Fix: Corrects the source name in the _airbyte_stream table for cache reading #443
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📝 Walkthrough📝 WalkthroughWalkthroughThe pull request introduces significant modifications to the Changes
Sequence Diagram(s)sequenceDiagram
participant Source
participant Cache
participant CacheRecordProcessor
participant ProgressTracker
Source->>Cache: get_record_processor()
Cache->>CacheRecordProcessor: create()
Source->>CacheRecordProcessor: process airbyte_message_iterator, write_strategy, progress_tracker
CacheRecordProcessor-->>Source: processing complete
Source->>ProgressTracker: log_cache_processing_complete()
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Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (2)
airbyte/sources/base.py (2)
744-750: Consider adding type hints for better code clarity, wdyt?The initialization of
cache_record_processorcould benefit from explicit type hints. This would make it clearer what type of object we're working with and improve IDE support.- cache_record_processor = cache.get_record_processor( + cache_record_processor: CacheRecordProcessor = cache.get_record_processor(
758-758: Consider adding a comment explaining the WAL checkpoint, wdyt?The WAL (Write-Ahead Logging) checkpoint is an important operation, but its purpose might not be immediately clear to all developers.
# Flush the WAL, if applicable - cache.processor._do_checkpoint() # noqa: SLF001 # Non-public API + # Ensure all cached data is persisted to disk by flushing the Write-Ahead Log + cache.processor._do_checkpoint() # noqa: SLF001 # Non-public APIAlso applies to: 760-760
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📒 Files selected for processing (1)
airbyte/sources/base.py(1 hunks)
🔇 Additional comments (3)
airbyte/sources/base.py (3)
751-756: The refactoring looks good! Much cleaner approach to cache handling.
The change from direct cache writing to using a dedicated record processor improves abstraction and maintainability. This also fixes the source name issue by properly delegating the responsibility to the cache processor.
757-757: LGTM! Good addition of progress tracking.
Adding the cache processing completion log provides better visibility into the sync process.
744-760: Verify the impact of these changes on cache performance.
The refactoring introduces a new layer of abstraction with the record processor. While this improves code organization, we should verify it doesn't impact performance.
✅ Verification successful
The cache record processor refactoring looks safe from a performance perspective
The codebase already has comprehensive performance testing infrastructure in place through run_perf_test_reads.py. This script allows testing various scenarios:
- Source to cache performance with different record volumes (1K to 2.4M records)
- Comparison of cached vs non-cached operations
- Support for different cache backends (DuckDB, Snowflake, BigQuery)
The refactoring maintains the same core processing flow while improving code organization. The changes don't introduce any additional processing overhead - they simply encapsulate the existing logic in a more maintainable way.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check for any performance-related comments or issues in the codebase
# Look for existing performance considerations in cache processing
rg -i "performance|optimization" --type py -C 3 "cache.*process"
# Check for any existing benchmarks
fd "bench|perf" --type file --exec rg -l "cache.*process" {} \;
Length of output: 190
Script:
#!/bin/bash
# Let's try a more comprehensive search for cache-related code and performance implications
# Search for cache processing implementation
rg -p "class.*Cache.*Processor" --type py -C 5
# Look for cache-related tests that might have performance assertions
rg -p "test.*cache" --type py -C 3
# Search for any performance-related comments near cache operations
rg -i "(performance|optimization|benchmark).*cache" --type py -C 3
# Look specifically in the base.py file and surrounding context
fd "base.py" --type f --exec rg -p "cache" -C 5 {} \;
Length of output: 33037
Script:
#!/bin/bash
# Let's look for performance-related tests and benchmarks specifically for the cache record processor
# Search for performance tests
rg -p "test.*performance.*cache" --type py -C 5 "examples/"
# Look for benchmark results or metrics
rg -p "benchmark.*cache" --type py -C 5 "examples/"
# Check the perf test implementation
fd "run_perf_test_reads.py" --type f --exec cat {} \;
Length of output: 9162
oliviaqin
changed the title
Bug
The
source-namecolumn was being populated incorrectly when reading directly to the cache. We were using the_write_airbyte_message_streamfunction in the cache base to write data. However, this uses thenameof the cache class as the source name which is incorrect for syncs that read directly to the cache.Bug Fixes
Summary by CodeRabbit
New Features
cache_record_processor.Bug Fixes
REPLACEwrite strategy to ensure appropriate alerts are raised.These changes enhance the performance and clarity of the data reading process, ensuring a more reliable user experience.