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full-text search

140 articles · Page 2 of 2
Java Backend Technology
Java Backend Technology
Jan 18, 2022 · Databases

Master MySQL Full-Text Search: Inverted Indexes, Query Modes, and Optimization

This article explains how InnoDB implements full-text search using inverted indexes, shows how to create and use full-text indexes with various query modes—including natural language, boolean, and query expansion—covers relevance calculation, stopwords, token size limits, and demonstrates how to delete indexes, all illustrated with SQL examples and diagrams.

Boolean ModeMySQLQuery Expansion
0 likes · 13 min read
Master MySQL Full-Text Search: Inverted Indexes, Query Modes, and Optimization
JD Cloud Developers
JD Cloud Developers
Dec 24, 2021 · Databases

Boost Address Keyword Search with PostgreSQL: GIN, pg_trgm, and pg_bigm

This article explains how PostgreSQL's native full‑text search, GIN indexes, and extensions like pg_trgm, pg_bigm, and pg_jieba can dramatically improve the speed and accuracy of Chinese address keyword searches, offering a cost‑effective alternative to external search engines.

GIN IndexPostgreSQLaddress keyword search
0 likes · 6 min read
Boost Address Keyword Search with PostgreSQL: GIN, pg_trgm, and pg_bigm
Laravel Tech Community
Laravel Tech Community
Dec 9, 2021 · Backend Development

Apache Lucene 9.0 Released – New Features and Improvements

Apache Lucene 9.0, a high‑performance Java full‑text search library, introduces high‑dimensional vector indexing, new language analyzers, faster faceting and sorting, updated file formats, and several performance optimizations, providing developers with a richer, more efficient search toolkit.

Apache LuceneJavafull-text search
0 likes · 3 min read
Apache Lucene 9.0 Released – New Features and Improvements
Programmer DD
Programmer DD
Dec 3, 2021 · Backend Development

Build a File Upload & Search System with Elasticsearch and IK Analyzer

This guide walks through creating a file upload service that indexes Word, PDF, and TXT files in Elasticsearch, uses an ingest‑attachment pipeline to extract text, configures Chinese IK analyzers for precise keyword search, and demonstrates Java code for indexing, querying, and highlighting results.

ElasticsearchIK analyzerIngest Pipeline
0 likes · 12 min read
Build a File Upload & Search System with Elasticsearch and IK Analyzer
21CTO
21CTO
Nov 3, 2021 · Databases

Master MySQL Full‑Text Search: Index Creation, Modes, and Internals

This tutorial explains how MySQL implements full‑text search, covering the creation of full‑text indexes (including Chinese ngram support), the three query modes (natural language, boolean, and query expansion), relevance ranking, underlying inverted‑index structures, cache handling, and common DML operations.

Boolean ModeMySQLQuery Expansion
0 likes · 14 min read
Master MySQL Full‑Text Search: Index Creation, Modes, and Internals
Top Architect
Top Architect
Sep 9, 2021 · Big Data

Building a Site Search Engine with Elasticsearch, Spring Boot, and IK Analyzer

This article demonstrates how to construct a full‑text site search solution by selecting Elasticsearch as the search engine, Spring Boot for the backend service, and the IK analyzer for Chinese tokenization, covering environment setup, project architecture, key code implementations, UI pages, and a concise conclusion on the effectiveness of the approach.

ElasticsearchIK analyzerJava
0 likes · 18 min read
Building a Site Search Engine with Elasticsearch, Spring Boot, and IK Analyzer
vivo Internet Technology
vivo Internet Technology
Jul 14, 2021 · Databases

An Overview of Lucene: Architecture, Indexing Workflow, and Code Implementation

The article introduces Apache Lucene 7.3.1, explains its core architecture and index hierarchy, details the two‑phase indexing and search workflow with code examples for document addition, deletion, merging, and query execution, and highlights its suitability for small‑to‑medium projects versus distributed alternatives.

Code ExampleIndexingJava
0 likes · 20 min read
An Overview of Lucene: Architecture, Indexing Workflow, and Code Implementation
Efficient Ops
Efficient Ops
Jun 23, 2021 · Backend Development

Why Can’t Elasticsearch Find My Logs? Uncovering Full‑Text Search Pitfalls and Tokenizer Tweaks

This article explains why large‑scale Elasticsearch clusters may miss log entries during keyword searches, dives into the fundamentals of inverted indexes and tokenization, and demonstrates practical index‑time and query‑time tokenizer optimizations—including custom analyzers for English and Chinese—to dramatically improve search recall and precision.

