Changes:
1. docker-compose.yml: Changed ~/.m2 to ${HOME}/.m2
- Ensures proper path expansion in GitHub Actions
- $HOME is /home/runner in GitHub Actions runners
2. Added verification step in workflow:
- Lists all SNAPSHOT artifacts before tests
- Shows what's available in Maven local repo
- Will help diagnose if artifacts aren't being restored correctly
This should ensure the Maven container can access the locally built
3.80.1-SNAPSHOT JARs with our debug logging code.
Added -U flag to mvn install to force dependency updates
Added verification step using javap to check compiled bytecode
This will show if the JAR actually contains the new logging code:
- If 'totalPosition' string is found → JAR is updated
- If not found → Something is wrong with the build
The verification output will help diagnose why INFO logs aren't showing.
Troubleshooting 'seaweedfs-volume: Temporary failure in name resolution':
docker-compose.yml changes:
- Add MAVEN_OPTS to disable Java DNS caching (ttl=0)
Java caches DNS lookups which can cause stale results
- Add ping tests before mvn test to verify DNS resolution
Tests: ping -c 1 seaweedfs-volume && ping -c 1 seaweedfs-filer
- This will show if DNS works before tests run
workflow changes:
- List Docker networks before running tests
- Shows network configuration for debugging
- Helps verify spark-tests joins correct network
If ping succeeds but tests fail, it's a Java/Maven DNS issue.
If ping fails, it's a Docker networking configuration issue.
Note: Previous test failures may be from old code before Docker networking fix.
Better approach than mixing host and container networks.
Changes to docker-compose.yml:
- Remove 'network_mode: host' from spark-tests container
- Add spark-tests to seaweedfs-spark bridge network
- Update SEAWEEDFS_FILER_HOST from 'localhost' to 'seaweedfs-filer'
- Add depends_on to ensure services are healthy before tests
- Update volume publicUrl from 'localhost:8080' to 'seaweedfs-volume:8080'
Changes to workflow:
- Remove separate build and test steps
- Run tests via 'docker compose up spark-tests'
- Use --abort-on-container-exit and --exit-code-from for proper exit codes
- Simpler: one step instead of two
Benefits:
✓ All components use Docker DNS (seaweedfs-master, seaweedfs-volume, seaweedfs-filer)
✓ No host/container network split or DNS resolution issues
✓ Consistent with how other SeaweedFS integration tests work
✓ Tests are fully containerized and reproducible
✓ Volume server accessible via seaweedfs-volume:8080 for all clients
✓ Automatic volume creation works (master can reach volume via gRPC)
✓ Data writes work (Spark can reach volume via Docker network)
This matches the architecture of other integration tests and is cleaner.
Root cause identified:
- Volume server was using -ip=127.0.0.1
- Master couldn't reach volume server at 127.0.0.1 from its container
- When Spark requested assignment, master tried to create volume via gRPC
- Master's gRPC call to 127.0.0.1:18080 failed (reached itself, not volume server)
- Result: 'No writable volumes' error
Solution:
- Change volume server to use -ip=seaweedfs-volume (container hostname)
- Master can now reach volume server at seaweedfs-volume:18080
- Automatic volume creation works as designed
- Kept -publicUrl=127.0.0.1:8080 for external clients (host network)
Workflow changes:
- Remove forced volume creation (curl POST to /vol/grow)
- Volumes will be created automatically on first write request
- Keep diagnostic output for troubleshooting
- Simplified startup verification
This matches how other SeaweedFS tests work with Docker networking.
Root cause: With -max=0 (unlimited volumes), volumes are created on-demand,
but no volumes existed when tests started, causing first write to fail.
Solution:
- Explicitly trigger volume growth via /vol/grow API
- Create 3 volumes with replication=000 before running tests
- Verify volumes exist before proceeding
- Fail early with clear message if volumes can't be created
Changes:
- POST to http://localhost:9333/vol/grow?replication=000&count=3
- Wait up to 10 seconds for volumes to appear
- Show volume count and layout status
- Exit with error if no volumes after 10 attempts
- Applied to both spark-tests and spark-example jobs
This ensures writable volumes exist before Spark tries to write data.
- Add 'weed shell' execution to run 'volume.list' on failure
- Shows which volumes exist, their status, and available space
- Add cluster status JSON output for detailed topology view
- Helps diagnose volume allocation issues and full volumes
- Added to both spark-tests and spark-example jobs
- Diagnostic runs only when tests fail (if: failure())
- Add 'docker compose down -v' before starting services to clean up stale volumes
- Prevents accumulation of data/buckets from previous test runs
- Add volume registration verification after service startup
- Check that volume server has registered with master and volumes are available
- Helps diagnose 'No writable volumes' errors
- Shows volume count and waits up to 30 seconds for volumes to be created
- Both spark-tests and spark-example jobs updated with same improvements
- Add -Dcentral.publishing.skip=true to all Maven builds
- Central publishing plugin is only needed for Maven Central releases
- Prevents plugin resolution errors during CI builds
- Complements existing -Dgpg.skip=true flag
- Add container status (docker compose ps -a) on startup failure
- Add detailed logs for all three services (master, volume, filer)
- Add container inspection to verify binary exists
- Add debugging info for spark-example job
- Helps diagnose startup failures before containers are torn down
- Add ls -la to show build-artifacts/docker/ contents
- Add file command to verify binary type
- Add --no-cache to docker compose build to prevent stale cache issues
- Ensures fresh build with current binary
- Download artifacts to 'build-artifacts' directory instead of '.'
- Prevents checkout from overwriting downloaded files
- Explicitly copy weed binary from build-artifacts to docker/ directory
- Update Maven artifact restoration to use new path
- Add step to chmod +x the weed binary after downloading artifacts
- Artifacts lose executable permissions during upload/download
- Prevents 'Permission denied' errors when Docker tries to run the binary
- Add step to restore Maven artifacts from download to ~/.m2/repository
- Restructure artifact upload to use consistent directory layout
- Remove obsolete 'version' field from docker-compose.yml to eliminate warnings
- Ensures SeaweedFS Java dependencies are available during test execution
1. Add explicit permissions (least privilege):
- contents: read
- checks: write (for test reports)
- pull-requests: write (for PR comments)
2. Extract duplicate build steps into shared 'build-deps' job:
- Eliminates duplication between spark-tests and spark-example
- Build artifacts are uploaded and reused by dependent jobs
- Reduces CI time and ensures consistency
3. Fix spark-example service startup verification:
- Match robust approach from spark-tests job
- Add explicit timeout and failure handling
- Verify all services (master, volume, filer)
- Include diagnostic logging on failure
- Prevents silent failures and obscure errors
These changes improve maintainability, security, and reliability
of the Spark integration test workflow.