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DataFunTalk
DataFunTalk
Sep 26, 2022 · Artificial Intelligence

Intelligent Entity Recommendation in Search Scenarios: Architecture, Relevance, Sparse Data Recall, and Multi‑Domain Strategies

This article presents a comprehensive overview of intelligent entity recommendation for search, covering scenario introduction, relevance modeling, handling sparse query and entity data with graph‑based methods, and multi‑domain, multi‑scenario ranking techniques to improve user experience.

Knowledge GraphMulti-domainSearch
0 likes · 15 min read
Intelligent Entity Recommendation in Search Scenarios: Architecture, Relevance, Sparse Data Recall, and Multi‑Domain Strategies
Selected Java Interview Questions
Selected Java Interview Questions
Sep 13, 2022 · Big Data

Java API for Elasticsearch: Configuration, CRUD, DSL Queries, Pagination, Sorting, and Highlighting

This article demonstrates how to integrate Elasticsearch 6.2.1 with a Spring Boot project using the high‑level REST client, covering Maven dependencies, bean configuration, index creation and deletion, various DSL queries, pagination, sorting, boosting, boolean filters, and result highlighting with complete Java code examples.

DSLElasticsearchSearch
0 likes · 17 min read
Java API for Elasticsearch: Configuration, CRUD, DSL Queries, Pagination, Sorting, and Highlighting
DataFunTalk
DataFunTalk
Sep 13, 2022 · Artificial Intelligence

Intelligent Question Answering in QQ Browser Search: Background, Key Technologies, and Frontier Research

This article presents an in‑depth overview of intelligent question answering in QQ Browser search, covering its background, the core KBQA and DeepQA technologies, system architecture, challenges, recent advances such as end‑to‑end, knowledge‑guided and multimodal QA, and practical Q&A for deployment.

AIKnowledge GraphMultimodal
0 likes · 22 min read
Intelligent Question Answering in QQ Browser Search: Background, Key Technologies, and Frontier Research
MaGe Linux Operations
MaGe Linux Operations
Sep 3, 2022 · Databases

RedisJSON Outperforms MongoDB & ElasticSearch – Up to 200× Faster Writes

A comprehensive benchmark shows RedisJSON delivering dramatically higher throughput and lower latency than MongoDB and ElasticSearch across isolated writes, isolated reads, and mixed workloads, with up to 200‑fold faster writes and 500‑plus‑fold faster reads, while maintaining sub‑millisecond response times.

BenchmarkNoSQLRedisJSON
0 likes · 14 min read
RedisJSON Outperforms MongoDB & ElasticSearch – Up to 200× Faster Writes
HelloTech
HelloTech
Sep 2, 2022 · Artificial Intelligence

Search and Recommendation Algorithms: Evolution, Common Pipelines, and Integrated Engine Design

The article outlines how search and recommendation systems have evolved from simple hot‑list displays to sophisticated, data‑driven pipelines comprising recall, fine‑ranking and re‑ranking stages, describes an integrated low‑code engine with standardized features, configurable components and intelligent modules that enable rapid deployment across many scenarios, delivering notable CTR, GMV and engagement gains at 哈啰.

Data StandardizationEmbeddingMachine Learning
0 likes · 10 min read
Search and Recommendation Algorithms: Evolution, Common Pipelines, and Integrated Engine Design
政采云技术
政采云技术
Aug 23, 2022 · Backend Development

Understanding Elasticsearch Document Scoring and Aggregation Techniques

This article explains the underlying principles of Elasticsearch scoring, covering Boolean model queries, TF/IDF, field length normalization, the vector space model, and detailed aggregation examples with code snippets to illustrate practical search and analytics usage.

ElasticsearchScoringSearch
0 likes · 19 min read
Understanding Elasticsearch Document Scoring and Aggregation Techniques
DataFunSummit
DataFunSummit
Jul 13, 2022 · Artificial Intelligence

Construction and Application of Meituan's Life Service Knowledge Graph

This article details Meituan's "Meituan Brain" initiative, describing the roadmap and techniques for building large-scale life‑service knowledge graphs—including tag and dish graphs—through data mining, semantic extraction, synonym discovery, graph neural networks, and their integration into search, recommendation, and question‑answering systems.

AIGraph Neural NetworkKnowledge Graph
0 likes · 14 min read
Construction and Application of Meituan's Life Service Knowledge Graph
Dada Group Technology
Dada Group Technology
Jun 6, 2022 · Backend Development

Evolution of JD Daojia Search System Architecture from Version 1.0 to 3.0

The article details the progressive architectural evolution of JD Daojia's search system—starting from a simple, single‑layer ES‑based 1.0 design, through the 2.0 overhaul that introduced full‑recall, independent ranking services, and index disaster‑recovery, to the 3.0 version that adds multi‑path recall, sophisticated ranking models, and automated routing for high availability.

ElasticsearchScalabilitySearch
0 likes · 20 min read
Evolution of JD Daojia Search System Architecture from Version 1.0 to 3.0
Architects Research Society
Architects Research Society
Jun 4, 2022 · Operations

Improving Solr Search Stability and Performance in a High‑Traffic Personalization Service

This article describes how a team tackled stability and performance problems in a SolrCloud‑based search and recommendation stack serving 150,000 requests per minute, detailing root‑cause analysis, memory and GC tuning, replica configuration changes, and the resulting reductions in latency, resource usage, and operational complexity.

