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126 articles

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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.

Big DataElasticsearchFull-Text Search

0 likes · 46 min read

Master Elasticsearch: From Basics to SpringBoot Integration and Advanced Queries

Java High-Performance Architecture

Jan 20, 2020 · Fundamentals

How Inverted Indexes Power Fast Full-Text Search

This article explains what an inverted index is, why it’s essential for full‑text search, how it is built and queried, and common token transformations such as stop‑word removal, lemmatization, and stemming.

Full-Text Searchinformation retrievalinverted index

0 likes · 4 min read

How Inverted Indexes Power Fast Full-Text Search

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.

ElasticsearchFull-Text SearchSolr

0 likes · 15 min read

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

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+TreeFull-Text SearchHash Index

0 likes · 14 min read

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

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.

ElasticsearchFull-Text SearchJava

0 likes · 14 min read

Integrating Elasticsearch with Spring Boot for Full-Text Product Search

Coder Circle

May 15, 2019 · Databases

How Elasticsearch Implements CRUD Operations Like a Relational Database

This article explains how Elasticsearch stores JSON documents, indexes them, and uses RESTful PUT, GET, DELETE, and search APIs to perform create, read, update, and delete operations, illustrating each step with concrete employee examples and query syntax.

CRUDDocumentElasticsearch

0 likes · 8 min read

How Elasticsearch Implements CRUD Operations Like a Relational Database

Java Backend Technology

Apr 30, 2019 · Fundamentals

Solr vs Elasticsearch: Choosing the Right Full‑Text Search Engine

This article explains the fundamentals of full‑text search, compares Lucene‑based engines Solr and Elasticsearch, and provides practical guidance on selecting the appropriate solution based on use cases, performance, scalability, and community support.

ElasticsearchFull-Text SearchSolr

0 likes · 17 min read

Solr vs Elasticsearch: Choosing the Right Full‑Text Search Engine

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.

ElasticsearchFull-Text SearchSolr

0 likes · 18 min read

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

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.

EXPLAINFull-Text SearchJoin

0 likes · 12 min read

19 Essential MySQL Optimization Techniques Every Developer Should Know

dbaplus Community

Sep 25, 2018 · Databases

Unlock PostgreSQL’s NoSQL Power: JSON vs JSONB Performance & Full‑Text Search

This article explores PostgreSQL’s NoSQL capabilities by comparing JSON and JSONB data types, demonstrating their storage differences, read/write performance tests on millions of rows, index strategies, and the new full‑text search support for JSON/JSONB introduced in version 10.

DatabaseFull-Text SearchGIN Index

0 likes · 26 min read

Unlock PostgreSQL’s NoSQL Power: JSON vs JSONB Performance & Full‑Text Search

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.

ElasticsearchFull-Text SearchToken Filter

0 likes · 5 min read

Understanding Elasticsearch Analyzer, Tokenizer, and Token Filters

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.

ClusterDistributed SystemsElasticsearch

0 likes · 4 min read

What Is Elasticsearch? Core Concepts and Fundamentals

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.

Big DataELKElasticsearch

0 likes · 7 min read

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

Java Captain

Mar 29, 2018 · Fundamentals

Understanding Full‑Text Search and Indexing with Lucene: Core Concepts and Processes

This article explains the fundamentals of full‑text search, describing how Lucene builds and uses inverted indexes, the steps of tokenization, linguistic processing, term weighting, and relevance scoring, and illustrates these concepts with examples, tables, and diagrams.

Full-Text SearchTerm WeightVector Space Model

0 likes · 21 min read

Understanding Full‑Text Search and Indexing with Lucene: Core Concepts and Processes

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

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.

CLIFull-Text SearchInstallation

0 likes · 14 min read

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

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

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.

Backend DevelopmentChinese AnalyzerElasticsearch

0 likes · 13 min read

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

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.

Full-Text SearchMobile DevelopmentSQLite

0 likes · 13 min read

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

StarRing Big Data Open Lab

Sep 22, 2017 · Databases

Mastering Search SQL: Advanced Full‑Text Queries with CONTAINS, NEAR, and FUZZY

This tutorial demonstrates how to create a table with a Chinese analyzer, insert multilingual records, and leverage Search SQL's CONTAINS, NEAR, and FUZZY operators to perform precise, high‑performance full‑text searches beyond simple LIKE patterns.

CONTAINSChinese AnalyzerFUZZY

0 likes · 9 min read

Mastering Search SQL: Advanced Full‑Text Queries with CONTAINS, NEAR, and FUZZY

StarRing Big Data Open Lab

Sep 15, 2017 · Big Data

Boost Full‑Text Search with Search SQL: Tokenization, CONTAINS, NEAR & FUZZY

This article explains how Search SQL enables easy full‑text search on Transwarp Search by using standard SQL syntax, covering tokenization, analyzer configuration, CONTAINS queries, and advanced NEAR and FUZZY operators to improve performance and query semantics.

FUZZYFull-Text SearchNEAR

0 likes · 9 min read

Boost Full‑Text Search with Search SQL: Tokenization, CONTAINS, NEAR & FUZZY

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

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 InternalsFull-Text SearchInnoDB

0 likes · 23 min read

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.

DatabaseFull-Text SearchInnoDB

0 likes · 17 min read

InnoDB Full-Text Index Architecture and Operations in MySQL 5.7

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.

ElasticsearchFull-Text SearchIK Analyzer

0 likes · 12 min read

How to Build a Powerful Site Search with Elasticsearch on Ubuntu

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.

Data ManagementFull-Text SearchKingbaseES

0 likes · 6 min read