
Jiaqi Zhou contributed to apache/cloudberry by engineering advanced query optimization and storage features, focusing on the ORCA optimizer and PAX storage engine. He implemented segment-level NDV statistics and vectorized window aggregation to improve query planning and execution, while also enhancing single-node deployment stability. Zhou refactored internal optimizer logic for efficiency and ensured ASF policy compliance by replacing submodules with local sources. His work involved C++ and SQL, emphasizing code refactoring, distributed systems, and build system configuration. The solutions addressed performance, reliability, and maintainability, demonstrating a deep understanding of database internals and production-ready engineering in a complex codebase.

2025-07 Monthly Summary for apache/cloudberry focusing on delivering business value through improved query planning, performance, and stability. Key outcomes include more accurate cost estimations for two-stage aggregations via segment-level NDV statistics, faster windowing paths with Vectorized WindowHashAgg, hardened single-node operation, and a series of reliability and policy-compliance improvements.
2025-07 Monthly Summary for apache/cloudberry focusing on delivering business value through improved query planning, performance, and stability. Key outcomes include more accurate cost estimations for two-stage aggregations via segment-level NDV statistics, faster windowing paths with Vectorized WindowHashAgg, hardened single-node operation, and a series of reliability and policy-compliance improvements.
June 2025 performance and engineering summary for apache/cloudberry. Focused on advancing query optimization and production tooling. Key features delivered: ORCA Optimizer Enhancements—push-down of partial aggregates below joins to enable earlier aggregation; new configuration knob to control redistribution keys for aggregates to reduce overhead and mitigate data skew. Production Build Optimization—disable googlebench by default in release builds to align artifacts with production needs and reduce tooling in the PAX storage component. Major bugs fixed: none recorded this month. Overall impact: expected improvements in query latency for heavy join workloads and leaner release artifacts, contributing to more reliable production deployments. Technologies/skills demonstrated: advanced query optimization techniques, execution plan transformations, build/release engineering, configuration management, and data-skew mitigation strategies.
June 2025 performance and engineering summary for apache/cloudberry. Focused on advancing query optimization and production tooling. Key features delivered: ORCA Optimizer Enhancements—push-down of partial aggregates below joins to enable earlier aggregation; new configuration knob to control redistribution keys for aggregates to reduce overhead and mitigate data skew. Production Build Optimization—disable googlebench by default in release builds to align artifacts with production needs and reduce tooling in the PAX storage component. Major bugs fixed: none recorded this month. Overall impact: expected improvements in query latency for heavy join workloads and leaner release artifacts, contributing to more reliable production deployments. Technologies/skills demonstrated: advanced query optimization techniques, execution plan transformations, build/release engineering, configuration management, and data-skew mitigation strategies.
Month: 2025-05 — Focused on optimizer enhancements and stability work in apache/cloudberry. Delivered several high-impact features in the ORCA optimizer and fixed critical issues affecting query execution and planning on large/partitioned datasets. Result: faster queries, reduced resource usage, and more robust planning.
Month: 2025-05 — Focused on optimizer enhancements and stability work in apache/cloudberry. Delivered several high-impact features in the ORCA optimizer and fixed critical issues affecting query execution and planning on large/partitioned datasets. Result: faster queries, reduced resource usage, and more robust planning.
April 2025 monthly summary for apache/cloudberry: Focused on reliability and maintainability across storage, optimization, and repository dependencies. Key outcomes include stability improvements in PAX storage, ORCA optimizer fixes, and refreshed submodule dependencies, delivering concrete business value through more reliable data processing, fewer CI failures, and smoother future maintenance.
April 2025 monthly summary for apache/cloudberry: Focused on reliability and maintainability across storage, optimization, and repository dependencies. Key outcomes include stability improvements in PAX storage, ORCA optimizer fixes, and refreshed submodule dependencies, delivering concrete business value through more reliable data processing, fewer CI failures, and smoother future maintenance.
In March 2025, delivered PAX storage integration with ORCA and readiness for Cloudberry CBDB, including updates to reads/writes for non-fixed-length columns via offset arrays and enabling PAX in optimizer planning; aligned regression tests with CBDB. Implemented ORCA core enhancements for stability and performance, including an Append operator for partitioned tables and a new GUC to control dynamic table scans, along with interconnect code simplifications and test stabilization. Major bug fixes focused on improving test reliability, including ORCA unit-test fixes and test adaptations for CBDB. These efforts collectively improve analytics performance, reliability, and CI readiness across the ORCA/Cloudberry integration.
