8 repository-uri
Techniques for improving database execution plans, such as injecting literal values into SQL statements.
Distinct from Deterministic Value Injection: The candidates focus on language literals or test injection, not database-specific execution plan optimization.
Explore 8 awesome GitHub repositories matching data & databases · Query Plan Optimizations. Refine with filters or upvote what's useful.
Dapper is a high-performance micro-ORM and SQL object mapper for .NET. It functions as an ADO.NET extension library that adds data mapping capabilities directly to database connections, allowing SQL query results to be transformed into typed objects. The project prioritizes execution speed and low memory overhead by using intermediate language generation to map database columns to object properties. It further optimizes performance through the use of concurrent caching for mapping functions and literal value injection to improve database execution plans. The library covers a broad range of d
Allows embedding numeric or boolean constants directly into queries to improve database index efficiency.
Apache DataFusion is an extensible, columnar SQL query engine that runs embedded within a host application without requiring a separate server process. It processes data in columnar batches using Apache Arrow for memory-efficient analytics, and can scale analytic workloads across multiple nodes for parallel execution. The engine supports both SQL and DataFrame queries through a modular, streaming architecture that allows custom operators, data sources, functions, and optimizer rules. The engine distinguishes itself through its modular extension framework, which enables building custom query e
Applies advanced optimizations like filter pushdown, join reordering, and expression simplification automatically.
Soar is a suite of specialized tools designed for analyzing MySQL performance, advising on indexing, and optimizing SQL syntax. It functions as a performance analyzer, index advisor, and query optimizer to identify bottlenecks and suggest structural improvements for faster execution. The project distinguishes itself through a system for rewriting SQL statements into optimized equivalent versions using custom heuristic rules and patterns. It also features a dedicated index advisor that evaluates query patterns and database metadata to recommend the creation of new indexes. Its broader capabil
Applies a fixed set of rewrite rules to transform logical plans and improve execution speed.
Calcite este un framework pentru parsarea, optimizarea și traducerea interogărilor SQL în algebră relațională pentru execuție pe diverse surse de date. Funcționează ca un motor de interogare cross-source, o bibliotecă de parsare SQL și un optimizator de algebră relațională. Proiectul oferă un motor de optimizare bazat pe costuri care transformă planurile logice de interogare în planuri de execuție fizică eficiente, folosind reguli pluggable. Utilizează adaptoare de traducere pentru a converti cererile SQL standard în formatele native ale bazelor de date externe și ale sistemelor de mesagerie, permițând federarea datelor între sisteme de stocare eterogene. Sistemul acoperă întregul ciclu de viață al interogării, incluzând parsarea SQL și validarea pe baza schemelor, traducerea expresiilor în operatori algebrici și selectarea planurilor de execuție eficiente. Include, de asemenea, o interfață de linie de comandă pentru executarea interogărilor și gestionarea conexiunilor la sursele de date.
Transforms logical plans into efficient physical plans using pluggable rules and cost-based functions.
Redka este un magazin de tip cheie-valoare susținut de SQL care implementează o interfață compatibilă cu Redis. Acesta acționează ca o punte de date relaționale, traducând comenzile de protocol non-relaționale în interogări relaționale pentru a oferi persistență și tranzacții ACID folosind un backend de bază de date SQL. Sistemul permite introspecția datelor relaționale prin expunerea datelor interne cheie-valoare ca vizualizări SQL, permițând interogarea și analiza directă prin sintaxă relațională. Poate fi implementat ca server de rețea independent sau ca bibliotecă încorporată într-o aplicație Go. Proiectul suportă o varietate de structuri de date, inclusiv șiruri de caractere, liste, hash-uri, seturi neordonate și seturi sortate. Oferă capabilități pentru gestionarea ciclului de viață al cheilor cu metadate de tip time-to-live, operații numerice atomice și algebră de seturi. Pentru a gestiona performanța și accesul, include un mod de stocare în memorie și un mod de conexiune read-only.
Exposes internal key-value data as SQL views to enable direct querying and analysis via relational syntax.
This project is a Chinese localization repository and technical translation project designed to make concise programming projects and technical documentation accessible to Chinese speakers. It provides a collection of translated resources and curated mappings of computer science terminology to ensure consistent translation of technical concepts. The project implements a software localization workflow that converts English-language technical guides and codebase documentation into Chinese. This process utilizes a technical glossary resource and a resource-driven localization model to maintain t
Transforms query programs into more efficient versions using priority-based restructuring functions.
MiniOB is an open-source educational relational database kernel designed for learning the internals of database systems. It implements a dual-engine storage architecture combining B+ Tree and LSM-Tree, supports SQL parsing and query execution, and provides transactional processing with multi-version concurrency control. The system communicates with clients using the MySQL wire protocol and includes a vector database extension for storing and querying high-dimensional vectors. The project distinguishes itself through its comprehensive coverage of core database concepts in a single, learnable c
Rewrites query syntax trees using rules and statistics to produce faster execution plans.
This project is an educational resource and technical manual for Apache Spark, focused on the architecture and practical application of large-scale data processing. It serves as a guide for big data engineering and distributed computing, covering the principles of parallel processing and fault-tolerant data distribution. The material provides instructional content on designing distributed ETL pipelines and implementing data analysis workflows. It includes tutorials for polyglot data processing, offering patterns and examples for using Python, Scala, and Java within a unified environment. The
Provides detailed explanations of the Catalyst optimizer's rule-based and cost-based relational query transformation.