BestHub
Sign in
Tagged articles
636 articles
Page 6 of 7
Didi Tech
Didi Tech
Oct 8, 2019 · Databases

Design and Implementation of Fusion-NewSQL: A NewSQL System Built on Distributed NoSQL Storage

Fusion‑NewSQL is a NewSQL layer built atop Didi’s distributed KV store Fusion, translating MySQL queries into Redis‑style hashmaps, asynchronously maintaining secondary indexes, supporting fast Hive‑to‑Fusion loads and Elasticsearch integration, thereby delivering over 2 million QPS, 600 TB storage and flexible schema evolution for dozens of services.

MySQL compatibilityNewSQLfusion
0 likes · 15 min read
Design and Implementation of Fusion-NewSQL: A NewSQL System Built on Distributed NoSQL Storage
Big Data Technology Architecture
Big Data Technology Architecture
Sep 26, 2019 · Databases

Elasticsearch Core Overview and Key Performance Metrics

This article provides a comprehensive guide to Elasticsearch’s architecture, node roles, data organization, and the most important performance metrics—including search, indexing, memory, JVM garbage collection, host‑level system metrics, cluster health, and resource saturation—offering practical advice on monitoring and tuning the cluster for reliability and efficiency.

Cluster ManagementElasticsearchJVM
0 likes · 27 min read
Elasticsearch Core Overview and Key Performance Metrics
Alibaba Cloud Developer
Alibaba Cloud Developer
Sep 24, 2019 · Big Data

Inside Alibaba’s 10‑Year Search Engine: Architecture, Data Flow, and Indexing

Alibaba’s 10‑year‑old search engine combines data source aggregation, incremental and real‑time indexing, and online services through platforms like Tisplus, Bahamut, Maat, Ha3, Build Service and Drogo, illustrating a comprehensive architecture that powers 1688’s search capabilities across multiple engines and deployment pipelines.

Backend ArchitectureBig DataDistributed Systems
0 likes · 10 min read
Inside Alibaba’s 10‑Year Search Engine: Architecture, Data Flow, and Indexing
Architect's Tech Stack
Architect's Tech Stack
Sep 13, 2019 · Databases

MySQL Query Optimization: Indexing, Subqueries, and Join Strategies

This article demonstrates how to dramatically improve MySQL query performance by analyzing execution plans, adding appropriate single‑column and composite indexes, converting slow subqueries to efficient joins, and applying covering indexes and ordering optimizations, with detailed examples and timing results.

SQL Optimizationindexingmysql
0 likes · 12 min read
MySQL Query Optimization: Indexing, Subqueries, and Join Strategies
Efficient Ops
Efficient Ops
Sep 9, 2019 · Operations

How to Diagnose and Fix High CPU Usage in a Java Web Portal

This guide walks through diagnosing a Java portal's high CPU usage by checking system load, identifying the offending thread, analyzing JVM stack traces, pinpointing a slow MySQL query, and resolving the issue with data cleanup and index creation, reducing CPU load from 800% to 40%.

indexingperformancetroubleshooting
0 likes · 4 min read
How to Diagnose and Fix High CPU Usage in a Java Web Portal
Java Captain
Java Captain
Sep 5, 2019 · Databases

MySQL Optimization and Best Practices: Indexing, Partitioning, Replication, and Performance Tuning

This article provides a comprehensive guide to MySQL performance optimization, covering database design principles, field type selection, indexing strategies, storage engine choices, query caching, partitioning methods, master‑slave replication setup, read/write splitting, load balancing, and profiling tools for diagnosing slow queries.

PartitioningReplicationindexing
0 likes · 43 min read
MySQL Optimization and Best Practices: Indexing, Partitioning, Replication, and Performance Tuning
Big Data Technology & Architecture
Big Data Technology & Architecture
Sep 2, 2019 · Databases

Apache Phoenix Tutorial: Quick Start, Data Types, DML, Indexes, Salted Tables, and Advanced Features

This comprehensive guide introduces Apache Phoenix as an HBase SQL layer, covering quick‑start steps, supported data types, DML syntax, salted tables to prevent hotspots, various secondary index types, bulk‑load methods, auto‑increment IDs, dynamic columns, pagination, query plan analysis, and data migration techniques.

Apache PhoenixData MigrationHBase
0 likes · 33 min read
Apache Phoenix Tutorial: Quick Start, Data Types, DML, Indexes, Salted Tables, and Advanced Features
Xianyu Technology
Xianyu Technology
Aug 28, 2019 · Big Data

Unified Search System Architecture and Automation for Multiple Business Scenarios

To avoid building separate search services for each Xianyu business, the team created a unified, generic search architecture based on Alibaba’s HA3 engine and a control layer that automates data dumping, indexing, query translation, and result ranking across five subsystems, enabling new services to be onboarded in minutes instead of weeks.

AutomationBig Datadata pipeline
0 likes · 18 min read
Unified Search System Architecture and Automation for Multiple Business Scenarios
Liangxu Linux
Liangxu Linux
Aug 27, 2019 · Databases

19 Essential MySQL Optimization Techniques Every Developer Should Know

This guide compiles nineteen practical MySQL optimization tips—from using EXPLAIN and avoiding costly IN clauses to leveraging full‑text indexes, proper pagination, and join strategies—providing concrete SQL examples and actionable advice to improve query performance and reduce resource consumption.