ElasticsearchSearch OptimizationTokenizer
0 likes · 13 min read
Why Can’t Elasticsearch Find My Logs? Uncovering Full‑Text Search Pitfalls and Tokenizer Tweaks
Wukong Talks Architecture
Wukong Talks Architecture
Apr 8, 2021 · Backend Development

Integrating Elasticsearch with Spring Boot for Full‑Text Search in a Microservice Architecture

This tutorial demonstrates how to integrate Elasticsearch into a Spring Boot microservice, covering component selection, Maven configuration, client setup, index creation, data insertion, complex query execution, synchronization of question data, and front‑end search handling, all illustrated with complete Java code examples.

ElasticsearchJavaSpring Boot
0 likes · 21 min read
Integrating Elasticsearch with Spring Boot for Full‑Text Search in a Microservice Architecture
Laravel Tech Community
Laravel Tech Community
Feb 25, 2021 · Backend Development

Apache Lucene 8.8.1 Released – New Features and Fixes

Apache Lucene 8.8.1, a high‑performance Java full‑text search engine library, has been released, fixing bugs from 8.8.0 and including optimizations, while the previous 8.8.0 version introduced features such as LatLonPoint spatial queries, configurable Doc value compression, and FeatureField’s newLinearQuery scoring.

Apache LuceneBackendJava
0 likes · 2 min read
Apache Lucene 8.8.1 Released – New Features and Fixes
Tencent Cloud Developer
Tencent Cloud Developer
Oct 30, 2020 · Backend Development

Rebuilding QQ Mail Full-Text Search with Elasticsearch: Architecture, Implementation, and Optimization

To overcome aging hardware and code limitations, QQ Mail rebuilt its full‑text search using Tencent Cloud Elasticsearch, adding an esproxy layer, MQ‑driven updates, HTML‑to‑text extraction, protobuf‑JSON conversion, index sorting, two‑stage precise/fuzzy queries, and custom tokenizers, delivering scalable, low‑latency email search.

ElasticsearchProtobufSearch Optimization
0 likes · 17 min read
Rebuilding QQ Mail Full-Text Search with Elasticsearch: Architecture, Implementation, and Optimization
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Oct 18, 2020 · Backend Development

Spring Boot 2.0.5 Integration with Elasticsearch: Installation, Configuration, Entity Mapping, CRUD, and Full‑Text Search

This guide demonstrates how to integrate Spring Boot 2.0.5 with Elasticsearch 5.6.11 by installing Elasticsearch and Kibana, adding the required Maven dependencies, configuring the client via application.yml or Java code, defining @Document‑annotated entities, implementing repository, service and controller layers for CRUD and full‑text search, handling Netty conflicts at startup, and verifying the setup with health, list and search endpoints.

ElasticsearchJavaKotlin
0 likes · 8 min read
Spring Boot 2.0.5 Integration with Elasticsearch: Installation, Configuration, Entity Mapping, CRUD, and Full‑Text Search
Programmer DD
Programmer DD
Apr 12, 2020 · Big Data

Master Elasticsearch: From Basics to SpringBoot Integration and Advanced Queries

This comprehensive guide introduces Elasticsearch fundamentals, its features and use cases, then walks through integrating it with SpringBoot, configuring Maven dependencies, performing index and document operations, and demonstrates a variety of query types and aggregations using both RESTful APIs and Java code examples.

ElasticsearchJavaSpringBoot
0 likes · 46 min read
Master Elasticsearch: From Basics to SpringBoot Integration and Advanced Queries
Big Data Technology Architecture
Big Data Technology Architecture
Aug 12, 2019 · Fundamentals

Understanding Full‑Text Search and Comparing Solr, Lucene, and Elasticsearch

This article explains the principles of full‑text search, contrasts structured and unstructured data retrieval methods, introduces Lucene, Solr, and Elasticsearch, and provides a detailed comparison of their features, community support, maturity, and documentation to help developers choose the right search engine for their projects.

