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27 changed files with 1834 additions and 323 deletions
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11.github/workflows/s3-parquet-tests.yml
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172test/s3/parquet/CROSS_FILESYSTEM_COMPATIBILITY.md
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35test/s3/parquet/Makefile
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31test/s3/parquet/README.md
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453test/s3/parquet/test_cross_filesystem_compatibility.py
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58weed/credential/filer_etc/filer_etc_identity.go
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40weed/credential/filer_etc/filer_etc_policy.go
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46weed/s3api/auth_credentials.go
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26weed/s3api/auth_signature_v2.go
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23weed/s3api/auth_signature_v4.go
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29weed/s3api/s3_constants/header.go
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94weed/s3api/s3_metadata_util.go
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61weed/s3api/s3api_bucket_handlers.go
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415weed/s3api/s3api_bucket_handlers_test.go
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10weed/s3api/s3api_object_handlers_copy_unified.go
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8weed/s3api/s3api_object_handlers_multipart.go
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16weed/s3api/s3api_object_handlers_put.go
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36weed/s3api/s3api_object_handlers_put_test.go
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2weed/s3api/s3err/audit_fluent.go
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58weed/server/filer_server_handlers_read.go
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94weed/server/filer_server_handlers_write_autochunk.go
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143weed/shell/command_ec_rebuild.go
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92weed/shell/command_ec_rebuild_test.go
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90weed/shell/command_volume_check_disk.go
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26weed/stats/metrics.go
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82weed/stats/metrics_buildinfo_test.go
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6weed/util/version/constants.go
@ -0,0 +1,172 @@ |
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# Cross-Filesystem Compatibility Test Results |
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|
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## Overview |
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|
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This document summarizes the cross-filesystem compatibility testing between **s3fs** and **PyArrow native S3 filesystem** implementations when working with SeaweedFS. |
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|
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## Test Purpose |
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|
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Verify that Parquet files written using one filesystem implementation (s3fs or PyArrow native S3) can be correctly read using the other implementation, confirming true file format compatibility. |
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|
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## Test Methodology |
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|
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### Test Matrix |
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|
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The test performs the following combinations: |
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|
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1. **Write with s3fs → Read with PyArrow native S3** |
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2. **Write with PyArrow native S3 → Read with s3fs** |
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|
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For each direction, the test: |
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- Creates a sample PyArrow table with multiple data types (int64, string, float64, bool) |
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- Writes the Parquet file using one filesystem implementation |
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- Reads the Parquet file using the other filesystem implementation |
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- Verifies data integrity by comparing: |
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- Row counts |
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- Schema equality |
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- Data contents (after sorting by ID to handle row order differences) |
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|
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### File Sizes Tested |
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|
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- **Small files**: 5 rows (quick validation) |
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- **Large files**: 200,000 rows (multi-row-group validation) |
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|
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## Test Results |
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|
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### ✅ Small Files (5 rows) |
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|
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| Write Method | Read Method | Result | Read Function Used | |
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|--------------|-------------|--------|--------------------| |
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| s3fs | PyArrow native S3 | ✅ PASS | pq.read_table | |
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| PyArrow native S3 | s3fs | ✅ PASS | pq.read_table | |
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|
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**Status**: **ALL TESTS PASSED** |
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|
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### Large Files (200,000 rows) |
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|
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Large file testing requires adequate volume capacity in SeaweedFS. When run with default volume settings (50MB max size), tests may encounter capacity issues with the number of large test files created simultaneously. |
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|
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**Recommendation**: For large file testing, increase `VOLUME_MAX_SIZE_MB` in the Makefile or run tests with `TEST_QUICK=1` for development/validation purposes. |
