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DataFunSummit
DataFunSummit
May 17, 2026 · Artificial Intelligence

How Agentic Architecture Powers Next‑Generation Recommendation and Search Systems

The article reviews cutting‑edge AI search and recommendation techniques—including Alibaba Cloud's Agentic RAG, Huawei Noah's LLM‑enhanced recommender, Baidu's generative ranking model GRAB, and Elasticsearch‑based vector RAG—detailing their challenges, architectural evolutions, performance gains, and real‑world deployment results.

AI searchAgentic RAGElasticsearch
0 likes · 6 min read
How Agentic Architecture Powers Next‑Generation Recommendation and Search Systems
DataFunSummit
DataFunSummit
May 15, 2026 · Artificial Intelligence

From Text to Images: Building Multimodal Product Search with Elasticsearch Serverless

The article analyzes the shift from keyword‑based to multimodal e‑commerce search, outlines a generic architecture that combines text and image embedding with vector retrieval, and demonstrates how Elasticsearch Serverless and Alibaba Cloud AI Search platform enable a low‑cost, scalable, and high‑performance product search solution.

AI searchElasticsearchEmbedding
0 likes · 20 min read
From Text to Images: Building Multimodal Product Search with Elasticsearch Serverless
Mingyi World Elasticsearch
Mingyi World Elasticsearch
May 12, 2026 · Backend Development

From Zero to One: Building a Personalized E‑commerce Search with Easysearch

The article walks through constructing a fully personalized e‑commerce search system using Easysearch and Python Flask, detailing product modeling, behavior collection, profile building with time decay and LLM augmentation, and how to inject these signals into Elasticsearch DSL for real‑time, user‑specific ranking and recommendation.

EasysearchElasticsearchLLM
0 likes · 18 min read
From Zero to One: Building a Personalized E‑commerce Search with Easysearch
DataFunSummit
DataFunSummit
May 7, 2026 · Artificial Intelligence

From Text to Images: Building Multimodal Product Search with Elasticsearch Serverless

This article walks through a complete multimodal product search solution, explaining how embedding and vector retrieval technologies—combined with Elasticsearch Serverless and Alibaba Cloud AI Search—enable image‑based and semantic queries, detailing the architecture, key algorithms, quantization tricks, and practical deployment steps.

AI searchElasticsearchEmbedding
0 likes · 22 min read
From Text to Images: Building Multimodal Product Search with Elasticsearch Serverless
DataFunSummit
DataFunSummit
May 1, 2026 · Artificial Intelligence

How Agentic Architectures Power the Next‑Gen Recommendation and Search Systems

This article summarizes a technical ebook that analyzes the evolution of recommendation and search systems—from deep‑learning models to large‑language‑model agents—detailing multi‑agent RAG architectures, Huawei’s KAR knowledge adapters, Baidu’s generative ranking (GRAB), Elasticsearch vector search, and performance results such as a 1.5% AUC lift and GPU‑accelerated throughput gains.

ElasticsearchGenerative RankingMulti-Agent Architecture
0 likes · 6 min read
How Agentic Architectures Power the Next‑Gen Recommendation and Search Systems
Woodpecker Software Testing
Woodpecker Software Testing
Apr 30, 2026 · Databases

Datafaker: A Powerful Tool for Bulk Test Data Generation

Datafaker is a Python‑compatible utility that creates large volumes of synthetic test data for databases, streams, files, and messaging systems, offering flexible metadata rules, multi‑backend support, and command‑line options for quick data provisioning.

ElasticsearchKafkaPython
0 likes · 14 min read
Datafaker: A Powerful Tool for Bulk Test Data Generation
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Apr 30, 2026 · Artificial Intelligence

Reinventing Search: Alibaba Cloud Elasticsearch Introduces Agent‑Native AI Memory Lake

Facing a projected 175ZB of global data by 2025 and 80% unstructured content, Alibaba Cloud Elasticsearch re‑architects its engine to deliver Agent‑native search, offering structured JSON/Markdown results, high‑performance vector indexing, and a unified enterprise knowledge lake for AI agents.

AI searchAgentCloud AI
0 likes · 9 min read
Reinventing Search: Alibaba Cloud Elasticsearch Introduces Agent‑Native AI Memory Lake
JD Tech
JD Tech
Apr 23, 2026 · Backend Development

How JD Upgraded Its B‑Side Order Storage Architecture to Tackle Elasticsearch High‑Concurrency Pressure

Facing explosive merchant growth and soaring order volumes, JD redesigned its B‑side POP order storage by isolating large tenants, applying double‑hash routing, expanding clusters, buffering updates, and automating data archiving, ultimately delivering a high‑performance, scalable Elasticsearch platform that sustains massive traffic spikes.

