FoundationDB/fdb-record-layer
Dec 2025 – Apr 2026
4 Months active
Languages Used
JavaSQLYAML
Technical Skills
Database ManagementJavaSQLYAMLYAML configurationbackend development
sergei-pustovykh
PROFILE
Sergei-pustovykh
During December 2025, this developer delivered advanced SQL INNER JOIN support for the FoundationDB/fdb-record-layer repository, enabling multi-table joins using standard SQL syntax. They enhanced the logical plan and planner visitor to correctly parse and optimize inner join expressions, allowing for more complex reporting and efficient retrieval of related data within a single query. By reducing the need for client-side data stitching and minimizing round-trips, the update improved both usability and performance. The work was implemented using Java and SQL, with careful attention to maintaining backward compatibility and stable performance across existing features, demonstrating depth in database management and query optimization.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
11Total
Bugs
2
Commits
11
Features
6
Lines of code
13,012
Activity Months4
Your Network
624 peopleSame Organization
@apple.com595
Shared Repositories
29
Arnaud LacurieMember
Alec GrieserMember
Alec GrieserMember
Aaron MolitorMember
Scott FinesMember
Christos ChrysafisMember
FoundationDB CIMember
Pranjal GuptaMember
Arnaud LacurieMember
Work History
April 2026
4 Commits • 1 Features
Apr 1, 2026In April 2026, delivered major enhancements to the fdb-record-layer's plan cache and explain pipeline, improving query planning performance, cache efficiency, and telemetry. Key changes include per-level LRU eviction metrics for the MultiStageCache, enabling EXPLAIN to reuse cached plans for corresponding data queries, and collecting PLANNER_METRICS for every plan generation (including when served from cache). Also implemented a deterministic Correlation Identifier for plan serialization to improve reproducibility of EXPLAIN output. These changes reduce expensive plan recomputation, increase cache hit rates, and provide richer planning telemetry for operational insight and debugging.
4 Commits • 1 Features
Apr 1, 2026In April 2026, delivered major enhancements to the fdb-record-layer's plan cache and explain pipeline, improving query planning performance, cache efficiency, and telemetry. Key changes include per-level LRU eviction metrics for the MultiStageCache, enabling EXPLAIN to reuse cached plans for corresponding data queries, and collecting PLANNER_METRICS for every plan generation (including when served from cache). Also implemented a deterministic Correlation Identifier for plan serialization to improve reproducibility of EXPLAIN output. These changes reduce expensive plan recomputation, increase cache hit rates, and provide richer planning telemetry for operational insight and debugging.
April 2026
March 2026
2 Commits • 1 Features
Mar 1, 2026In 2026-03, the team pursued performance improvements in FoundationDB/fdb-record-layer by implementing an SQL Explain Plan Caching Enhancement to reuse cached plans between explain requests and the corresponding data queries. The change included canonical query string-based cache keys and ParseTree adjustments to ensure symmetric caching and correct explain formatting. After extensive validation, stability concerns were identified, leading to the rollback of the feature to preserve reliability (reverting commit 5fc581... in PR #4031). The investigation and rollback provided critical insights into explain caching trade-offs and established a path for a safer reimplementation with stronger tests and safeguards. Technologies demonstrated include ParseTree manipulation, canonical query generation, NormalizedQueryExecutionContext, and MutablePlanGenerationContext. Business value: reduced unnecessary plan generation opportunities when explain requests are frequent, while maintaining stable and predictable performance for production workloads.
March 2026
2 Commits • 1 Features
Mar 1, 2026In 2026-03, the team pursued performance improvements in FoundationDB/fdb-record-layer by implementing an SQL Explain Plan Caching Enhancement to reuse cached plans between explain requests and the corresponding data queries. The change included canonical query string-based cache keys and ParseTree adjustments to ensure symmetric caching and correct explain formatting. After extensive validation, stability concerns were identified, leading to the rollback of the feature to preserve reliability (reverting commit 5fc581... in PR #4031). The investigation and rollback provided critical insights into explain caching trade-offs and established a path for a safer reimplementation with stronger tests and safeguards. Technologies demonstrated include ParseTree manipulation, canonical query generation, NormalizedQueryExecutionContext, and MutablePlanGenerationContext. Business value: reduced unnecessary plan generation opportunities when explain requests are frequent, while maintaining stable and predictable performance for production workloads.
February 2026
4 Commits • 3 Features
Feb 1, 2026February 2026 (FoundationDB/fdb-record-layer): Focused on expanding test expressiveness and SQL usability while preserving stability. Work included exploratory test representation changes, a new test tag for column-position validation, and enhancements to JOIN behavior.
4 Commits • 3 Features
Feb 1, 2026February 2026 (FoundationDB/fdb-record-layer): Focused on expanding test expressiveness and SQL usability while preserving stability. Work included exploratory test representation changes, a new test tag for column-position validation, and enhancements to JOIN behavior.
February 2026
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025: Delivered Advanced SQL INNER JOIN Support for FoundationDB/fdb-record-layer, enabling multi-table joins via standard SQL syntax and improved data retrieval across related tables. Updated the logical plan and planner visitor to support inner join expressions, enhancing query capabilities while maintaining compatibility and performance.
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025: Delivered Advanced SQL INNER JOIN Support for FoundationDB/fdb-record-layer, enabling multi-table joins via standard SQL syntax and improved data retrieval across related tables. Updated the logical plan and planner visitor to support inner join expressions, enhancing query capabilities while maintaining compatibility and performance.
Activity
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Quality Metrics
Correctness96.4%
Maintainability81.8%
Architecture87.2%
Performance85.4%
AI Usage31.0%
Skills & Technologies
Programming Languages
JavaSQLYAML
Technical Skills
Backend DevelopmentCachingDatabase ManagementJavaPerformance OptimizationSQLSoftware TestingYAMLYAML configurationbackend developmentdatabase designdatabase managementmetrics trackingperformance optimizationsoftware development
Repositories Contributed To
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