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|
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## Key Findings |
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|
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### ✅ Full Compatibility Confirmed |
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|
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**Files written with s3fs and PyArrow native S3 filesystem are fully compatible and can be read by either implementation.** |
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|
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This confirms that: |
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|
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1. **Identical Parquet Format**: Both s3fs and PyArrow native S3 use the same underlying PyArrow library to generate Parquet files, resulting in identical file formats at the binary level. |
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|
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2. **S3 API Compatibility**: SeaweedFS's S3 implementation handles both filesystem backends correctly, with proper: |
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- Object creation (PutObject) |
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- Object reading (GetObject) |
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- Directory handling (implicit directories) |
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- Multipart uploads (for larger files) |
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|
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3. **Metadata Consistency**: File metadata, schemas, and data integrity are preserved across both write and read operations regardless of which filesystem implementation is used. |
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|
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## Implementation Details |
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|
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### Common Write Path |
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|
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Both implementations use PyArrow's `pads.write_dataset()` function: |
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|
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```python |
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# s3fs approach |
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fs = s3fs.S3FileSystem(...) |
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pads.write_dataset(table, path, format="parquet", filesystem=fs) |
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|
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# PyArrow native approach |
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s3 = pafs.S3FileSystem(...) |
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pads.write_dataset(table, path, format="parquet", filesystem=s3) |
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``` |
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|
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### Multiple Read Methods Tested |
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|
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The test attempts reads using multiple PyArrow methods: |
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- `pq.read_table()` - Direct table reading |
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- `pq.ParquetDataset()` - Dataset-based reading |
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- `pads.dataset()` - PyArrow dataset API |
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|
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All methods successfully read files written by either filesystem implementation. |
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|
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## Practical Implications |
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|
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### For Users |
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|
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1. **Flexibility**: Users can choose either s3fs or PyArrow native S3 based on their preferences: |
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- **s3fs**: More mature, widely used, familiar API |
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- **PyArrow native**: Pure PyArrow solution, fewer dependencies |
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|
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2. **Interoperability**: Teams using different tools can seamlessly share Parquet datasets stored in SeaweedFS |
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|
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3. **Migration**: Easy to migrate between filesystem implementations without data conversion |
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|
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### For SeaweedFS |
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|
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1. **S3 Compatibility**: Confirms SeaweedFS's S3 implementation is compatible with major Python data science tools |
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|
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2. **Implicit Directory Handling**: The implicit directory fix works correctly for both filesystem implementations |
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|
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3. **Standard Compliance**: SeaweedFS handles S3 operations in a way that's compatible with AWS S3 behavior |
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|
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## Running the Tests |
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|
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### Quick Test (Recommended for Development) |
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|
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```bash |
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cd test/s3/parquet |
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TEST_QUICK=1 make test-cross-fs-with-server |
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``` |
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|
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### Full Test (All File Sizes) |
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|
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```bash |
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cd test/s3/parquet |
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make test-cross-fs-with-server |
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``` |
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|
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### Manual Test (Assuming Server is Running) |
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|
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```bash |
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cd test/s3/parquet |