Query TuningSQLindexing
0 likes · 11 min read
19 Essential MySQL Optimization Techniques Every Developer Should Know
ITPUB
ITPUB
Aug 23, 2019 · Databases

Essential MySQL Database Design and Indexing Best Practices

This guide compiles comprehensive MySQL conventions covering object naming, storage engine choices, character sets, table and column design, indexing strategies, query optimization, and operational safeguards to improve performance, maintainability, and data integrity in production environments.

Database designPerformance OptimizationSQL Best Practices
0 likes · 19 min read
Essential MySQL Database Design and Indexing Best Practices
dbaplus Community
dbaplus Community
Jul 17, 2019 · Databases

Rethinking Prometheus TSDB: From V2 Bottlenecks to the Scalable V3 Design

This article examines the limitations of Prometheus's original V2 time‑series storage, proposes a block‑oriented V3 architecture that tackles series churn, write amplification, and indexing inefficiencies, and validates the new design with extensive benchmarks showing dramatic reductions in memory, CPU, and disk usage.

KubernetesPrometheusTSDB
0 likes · 36 min read
Rethinking Prometheus TSDB: From V2 Bottlenecks to the Scalable V3 Design
Aikesheng Open Source Community
Aikesheng Open Source Community
Jun 27, 2019 · Databases

Understanding MongoDB Sort Memory Limits and Index Optimization

This article analyzes MongoDB sort operation memory limits, explains why queries may exceed the 32 MB in‑memory sort threshold, demonstrates how to inspect and adjust server parameters, create appropriate compound indexes, and use allowDiskUse in aggregation pipelines to avoid sort‑related errors.

MemoryLimitMongoDBaggregation
0 likes · 14 min read
Understanding MongoDB Sort Memory Limits and Index Optimization
Architect's Tech Stack
Architect's Tech Stack
Jun 23, 2019 · Big Data

Elasticsearch Interview Questions: Architecture, Indexing, Optimization, and Operations

This article compiles common Elasticsearch interview questions and detailed answers covering cluster architecture, inverted index fundamentals, index design, write/query optimizations, master election, document indexing flow, search process, Linux tuning, and Lucene internals, providing practical guidance for candidates.

ClusterElasticsearchindexing
0 likes · 10 min read
Elasticsearch Interview Questions: Architecture, Indexing, Optimization, and Operations
Tencent Cloud Developer
Tencent Cloud Developer
Jun 3, 2019 · Databases

Storage Engine Overview and InnoDB Feature Design

An InnoDB storage engine sits above the file system and below SQL tools, providing transactions with redo/undo logs, row and table locking, MVCC, B+‑tree and adaptive hash indexes, compression, encryption, checkpointing, multi‑threaded buffering, backup and replication mechanisms, and extensive performance‑monitoring commands.

Database InternalsInnoDBPerformance Monitoring
0 likes · 11 min read
Storage Engine Overview and InnoDB Feature Design
Fangduoduo Tech
Fangduoduo Tech
May 25, 2019 · Backend Development

How Fangdd Scales Real‑Estate Search with Elasticsearch: Architecture & Lessons

This article explains how Fangdd leverages Elasticsearch to boost search performance across consumer, broker, and internal products, detailing a platformized architecture that separates indexing and querying, addresses operational challenges, and outlines design patterns for index management and incremental updates.

Backend DevelopmentElasticsearchMicroservices
0 likes · 12 min read
How Fangdd Scales Real‑Estate Search with Elasticsearch: Architecture & Lessons
58 Tech
58 Tech
May 14, 2019 · Databases

Designing Structured Table and Index Storage in RocksDB for NewSQL Systems

This article explains how to map relational table rows and various indexes—including primary key, integer, float, string, and composite indexes—into RocksDB key‑value pairs using custom serialization, big‑endian ordering, and encoding functions to enable efficient point, range, and multi‑field queries.

NewSQLRocksDBindexing
0 likes · 14 min read
Designing Structured Table and Index Storage in RocksDB for NewSQL Systems
Tencent Cloud Developer
Tencent Cloud Developer
May 5, 2019 · Databases

Handling ORDER BY When Index Order Differs and Using Descending Indexes in MySQL

MySQL can avoid a filesort for ORDER BY clauses that match an index’s direction by scanning the index forward or backward, and MySQL 8.0’s descending indexes let mixed‑direction sorts be satisfied similarly; for older versions you can emulate this by retrieving rows in index order and reversing groups in the application.

Descending IndexOrder Bydatabase
0 likes · 9 min read
Handling ORDER BY When Index Order Differs and Using Descending Indexes in MySQL
Aikesheng Open Source Community
Aikesheng Open Source Community
Apr 23, 2019 · Databases

Key Improvements in MySQL 8.0.13 and 8.0.14

This article reviews the most notable enhancements introduced in MySQL 8.0.13 and 8.0.14, covering query speed optimizations, the new Skip Scan access method, changes to index design rules, deprecated features, and several operational and security improvements for database administrators and developers.

8.0.138.0.14Skip Scan
0 likes · 9 min read
Key Improvements in MySQL 8.0.13 and 8.0.14
Senior Brother's Insights
Senior Brother's Insights
Apr 20, 2019 · Databases

Essential MySQL Database Design and Coding Standards for Reliable Systems

This guide outlines comprehensive MySQL naming conventions, table and column design rules, indexing best practices, SQL coding standards, and operational recommendations to improve performance, maintainability, and security while avoiding common pitfalls such as redundant indexes, unsafe data types, and excessive batch operations.