OperationsScalabilitySearch
0 likes · 14 min read
Improving Solr Search Stability and Performance in a High‑Traffic Personalization Service
Top Architect
Top Architect
May 29, 2022 · Backend Development

Integrating Spring Data Elasticsearch with Spring Boot: Configuration, Entity, Repository, and Query Examples

This tutorial demonstrates how to set up Elasticsearch 7.6 with the IK analyzer in a Spring Boot 2.3 project, import the appropriate Spring Data Elasticsearch dependency, configure the client, define indexed entity classes, create repository interfaces, and implement REST controllers for CRUD, pagination, and highlighted search queries, complete with code examples and test results.

ElasticsearchJavaREST
0 likes · 9 min read
Integrating Spring Data Elasticsearch with Spring Boot: Configuration, Entity, Repository, and Query Examples
DataFunTalk
DataFunTalk
May 23, 2022 · Artificial Intelligence

A Survey of Deep Matching Models for Search and Recommendation

This article surveys recent deep learning approaches for matching in search and recommendation systems, presenting a unified view of matching, categorizing methods into representation learning and matching function learning, and detailing model architectures from input to output layers, while highlighting broader applications such as QA and image captioning.

SearchSurveydeep learning
0 likes · 4 min read
A Survey of Deep Matching Models for Search and Recommendation
Architecture Digest
Architecture Digest
May 13, 2022 · Big Data

Step-by-Step Guide to Deploy a Multi-Node Elasticsearch Cluster with Docker

This article provides a comprehensive tutorial on pulling Elasticsearch Docker images, configuring data directories, creating cluster configuration files, adjusting JVM settings, launching three Elasticsearch nodes in Docker containers, and verifying the cluster using both the REST API and the elasticsearch‑head UI.

DockerElasticsearchSearch
0 likes · 12 min read
Step-by-Step Guide to Deploy a Multi-Node Elasticsearch Cluster with Docker
政采云技术
政采云技术
May 12, 2022 · Fundamentals

Understanding Lucene Query Process and Core Principles

This article explains Lucene's query types, the step‑by‑step query execution flow—including entry, rewrite, weight creation, scoring, and result collection—while providing code examples and performance considerations to help developers troubleshoot and optimize search performance.

BM25ElasticsearchJava
0 likes · 15 min read
Understanding Lucene Query Process and Core Principles
Sohu Tech Products
Sohu Tech Products
May 11, 2022 · Backend Development

Elasticsearch Pagination: From/Size, Deep Paging Issues, Scroll, Search After, PIT and Best Practices

This article explains Elasticsearch pagination mechanisms—including from/size, deep paging drawbacks, scroll, scroll‑scan, sliced scroll, search_after and point‑in‑time—detailing their inner workings, performance trade‑offs, configuration limits, and practical recommendations for handling large result sets.

Deep PagingElasticsearchSearch
0 likes · 17 min read
Elasticsearch Pagination: From/Size, Deep Paging Issues, Scroll, Search After, PIT and Best Practices
Top Architect
Top Architect
May 9, 2022 · Big Data

Using Elasticsearch for File Upload, Text Extraction, and Keyword Search with Ingest Pipelines and IK Analyzer

This tutorial explains how to leverage Elasticsearch to support file upload and download, preprocess PDF/Word/TXT files via ingest pipelines and the attachment processor, configure index mappings with Chinese IK analyzers, and perform accurate keyword searches with highlighting, all demonstrated with Java code examples.

ElasticsearchIK AnalyzerIngest Pipeline
0 likes · 13 min read
Using Elasticsearch for File Upload, Text Extraction, and Keyword Search with Ingest Pipelines and IK Analyzer
GrowingIO Tech Team
GrowingIO Tech Team
Mar 10, 2022 · Frontend Development

How We Replaced Gitbook with Docusaurus for Scalable Documentation

Facing limitations with Gitbook for SaaS and private deployments, we rebuilt our help documentation platform using Docusaurus, detailing the challenges of multi‑version support, changelog review, offline export, and the step‑by‑step setup, configuration, and deployment processes that streamlined our documentation workflow.

DocumentationDocusaurusPDF export
0 likes · 15 min read
How We Replaced Gitbook with Docusaurus for Scalable Documentation
DataFunSummit
DataFunSummit
Feb 21, 2022 · Artificial Intelligence

Advances in E‑commerce Search: Embedding, Knowledge Graphs, and Retrieval Models

This article reviews recent research on e‑commerce search, covering transformer‑based complementary rankings, Alibaba's cognitive concept net and its extension, joint deep retrieval with product quantization, personalized semantic retrieval, multi‑granularity deep semantic retrieval, and graph‑attention networks for long‑tail shop search.

AIEmbeddingGraph Neural Network
0 likes · 12 min read
Advances in E‑commerce Search: Embedding, Knowledge Graphs, and Retrieval Models
IT Architects Alliance
IT Architects Alliance
Feb 18, 2022 · Databases

Designing and Deploying Elasticsearch for Large‑Scale Reading Records and Search in a .NET Platform

This article explains how to evaluate, select, and implement Elasticsearch as a scalable NoSQL search engine for handling tens of millions of reading‑record entries and full‑text work‑search, covering architectural trade‑offs, memory usage, indexing strategies, cluster sharding, pagination limits, server sizing, and .NET integration with code examples.