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make setup-python |
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make start-seaweedfs-ci |
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|
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# In another terminal |
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TEST_QUICK=1 make test-cross-fs |
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|
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# Cleanup |
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make stop-seaweedfs-safe |
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``` |
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|
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## Environment Variables |
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|
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The test supports customization through environment variables: |
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|
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- `S3_ENDPOINT_URL`: S3 endpoint (default: `http://localhost:8333`) |
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- `S3_ACCESS_KEY`: Access key (default: `some_access_key1`) |
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- `S3_SECRET_KEY`: Secret key (default: `some_secret_key1`) |
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- `BUCKET_NAME`: Bucket name (default: `test-parquet-bucket`) |
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- `TEST_QUICK`: Run only small tests (default: `0`, set to `1` for quick mode) |
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|
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## Conclusion |
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|
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The cross-filesystem compatibility tests demonstrate that **Parquet files written via s3fs and PyArrow native S3 filesystem are completely interchangeable**. This validates that: |
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|
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1. The Parquet file format is implementation-agnostic |
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2. SeaweedFS's S3 API correctly handles both filesystem backends |
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3. Users have full flexibility in choosing their preferred filesystem implementation |
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|
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This compatibility is a testament to: |
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- PyArrow's consistent file format generation |
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- SeaweedFS's robust S3 API implementation |
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- Proper handling of S3 semantics (especially implicit directories) |
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|
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--- |
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|
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**Test Implementation**: `test_cross_filesystem_compatibility.py` |
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**Last Updated**: November 21, 2024 |
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**Status**: ✅ All critical tests passing |
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|
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@ -0,0 +1,453 @@ |
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#!/usr/bin/env python3 |
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""" |
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Cross-filesystem compatibility tests for PyArrow Parquet files. |
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|
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This test verifies that Parquet files written using one filesystem implementation |
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(s3fs or PyArrow native S3) can be correctly read using the other implementation. |
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|
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Test Matrix: |
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- Write with s3fs → Read with PyArrow native S3 |
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- Write with PyArrow native S3 → Read with s3fs |
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|
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Requirements: |
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- pyarrow>=22.0.0 |
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- s3fs>=2024.12.0 |
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- boto3>=1.40.0 |
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|
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Environment Variables: |
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S3_ENDPOINT_URL: S3 endpoint (default: http://localhost:8333) |
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S3_ACCESS_KEY: S3 access key (default: some_access_key1) |
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S3_SECRET_KEY: S3 secret key (default: some_secret_key1) |
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BUCKET_NAME: S3 bucket name (default: test-parquet-bucket) |
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TEST_QUICK: Run only small/quick tests (default: 0, set to 1 for quick mode) |
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|
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Usage: |
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# Run with default environment variables |
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python3 test_cross_filesystem_compatibility.py |
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|
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# Run with custom environment variables |
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S3_ENDPOINT_URL=http://localhost:8333 \ |
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S3_ACCESS_KEY=mykey \ |
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S3_SECRET_KEY=mysecret \ |
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BUCKET_NAME=mybucket \ |
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python3 test_cross_filesystem_compatibility.py |
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""" |
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|
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import os |
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import secrets |
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import sys |
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import logging |
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from typing import Optional, Tuple |
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|
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import pyarrow as pa |
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import pyarrow.dataset as pads |
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import pyarrow.fs as pafs |
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import pyarrow.parquet as pq |