Database designSQL Standardsbest practices
0 likes · 19 min read
Essential MySQL Database Design and Coding Standards for Reliable Systems
Architecture Digest
Architecture Digest
Apr 18, 2019 · Databases

MySQL High Performance Optimization Guidelines and Best Practices

This article presents a comprehensive set of MySQL high‑performance optimization guidelines, covering naming conventions, table design, data types, index strategies, SQL coding standards, replication, backup, and operational best practices to improve efficiency, reliability, and scalability of database systems.

Database designOperationsPerformance Optimization
0 likes · 19 min read
MySQL High Performance Optimization Guidelines and Best Practices
Java High-Performance Architecture
Java High-Performance Architecture
Mar 28, 2019 · Databases

Mastering MySQL Indexes: From Hash Tables to B+ Trees and Beyond

This article explains the main index structures used in MySQL—including hash tables, ordered arrays, search trees, and B+ trees—covers why InnoDB prefers B+ trees, the benefits of auto‑increment primary keys, and key concepts such as covering indexes, the left‑most prefix rule, and index‑pushdown for query optimization.

B+TreeDatabase OptimizationSQL
0 likes · 7 min read
Mastering MySQL Indexes: From Hash Tables to B+ Trees and Beyond
Java Captain
Java Captain
Mar 20, 2019 · Databases

Comprehensive MySQL Database Design and Development Standards

This article presents a detailed set of MySQL database naming conventions, design principles, field type recommendations, index strategies, and SQL development best practices to improve performance, maintainability, and security while avoiding common pitfalls such as reserved keywords, oversized tables, and inefficient queries.

SQL Standardsindexingmysql
0 likes · 17 min read
Comprehensive MySQL Database Design and Development Standards
High Availability Architecture
High Availability Architecture
Mar 14, 2019 · Databases

SlimTrie: A Space‑Efficient Trie‑Based Index for Large‑Scale Storage Systems

This article presents SlimTrie, a trie‑based indexing structure that dramatically reduces memory consumption while maintaining fast query speeds, detailing its design, compression techniques, implementation steps, memory analysis, and performance comparisons with map and B‑Tree structures for large‑scale storage systems.

GoMemory OptimizationSlimTrie
0 likes · 20 min read
SlimTrie: A Space‑Efficient Trie‑Based Index for Large‑Scale Storage Systems
Efficient Ops
Efficient Ops
Mar 12, 2019 · Databases

Master MySQL: Essential Naming, Design, and Indexing Standards

This guide outlines comprehensive MySQL best practices, covering naming conventions, basic schema design, field type selection, index strategies, foreign‑key usage, SQL coding standards, batch operations, online schema changes, and permission principles to ensure performant and maintainable databases.

Database designSQL Best Practicesindexing
0 likes · 20 min read
Master MySQL: Essential Naming, Design, and Indexing Standards
dbaplus Community
dbaplus Community
Feb 24, 2019 · Databases

How to Boost MySQL Query Speed: Key Factors and Proven Optimizations

This comprehensive guide explains the main factors that slow down MySQL queries—including inefficient SQL, concurrency limits, CPU and disk I/O bottlenecks, network issues, large tables, and transaction overhead—while offering concrete configuration tweaks, storage‑engine choices, indexing strategies, and sharding techniques to dramatically improve performance.

databaseindexingmysql
0 likes · 24 min read
How to Boost MySQL Query Speed: Key Factors and Proven Optimizations
ITPUB
ITPUB
Feb 22, 2019 · Databases

Why B‑Tree vs B+Tree Matters: MySQL Indexing Essentials

This article explains MySQL’s storage engines, compares B‑Tree and B+Tree indexes, details their structures and search processes, and outlines key principles for designing efficient indexes to avoid slow queries in relational databases.

B+TreeB-Treedatabase
0 likes · 12 min read
Why B‑Tree vs B+Tree Matters: MySQL Indexing Essentials
JD Tech
JD Tech
Feb 21, 2019 · Databases

Analysis of MySQL Master‑Slave Replication Delay and Mitigation Strategies

The article recounts a pre‑promotion MySQL replication incident at JD.com, explains the master‑slave architecture and thread roles, identifies slow‑SQL and missing indexes as root causes of replication lag, and proposes practical measures to reduce latency and improve system stability.

LatencyMaster‑SlaveReplication
0 likes · 6 min read
Analysis of MySQL Master‑Slave Replication Delay and Mitigation Strategies
System Architect Go
System Architect Go
Feb 9, 2019 · Backend Development

Elasticsearch Performance Optimization: General Recommendations, Indexing Speed, Search Speed, and Disk Usage

This guide presents comprehensive Elasticsearch tuning strategies—including limiting result sets, avoiding large documents, optimizing indexing with bulk requests and refresh intervals, enhancing search speed through field modeling and caching, and reducing disk usage via compression and shard management—to improve both indexing and query performance.

BackendSearchindexing
0 likes · 13 min read
Elasticsearch Performance Optimization: General Recommendations, Indexing Speed, Search Speed, and Disk Usage
dbaplus Community
dbaplus Community
Jan 21, 2019 · Databases

52 Proven SQL Performance Optimization Tips to Supercharge Your Queries

This article compiles 52 practical SQL performance optimization strategies—including indexing best practices, query rewriting, use of temporary tables, storage engine selection, data type choices, backup procedures, and diagnostic tools—to help developers write faster, more efficient database queries.