In March 2025, delivered PAX storage integration with ORCA and readiness for Cloudberry CBDB, including updates to reads/writes for non-fixed-length columns via offset arrays and enabling PAX in optimizer planning; aligned regression tests with CBDB. Implemented ORCA core enhancements for stability and performance, including an Append operator for partitioned tables and a new GUC to control dynamic table scans, along with interconnect code simplifications and test stabilization. Major bug fixes focused on improving test reliability, including ORCA unit-test fixes and test adaptations for CBDB. These efforts collectively improve analytics performance, reliability, and CI readiness across the ORCA/Cloudberry integration.
February 2025 monthly summary for apache/cloudberry focusing on delivering optimizer improvements, AO index-scan support, CBDB integration, and build/test infrastructure enhancements. The work demonstrates strong alignment with business value (query performance, reliability, and scalable distributed planning) and technical mastery across the optimizer, storage, extensions, and CI. Key achievements include a set of targeted commits addressing correctness, integration, and stability across the GPORCA/ORCA optimizer, AO/PAX storage, and CBDB extension compatibility, as well as infrastructure cleanup to improve build/test reliability.
February 2025 monthly summary for apache/cloudberry focusing on delivering optimizer improvements, AO index-scan support, CBDB integration, and build/test infrastructure enhancements. The work demonstrates strong alignment with business value (query performance, reliability, and scalable distributed planning) and technical mastery across the optimizer, storage, extensions, and CI. Key achievements include a set of targeted commits addressing correctness, integration, and stability across the GPORCA/ORCA optimizer, AO/PAX storage, and CBDB extension compatibility, as well as infrastructure cleanup to improve build/test reliability.
In 2025-01, focused on hardening the Apache Cloudberry optimizer path and stabilizing build workflows to deliver reliable, scalable analytics. The work centers on ORCA robustness, storage alignment, and build-system improvements that together reduce crash risk, improve correctness for complex grouping scenarios, and streamline developer workflows.
In 2025-01, focused on hardening the Apache Cloudberry optimizer path and stabilizing build workflows to deliver reliable, scalable analytics. The work centers on ORCA robustness, storage alignment, and build-system improvements that together reduce crash risk, improve correctness for complex grouping scenarios, and streamline developer workflows.
December 2024 – Apache/CloudBerry: Key features delivered include the PAX sparse filter overhaul (nested structures, vectorized expressions, CAST in PG path) and ORCA PG14 enhancements (distribution in DQA, NL-index support, Derive Combined Hashed Spec For Outer Joins), plus a table writer encoding options cache for performance. Major bugs fixed covered runtime reliability (memory leaks, ordered-set agg crash risk, atomic counting in filter stats), PG14 dynamic scans compatibility (bitmap/index/table), Pax storage statistics accuracy, and test stability. Overall impact: stronger query capability with richer filtering and joins, improved stability and reliability, and tangible performance gains across workloads. Technologies demonstrated: PAX architecture, ORCA optimizer, PostgreSQL 14 compatibility, vectorized and nested expressions, multithreading correctness, caching strategies, and test stabilization.
December 2024 – Apache/CloudBerry: Key features delivered include the PAX sparse filter overhaul (nested structures, vectorized expressions, CAST in PG path) and ORCA PG14 enhancements (distribution in DQA, NL-index support, Derive Combined Hashed Spec For Outer Joins), plus a table writer encoding options cache for performance. Major bugs fixed covered runtime reliability (memory leaks, ordered-set agg crash risk, atomic counting in filter stats), PG14 dynamic scans compatibility (bitmap/index/table), Pax storage statistics accuracy, and test stability. Overall impact: stronger query capability with richer filtering and joins, improved stability and reliability, and tangible performance gains across workloads. Technologies demonstrated: PAX architecture, ORCA optimizer, PostgreSQL 14 compatibility, vectorized and nested expressions, multithreading correctness, caching strategies, and test stabilization.