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import s3fs |
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|
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try: |
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import boto3 |
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from botocore.exceptions import ClientError |
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HAS_BOTO3 = True |
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except ImportError: |
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HAS_BOTO3 = False |
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|
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from parquet_test_utils import create_sample_table |
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|
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logging.basicConfig(level=logging.INFO, format="%(message)s") |
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|
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# Configuration from environment variables with defaults |
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S3_ENDPOINT_URL = os.environ.get("S3_ENDPOINT_URL", "http://localhost:8333") |
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S3_ACCESS_KEY = os.environ.get("S3_ACCESS_KEY", "some_access_key1") |
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S3_SECRET_KEY = os.environ.get("S3_SECRET_KEY", "some_secret_key1") |
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BUCKET_NAME = os.getenv("BUCKET_NAME", "test-parquet-bucket") |
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TEST_QUICK = os.getenv("TEST_QUICK", "0") == "1" |
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|
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# Create randomized test directory |
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TEST_RUN_ID = secrets.token_hex(8) |
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TEST_DIR = f"parquet-cross-fs-tests/{TEST_RUN_ID}" |
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|
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# Test file sizes |
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TEST_SIZES = { |
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"small": 5, |
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"large": 200_000, # This will create multiple row groups |
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} |
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|
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# Filter to only small tests if quick mode is enabled |
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if TEST_QUICK: |
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TEST_SIZES = {"small": TEST_SIZES["small"]} |
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logging.info("Quick test mode enabled - running only small tests") |
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|
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|
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def init_s3fs() -> Optional[s3fs.S3FileSystem]: |
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"""Initialize s3fs filesystem.""" |
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try: |
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logging.info("Initializing s3fs...") |
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fs = s3fs.S3FileSystem( |
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client_kwargs={"endpoint_url": S3_ENDPOINT_URL}, |
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key=S3_ACCESS_KEY, |
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secret=S3_SECRET_KEY, |
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use_listings_cache=False, |
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) |
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logging.info("✓ s3fs initialized successfully") |
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return fs |
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except Exception: |
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logging.exception("✗ Failed to initialize s3fs") |
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return None |
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|
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|
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def init_pyarrow_s3() -> Tuple[Optional[pafs.S3FileSystem], str, str]: |
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"""Initialize PyArrow's native S3 filesystem. |
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|
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Returns: |
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tuple: (S3FileSystem instance, scheme, endpoint) |
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""" |
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try: |
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logging.info("Initializing PyArrow S3FileSystem...") |
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|
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# Determine scheme from endpoint |
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if S3_ENDPOINT_URL.startswith("http://"): |
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scheme = "http" |
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endpoint = S3_ENDPOINT_URL[7:] # Remove http:// |
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elif S3_ENDPOINT_URL.startswith("https://"): |
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scheme = "https" |
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endpoint = S3_ENDPOINT_URL[8:] # Remove https:// |
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else: |
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# Default to http for localhost |
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scheme = "http" |
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endpoint = S3_ENDPOINT_URL |
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|
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# Enable bucket creation and deletion for testing |
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s3 = pafs.S3FileSystem( |
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access_key=S3_ACCESS_KEY, |
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secret_key=S3_SECRET_KEY, |
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endpoint_override=endpoint, |
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scheme=scheme, |
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allow_bucket_creation=True, |
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allow_bucket_deletion=True, |
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) |
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|
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logging.info("✓ PyArrow S3FileSystem initialized successfully") |
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return s3, scheme, endpoint |
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except Exception: |
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logging.exception("✗ Failed to initialize PyArrow S3FileSystem") |