ElasticsearchNoSQLSearch
0 likes · 31 min read
Designing and Deploying Elasticsearch for Large‑Scale Reading Records and Search in a .NET Platform
Laravel Tech Community
Laravel Tech Community
Feb 13, 2022 · Backend Development

Key New Features and Changes in Elasticsearch 8.0 Release

Elasticsearch 8.0 introduces major updates such as 7.x REST API compatibility headers, default‑enabled security with enrollment tokens, protected system indices, a preview KNN search API, storage‑efficient field types, faster geo indexing, PyTorch model support, and numerous deprecations and bug fixes across aggregations, allocation, analysis, authentication, and core engine components.

APISearchSecurity
0 likes · 9 min read
Key New Features and Changes in Elasticsearch 8.0 Release
DataFunTalk
DataFunTalk
Feb 4, 2022 · Databases

Exploring Tencent Music's Knowledge Graph: Architecture, Database Selection, and Search Applications

This article details Tencent Music's music knowledge graph, covering data classification, graph database evaluation, system architecture, online and offline data pipelines, advanced search use cases, and practical business scenarios, illustrating how graph technology enhances intelligent retrieval and recommendation.

Graph DatabaseKnowledge GraphNebulaGraph
0 likes · 11 min read
Exploring Tencent Music's Knowledge Graph: Architecture, Database Selection, and Search Applications
Sanyou's Java Diary
Sanyou's Java Diary
Jan 30, 2022 · Fundamentals

Master GitHub: Essential Terms, Precise Search, and Handy Shortcuts

Learn the most common GitHub terminology, how to perform precise searches using keywords, stars, forks, and the awesome list, and discover useful shortcuts for code highlighting, file navigation, and locating active users, enabling you to efficiently explore and leverage projects on the platform.

Awesome ListCode HighlightingGitHub
0 likes · 9 min read
Master GitHub: Essential Terms, Precise Search, and Handy Shortcuts
DataFunTalk
DataFunTalk
Jan 22, 2022 · Artificial Intelligence

Multimodal Content Understanding Techniques in Search Systems

This talk presents Tencent's multimodal content understanding framework for search, covering hierarchical content features, large‑scale ranking, fine‑grained image semantic vectors, video and document analysis, quality detection, duplicate removal, and future directions in AI‑driven search.

AIImage EmbeddingMultimodal
0 likes · 17 min read
Multimodal Content Understanding Techniques in Search Systems
Liangxu Linux
Liangxu Linux
Dec 24, 2021 · Fundamentals

Master Linux Grep: Quickly Find Any Text Across Files and Directories

Learn how to use the powerful grep command on Linux to recursively search for specific text, filter results with options like whole‑word matching, case‑insensitivity, include/exclude patterns, and display line numbers, all illustrated with clear examples and command syntax.

GrepSearchcommand-line
0 likes · 4 min read
Master Linux Grep: Quickly Find Any Text Across Files and Directories
Meituan Technology Team
Meituan Technology Team
Dec 2, 2021 · Artificial Intelligence

Pretraining Techniques for Search Advertising Relevance at Meituan

Meituan improves search‑ad relevance by applying pre‑trained BERT models enhanced with data‑augmented samples, multi‑task learning, keyword extraction and two‑stage knowledge distillation, producing a lightweight distilled model that, when fused with traditional relevance signals, boosts CTR, lowers Badcase@5 and raises NDCG while preserving revenue.

BERTKnowledge DistillationMachine Learning
0 likes · 30 min read
Pretraining Techniques for Search Advertising Relevance at Meituan
58 Tech
58 Tech
Nov 18, 2021 · Artificial Intelligence

Intelligent Search Strategy for 58 Recruitment: Breaking Category Constraints and Building a Smart Recall Framework

This article describes how 58 recruitment revamped its search system by removing rigid category limits, introducing query rewriting, intent recognition, doc understanding, and vector‑based recall, resulting in significantly higher relevance, reduced bad cases, and improved commercial performance.

AIQuery RewritingSearch
0 likes · 14 min read
Intelligent Search Strategy for 58 Recruitment: Breaking Category Constraints and Building a Smart Recall Framework
Qunar Tech Salon
Qunar Tech Salon
Aug 30, 2021 · Backend Development

Design of a High‑Concurrency Inventory Search System with Caching and Asynchronous Processing

The article describes the architecture and optimization techniques of Qunar's inventory search service, covering background business flow, challenges of high‑traffic multi‑channel integration, and detailed solutions such as product cataloging, channel cache utilization, request replay, cache isolation, unified cache management, cold‑hot segregation, and full‑process asynchronous handling to improve cache hit rate, update efficiency, and overall throughput.

AsynchronousCachingSearch
0 likes · 14 min read
Design of a High‑Concurrency Inventory Search System with Caching and Asynchronous Processing
Baidu Intelligent Testing
Baidu Intelligent Testing
Aug 5, 2021 · Operations

Baidu Search Stability Issue Analysis: Automated Fault Detection and Resolution Techniques

This article details Baidu Search's high‑availability engineering, describing eight major challenges in fault analysis and the corresponding innovations—index mirroring, streaming analysis, comprehensive label sets, feature engineering, query reconstruction, intelligent ranking, timeline analysis, and chaos engineering—that together enable near‑real‑time, 99% accurate detection and mitigation of search service failures.

Big DataReliabilitySearch
0 likes · 13 min read
Baidu Search Stability Issue Analysis: Automated Fault Detection and Resolution Techniques
Youzan Coder
Youzan Coder
Jul 19, 2021 · Operations

How We Built a Robust Search Middle Platform: From Pain Points to Full‑Scale Quality Assurance

This article examines the challenges faced by a search middle platform—such as inaccurate impact assessment, unstable underlying clusters, and missing process standards—and details a comprehensive quality‑assurance strategy that includes baseline test suites, stability practices, performance testing, emergency drills, and systematic monitoring to ensure reliable search services.