Database TuningSQLindexing
0 likes · 23 min read
52 Proven SQL Performance Optimization Tips to Supercharge Your Queries
dbaplus Community
dbaplus Community
Jan 15, 2019 · Databases

Essential MySQL Naming, Design, and Indexing Standards for Reliable Databases

This guide outlines comprehensive MySQL best‑practice rules covering object naming, table engine and charset choices, column design, index strategies, SQL coding conventions, and operational safeguards to improve performance, maintainability, and data integrity in production environments.

Database designSQL Best Practicesindexing
0 likes · 20 min read
Essential MySQL Naming, Design, and Indexing Standards for Reliable Databases
ITPUB
ITPUB
Jan 10, 2019 · Databases

Mastering Neo4j: From Graph Modeling to Advanced Cypher Queries

This comprehensive guide explains Neo4j's label‑property graph model, node and relationship creation, Cypher syntax, indexing, constraints, schema inspection, and best practices for avoiding duplicate data, providing practical examples and performance tips.

ConstraintsCypherNeo4j
0 likes · 29 min read
Mastering Neo4j: From Graph Modeling to Advanced Cypher Queries
JD Retail Technology
JD Retail Technology
Jan 8, 2019 · Backend Development

Performance, Storage, Indexing, and Caching Design of JMQ4 Middleware

The article presents an in‑depth technical overview of JD's self‑developed JMQ middleware, detailing its performance improvements over previous versions, comparing write throughput with Kafka under synchronous and asynchronous scenarios, and explaining JMQ4's storage architecture, dense indexing, high‑performance I/O, and cache management strategies.

JMQMessage Queuecaching
0 likes · 11 min read
Performance, Storage, Indexing, and Caching Design of JMQ4 Middleware
dbaplus Community
dbaplus Community
Jan 3, 2019 · Backend Development

Supercharging Elasticsearch for Billion-Row Queries: Practical Tips

This guide details how to optimize Elasticsearch for handling billions of daily records, covering core Lucene concepts, index and shard configuration, performance‑tuning parameters, and practical testing methods to achieve sub‑second query responses and long‑term data retention.

Big DataElasticsearchPerformance Optimization
0 likes · 13 min read
Supercharging Elasticsearch for Billion-Row Queries: Practical Tips
dbaplus Community
dbaplus Community
Jan 1, 2019 · Databases

19 Essential MySQL Optimization Techniques Every Developer Should Know

This article presents 19 practical MySQL optimization tips, ranging from using EXPLAIN and proper indexing to rewriting IN/EXISTS queries, avoiding costly ORDER BY RAND(), improving pagination, leveraging full‑text indexes, and applying join and execution‑plan strategies for faster, more efficient database performance.

Query TuningSQLdatabase
0 likes · 12 min read
19 Essential MySQL Optimization Techniques Every Developer Should Know
Qunar Tech Salon
Qunar Tech Salon
Dec 18, 2018 · Big Data

Practical Insights on Deploying and Operating Elasticsearch at Scale

This article shares extensive practical experience from Qunar's large‑scale Elasticsearch deployment, covering suitable use cases, index‑type design, document ID strategies, scaling considerations for index and data volume, hardware sizing, and storage architecture recommendations to help newcomers avoid common pitfalls.

Big DataElasticsearchSearch
0 likes · 10 min read
Practical Insights on Deploying and Operating Elasticsearch at Scale
MaGe Linux Operations
MaGe Linux Operations
Dec 17, 2018 · Databases

How We Turned a Sluggish ERP Database into a High‑Performance System

This article walks through a real‑world ERP database performance case, detailing the symptoms, metric analysis, root‑cause investigation across hardware, environment, and code, and a three‑phase optimization strategy that dramatically reduced latency and improved system stability.

Database PerformanceERPHardware Tuning
0 likes · 11 min read
How We Turned a Sluggish ERP Database into a High‑Performance System
DataFunTalk
DataFunTalk
Nov 9, 2018 · Backend Development

From Zero to One: Building and Optimizing Search Engines with Elasticsearch – Insights and Case Studies

This article presents a comprehensive overview of constructing a search engine using Elasticsearch, covering architecture components, data read/write mechanisms, shard management, caching strategies, and real‑world case studies that illustrate performance tuning, isolation, and deployment best practices.

Backend DevelopmentDistributed SystemsElasticsearch
0 likes · 14 min read
From Zero to One: Building and Optimizing Search Engines with Elasticsearch – Insights and Case Studies
Java Captain
Java Captain
Oct 6, 2018 · Databases

Exploring MySQL Database Fundamentals and Indexing Principles

This article examines MySQL database fundamentals, including storage architecture, block-based data access, disk I/O bottlenecks, and detailed explanations of B+Tree and hash indexes in MyISAM and InnoDB, while offering practical guidance on index design, selectivity, left‑most prefix rules, and using EXPLAIN for SQL optimization.

B+TreeDatabase FundamentalsSQL Optimization
0 likes · 11 min read
Exploring MySQL Database Fundamentals and Indexing Principles
360 Quality & Efficiency
360 Quality & Efficiency
Sep 29, 2018 · Databases

Diagnosing and Optimizing MySQL Query Performance Issues

This article explains how large data volumes and differing environments can degrade MySQL query performance, demonstrates using EXPLAIN to analyze index usage and row scans, and offers practical steps such as adding filters, pagination, and code adjustments to improve speed.