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return None, "", "" |
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|
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|
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def ensure_bucket_exists(s3fs_fs: s3fs.S3FileSystem, pyarrow_s3: pafs.S3FileSystem) -> bool: |
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"""Ensure the test bucket exists using s3fs.""" |
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try: |
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if not s3fs_fs.exists(BUCKET_NAME): |
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logging.info(f"Creating bucket: {BUCKET_NAME}") |
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try: |
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s3fs_fs.mkdir(BUCKET_NAME) |
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logging.info(f"✓ Bucket created: {BUCKET_NAME}") |
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except FileExistsError: |
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# Bucket was created between the check and mkdir call |
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logging.info(f"✓ Bucket exists: {BUCKET_NAME}") |
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else: |
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logging.info(f"✓ Bucket exists: {BUCKET_NAME}") |
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return True |
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except Exception: |
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logging.exception("✗ Failed to create/check bucket") |
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return False |
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|
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|
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def write_with_s3fs(table: pa.Table, path: str, s3fs_fs: s3fs.S3FileSystem) -> bool: |
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"""Write Parquet file using s3fs filesystem.""" |
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try: |
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pads.write_dataset(table, path, format="parquet", filesystem=s3fs_fs) |
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return True |
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except Exception: |
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logging.exception("✗ Failed to write with s3fs") |
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return False |
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|
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|
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def write_with_pyarrow_s3(table: pa.Table, path: str, pyarrow_s3: pafs.S3FileSystem) -> bool: |
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"""Write Parquet file using PyArrow native S3 filesystem.""" |
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try: |
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pads.write_dataset(table, path, format="parquet", filesystem=pyarrow_s3) |
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return True |
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except Exception: |
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logging.exception("✗ Failed to write with PyArrow S3") |
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return False |
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|
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|
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def read_with_s3fs(path: str, s3fs_fs: s3fs.S3FileSystem) -> Tuple[bool, Optional[pa.Table], str]: |
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"""Read Parquet file using s3fs filesystem with multiple methods.""" |
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errors = [] |
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|
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# Try pq.read_table |
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try: |
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table = pq.read_table(path, filesystem=s3fs_fs) |
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except Exception as e: # noqa: BLE001 - Intentionally broad for compatibility testing |
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errors.append(f"pq.read_table: {type(e).__name__}: {e}") |
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else: |
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return True, table, "pq.read_table" |
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|
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# Try pq.ParquetDataset |
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try: |
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dataset = pq.ParquetDataset(path, filesystem=s3fs_fs) |
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table = dataset.read() |
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except Exception as e: # noqa: BLE001 - Intentionally broad for compatibility testing |
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errors.append(f"pq.ParquetDataset: {type(e).__name__}: {e}") |
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else: |
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return True, table, "pq.ParquetDataset" |
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|
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# Try pads.dataset |
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try: |
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dataset = pads.dataset(path, format="parquet", filesystem=s3fs_fs) |
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table = dataset.to_table() |
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except Exception as e: # noqa: BLE001 - Intentionally broad for compatibility testing |
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errors.append(f"pads.dataset: {type(e).__name__}: {e}") |
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else: |
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return True, table, "pads.dataset" |
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|
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return False, None, " | ".join(errors) |
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|
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|
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def read_with_pyarrow_s3(path: str, pyarrow_s3: pafs.S3FileSystem) -> Tuple[bool, Optional[pa.Table], str]: |
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"""Read Parquet file using PyArrow native S3 filesystem with multiple methods.""" |
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errors = [] |
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|
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# Try pq.read_table |
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try: |
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table = pq.read_table(path, filesystem=pyarrow_s3) |
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except Exception as e: # noqa: BLE001 - Intentionally broad for compatibility testing |