OperationsSearchbackend
0 likes · 13 min read
How We Built a Robust Search Middle Platform: From Pain Points to Full‑Scale Quality Assurance
ITPUB
ITPUB
Jun 18, 2021 · Databases

How to Build a Fast Search API with Redis: From Complex SQL to Set‑Based Caching

This article walks through the challenges of implementing a multi‑criteria product search for a shopping site, compares a naïve SQL solution with optimized query splitting, and then shows how Redis sets, sorted sets, and transactions can dramatically improve performance while adding pagination and update handling.

RedisSQLSearch
0 likes · 9 min read
How to Build a Fast Search API with Redis: From Complex SQL to Set‑Based Caching
Qunar Tech Salon
Qunar Tech Salon
Jun 11, 2021 · Backend Development

Optimizing Flight Ticket Pricing Search Performance at Qunar: Architecture, Bottlenecks, and Solutions

This article examines the rapid growth of Qunar's domestic flight pricing system, identifies response time bottlenecks caused by increased request volume and complex calculations, and details a series of architectural and algorithmic optimizations—including caching, search structure changes, election logic refinement, and fault‑tolerant mechanisms—that reduced average latency by up to 40%.

CachingSearchSystem architecture
0 likes · 9 min read
Optimizing Flight Ticket Pricing Search Performance at Qunar: Architecture, Bottlenecks, and Solutions
Aikesheng Open Source Community
Aikesheng Open Source Community
May 26, 2021 · Databases

Practical Guide to Using MySQL Full-Text Indexes

This article explains MySQL full‑text indexing, compares its syntax with ordinary SQL, demonstrates how to create and query a full‑text index using natural language, boolean, and query‑expansion modes, and shows performance differences through execution‑plan analysis and relevance ranking.

Boolean ModeFull-Text IndexMySQL
0 likes · 9 min read
Practical Guide to Using MySQL Full-Text Indexes
Java Tech Enthusiast
Java Tech Enthusiast
May 18, 2021 · Backend Development

Master ElasticSearch: Install, Index, and Run Advanced Java Queries

This guide walks you through downloading and installing ElasticSearch, explains core concepts like indices, types, documents, and fields, demonstrates CRUD operations via RESTful APIs, shows advanced query techniques, and provides complete Java integration examples using Maven and Docker.

Advanced QueriesElasticsearchInstallation
0 likes · 18 min read
Master ElasticSearch: Install, Index, and Run Advanced Java Queries
Big Data Technology Architecture
Big Data Technology Architecture
May 6, 2021 · Databases

Elasticsearch Pagination: From+size, search_after, and Scroll – Differences, Advantages, and Use Cases

This article explains Elasticsearch’s three pagination methods—From + size, search_after, and Scroll—detailing their definitions, code examples, advantages, disadvantages, and suitable scenarios, while also discussing max_result_window limits, PIT views, and best practices for handling large result sets.

ElasticsearchSearchbackend
0 likes · 13 min read
Elasticsearch Pagination: From+size, search_after, and Scroll – Differences, Advantages, and Use Cases
Programmer DD
Programmer DD
May 6, 2021 · Backend Development

Building a Fast Search with Redis: From Complex SQL to Set Operations

This article walks through the challenges of implementing a complex e‑commerce search interface, compares a naïve SQL solution with optimized multi‑query and Redis‑based approaches, and demonstrates how to use Redis sets, sorted sets, and transactions to achieve efficient querying, pagination, and data updates.

SearchSet Operationsbackend
0 likes · 9 min read
Building a Fast Search with Redis: From Complex SQL to Set Operations
Spring Full-Stack Practical Cases
Spring Full-Stack Practical Cases
Apr 29, 2021 · Backend Development

Master Elasticsearch CRUD and Advanced Queries with Spring Boot 2.3

This tutorial demonstrates how to configure Spring Boot 2.3 with Elasticsearch 7.8, covering required Maven dependencies, creating a high‑level REST client, and providing complete Java examples for index management, document CRUD, bulk operations, and a variety of advanced search techniques including pagination, sorting, filtering, range, highlighting, aggregations, and grouping.

CRUDSearchSpring Boot
0 likes · 14 min read
Master Elasticsearch CRUD and Advanced Queries with Spring Boot 2.3
Architecture Digest
Architecture Digest
Apr 6, 2021 · Backend Development

Integrating Spring Boot with Elasticsearch Using Java API

This tutorial explains how to set up a Spring Boot project with Elasticsearch 6.2.1, configure RestHighLevelClient and RestClient beans, define ES host settings, and perform index creation, deletion, pagination, various query types, sorting, and highlighting through the Java API.

ElasticsearchJavaREST API
0 likes · 18 min read
Integrating Spring Boot with Elasticsearch Using Java API
DataFunTalk
DataFunTalk
Mar 18, 2021 · Artificial Intelligence

Advances in Baidu Knowledge Graph: Technologies, Applications, and Future Directions

This presentation by Baidu senior R&D engineer Wang Quan outlines the evolution, architecture, and recent breakthroughs of Baidu's knowledge graph, covering universal, event, video, and industry-specific graphs, key technologies such as open knowledge mining, self‑learning, multi‑source fusion, and their applications in search, recommendation, dialogue, and intelligent services.

