Month: 2026-05 Focused on delivering storage efficiency, data correctness, and performance improvements for OpenSearch through targeted feature work, bug fixes, and robust testing. Highlights include Parquet encoding/compression configuration with metadata exposure, DataFormatAwareEngine segment statistics enhancements, and a critical large-file merge correctness bugfix, all backed by integration tests and code surface area improvements.

April 2026 monthly summary for opensearch-project/OpenSearch focused on delivering robust Parquet data processing and strengthening testability, with measurable business value in data ingestion reliability and performance. Key features delivered: - Parquet Data Merge with K-way streaming sort: introduced support for merging Parquet data using a K-way streaming sort, enabling scalable, efficient merges in Parquet workflows. Included optimizations for ColumnMapping, addition of ParquetSortConfig class, and integration tests. Enhanced Rust bridge to improve functionality and correctness (sync_to_disk test). - Rust bridge enhancements: added InvokeIO, CRC-related improvements, and support for End-to-End IntegTests to ensure end-to-end validation of the Parquet merge path. Major bugs fixed: - Resolved sync_to_disk test failures related to Parquet merge workflow, improving CI stability. - Stabilized integration tests and addressed test comments during refactor iterations to improve reliability. Overall impact and accomplishments: - Enhanced data ingestion reliability and performance for Parquet-based pipelines, enabling faster, more dependable data processing in production. - Improved code quality and maintainability through targeted refactors, test coverage expansions, and CI hygiene (Spotless formatting). - Strengthened end-to-end validation with IntegTests and CRC checks, reducing risk of regressions in data processing workflows. Technologies/skills demonstrated: - Rust integration and bridge development, Parquet data format handling, and K-way streaming sort algorithms. - Test automation with integration tests, end-to-end validation, and CRC checks. - Code refactoring, Spotless formatting, and CI/CD hygiene.

June 2025: Implemented Star-Tree Nested Aggregations Support in wazuh/wazuh-indexer, enabling nested aggregations inside Star-Tree for complex analytics queries. This delivers deeper insights with fewer steps and improves performance for multi-level aggregations. Commit 6fd93298f46b1bbbabeef5770f857878666e5426 was merged as part of this work.

Month: 2025-04 — The primary deliverable for wazuh-indexer this month was expanding Star Tree indexing to support unsigned long data types, enabling analytics across larger numeric ranges and expanding dimensional capabilities. This involved updating query logic and data handling to correctly process and filter unsigned long dimensions, paving the way for more scalable analytics and broader data-schema compatibility. The work is captured in the commit referencing the unsigned-long support and aligns with goals to improve data-schema flexibility and performance for large datasets. Major outcomes included: - Star Tree Indexing: Added support for unsigned long data types, updating query logic and data handling to correctly process and filter data based on unsigned long dimensions. - Broader analytics: Enables analytics across larger integer ranges and expands dimensional capabilities in wazuh-indexer. - Clear traceability: Changes are documented in the commit 3e10fe3f4eacbc950f09e7f2a285797b78df8ca1 with message 'Add query changes to support unsigned-long in star tree (#17275)'. Overall impact: Enhanced data-model flexibility and analytics scalability, contributing to business value by supporting larger-scale dashboards and analytics scenarios. Technologies/skills demonstrated: Star Tree indexing architecture, unsigned data type handling, query logic updates, code traceability via commit messages, and collaboration across indexing components.

March 2025: Focused on correctness and reliability of unsigned long data handling in wazuh-indexer. Implemented a dedicated UnsignedLongHashSet to correctly process unsigned long values, integrated into the SortedUnsignedLongDocValuesSetQuery, and expanded tests to validate sorting behavior and unsigned data assertions. These changes reduce data misordering risk and improve analytics reliability.

January 2025 monthly summary for wazuh-indexer. Focused on delivering enhanced analytics capabilities through Star Tree unsigned-long data type indexing, including dimension handling changes, metadata updates, and tests. This work expands numeric data support for large-scale dashboards and complements existing analytics workloads. Major bugs fixed: none reported this month.