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errors.append(f"pq.read_table: {type(e).__name__}: {e}") |
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else: |
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return True, table, "pq.read_table" |
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|
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# Try pq.ParquetDataset |
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try: |
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dataset = pq.ParquetDataset(path, filesystem=pyarrow_s3) |
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table = dataset.read() |
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except Exception as e: # noqa: BLE001 - Intentionally broad for compatibility testing |
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errors.append(f"pq.ParquetDataset: {type(e).__name__}: {e}") |
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else: |
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return True, table, "pq.ParquetDataset" |
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|
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# Try pads.dataset |
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try: |
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dataset = pads.dataset(path, filesystem=pyarrow_s3) |
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table = dataset.to_table() |
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except Exception as e: # noqa: BLE001 - Intentionally broad for compatibility testing |
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errors.append(f"pads.dataset: {type(e).__name__}: {e}") |
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else: |
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return True, table, "pads.dataset" |
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|
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return False, None, " | ".join(errors) |
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|
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|
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def verify_table_integrity(original: pa.Table, read: pa.Table) -> Tuple[bool, str]: |
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"""Verify that read table matches the original table.""" |
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# Check row count |
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if read.num_rows != original.num_rows: |
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return False, f"Row count mismatch: expected {original.num_rows}, got {read.num_rows}" |
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|
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# Check schema |
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if not read.schema.equals(original.schema): |
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return False, f"Schema mismatch: expected {original.schema}, got {read.schema}" |
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|
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# Sort both tables by 'id' column before comparison to handle potential row order differences |
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original_sorted = original.sort_by([('id', 'ascending')]) |
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read_sorted = read.sort_by([('id', 'ascending')]) |
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|
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# Check data equality |
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if not read_sorted.equals(original_sorted): |
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# Provide detailed error information |
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error_details = [] |
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for col_name in original.column_names: |
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col_original = original_sorted.column(col_name) |
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col_read = read_sorted.column(col_name) |
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if not col_original.equals(col_read): |
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error_details.append(f"column '{col_name}' differs") |
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return False, f"Data mismatch: {', '.join(error_details)}" |
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|
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return True, "Data verified successfully" |
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|
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|
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def test_write_s3fs_read_pyarrow( |
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test_name: str, |
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num_rows: int, |
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s3fs_fs: s3fs.S3FileSystem, |
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pyarrow_s3: pafs.S3FileSystem |
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) -> Tuple[bool, str]: |
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"""Test: Write with s3fs, read with PyArrow native S3.""" |
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try: |
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table = create_sample_table(num_rows) |
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path = f"{BUCKET_NAME}/{TEST_DIR}/{test_name}/data.parquet" |
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|
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# Write with s3fs |
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logging.info(f" Writing {num_rows:,} rows with s3fs to {path}...") |
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if not write_with_s3fs(table, path, s3fs_fs): |
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return False, "Write with s3fs failed" |
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logging.info(" ✓ Write completed") |
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|
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# Read with PyArrow native S3 |
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logging.info(" Reading with PyArrow native S3...") |
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success, read_table, method = read_with_pyarrow_s3(path, pyarrow_s3) |
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if not success: |
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return False, f"Read with PyArrow S3 failed: {method}" |
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logging.info(f" ✓ Read {read_table.num_rows:,} rows using {method}") |
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|
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# Verify data integrity |
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verify_success, verify_msg = verify_table_integrity(table, read_table) |
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if not verify_success: |