Environmentindexingmysql
0 likes · 6 min read
Diagnosing and Optimizing MySQL Query Performance Issues
dbaplus Community
dbaplus Community
Sep 24, 2018 · Databases

Master MySQL Performance: Practical Optimizations for Large Tables

This guide explains why MySQL performance drops when a single table grows huge and provides a comprehensive set of optimization steps—including field type choices, index design, query tuning, engine selection, system parameters, hardware scaling, read/write splitting, caching, partitioning, vertical and horizontal sharding, and architecture recommendations—to keep MySQL fast and reliable at scale.

Database TuningSystem Parameterscaching
0 likes · 24 min read
Master MySQL Performance: Practical Optimizations for Large Tables
Tencent Cloud Developer
Tencent Cloud Developer
Sep 17, 2018 · Databases

MySQL Schema Design and SQL Development Standards Practice

Tencent Cloud Academy will livestream a MySQL schema design and development standards session on September 17 at 20:00, featuring experts Ye Jinrong and Wu Bingxi, covering best practices such as default InnoDB engine, utf8mb4 charset, row size limits, partitioning, appropriate data types, index guidelines, and operational recommendations.

Database AdministrationDevelopment StandardsInnoDB
0 likes · 9 min read
MySQL Schema Design and SQL Development Standards Practice
58 Tech
58 Tech
Aug 17, 2018 · Cloud Computing

Design and Architecture of 58 Cloud Search Platform Using Kubernetes and Docker

The article describes how 58's search technology team standardized and modularized their vertical search services into a cloud-native platform, detailing the overall architecture, Kubernetes‑based deployment, service and deployment designs, stateful indexing challenges, and solutions for high‑availability and scalability.

DockerKubernetesMicroservices
0 likes · 10 min read
Design and Architecture of 58 Cloud Search Platform Using Kubernetes and Docker
DataFunTalk
DataFunTalk
Jul 13, 2018 · Big Data

Applying BitMap Indexing with HBase for Precise Marketing in Big Data

This article details a big‑data precise‑marketing solution that leverages HBase storage and Roaring BitMap indexing to efficiently handle billions of user records, describing project background, technology selection, architecture, partitioning strategy, and coprocessor implementation for fast multidimensional queries.

BitmapHBaseRoaring Bitmap
0 likes · 13 min read
Applying BitMap Indexing with HBase for Precise Marketing in Big Data
Meituan Technology Team
Meituan Technology Team
May 10, 2018 · Backend Development

Design and Implementation of a Real‑Time Advertising Index System at Meituan‑Dianping

Meituan‑Dianping built a custom C++11 real‑time advertising index featuring a hierarchical model, lock‑free three‑layer architecture, specialized memory allocators, and forward/inverted indexes to achieve millisecond updates, high throughput, and scalability for search ads, with plans for Java integration and SQL support.

C++System Architectureindexing
0 likes · 21 min read
Design and Implementation of a Real‑Time Advertising Index System at Meituan‑Dianping
Efficient Ops
Efficient Ops
May 7, 2018 · Databases

Unveiling MySQL Query Optimization: Architecture, Execution, and Practical Tips

This article demystifies MySQL query optimization by explaining the server's logical architecture, the end‑to‑end query processing flow, the role of the client/server protocol, query cache, parsing, optimizer, execution engine, and result delivery, and then offers concrete performance‑tuning recommendations on schema design, data types, indexing strategies, and specific query patterns such as COUNT(), JOIN, LIMIT pagination, and UNION.

Database PerformanceSQLindexing
0 likes · 35 min read
Unveiling MySQL Query Optimization: Architecture, Execution, and Practical Tips
ITPUB
ITPUB
Mar 12, 2018 · Databases

How to Choose the Right Indexes for MySQL Query Optimization

This guide explains practical, rule‑based steps for creating effective compound indexes in MySQL, MariaDB, and PerconaDB, illustrates the process with a concrete query example, and warns against common indexing mistakes such as over‑indexing, OR conditions, and wrong column order.

compound indexindexingmysql
0 likes · 9 min read
How to Choose the Right Indexes for MySQL Query Optimization
Architecture Digest
Architecture Digest
Feb 1, 2018 · Fundamentals

How Search Engines Work: Building Inverted Indexes

This article explains the core of search engine technology by describing what an inverted index is, how it is built using single‑pass memory and multi‑way merge methods, how indexes can be partitioned and incrementally updated, and how Hadoop can be used for large‑scale indexing.

Big DataHadoopindexing
0 likes · 10 min read
How Search Engines Work: Building Inverted Indexes
21CTO
21CTO
Jan 6, 2018 · Big Data

Build Your Own Full‑Text Search Engine with Elasticsearch: A Step‑by‑Step Guide

This tutorial walks you through installing Elasticsearch, understanding its core concepts such as nodes, clusters, indexes, documents and types, configuring Chinese analyzers, performing CRUD operations, and executing various search queries with practical command‑line examples.

Chinese AnalyzerElasticsearchFull‑Text Search
0 likes · 14 min read
Build Your Own Full‑Text Search Engine with Elasticsearch: A Step‑by‑Step Guide
ITPUB
ITPUB
Jan 2, 2018 · Databases

10 Proven Techniques to Supercharge Your Database Performance

Learn ten practical strategies to accelerate database queries—including proper schema design, using EXPLAIN, caching, selective column retrieval, LIMIT clauses, avoiding loops, replacing subqueries with joins, careful wildcard use, UNION over OR, and indexing—to reduce server load and improve application responsiveness.

