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Baidu Geek Talk

Dec 16, 2024 · Artificial Intelligence

AIAPI: Baidu's AI-Native Retrieval System for Large Language Model Applications

AIAPI, Baidu’s AI‑native retrieval platform for large language models, tackles hallucination, slow domain updates, and output opacity by delivering authoritative, timely, full‑content data through a dual‑channel architecture that combines traditional search and RAG, employs reusable ranking, graph‑enhanced data layers, dynamic caching that cuts storage by 70 %, and QueryPlan‑based QoS, achieving markedly higher retrieval quality and a 34 % speed gain with Wenxin 4.0.

AI-Native SystemsAIAPICost Optimization

0 likes · 12 min read

AIAPI: Baidu's AI-Native Retrieval System for Large Language Model Applications

JD Retail Technology

May 8, 2024 · Databases

Understanding MySQL Cost Model for Index Optimization and Conflict Resolution

This article explains MySQL's cost‑based optimizer, demonstrates how to calculate query costs for full‑table, covering, ref and range scans using actual source‑code constants, and applies the model to resolve index‑conflict cases in a store‑goods table, offering practical optimization guidelines and future tool ideas.

Index OptimizationMySQLQuery Planning

0 likes · 22 min read

Understanding MySQL Cost Model for Index Optimization and Conflict Resolution

Ctrip Technology

Oct 20, 2022 · Databases

Practical Slow Query Optimization for MySQL at Ctrip

This article describes Ctrip's practical approach to identifying and optimizing MySQL slow queries, covering background, improved SQL review workflow, execution plan analysis, common index problems, query rewriting, pagination issues, resource contention, and best‑practice recommendations for long‑term performance.

Database OptimizationIndexingMySQL

0 likes · 10 min read

Practical Slow Query Optimization for MySQL at Ctrip

DataFunSummit

Oct 17, 2021 · Databases

Databend: Cloud‑Native Modern Data Warehouse Architecture and Features

This article explains how Databend, a cloud‑native data warehouse, addresses modern OLAP requirements through storage‑compute separation, elastic scaling, multi‑cloud support, advanced query planning, and serverless‑ready design, contrasting it with traditional data warehouse limitations.

Big DataData WarehouseDatabend

0 likes · 11 min read

Databend: Cloud‑Native Modern Data Warehouse Architecture and Features

Code Ape Tech Column

May 8, 2021 · Databases

Understanding MySQL Pagination Performance and Index Optimization

The article explores why MySQL pagination with large offsets is slow, explains index structures such as clustered and secondary indexes, describes logical query operators, and presents two practical optimization strategies to improve query performance.

Index OptimizationMySQLQuery Planning

0 likes · 6 min read

Understanding MySQL Pagination Performance and Index Optimization

Xianyu Technology

Mar 18, 2021 · Backend Development

Multi-Engine Concurrent Search Architecture for Idlefish

Idlefish’s new multi‑engine concurrent search architecture replaces the tightly‑coupled single‑engine pipeline with deep engine isolation, asynchronous multi‑engine recall, and unified result merging, cutting dump build time from 14 h to 5 h, shrinking memory use dramatically, improving latency by only ~15 ms, and boosting exposure by 50 % and orders by 33 %.

Big DataJavaLua

0 likes · 10 min read

Multi-Engine Concurrent Search Architecture for Idlefish

Aikesheng Open Source Community

Feb 24, 2021 · Databases

Understanding Composite (Multi‑Column) Indexes in MySQL

This article explains how MySQL composite indexes work, the syntax for creating them, the conditions required for their use, and how different query patterns affect index utilization, illustrated with multiple SQL examples and execution‑plan analyses.

MySQLQuery PlanningSQL Optimization

0 likes · 14 min read

Understanding Composite (Multi‑Column) Indexes in MySQL

Aikesheng Open Source Community

Dec 9, 2019 · Databases

Cross‑Database JOIN and Distributed Query Planning in DBLE Middleware

This tutorial explains how DBLE splits tables using different rules, demonstrates cross‑database INNER, LEFT, and RIGHT JOINs with jump‑hash sharding, and details the distributed query plan and sorting optimization that reduces join complexity in a middleware environment.

DBLEQuery PlanningSQL

0 likes · 7 min read

Cross‑Database JOIN and Distributed Query Planning in DBLE Middleware

Efficient Ops

Aug 4, 2019 · Databases

Master MySQL Indexes: When and How They’re Used for Queries, LIKE, and Sorting

This article explains how MySQL decides whether an index can be used for range queries, LIKE patterns, and ORDER BY operations, detailing key length calculation, index key vs. filter vs. table filter, and practical examples for BETWEEN and sorting scenarios.

Index OptimizationMySQLQuery Planning

0 likes · 11 min read

Master MySQL Indexes: When and How They’re Used for Queries, LIKE, and Sorting

DataFunTalk

Apr 22, 2019 · Databases

Deep Dive into TiDB SQL Optimizer and Execution Engine

This article provides a comprehensive technical overview of TiDB's architecture, its SQL optimizer—including logical and physical optimization phases, rule‑based transformations, join ordering, and statistics collection—and outlines future work to improve query planning stability and performance.

Database InternalsDistributed DatabaseQuery Planning

0 likes · 16 min read

Deep Dive into TiDB SQL Optimizer and Execution Engine

Efficient Ops

Nov 28, 2018 · Databases

Master MySQL Indexes: When and How They’re Used for Queries

This article explains how MySQL decides whether an index can be used for range queries, LIKE patterns, and sorting, detailing key_len calculation, index key vs. filter vs. table filter concepts, and practical examples with BETWEEN and ORDER BY.

Index OptimizationMySQLQuery Planning

0 likes · 11 min read

Master MySQL Indexes: When and How They’re Used for Queries

360 Quality & Efficiency

May 17, 2016 · Databases

Understanding Database Indexes: Benefits, Usage Principles, and Analysis with EXPLAIN

This article explains the advantages and disadvantages of database indexes, outlines practical principles for their use, demonstrates how to analyze index effectiveness with MySQL's EXPLAIN command, and lists common situations that cause index loss, providing clear guidance for performance optimization.

EXPLAINIndexesMySQL

0 likes · 9 min read

Understanding Database Indexes: Benefits, Usage Principles, and Analysis with EXPLAIN