Artificial IntelligenceEvent ExtractionKnowledge Graph
0 likes · 22 min read
Advances in Baidu Knowledge Graph: Technologies, Applications, and Future Directions
21CTO
21CTO
Mar 11, 2021 · Artificial Intelligence

Why Search Engines Are Evolving Beyond Traffic Gateways

The article analyzes how search traffic has shifted from Google dominance to a balanced ecosystem with Facebook, mobile content platforms, and AI-driven recommendation, highlighting the rise of omnichannel "full‑stack" search that integrates content, services, and emerging technologies.

AIMobileSearch
0 likes · 14 min read
Why Search Engines Are Evolving Beyond Traffic Gateways
Architecture Digest
Architecture Digest
Feb 18, 2021 · Big Data

Elasticsearch Write, Read, and Search Processes: Underlying Mechanisms and Lucene Inverted Index

This article explains how Elasticsearch handles data ingestion, retrieval, and full‑text search by describing the roles of coordinating, primary, and replica nodes, the refresh‑commit‑flush cycle, segment files, translog, and the Lucene‑based inverted index that powers its near‑real‑time capabilities.

ElasticsearchRead ProcessSearch
0 likes · 11 min read
Elasticsearch Write, Read, and Search Processes: Underlying Mechanisms and Lucene Inverted Index
Architect
Architect
Feb 15, 2021 · Big Data

Elasticsearch Optimization Practices for Large-Scale Data Queries

This article explains how to optimize Elasticsearch for cross‑month and multi‑year queries on billions of records, covering Lucene fundamentals, index and search performance tweaks, configuration settings, and practical testing results to achieve sub‑second response times.

Big DataElasticsearchOptimization
0 likes · 14 min read
Elasticsearch Optimization Practices for Large-Scale Data Queries
DataFunTalk
DataFunTalk
Feb 3, 2021 · Artificial Intelligence

Travel Search Technology and Innovations at Alibaba Feizhu

This article presents an in‑depth overview of Alibaba Feizhu's travel‑scene search system, covering its background, architecture, query understanding, tagging, POI mining, synonym extraction, recall strategies, model designs, performance results, and future directions for personalization and explainability.

AINLPSearch
0 likes · 18 min read
Travel Search Technology and Innovations at Alibaba Feizhu
DataFunTalk
DataFunTalk
Jan 21, 2021 · Big Data

Kuaishou Metadata Platform: Evolution, Architecture, and Application Scenarios

This article introduces the development history, current architecture, abstraction methods, and key application scenarios of Kuaishou's metadata platform, highlighting challenges such as heterogeneous data integration, large-scale asset management, and the platform's role in data search, lineage, governance, and future enhancements.

Data LineageKuaishouSearch
0 likes · 16 min read
Kuaishou Metadata Platform: Evolution, Architecture, and Application Scenarios
Java Interview Crash Guide
Java Interview Crash Guide
Jan 9, 2021 · Databases

Master Elasticsearch Performance: Practical Tuning Tips for Faster Clusters

This guide consolidates everyday Elasticsearch tuning techniques—covering configuration file tweaks, system‑level settings, and usage‑level optimizations such as memory locking, discovery settings, fault detection, queue sizing, translog handling, bulk indexing, shard management, and disk I/O—to help you build a stable, high‑throughput search cluster.

Cluster OptimizationElasticsearchScalability
0 likes · 18 min read
Master Elasticsearch Performance: Practical Tuning Tips for Faster Clusters
DataFunTalk
DataFunTalk
Dec 25, 2020 · Fundamentals

Curated Collection of Algorithm and Data Structure Problems with Solution Articles

This article compiles a comprehensive list of over 400 algorithm and data‑structure problem solutions—including dynamic programming, backtracking, DFS/BFS, binary‑tree, linked‑list, stack, sorting, searching and classic puzzles—organized by topic and linked to detailed explanations for easy reference.

AlgorithmsBacktrackingData Structures
0 likes · 9 min read
Curated Collection of Algorithm and Data Structure Problems with Solution Articles
Big Data Technology & Architecture
Big Data Technology & Architecture
Dec 13, 2020 · Big Data

Elasticsearch Write, Read, Search Processes and Performance Tuning Guide

This article explains Elasticsearch's data ingestion, retrieval, and search workflows, details the underlying indexing mechanisms, and provides comprehensive system‑level, shard‑level, and query‑level tuning recommendations—including configuration snippets and best‑practice strategies for high‑throughput and low‑latency deployments.

Cluster ConfigurationElasticsearchPerformance tuning
0 likes · 20 min read
Elasticsearch Write, Read, Search Processes and Performance Tuning Guide
Big Data Technology & Architecture
Big Data Technology & Architecture
Dec 2, 2020 · Big Data

Elasticsearch Search Request Structure and Query DSL Guide

This article provides a comprehensive guide to Elasticsearch search requests, detailing the routing process, request structure, core modules like query, size, from, _source, and sort, and illustrating various query and filter types such as match, term, range, bool, and wildcard with practical curl examples.

ElasticsearchQuery DSLREST API
0 likes · 21 min read
Elasticsearch Search Request Structure and Query DSL Guide
Programmer DD
Programmer DD
Nov 26, 2020 · Databases

Unveiling Elasticsearch: Inside Nodes, Shards, and Lucene’s Inverted Index

This article explains Elasticsearch’s internal architecture, from cloud clusters and nodes to shards and Lucene’s inverted index, covering indexing, storage structures, query processing, caching, scaling, routing, and real‑world request handling, with detailed diagrams and examples.