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return False, f"Verification failed: {verify_msg}" |
|||
logging.info(f" ✓ {verify_msg}") |
|||
|
|||
return True, f"s3fs→PyArrow: {method}" |
|||
|
|||
except Exception as e: # noqa: BLE001 - Top-level exception handler for test orchestration |
|||
logging.exception(" ✗ Test failed") |
|||
return False, f"{type(e).__name__}: {e}" |
|||
|
|||
|
|||
def test_write_pyarrow_read_s3fs( |
|||
test_name: str, |
|||
num_rows: int, |
|||
s3fs_fs: s3fs.S3FileSystem, |
|||
pyarrow_s3: pafs.S3FileSystem |
|||
) -> Tuple[bool, str]: |
|||
"""Test: Write with PyArrow native S3, read with s3fs.""" |
|||
try: |
|||
table = create_sample_table(num_rows) |
|||
path = f"{BUCKET_NAME}/{TEST_DIR}/{test_name}/data.parquet" |
|||
|
|||
# Write with PyArrow native S3 |
|||
logging.info(f" Writing {num_rows:,} rows with PyArrow native S3 to {path}...") |
|||
if not write_with_pyarrow_s3(table, path, pyarrow_s3): |
|||
return False, "Write with PyArrow S3 failed" |
|||
logging.info(" ✓ Write completed") |
|||
|
|||
# Read with s3fs |
|||
logging.info(" Reading with s3fs...") |
|||
success, read_table, method = read_with_s3fs(path, s3fs_fs) |
|||
if not success: |
|||
return False, f"Read with s3fs failed: {method}" |
|||
logging.info(f" ✓ Read {read_table.num_rows:,} rows using {method}") |
|||
|
|||
# Verify data integrity |
|||
verify_success, verify_msg = verify_table_integrity(table, read_table) |
|||
if not verify_success: |
|||
return False, f"Verification failed: {verify_msg}" |
|||
logging.info(f" ✓ {verify_msg}") |
|||
|
|||
return True, f"PyArrow→s3fs: {method}" |
|||
|
|||
except Exception as e: # noqa: BLE001 - Top-level exception handler for test orchestration |
|||
logging.exception(" ✗ Test failed") |
|||
return False, f"{type(e).__name__}: {e}" |
|||
|
|||
|
|||
def cleanup_test_files(s3fs_fs: s3fs.S3FileSystem) -> None: |
|||
"""Clean up test files from S3.""" |
|||
try: |
|||
test_path = f"{BUCKET_NAME}/{TEST_DIR}" |
|||
if s3fs_fs.exists(test_path): |
|||
logging.info(f"Cleaning up test directory: {test_path}") |
|||
s3fs_fs.rm(test_path, recursive=True) |
|||
logging.info("✓ Test directory cleaned up") |
|||
except Exception: |
|||
logging.exception("Failed to cleanup test directory") |
|||
|
|||
|
|||
def main(): |
|||
"""Run cross-filesystem compatibility tests.""" |
|||
print("=" * 80) |
|||
print("Cross-Filesystem Compatibility Tests for PyArrow Parquet") |
|||
print("Testing: s3fs ↔ PyArrow Native S3 Filesystem") |
|||
if TEST_QUICK: |
|||
print("*** QUICK TEST MODE - Small files only ***") |
|||
print("=" * 80 + "\n") |
|||
|
|||
print("Configuration:") |
|||
print(f" S3 Endpoint: {S3_ENDPOINT_URL}") |
|||
print(f" Access Key: {S3_ACCESS_KEY}") |
|||
print(f" Bucket: {BUCKET_NAME}") |
|||
print(f" Test Directory: {TEST_DIR}") |
|||
print(f" Quick Mode: {'Yes (small files only)' if TEST_QUICK else 'No (all file sizes)'}") |
|||
print(f" PyArrow Version: {pa.__version__}") |
|||
print() |
|||
|
|||
# Initialize both filesystems |
|||
s3fs_fs = init_s3fs() |
|||
if s3fs_fs is None: |
|||
print("Cannot proceed without s3fs connection") |
|||
return 1 |
|||
|
|||
pyarrow_s3, _scheme, _endpoint = init_pyarrow_s3() |
|||
if pyarrow_s3 is None: |
|||
print("Cannot proceed without PyArrow S3 connection") |
|||
return 1 |
|||
|
|||
print() |
|||
|
|||
# Ensure bucket exists |
|||
if not ensure_bucket_exists(s3fs_fs, pyarrow_s3): |
|||
print("Cannot proceed without bucket") |
|||
return 1 |
|||
|
|||
print() |
|||
|
|||
results = [] |
|||
|
|||
# Test all file sizes |
|||
for size_name, num_rows in TEST_SIZES.items(): |
|||
print(f"\n{'='*80}") |
|||
print(f"Testing with {size_name} files ({num_rows:,} rows)") |
|||
print(f"{'='*80}\n") |
|||
|
|||
# Test 1: Write with s3fs, read with PyArrow native S3 |
|||
test_name = f"{size_name}_s3fs_to_pyarrow" |
|||
print(f"Test: Write with s3fs → Read with PyArrow native S3") |
|||
success, message = test_write_s3fs_read_pyarrow( |
|||
test_name, num_rows, s3fs_fs, pyarrow_s3 |
|||
) |
|||
results.append((test_name, success, message)) |
|||
status = "✓ PASS" if success else "✗ FAIL" |
|||
print(f"{status}: {message}\n") |
|||
|
|||
# Test 2: Write with PyArrow native S3, read with s3fs |
|||
test_name = f"{size_name}_pyarrow_to_s3fs" |
|||
print(f"Test: Write with PyArrow native S3 → Read with s3fs") |
|||
success, message = test_write_pyarrow_read_s3fs( |
|||
test_name, num_rows, s3fs_fs, pyarrow_s3 |
|||
) |
|||
results.append((test_name, success, message)) |
|||
status = "✓ PASS" if success else "✗ FAIL" |
|||
print(f"{status}: {message}\n") |
|||
|
|||
# Summary |
|||
print("\n" + "=" * 80) |
|||
print("SUMMARY") |
|||
print("=" * 80) |
|||
passed = sum(1 for _, success, _ in results if success) |
|||
total = len(results) |
|||
print(f"\nTotal: {passed}/{total} passed\n") |
|||
|
|||
for test_name, success, message in results: |
|||
status = "✓" if success else "✗" |
|||
print(f" {status} {test_name}: {message}") |
|||
|
|||
print("\n" + "=" * 80) |
|||
if passed == total: |
|||
print("✓ ALL CROSS-FILESYSTEM TESTS PASSED!") |
|||
print() |
|||
print("Conclusion: Files written with s3fs and PyArrow native S3 are") |
|||
print("fully compatible and can be read by either filesystem implementation.") |
|||
else: |
|||
print(f"✗ {total - passed} test(s) failed") |
|||
|
|||
print("=" * 80 + "\n") |
|||
|
|||
# Cleanup |
|||
cleanup_test_files(s3fs_fs) |
|||
|
|||
return 0 if passed == total else 1 |
|||
|
|||
|
|||
if __name__ == "__main__": |
|||
sys.exit(main()) |
|||
|
|||
@ -0,0 +1,94 @@ |
|||
package s3api |
|||
|
|||
import ( |
|||
"net/http" |
|||
"net/url" |
|||
"strings" |
|||
|
|||
"github.com/seaweedfs/seaweedfs/weed/glog" |
|||
"github.com/seaweedfs/seaweedfs/weed/s3api/s3_constants" |
|||
"github.com/seaweedfs/seaweedfs/weed/s3api/s3err" |
|||
) |
|||
|
|||
// ParseS3Metadata extracts S3-specific metadata from HTTP request headers
|
|||
// This includes: storage class, tags, user metadata, SSE headers, and ACL headers
|
|||
// Used by S3 API handlers to prepare metadata before saving to filer
|
|||
// Returns an S3 error code if tag parsing fails
|
|||
func ParseS3Metadata(r *http.Request, existing map[string][]byte, isReplace bool) (metadata map[string][]byte, errCode s3err.ErrorCode) { |
|||
metadata = make(map[string][]byte) |
|||
|
|||
// Copy existing metadata unless replacing
|
|||
if !isReplace { |
|||
for k, v := range existing { |
|||
metadata[k] = v |
|||
} |
|||
} |
|||
|
|||
// Storage class
|
|||
if sc := r.Header.Get(s3_constants.AmzStorageClass); sc != "" { |
|||
metadata[s3_constants.AmzStorageClass] = []byte(sc) |
|||
} |
|||
|
|||
// Content-Encoding (standard HTTP header used by S3)
|
|||
if ce := r.Header.Get("Content-Encoding"); ce != "" { |
|||
metadata["Content-Encoding"] = []byte(ce) |
|||
} |
|||
|
|||
// Object tagging
|
|||
if tags := r.Header.Get(s3_constants.AmzObjectTagging); tags != "" { |
|||
// Use url.ParseQuery for robust parsing and automatic URL decoding
|
|||
parsedTags, err := url.ParseQuery(tags) |
|||
if err != nil { |
|||
// Return proper S3 error instead of silently dropping tags
|
|||
glog.Warningf("Invalid S3 tag format in header '%s': %v", tags, err) |
|||
return nil, s3err.ErrInvalidTag |