ElasticsearchLuceneSolr
0 likes · 15 min read
Understanding Full‑Text Search and Comparing Solr, Lucene, and Elasticsearch
Architect's Tech Stack
Architect's Tech Stack
Jun 4, 2019 · Databases

Understanding B+ Tree, Hash, and Full‑Text Indexes in MySQL

This article explains the principles, structures, and operations of MySQL indexes, covering B+ tree indexes, their search, insertion, and deletion mechanisms, as well as hash indexes, adaptive hash indexing, and full‑text indexes with inverted indexing, cache handling, and practical limitations.

B+ TreeMySQLfull-text search
0 likes · 14 min read
Understanding B+ Tree, Hash, and Full‑Text Indexes in MySQL
macrozheng
macrozheng
May 20, 2019 · Backend Development

Integrating Elasticsearch with Spring Boot for Full-Text Product Search

This guide walks through installing Elasticsearch and Kibana, configuring a Chinese analyzer, defining Spring Data Elasticsearch annotations, creating repository and service layers, building a REST controller, and testing product search functionality within a Spring Boot mall application.

ElasticsearchJavaSpring Boot
0 likes · 14 min read
Integrating Elasticsearch with Spring Boot for Full-Text Product Search
Programmer DD
Programmer DD
Apr 16, 2019 · Big Data

Solr vs Elasticsearch: Which Full‑Text Search Engine Wins in 2024?

This article explains the fundamentals of full‑text search, compares Solr, Elasticsearch and their underlying Lucene library, discusses when to choose each engine, and provides practical guidance for developers facing unstable search services or needing scalable, distributed indexing solutions.

ElasticsearchSolrfull-text search
0 likes · 18 min read
Solr vs Elasticsearch: Which Full‑Text Search Engine Wins in 2024?
Liangxu Linux
Liangxu Linux
Feb 20, 2019 · Databases

19 Essential MySQL Optimization Techniques Every Developer Should Know

This guide presents 19 practical MySQL optimization tips—including using EXPLAIN, avoiding SELECT *, limiting IN lists, preferring UNION ALL, improving pagination, leveraging full‑text indexes, and proper join strategies—to help developers write faster, more efficient queries.

EXPLAINJOINMySQL
0 likes · 12 min read
19 Essential MySQL Optimization Techniques Every Developer Should Know
System Architect Go
System Architect Go
Sep 3, 2018 · Fundamentals

Understanding Elasticsearch Analyzer, Tokenizer, and Token Filters

This article explains the core components of Elasticsearch's full‑text search analysis—Analyzers, Tokenizers, and Token Filters—detailing their roles, building blocks, built‑in types, and how they combine to customize text processing for effective indexing and querying.

ElasticsearchToken FilterTokenizer
0 likes · 5 min read
Understanding Elasticsearch Analyzer, Tokenizer, and Token Filters
System Architect Go
System Architect Go
Jul 29, 2018 · Databases

What Is Elasticsearch? Core Concepts and Fundamentals

Elasticsearch is an open‑source, scalable, high‑availability distributed full‑text search engine that operates in near real‑time, using clusters of nodes, indexes, documents, shards and replicas to efficiently store and retrieve large volumes of data.

ElasticsearchNear Real-Timecluster
0 likes · 4 min read
What Is Elasticsearch? Core Concepts and Fundamentals
UCloud Tech
UCloud Tech
Apr 18, 2018 · Big Data

How Elasticsearch Powers Billion‑Record Log Analysis and Full‑Text Search

This article explains how Elasticsearch and the ELK stack address challenges of storing, securing, retrieving, and analyzing massive data volumes by providing distributed real‑time search, log collection, visualization, and even serving as a NoSQL alternative for large‑scale applications.

ELKElasticsearchbig data
0 likes · 7 min read
How Elasticsearch Powers Billion‑Record Log Analysis and Full‑Text Search
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 AnalyzerElasticsearchIndexing
0 likes · 14 min read
Build Your Own Full‑Text Search Engine with Elasticsearch: A Step‑by‑Step Guide
Architecture Digest
Architecture Digest
Jan 5, 2018 · Backend Development

Step-by-Step Guide to Installing and Using Elasticsearch for Full‑Text Search

This article provides a comprehensive, from‑scratch tutorial on installing Elasticsearch, explaining core concepts such as nodes, clusters, indices, documents, and types, and demonstrates how to create, delete, update, and query data—including Chinese tokenization—using command‑line curl requests.