DistributedSearchShards
0 likes · 13 min read
Unveiling Elasticsearch: Inside Nodes, Shards, and Lucene’s Inverted Index
Laravel Tech Community
Laravel Tech Community
Nov 22, 2020 · Backend Development

Using PHP's array_search() to Locate a Value Within an Array

This article explains how PHP's array_search() function searches for a specified needle in a haystack array, describes its parameters—including the optional strict mode—and shows example code demonstrating how to retrieve the key of a matching element.

PHPSearcharray_search
0 likes · 2 min read
Using PHP's array_search() to Locate a Value Within an Array
MaGe Linux Operations
MaGe Linux Operations
Nov 19, 2020 · Backend Development

Supercharging Elasticsearch: Practical Index & Search Optimizations for Billion-Row Queries

This article shares practical Elasticsearch and Lucene optimization techniques—including index structure tuning, shard routing, DocValues management, and query pagination—to achieve sub‑second search performance on datasets exceeding a billion records while supporting multi‑year historical queries.

ElasticsearchSearchindexing
0 likes · 13 min read
Supercharging Elasticsearch: Practical Index & Search Optimizations for Billion-Row Queries
System Architect Go
System Architect Go
Nov 17, 2020 · Big Data

Elasticsearch Distributed Search Mechanisms: query_then_fetch and dfs_query_then_fetch

Elasticsearch provides two search types—query_then_fetch (default) and dfs_query_then_fetch—each involving a multi-step process where the client node distributes queries to relevant shards, shards execute searches using local or global term frequencies, aggregate results, and retrieve full documents, with noted trade‑offs.

DistributedElasticsearchSearch
0 likes · 5 min read
Elasticsearch Distributed Search Mechanisms: query_then_fetch and dfs_query_then_fetch
DataFunTalk
DataFunTalk
Nov 15, 2020 · Artificial Intelligence

Query Intent Recognition in Vertical Search: Challenges, Methods, and Case Studies

The article reviews the importance of query intent recognition in vertical search, outlines its definition, highlights practical challenges such as ambiguous input, multi‑intent queries, timeliness and cold‑start issues, and surveys common rule‑based, statistical, and machine‑learning solutions together with real‑world case studies.

Machine LearningNLUSearch
0 likes · 17 min read
Query Intent Recognition in Vertical Search: Challenges, Methods, and Case Studies
dbaplus Community
dbaplus Community
Nov 10, 2020 · Operations

Essential Elasticsearch Tuning Tips for Performance and Stability

This guide consolidates practical Elasticsearch tuning techniques—from configuration file settings and system‑level adjustments to usage‑level optimizations—covering memory locking, discovery, fault detection, queue sizing, JVM heap, file descriptors, translog handling, bulk indexing, shard management, and best practices to achieve a stable, high‑performance cluster.

ClusterOperationsSearch
0 likes · 18 min read
Essential Elasticsearch Tuning Tips for Performance and Stability
DataFunTalk
DataFunTalk
Nov 4, 2020 · Artificial Intelligence

Intelligent E‑commerce Search: Architecture, Techniques, and Real‑World Impact

This article explores the evolution of e‑commerce search, detailing why search matters, the technical pipeline—including query preprocessing, entity and intent recognition, knowledge‑graph construction, recall, coarse and fine ranking—and demonstrates substantial performance gains through real‑world case studies.

AIKnowledge GraphMachine Learning
0 likes · 16 min read
Intelligent E‑commerce Search: Architecture, Techniques, and Real‑World Impact
Top Architect
Top Architect
Oct 30, 2020 · Backend Development

Implementing Search with Redis: A Backend Development Case Study

This article demonstrates how to replace complex SQL search queries with a Redis‑based solution by caching intermediate result sets using sets and sorted sets, optimizing performance through multi‑command transactions, and adding pagination, offering a practical backend development pattern for high‑traffic e‑commerce search.

Performance OptimizationSQLSearch
0 likes · 9 min read
Implementing Search with Redis: A Backend Development Case Study
DataFunTalk
DataFunTalk
Oct 28, 2020 · Artificial Intelligence

All-Rounder Recall Representation Algorithm Practice

This article presents a comprehensive overview of NetEase Yanxuan’s recall representation algorithms, detailing problem definition, model value, iterative implementations—including session-based embedding, GCN, GraphSAGE, LightGCN, and multi-interest models—along with engineering solutions, performance comparisons, and real-world deployment outcomes in search and recommendation systems.

EmbeddingGraph Neural NetworkMachine Learning
0 likes · 16 min read
All-Rounder Recall Representation Algorithm Practice
DevOps Coach
DevOps Coach
Oct 19, 2020 · Operations

Why Elasticsearch Query Latency Spikes Occur and How to Diagnose Them

This article examines the common causes of Elasticsearch query latency spikes—especially GC pauses, system cache misses, and I/O overhead—provides step‑by‑step methods to identify the root cause, and offers practical tuning recommendations to mitigate the issue.

ElasticsearchI/OSearch
0 likes · 14 min read
Why Elasticsearch Query Latency Spikes Occur and How to Diagnose Them
Laravel Tech Community
Laravel Tech Community
Oct 14, 2020 · Fundamentals

Ten Fundamental Algorithms: Sorting, Searching, Graph Traversal, and More

This article introduces ten essential algorithms—including Quick Sort, Heap Sort, Merge Sort, Binary Search, BFPRT, Depth‑First Search, Breadth‑First Search, Dijkstra's shortest‑path, Dynamic Programming, and Naive Bayes—explaining their principles, typical use cases, and step‑by‑step procedures.