Query TuningSQL Performanceindexing
0 likes · 9 min read
10 Proven Techniques to Supercharge Your Database Performance
Qunar Tech Salon
Qunar Tech Salon
Dec 28, 2017 · Databases

7 Essential Tips for Optimizing MySQL Performance

This article presents seven practical techniques—including using EXPLAIN, creating proper indexes, adjusting default settings, loading data into memory, leveraging SSD storage, scaling horizontally, and improving observability—to keep MySQL databases fast, stable, and responsive as workloads grow.

ConfigurationSSDindexing
0 likes · 14 min read
7 Essential Tips for Optimizing MySQL Performance
dbaplus Community
dbaplus Community
Dec 19, 2017 · Databases

7 Essential MySQL Performance Tuning Techniques You Must Apply

This article presents seven practical MySQL performance‑tuning techniques—including mastering EXPLAIN, building effective indexes, overriding default settings, optimizing memory usage, adopting SSD storage, scaling horizontally, and improving visibility—while explaining key configuration variables and monitoring tools to keep your database fast and reliable.

Database OptimizationInnoDBexplain
0 likes · 16 min read
7 Essential MySQL Performance Tuning Techniques You Must Apply
Senior Brother's Insights
Senior Brother's Insights
Nov 29, 2017 · Databases

Mastering SQL Performance: Proven Optimization Techniques and Best Practices

Learn a comprehensive methodology for SQL performance tuning, from identifying resource bottlenecks and understanding query processing stages to applying practical optimization tactics such as efficient joins, index usage, avoiding costly operations, and best‑practice guidelines that improve execution speed and resource consumption.

Query TuningSQLdatabase
0 likes · 13 min read
Mastering SQL Performance: Proven Optimization Techniques and Best Practices
Tongcheng Travel Technology Center
Tongcheng Travel Technology Center
Nov 23, 2017 · Backend Development

Design and Implementation of a Search Open Platform for Rapid Interface Provision

The article describes the requirements, architecture, data‑sync strategy, monitoring, and operational workflow of a search open platform that enables fast, zero‑code creation of searchable interfaces, supporting real‑time indexing, customizable ranking, and extensible backend services.

Backend DevelopmentSearch Platformdata synchronization
0 likes · 12 min read
Design and Implementation of a Search Open Platform for Rapid Interface Provision
Efficient Ops
Efficient Ops
Nov 13, 2017 · Databases

How to Build a Distributed Full‑Text Search System Using a Distributed Database

This article explains the design, table schema, indexing workflow, and query processing of a distributed full‑text search system that stores documents and token information separately in a distributed database, improving scalability and performance over traditional Lucene‑based solutions.

Distributed SearchFull‑Text SearchScalability
0 likes · 13 min read
How to Build a Distributed Full‑Text Search System Using a Distributed Database
vivo Internet Technology
vivo Internet Technology
Nov 3, 2017 · Databases

Elasticsearch Indexing Performance Optimization - Part 3

Part 3 of the Elasticsearch indexing optimization guide advises balancing shard and replica counts, using index aliases, leveraging the Bulk API with appropriately sized batches, dedicating data nodes, and upgrading storage (SSD/RAID 0) while monitoring resources to achieve higher throughput and scalable, reliable clusters.

ElasticsearchReplicasShards
0 likes · 21 min read
Elasticsearch Indexing Performance Optimization - Part 3
Architecture Digest
Architecture Digest
Nov 3, 2017 · Databases

Understanding Database Sharding: Why It Matters and How to Implement It

Database sharding, or splitting databases into multiple instances and tables, is essential for scaling backend systems; this article explains its importance, historical context, core concepts, storage stretching techniques, index and consistency handling, and provides a practical design example for transaction systems.

Backend ArchitectureConsistencyPartitioning
0 likes · 11 min read
Understanding Database Sharding: Why It Matters and How to Implement It
ITPUB
ITPUB
Oct 14, 2017 · Databases

Cutting a Slow Oracle Search Query from Cost 13902 to Under 100

This article walks through diagnosing a sluggish Oracle search query with many optional filters, removing unnecessary joins and function calls, applying conditional MyBatis joins, and creating composite indexes to dramatically lower the execution plan cost from 13902 to under 100.

MyBatisOracleSQL
0 likes · 11 min read
Cutting a Slow Oracle Search Query from Cost 13902 to Under 100
ITPUB
ITPUB
Jul 31, 2017 · Databases

10 Proven MySQL Performance Tricks Every DBA Should Know

This guide presents ten practical MySQL performance techniques—from workload profiling and resource awareness to smart indexing, pagination, and monitoring—offering concrete steps, tool recommendations, and common pitfalls to help database administrators keep their servers fast, stable, and scalable.

Database Optimizationindexingmysql
0 likes · 13 min read
10 Proven MySQL Performance Tricks Every DBA Should Know
dbaplus Community
dbaplus Community
Jun 11, 2017 · Databases

Mastering Oracle SQL Optimization: Practical Techniques and Real-World Cases

This article compiles a DBAplus online session that presents a systematic SQL‑optimization methodology, rewrite tricks, common pitfalls, and a series of concrete Oracle examples—including CASE WHEN, ROWNUM pagination, hint usage, column selection, function‑call reduction, trigger avoidance, and ROWID access—plus a detailed Q&A that clarifies practical tuning questions.

Database PerformanceOracleQuery Tuning
0 likes · 19 min read
Mastering Oracle SQL Optimization: Practical Techniques and Real-World Cases
ITPUB
ITPUB
Jun 2, 2017 · Databases

Essential Principles for Building Effective Oracle Indexes (B‑Tree & Bitmap)

This guide outlines practical principles for creating Oracle indexes, compares B‑Tree and bitmap index types, explains their creation syntax, highlights performance characteristics, and lists common situations where indexes may be ignored or unsuitable.

