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Cache DynamicDestinationsHelper.ConstantTimePartitioningClusteringDestination clustering & partitioning #37014
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Summary of ChangesHello @stankiewicz, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request introduces a significant performance enhancement to the BigQuery I/O connector by optimizing how partitioning and clustering configurations are handled. Previously, these configurations were parsed from JSON for every element, leading to unnecessary overhead. The change implements a caching strategy within Highlights
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/gemini review |
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Code Review
The pull request aims to improve performance by caching the evaluation of partitioning and clustering configurations within ConstantTimePartitioningClusteringDestinations. This is a valuable optimization. However, a critical issue exists with the serialization of the initialized flag, which could lead to incorrect behavior and negate the caching benefits in a distributed environment.
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/gemini review |
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Code Review
This pull request introduces caching for partitioning and clustering configurations to avoid expensive repeated JSON parsing, which is a good performance improvement. The implementation uses double-checked locking with an AtomicBoolean for lazy initialization. My feedback includes a suggestion to make the initialized flag final for improved thread-safety and another to refactor duplicated logic for better maintainability.
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…ons is parsing per element json configuration for partitioning and clustering which is expensive. Cache the outcome of evaluation so it's done once.
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Assigning reviewers: R: @chamikaramj for label java. Note: If you would like to opt out of this review, comment Available commands:
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Reminder, please take a look at this pr: @chamikaramj |
Fixes #36989
DynamicDestinationsHelper.ConstantTimePartitioningClusteringDestinations is parsing per element json configuration for partitioning and clustering which is expensive. Cache the outcome of evaluation so it's done once.
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