AlgorithmsMachine LearningSearch
0 likes · 12 min read
Ten Fundamental Algorithms: Sorting, Searching, Graph Traversal, and More
DataFunTalk
DataFunTalk
Oct 10, 2020 · Product Management

Search Product Optimization: From System Architecture to User Demand and Content Strategies

This article outlines a comprehensive approach for search product managers to drive system improvements, covering overall architecture, query understanding, recall and ranking optimization, business and presentation rules, content enrichment, frontend design, and methods for uncovering user needs through data and behavior analysis.

Data AnalysisSearchcontent strategy
0 likes · 24 min read
Search Product Optimization: From System Architecture to User Demand and Content Strategies
Wukong Talks Architecture
Wukong Talks Architecture
Oct 9, 2020 · Big Data

Elasticsearch Fundamentals: Architecture, Indexing, Queries, Docker Setup, and Chinese Tokenization

This tutorial introduces Elasticsearch's core concepts, installation via Docker, index and document operations, query DSL, aggregations, and Chinese tokenization using the IK analyzer with custom dictionaries, providing step‑by‑step code examples for building a searchable log analysis stack.

Chinese TokenizationDockerElasticsearch
0 likes · 28 min read
Elasticsearch Fundamentals: Architecture, Indexing, Queries, Docker Setup, and Chinese Tokenization
Tencent Cloud Developer
Tencent Cloud Developer
Sep 8, 2020 · Backend Development

Implementing Autocomplete with MySQL, Redis, and Elasticsearch

The article explains autocomplete’s user‑friendly benefits and compares three backend approaches—simple MySQL LIKE queries, Redis sorted‑set range scans, and Elasticsearch’s completion suggester with FST indexing—highlighting their performance, scalability, and feature trade‑offs to help choose the best solution for a given dataset and latency requirement.

ElasticsearchMySQLSearch
0 likes · 8 min read
Implementing Autocomplete with MySQL, Redis, and Elasticsearch
Liangxu Linux
Liangxu Linux
Sep 6, 2020 · Fundamentals

Master Grep: Search Multiple Patterns Efficiently with One Command

This guide explains how to use the powerful grep command to search for multiple strings simultaneously, covering basic, extended, and Perl-compatible regular expressions, the OR operator syntax, case‑insensitive searches, whole‑word matching, and practical examples for log file analysis.

GrepSearchcommand-line
0 likes · 6 min read
Master Grep: Search Multiple Patterns Efficiently with One Command
DataFunTalk
DataFunTalk
Aug 28, 2020 · Artificial Intelligence

Intelligent Traffic Distribution in 58 Local Services: Algorithmic Practices and System Optimization

This article presents a comprehensive overview of 58 Local Services' traffic distribution system, detailing the ecosystem, user interaction flow, challenges such as information homogeneity and complex user structures, and the algorithmic solutions—including information and knowledge structuring, multi‑task user intent modeling, layered optimization, and system integration—used to improve recall, ranking, and real‑time personalization.

AISearchinformation structuring
0 likes · 21 min read
Intelligent Traffic Distribution in 58 Local Services: Algorithmic Practices and System Optimization
Swan Home Tech Team
Swan Home Tech Team
Jul 13, 2020 · Backend Development

Design and Evolution of the DaJia App Search System

This article explains the motivations, requirements, and technical design of the DaJia app's search system, compares relational databases with Lucene‑based solutions, describes the inverted index mechanism, outlines common search workflows, and details the system's three iterative development phases and future improvement plans.

ElasticsearchSearchbackend
0 likes · 12 min read
Design and Evolution of the DaJia App Search System
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Jul 6, 2020 · Big Data

Step-by-Step Guide: Installing ElasticSearch, ElasticSearch‑head, and Integrating with Spring Boot

This tutorial walks through installing ElasticSearch on CentOS, setting up the ElasticSearch‑head visual plugin, and integrating ElasticSearch with a Spring Boot application, including environment preparation, configuration, CRUD API implementation, and testing via Postman, providing a comprehensive guide for developers.

Searchbigdata
0 likes · 14 min read
Step-by-Step Guide: Installing ElasticSearch, ElasticSearch‑head, and Integrating with Spring Boot
ITPUB
ITPUB
Jun 22, 2020 · Backend Development

Essential Backend Development Tech Stack: Load Balancing, Microservices, Databases & More

This article provides a concise yet comprehensive overview of the backend development technology stack, covering load balancing, microservice ecosystems, RPC frameworks, service discovery, relational and NoSQL databases, caching strategies, message queues, object storage, and search engines, while highlighting practical configurations and real‑world trade‑offs.

Backend DevelopmentObject StorageSearch
0 likes · 24 min read
Essential Backend Development Tech Stack: Load Balancing, Microservices, Databases & More
21CTO
21CTO
Jun 9, 2020 · Product Management

Why WeChat Search Stays Passive While ByteDance Races Ahead

The article analyzes the fierce competition in China's search market, comparing WeChat's cautious, low‑key approach to ByteDance's aggressive expansion, and explains how content ecosystems, strategic partnerships, and product‑level decisions shape the future of mobile search services.

ByteDanceSearchmarket competition
0 likes · 12 min read
Why WeChat Search Stays Passive While ByteDance Races Ahead
MaGe Linux Operations
MaGe Linux Operations
Jun 9, 2020 · Backend Development

How to Search Student Records in Excel Using Python xlrd

This tutorial demonstrates how to use Python's xlrd library to read an Excel file containing student records and retrieve a specific student's information by name or ID, covering installation, code walkthrough, and sample output.