B+TreeBitmapDatabase Performance
0 likes · 8 min read
Essential Principles for Building Effective Oracle Indexes (B‑Tree & Bitmap)
ITPUB
ITPUB
May 22, 2017 · Databases

How to Speed Up MySQL Queries with Slow Query Log, EXPLAIN, and Indexes

Before profiling performance you must locate slow queries, enable MySQL's slow query log, use EXPLAIN to analyze execution plans, and add appropriate indexes—such as on picture.album_id—to dramatically reduce scanned rows and boost query speed by hundreds of times, while balancing read/write trade‑offs.

Database OptimizationSlow Query Logexplain
0 likes · 4 min read
How to Speed Up MySQL Queries with Slow Query Log, EXPLAIN, and Indexes
dbaplus Community
dbaplus Community
May 10, 2017 · Databases

Why InnoDB Needs a Primary Key and How B‑Tree Indexes Work

This article explains the data structures and algorithms behind MySQL indexing, covering B‑Tree fundamentals, insertion and deletion steps with visual examples, the differences between B‑Tree and B+Tree, InnoDB's clustered and secondary index implementations, and why monotonically increasing primary keys improve performance.

B+TreeB-TreeInnoDB
0 likes · 15 min read
Why InnoDB Needs a Primary Key and How B‑Tree Indexes Work
ITPUB
ITPUB
Apr 14, 2017 · Databases

Essential MySQL Optimization Techniques for High-Performance Databases

This guide outlines practical MySQL optimization strategies—including table schema design, index creation, SQL tuning, connection‑pool configuration, and historical data archiving—to help developers maintain fast, scalable databases as data volume grows.

Connection PoolDatabase OptimizationSQL Tuning
0 likes · 14 min read
Essential MySQL Optimization Techniques for High-Performance Databases
High Availability Architecture
High Availability Architecture
Apr 14, 2017 · Databases

Recent Improvements in Elasticsearch 5.x and Outlook for 6.0

This article reviews the latest Elasticsearch 5.x enhancements—including append‑only indexing, range fields, removal of the _all field, unified highlighter, keyword normalizer, multi‑word synonyms, field collapsing, cancellable searches, partitioned term aggregations, cluster allocation explain, Java REST client updates, cross‑cluster search, batched reduce phases—and previews the major features expected in Elasticsearch 6.0 such as sparse doc values, index sorting, sequence numbers, seamless rolling upgrades, type removal, index‑template inheritance, load‑aware shard routing, and X‑Pack extensions like SQL and machine learning.

Cluster ManagementElasticsearchSearch
0 likes · 15 min read
Recent Improvements in Elasticsearch 5.x and Outlook for 6.0
Tencent Architect
Tencent Architect
Apr 12, 2017 · Databases

Tencent File System (TFS): Architecture, 3D Indexing, High‑Performance Key‑Value Store, and Storage Engines

The article details Tencent File System (TFS), describing its platform components, 3D indexing techniques, high‑performance key‑value storage (TSSD) with MHT, dual‑read and smooth scaling mechanisms, hybrid index storage, host‑level FTL, Append‑Only and erasure‑coding storage engines, and how these innovations deliver scalable, low‑cost, high‑performance data storage for massive workloads.

Key-ValueSSDTFS
0 likes · 12 min read
Tencent File System (TFS): Architecture, 3D Indexing, High‑Performance Key‑Value Store, and Storage Engines
Baidu Waimai Technology Team
Baidu Waimai Technology Team
Mar 23, 2017 · Databases

Design and Implementation of the "Little Boy" Greenplum Optimization and Operations Platform

This article introduces the architecture, key modules, and implementation details of the Little Boy platform, a Greenplum optimization and operations system that parses SQL, applies index and distribution‑key tuning, manages resources, and outlines future enhancements for large‑scale data warehouses.

Big DataDatabase OptimizationGreenplum
0 likes · 15 min read
Design and Implementation of the "Little Boy" Greenplum Optimization and Operations Platform
21CTO
21CTO
Feb 15, 2017 · Fundamentals

How Twitter Evolved Its Search Engine: From MySQL to Earlybird and Beyond

This article explains the fundamentals of search engine architecture, covering text collection, indexing, ranking and evaluation, and then traces Twitter's internal search evolution from MySQL full‑text search to the Earlybird index server, Blender aggregation, and smart memory‑SSD strategies.

Big DataTwitterindexing
0 likes · 8 min read
How Twitter Evolved Its Search Engine: From MySQL to Earlybird and Beyond
Practical DevOps Architecture
Practical DevOps Architecture
Nov 22, 2016 · Databases

Common MySQL SQL Statements and Table Alteration Cheat Sheet

This article compiles frequently used MySQL SQL commands—including data migration, multi‑table updates, conditional updates, aggregation inserts, and various ALTER TABLE operations such as adding indexes, dropping and adding columns—to serve as a practical reference for database developers.

DDLDMLData Migration
0 likes · 6 min read
Common MySQL SQL Statements and Table Alteration Cheat Sheet
dbaplus Community
dbaplus Community
Nov 3, 2016 · Databases

Taming a Million‑Row Log Table: Real‑World SQL Performance Optimization

A detailed case study describes how a rapidly growing edit‑log feature caused query times to soar to 30 seconds, and walks through the step‑by‑step investigation, identification of a custom function bottleneck, data‑volume analysis, and the eventual implementation of partitioning, mandatory time filters, and composite indexing to restore acceptable performance.