November 2024 monthly summary for apache/cloudberry: Key features delivered: - PAX Storage Core Improvements: stabilizes and optimizes storage core, improving storage efficiency through selective alignment, reducing detoasting, fixing concurrent sequence generation, and resolving insertion issues for large block IDs. Commits include bce408d859b6b89a465ec4708618ef16fe4a8fa3; f835d47a1fae587abce081ac1fbad1cea824127d; 5d91bd643bd5f700405c3a4abaabbb67cd90b458; a43e647b8e6a542b8ef6b92038340793b7547003. - PAX Python API and Build/Install Integration: adds Paxpy Python 3 API for PAX storage and enables libpaxformat build/install with adjusted CMake/Makefile to support installation. Commits: 394603a1df3708b4249727615e5427d4ceab493e; c4cfe6ea948dfc370e8e22a46c597eb36b1c31fe. - GP Interconnect Configurability via gpconfig: fixes configuration of Gp_interconnect_queue_depth and Gp_interconnect_snd_queue_depth by removing an obstacle function and updating tests to accommodate related warnings. Commit: 4c2ed58f15e35ab89cfbfc57425f3590730b5d13. Major bugs fixed: - PAX fast sequence concurrency issue (ensures unique sequence under concurrent access). - Insertion failures in pax auxiliary table when block IDs exceed 32768. - Detoasting optimizations for unread and short header datum to improve memory efficiency. - gpconfig-related test warnings handling improved by removing obstacle function. Overall impact and accomplishments: - Improved storage throughput and reliability for PAX, enabling more predictable performance under high concurrency and large block IDs. - Enhanced developer productivity and deployment readiness through Paxpy Python API and a streamlined build/install process. - Reduced production risk by stabilizing interconnect configuration workflow and aligning tests with expected warnings. Technologies/skills demonstrated: - C/C++ optimization: memory alignment, detoasting, and concurrency correctness in storage core. - Python API development for storage systems (Paxpy) and integration with build tooling. - Build systems and deployment: CMake/Makefile adjustments, libpaxformat installation. - Configuration management and test maintenance for GP interconnects (gpconfig).
November 2024 monthly summary for apache/cloudberry: Key features delivered: - PAX Storage Core Improvements: stabilizes and optimizes storage core, improving storage efficiency through selective alignment, reducing detoasting, fixing concurrent sequence generation, and resolving insertion issues for large block IDs. Commits include bce408d859b6b89a465ec4708618ef16fe4a8fa3; f835d47a1fae587abce081ac1fbad1cea824127d; 5d91bd643bd5f700405c3a4abaabbb67cd90b458; a43e647b8e6a542b8ef6b92038340793b7547003. - PAX Python API and Build/Install Integration: adds Paxpy Python 3 API for PAX storage and enables libpaxformat build/install with adjusted CMake/Makefile to support installation. Commits: 394603a1df3708b4249727615e5427d4ceab493e; c4cfe6ea948dfc370e8e22a46c597eb36b1c31fe. - GP Interconnect Configurability via gpconfig: fixes configuration of Gp_interconnect_queue_depth and Gp_interconnect_snd_queue_depth by removing an obstacle function and updating tests to accommodate related warnings. Commit: 4c2ed58f15e35ab89cfbfc57425f3590730b5d13. Major bugs fixed: - PAX fast sequence concurrency issue (ensures unique sequence under concurrent access). - Insertion failures in pax auxiliary table when block IDs exceed 32768. - Detoasting optimizations for unread and short header datum to improve memory efficiency. - gpconfig-related test warnings handling improved by removing obstacle function. Overall impact and accomplishments: - Improved storage throughput and reliability for PAX, enabling more predictable performance under high concurrency and large block IDs. - Enhanced developer productivity and deployment readiness through Paxpy Python API and a streamlined build/install process. - Reduced production risk by stabilizing interconnect configuration workflow and aligning tests with expected warnings. Technologies/skills demonstrated: - C/C++ optimization: memory alignment, detoasting, and concurrency correctness in storage core. - Python API development for storage systems (Paxpy) and integration with build tooling. - Build systems and deployment: CMake/Makefile adjustments, libpaxformat installation. - Configuration management and test maintenance for GP interconnects (gpconfig).
In October 2024, contributions focused on the PAX storage engine in apache/cloudberry, delivering a safety fix, enabling arithmetic filtering, and improving error handling and test coverage. The work enhances data integrity, query expressiveness, and robustness of failure paths, with traceable commits and a solid testing regime.
In October 2024, contributions focused on the PAX storage engine in apache/cloudberry, delivering a safety fix, enabling arithmetic filtering, and improving error handling and test coverage. The work enhances data integrity, query expressiveness, and robustness of failure paths, with traceable commits and a solid testing regime.
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