ExcelSearchdata-processing
0 likes · 4 min read
How to Search Student Records in Excel Using Python xlrd
dbaplus Community
dbaplus Community
May 24, 2020 · Big Data

Why Cross-Index Queries Matter in Elasticsearch and How to Implement Them

This article explains why Elasticsearch cross-index queries are essential, outlines their technical principles, showcases classic use cases such as business analytics, big‑data pipelines and log management, and provides practical methods, code examples, and performance considerations for effective implementation.

Big DataCross-Index QueryElasticsearch
0 likes · 10 min read
Why Cross-Index Queries Matter in Elasticsearch and How to Implement Them
DataFunTalk
DataFunTalk
May 23, 2020 · Artificial Intelligence

iQIYI Deep Semantic Representation Learning Framework for Video Recommendation and Search

Based on academic and industry experience, iQIYI has designed a deep semantic representation learning framework that integrates multimodal side information and deep models such as Transformers and graph neural networks, improving recall, ranking, deduplication, diversity and semantic matching across recommendation and search scenarios.

MultimodalRecommendation SystemsSearch
0 likes · 27 min read
iQIYI Deep Semantic Representation Learning Framework for Video Recommendation and Search
Programmer DD
Programmer DD
May 16, 2020 · Databases

Master Elasticsearch SQL: From Basic Queries to Advanced DSL Translations

This article walks through using Elasticsearch SQL to query data, covering installation, loading sample datasets, describing index schemas, executing simple and complex SQL queries with functions, converting SQL to Elasticsearch DSL, reindexing, alias management, and performance considerations, all illustrated with code snippets.

@DataDSLElasticsearch
0 likes · 15 min read
Master Elasticsearch SQL: From Basic Queries to Advanced DSL Translations
iQIYI Technical Product Team
iQIYI Technical Product Team
May 15, 2020 · Artificial Intelligence

iQIYI Deep Semantic Representation Learning Framework: Design, Challenges, and Applications

iQIYI’s deep semantic representation learning framework integrates multimodal content, knowledge graphs, and user behavior through layered data, feature, strategy, and application components, employing early, late, and hybrid fusion with Transformers, GCNs, and other deep models to deliver high‑quality embeddings that boost recommendation, search, and streaming performance across dozens of business scenarios.

MultimodalSearchgraph neural networks
0 likes · 28 min read
iQIYI Deep Semantic Representation Learning Framework: Design, Challenges, and Applications
Big Data Technology Architecture
Big Data Technology Architecture
May 8, 2020 · Big Data

Comparative Analysis of Elasticsearch and Its Competing Products

This article provides a comprehensive comparison of Elasticsearch with its major competing technologies—including Lucene, Solr, relational databases, OpenTSDB, HBase, MongoDB, ClickHouse, and Druid—highlighting each product’s strengths, weaknesses, and suitable application scenarios, and concluding that Elasticsearch generally outperforms alternatives in search and many data use cases.

Data PlatformsElasticsearchSearch
0 likes · 14 min read
Comparative Analysis of Elasticsearch and Its Competing Products
Youzan Coder
Youzan Coder
Apr 7, 2020 · Backend Development

Building Youzan's Enterprise Search Platform: Architecture, Indexing & Scaling

This article explores Youzan's enterprise search middle platform, detailing the challenges of siloed architectures, the concept of cognitive folding, comprehensive index design, write/read mechanisms, configuration-driven routing, monitoring, and practical implementations that enable scalable, reusable search capabilities across diverse business domains.

Backend ArchitectureScalable SystemsSearch
0 likes · 16 min read
Building Youzan's Enterprise Search Platform: Architecture, Indexing & Scaling
ITPUB
ITPUB
Mar 12, 2020 · Fundamentals

Master Precise GitHub Project Search: Tips, Filters, and Code Snippets

Learn how to efficiently locate high‑quality open‑source projects on GitHub by understanding project components, using targeted search qualifiers like name, stars, forks, README, description, language, and recent activity, and applying practical code examples to narrow results to the most relevant repositories.

FiltersGitHubSearch
0 likes · 5 min read
Master Precise GitHub Project Search: Tips, Filters, and Code Snippets
Liangxu Linux
Liangxu Linux
Mar 9, 2020 · Fundamentals

How to Precisely Find Open‑Source Projects on GitHub

Learn step‑by‑step techniques to narrow down GitHub search results using filters like name, description, stars, forks, language, and last update date, so you can quickly locate high‑quality open‑source projects for practice.

FiltersREADMESearch
0 likes · 6 min read
How to Precisely Find Open‑Source Projects on GitHub
Programmer DD
Programmer DD
Feb 29, 2020 · Fundamentals

Master Precise GitHub Project Search: Tips, Filters, and Code Snippets

This guide teaches developers how to efficiently locate open‑source projects on GitHub by using advanced search qualifiers such as name, README, description, star/fork counts, language, and recent update dates, complete with practical code examples and visual results.

FiltersGitHubProject Discovery
0 likes · 6 min read
Master Precise GitHub Project Search: Tips, Filters, and Code Snippets
Python Programming Learning Circle
Python Programming Learning Circle
Feb 20, 2020 · Fundamentals

Binary Search Algorithm Explanation

This article explains the binary search algorithm for locating a target element in a sorted array, describing its midpoint‑starting process, halving of the search range, termination conditions, and includes a simple example with its output.

Binary SearchSearchalgorithm
0 likes · 3 min read
Binary Search Algorithm Explanation