CLIInstallationfull-text search
0 likes · 14 min read
Step-by-Step Guide to Installing and Using Elasticsearch for Full‑Text Search
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 SearchIndexingfull-text search
0 likes · 13 min read
How to Build a Distributed Full‑Text Search System Using a Distributed Database
21CTO
21CTO
Oct 19, 2017 · Backend Development

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

This tutorial walks you through installing Elasticsearch, configuring Java and network settings, understanding core concepts like nodes, clusters, indices and documents, setting up Chinese analyzers, performing CRUD operations, and executing powerful full‑text queries using the Elasticsearch REST API.

Chinese AnalyzerElasticsearchbackend development
0 likes · 13 min read
Build Your Own Full-Text Search Engine with Elasticsearch: Step‑by‑Step Guide
WeChat Client Technology Team
WeChat Client Technology Team
Oct 18, 2017 · Databases

How WeChat Supercharged Mobile Full‑Text Search with SQLite FTS Optimizations

This article explains the principles of SQLite’s Full‑Text Search extension, details WeChat’s architecture for mobile search, and shares practical performance‑tuning techniques—including custom tokenizers, offset function improvements, and SQL‑level ranking—to achieve sub‑50 ms query times on billions of records.

Mobile DevelopmentSQLiteWeChat
0 likes · 13 min read
How WeChat Supercharged Mobile Full‑Text Search with SQLite FTS Optimizations
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Nov 10, 2016 · Backend Development

How to Scale a Mid‑Size Website: From Caching to Search Indexes

This article walks through the evolution of a medium‑traffic website’s architecture, covering early rapid development, the introduction of caching, database‑app separation, read/write splitting, horizontal scaling with additional servers, and the later addition of full‑text search to handle millions of daily visits.

Cachingfull-text searchwebsite scaling
0 likes · 4 min read
How to Scale a Mid‑Size Website: From Caching to Search Indexes
21CTO
21CTO
Mar 2, 2016 · Databases

Inside MySQL InnoDB Full-Text Index: Architecture, Operations, and Optimization

This article examines MySQL’s InnoDB full‑text indexing from MySQL 5.6 onward, detailing supported search modes, the structure of auxiliary index files, the lifecycle of DML operations, transaction handling, cache synchronization, optimization procedures, background threads, monitoring tables, stop‑word configuration, and the built‑in n‑gram parser.

Database InternalsInnoDBMySQL
0 likes · 23 min read
Inside MySQL InnoDB Full-Text Index: Architecture, Operations, and Optimization
Architect
Architect
Mar 2, 2016 · Databases

InnoDB Full-Text Index Architecture and Operations in MySQL 5.7

This article explains MySQL InnoDB full-text indexing, covering supported modes, auxiliary tables, creation, DML handling, query processing, transaction management, cache synchronization, optimization, background threads, monitoring, stopwords, plugins, and the built‑in n‑gram parser, with code references from MySQL 5.7.

IndexingInnoDBMySQL
0 likes · 17 min read
InnoDB Full-Text Index Architecture and Operations in MySQL 5.7
21CTO
21CTO
Jan 10, 2016 · Backend Development

How to Build a Powerful Site Search with Elasticsearch on Ubuntu

This article walks through installing Elasticsearch on Ubuntu, adding the IK Chinese analyzer and synonym filter, configuring custom analyzers, and using the Node.js client to index and query documents, providing a complete, reproducible setup for site‑wide full‑text search.

ElasticsearchIK analyzerNode.js
0 likes · 12 min read
How to Build a Powerful Site Search with Elasticsearch on Ubuntu
ITPUB
ITPUB
Nov 18, 2015 · Databases

How KingbaseES Handles Unstructured Data with Full‑Text Search and Large Objects

The article explains the rapid growth of unstructured data, outlines typical sources and management challenges, and details how KingbaseES’s full‑text indexing, extensible ranking, and large‑object support (BLOB/CLOB up to 2 GB) enable efficient storage, retrieval, and processing of such data.

KingbaseESLarge Objectsdata management
0 likes · 6 min read
How KingbaseES Handles Unstructured Data with Full‑Text Search and Large Objects