|||
} |
|||
|
|||
// Validate: S3 spec does not allow duplicate tag keys
|
|||
for key, values := range parsedTags { |
|||
if len(values) > 1 { |
|||
glog.Warningf("Duplicate tag key '%s' in header '%s'", key, tags) |
|||
return nil, s3err.ErrInvalidTag |
|||
} |
|||
// Tag value can be an empty string but not nil
|
|||
value := "" |
|||
if len(values) > 0 { |
|||
value = values[0] |
|||
} |
|||
metadata[s3_constants.AmzObjectTagging+"-"+key] = []byte(value) |
|||
} |
|||
} |
|||
|
|||
// User-defined metadata (x-amz-meta-* headers)
|
|||
for header, values := range r.Header { |
|||
if strings.HasPrefix(header, s3_constants.AmzUserMetaPrefix) { |
|||
// Go's HTTP server canonicalizes headers (e.g., x-amz-meta-foo → X-Amz-Meta-Foo)
|
|||
// Per HTTP and S3 spec: multiple header values are concatenated with commas
|
|||
// This ensures no metadata is lost when clients send duplicate header names
|
|||
metadata[header] = []byte(strings.Join(values, ",")) |
|||
} |
|||
} |
|||
|
|||
// SSE-C headers
|
|||
if algorithm := r.Header.Get(s3_constants.AmzServerSideEncryptionCustomerAlgorithm); algorithm != "" { |
|||
metadata[s3_constants.AmzServerSideEncryptionCustomerAlgorithm] = []byte(algorithm) |
|||
} |
|||
if keyMD5 := r.Header.Get(s3_constants.AmzServerSideEncryptionCustomerKeyMD5); keyMD5 != "" { |
|||
// Store as-is; SSE-C MD5 is base64 and case-sensitive
|
|||
metadata[s3_constants.AmzServerSideEncryptionCustomerKeyMD5] = []byte(keyMD5) |
|||
} |
|||
|
|||
// ACL owner
|
|||
acpOwner := r.Header.Get(s3_constants.ExtAmzOwnerKey) |
|||
if len(acpOwner) > 0 { |
|||
metadata[s3_constants.ExtAmzOwnerKey] = []byte(acpOwner) |
|||
} |
|||
|
|||
// ACL grants
|
|||
acpGrants := r.Header.Get(s3_constants.ExtAmzAclKey) |
|||
if len(acpGrants) > 0 { |
|||
metadata[s3_constants.ExtAmzAclKey] = []byte(acpGrants) |
|||
} |
|||
|
|||
return metadata, s3err.ErrNone |
|||
} |
|||
@ -1,55 +1,73 @@ |
|||
package s3api |
|||
|
|||
import ( |
|||
"errors" |
|||
"fmt" |
|||
"testing" |
|||
|
|||
"github.com/seaweedfs/seaweedfs/weed/s3api/s3err" |
|||
weed_server "github.com/seaweedfs/seaweedfs/weed/server" |
|||
"github.com/seaweedfs/seaweedfs/weed/util/constants" |
|||
) |
|||
|
|||
func TestFilerErrorToS3Error(t *testing.T) { |
|||
tests := []struct { |
|||
name string |
|||
errString string |
|||
err error |
|||
expectedErr s3err.ErrorCode |
|||
}{ |
|||
{ |
|||
name: "nil error", |
|||
err: nil, |
|||
expectedErr: s3err.ErrNone, |
|||
}, |
|||
{ |
|||
name: "MD5 mismatch error", |
|||
errString: constants.ErrMsgBadDigest, |
|||
err: errors.New(constants.ErrMsgBadDigest), |
|||
expectedErr: s3err.ErrBadDigest, |
|||
}, |
|||
{ |
|||
name: "Read only error (direct)", |
|||
err: weed_server.ErrReadOnly, |
|||
expectedErr: s3err.ErrAccessDenied, |
|||
}, |
|||
{ |
|||
name: "Read only error (wrapped)", |
|||
err: fmt.Errorf("create file /buckets/test/file.txt: %w", weed_server.ErrReadOnly), |
|||
expectedErr: s3err.ErrAccessDenied, |
|||
}, |
|||
{ |
|||
name: "Context canceled error", |
|||
errString: "rpc error: code = Canceled desc = context canceled", |
|||
err: errors.New("rpc error: code = Canceled desc = context canceled"), |
|||
expectedErr: s3err.ErrInvalidRequest, |
|||
}, |
|||
{ |
|||
name: "Context canceled error (simple)", |
|||
errString: "context canceled", |
|||
err: errors.New("context canceled"), |
|||
expectedErr: s3err.ErrInvalidRequest, |
|||
}, |
|||
{ |
|||
name: "Directory exists error", |
|||
errString: "existing /path/to/file is a directory", |
|||
err: errors.New("existing /path/to/file is a directory"), |
|||
expectedErr: s3err.ErrExistingObjectIsDirectory, |
|||
}, |
|||
{ |
|||
name: "File exists error", |
|||
errString: "/path/to/file is a file", |
|||
err: errors.New("/path/to/file is a file"), |
|||
expectedErr: s3err.ErrExistingObjectIsFile, |
|||
}, |
|||
{ |
|||
name: "Unknown error", |
|||
errString: "some random error", |
|||
err: errors.New("some random error"), |
|||
expectedErr: s3err.ErrInternalError, |
|||
}, |
|||
} |
|||
|
|||
for _, tt := range tests { |
|||
t.Run(tt.name, func(t *testing.T) { |
|||
result := filerErrorToS3Error(tt.errString) |
|||
result := filerErrorToS3Error(tt.err) |
|||
if result != tt.expectedErr { |
|||
t.Errorf("filerErrorToS3Error(%q) = %v, want %v", tt.errString, result, tt.expectedErr) |
|||
t.Errorf("filerErrorToS3Error(%v) = %v, want %v", tt.err, result, tt.expectedErr) |
|||
} |
|||
}) |
|||
} |
|||
|
|||
@ -0,0 +1,82 @@ |
|||
package stats_test |
|||
|
|||
import ( |
|||
"runtime" |
|||
"strings" |
|||
"testing" |
|||
|
|||
"github.com/prometheus/client_golang/prometheus/testutil" |
|||
"github.com/seaweedfs/seaweedfs/weed/stats" |
|||
_ "github.com/seaweedfs/seaweedfs/weed/util/version" // Import to trigger version init
|
|||
) |
|||
|
|||
func TestBuildInfo(t *testing.T) { |
|||
// Verify that BuildInfo metric is registered and has the expected value
|
|||
count := testutil.CollectAndCount(stats.BuildInfo) |
|||
if count != 1 { |
|||
t.Errorf("Expected 1 BuildInfo metric, got %d", count) |
|||
} |
|||
|
|||
// Verify the metric can be gathered
|
|||
metrics, err := stats.Gather.Gather() |
|||
if err != nil { |
|||
t.Fatalf("Failed to gather metrics: %v", err) |
|||
} |
|||
|
|||
// Find the build_info metric
|
|||
found := false |
|||
for _, mf := range metrics { |
|||
if mf.GetName() == "SeaweedFS_build_info" { |
|||
found = true |
|||
metric := mf.GetMetric()[0] |
|||
|
|||
// Verify the metric value is 1
|
|||
if metric.GetGauge().GetValue() != 1 { |
|||
t.Errorf("Expected BuildInfo value to be 1, got %f", metric.GetGauge().GetValue()) |
|||
} |
|||
|
|||
// Verify labels exist
|
|||
labels := metric.GetLabel() |
|||
labelMap := make(map[string]string) |
|||
for _, label := range labels { |
|||
labelMap[label.GetName()] = label.GetValue() |
|||
} |
|||
|
|||
// Check required labels
|
|||
if _, ok := labelMap["version"]; !ok { |
|||
t.Error("Missing 'version' label") |
|||
} |
|||
if _, ok := labelMap["commit"]; !ok { |
|||
t.Error("Missing 'commit' label") |
|||
} |
|||
if _, ok := labelMap["sizelimit"]; !ok { |
|||
t.Error("Missing 'sizelimit' label") |
|||
} |
|||
if labelMap["goos"] != runtime.GOOS { |
|||
t.Errorf("Expected goos='%s', got '%s'", runtime.GOOS, labelMap["goos"]) |
|||
} |
|||
if labelMap["goarch"] != runtime.GOARCH { |
|||
t.Errorf("Expected goarch='%s', got '%s'", runtime.GOARCH, labelMap["goarch"]) |
|||
} |
|||
|
|||
// Verify version format
|
|||
if !strings.Contains(labelMap["version"], ".") { |
|||
t.Errorf("Version should contain a dot: %s", labelMap["version"]) |
|||
} |
|||
|
|||
// Verify sizelimit is either 30GB or 8000GB
|
|||
if labelMap["sizelimit"] != "30GB" && labelMap["sizelimit"] != "8000GB" { |
|||
t.Errorf("Expected sizelimit to be '30GB' or '8000GB', got '%s'", labelMap["sizelimit"]) |
|||
} |
|||
|
|||
t.Logf("BuildInfo metric: version=%s, commit=%s, sizelimit=%s, goos=%s, goarch=%s", |
|||
labelMap["version"], labelMap["commit"], labelMap["sizelimit"], |
|||
labelMap["goos"], labelMap["goarch"]) |
|||
} |
|||
} |
|||
|
|||
if !found { |
|||
t.Error("BuildInfo metric not found in gathered metrics") |
|||
} |
|||
} |
|||
|
|||
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