PL/SQLPartitioningSQL
0 likes · 12 min read
Taming a Million‑Row Log Table: Real‑World SQL Performance Optimization
ITPUB
ITPUB
Nov 1, 2016 · Databases

How to Slash Redo Log Generation and Logical Reads in Oracle UPDATE Statements

A detailed Oracle performance case study shows how adding selective predicates and a supporting index to an UPDATE that runs hourly can reduce redo log generation from over 100 MB to under 1 MB and cut logical reads by more than 95%, with step‑by‑step measurements and code examples.

Logical ReadsOracleSQL
0 likes · 8 min read
How to Slash Redo Log Generation and Logical Reads in Oracle UPDATE Statements
Java Backend Technology
Java Backend Technology
Oct 15, 2016 · Databases

Boost Query Speed in Million-Row Databases: Proven Optimization Techniques

This article presents a comprehensive set of practical strategies for improving database query performance, covering index design, SQL statement refinements, Java backend considerations, hardware tuning, and storage‑procedure usage to accelerate operations on large‑scale relational databases.

indexingperformance tuningquery optimization
0 likes · 13 min read
Boost Query Speed in Million-Row Databases: Proven Optimization Techniques
ITPUB
ITPUB
Oct 6, 2016 · Databases

How Adding Indexes Cut a 30‑Second MySQL View Query to 2 Seconds

A .NET MVC warehouse system’s MySQL view was taking over 30 seconds to fetch 70,000 inventory records, but by adding a composite index on the dictionary table, removing a UNION ALL, and adjusting view algorithms, the query time dropped to a few seconds, with a stored‑procedure alternative for flexible use.

Entity FrameworkStored ProcedureView Optimization
0 likes · 10 min read
How Adding Indexes Cut a 30‑Second MySQL View Query to 2 Seconds
ITPUB
ITPUB
Sep 23, 2016 · Databases

Master MySQL Performance: Practical Table, Index, and Connection Pool Optimizations

This article presents practical MySQL optimization techniques covering table schema design, character set choices, primary key strategies, field definitions, index creation, SQL query tuning, pagination tricks, join handling, connection‑pool parameter tuning, and historical data archiving for large‑scale databases.

Connection PoolDatabase OptimizationSQL Performance
0 likes · 13 min read
Master MySQL Performance: Practical Table, Index, and Connection Pool Optimizations
360 Zhihui Cloud Developer
360 Zhihui Cloud Developer
Sep 21, 2016 · Databases

10 Powerful MongoDB Performance Tricks You Need to Know

This guide shares ten practical MongoDB performance tips—including proper index ordering, using explain() and hint(), avoiding costly query operators, leveraging capped collections, upsert, sorting limits, aggregation, drop vs remove, batch inserts, and optimal indexing for arrays and range queries—to help developers boost database efficiency.

Database OptimizationMongoDBaggregation
0 likes · 5 min read
10 Powerful MongoDB Performance Tricks You Need to Know
dbaplus Community
dbaplus Community
Sep 13, 2016 · Databases

How to Speed Up Zabbix Latest Data Display by Adding Dedicated Tables and Indexes

This article explains why Zabbix's original table design slows down data insertion and query in large‑scale deployments, and provides a step‑by‑step code‑level optimization that creates separate "latest" tables with primary‑key indexes, modifies the server source, and updates the front‑end query to dramatically improve performance without affecting historical data ingestion.

Database OptimizationOracleZabbix
0 likes · 11 min read
How to Speed Up Zabbix Latest Data Display by Adding Dedicated Tables and Indexes
360 Zhihui Cloud Developer
360 Zhihui Cloud Developer
Sep 7, 2016 · Databases

MongoDB Indexing Best Practices: Real‑World Tips & Common Pitfalls

This article shares practical MongoDB indexing guidelines—including compound index rules, naming limits, cardinality considerations, TTL and geospatial indexes, lock behavior, and real‑world case studies—to help DBAs and developers design efficient, safe indexes for production workloads.

Database PerformanceGeospatial IndexMongoDB
0 likes · 8 min read
MongoDB Indexing Best Practices: Real‑World Tips & Common Pitfalls
360 Zhihui Cloud Developer
360 Zhihui Cloud Developer
Sep 1, 2016 · Databases

MongoDB Document Best Practices: Avoid Common Pitfalls with Real‑World Cases

This article outlines essential MongoDB document best‑practice guidelines, including key naming restrictions, collection organization, avoiding custom _id values, pitfalls of array fields, compression of large fields, using MD5 hashes for long strings, case‑sensitivity handling, and index size limits, illustrated with real‑world cases.

Document DesignMongoDBbest practices
0 likes · 11 min read
MongoDB Document Best Practices: Avoid Common Pitfalls with Real‑World Cases
dbaplus Community
dbaplus Community
Aug 17, 2016 · Databases

How We Turned a Sluggish Hospital HIS on SQL Server 2008R2 into a Faster System

This article walks through a real‑world case study of a hospital HIS running on SQL Server 2008R2, detailing the system’s hardware specs, performance metrics, three‑phase optimization process—including general tuning, statement‑level fixes, and deep CPU/memory analysis—and the measurable results achieved without adding new hardware.

Database OptimizationHospital HISSQL Server
0 likes · 12 min read
How We Turned a Sluggish Hospital HIS on SQL Server 2008R2 into a Faster System