Backend ArchitectureData SkewElasticsearch
0 likes · 16 min read
How JD Upgraded Its B‑Side Order Storage Architecture to Tackle Elasticsearch High‑Concurrency Pressure
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Apr 20, 2026 · Cloud Computing

How Alibaba Cloud’s Agentic Search Redefines Enterprise AI Search

The article analyzes Alibaba Cloud Elasticsearch’s shift from keyword‑based to Agent‑native search, detailing the Agent Native architecture, hybrid retrieval 2.0, FalconSeek engine performance gains of up to 300%, cost reductions of 40‑70%, and the ecosystem of ES Skills, cloud‑native enhancements, and observability that together enable a scalable AI search platform for enterprises.

AI searchAgentic ArchitectureCost reduction
0 likes · 13 min read
How Alibaba Cloud’s Agentic Search Redefines Enterprise AI Search
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Apr 19, 2026 · Industry Insights

ElasticStack 2026: Beyond New Versions, It’s Becoming an Agent Platform

In early 2026 ElasticStack transformed from a traditional search‑log‑visualization stack into an Agent platform, accelerating releases across three lines, elevating Elasticsearch to a context‑engineered infrastructure, unifying ES|QL as a platform‑wide interaction layer, and integrating Workflows, MCP, and vector enhancements to drive autonomous observability and security operations.

Agent PlatformElasticStackElasticsearch
0 likes · 20 min read
ElasticStack 2026: Beyond New Versions, It’s Becoming an Agent Platform
DataFunSummit
DataFunSummit
Apr 19, 2026 · Artificial Intelligence

How to Build a Multimodal Product Search Engine with Embedding and Vector Retrieval on Elasticsearch Serverless

This article explains a complete multimodal product search solution that combines text and image embeddings, dense, sparse, and hybrid models, vector similarity metrics, and Elasticsearch Serverless features such as dense_vector, sparse_vector, hybrid search, quantization, and RRF ranking to achieve fast, accurate, and cost‑effective retrieval.

AIElasticsearchEmbedding
0 likes · 20 min read
How to Build a Multimodal Product Search Engine with Embedding and Vector Retrieval on Elasticsearch Serverless
Coder Trainee
Coder Trainee
Apr 18, 2026 · Backend Development

Building a Tech Blog from Scratch: Implementing a Comment System and Full‑Text Search

This article walks through the design and implementation of a nested comment system with likes, @‑mentions, and sensitive‑word filtering, plus full‑text search using Elasticsearch, covering database schema changes, backend services, Vue components, and recommendation logic for a technical blog platform.

Comment SystemElasticsearchFull‑Text Search
0 likes · 23 min read
Building a Tech Blog from Scratch: Implementing a Comment System and Full‑Text Search
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Mar 31, 2026 · Artificial Intelligence

How to Build a Production‑Ready AI Memory System with Mem0 and Elasticsearch

This guide explains how to overcome the stateless nature of large language models by using the Mem0 framework together with Elasticsearch to create a persistent, vector‑searchable memory layer, covering architecture, real‑world scenarios, step‑by‑step deployment, and integration with the OpenClaw agent framework.

AI memoryElasticsearchLLM
0 likes · 15 min read
How to Build a Production‑Ready AI Memory System with Mem0 and Elasticsearch
DataFunSummit
DataFunSummit
Mar 29, 2026 · Artificial Intelligence

How to Build a Multimodal Product Search Engine with Embedding and Vector Retrieval on Elasticsearch Serverless

This article explores the evolution of e‑commerce search toward multimodal and cross‑modal capabilities, outlines a generic architecture that combines text and image processing via embedding and vector retrieval, and demonstrates how to implement the solution using Alibaba Cloud's AI Search Open Platform and Elasticsearch Serverless with detailed guidance on models, similarity metrics, quantization, and performance optimization.

AIElasticsearchEmbedding
0 likes · 22 min read
How to Build a Multimodal Product Search Engine with Embedding and Vector Retrieval on Elasticsearch Serverless
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Mar 27, 2026 · Backend Development

How EasySearch Rules Engine Tags Data at Ingest Time

The article walks through EasySearch's Rules plugin, showing how its high‑performance C++ rule engine can automatically match and tag documents during the ingest pipeline, enabling zero‑latency content classification for scenarios like regional, sentiment, and entity tagging.

CElasticsearchIngest Pipeline
0 likes · 9 min read
How EasySearch Rules Engine Tags Data at Ingest Time
JD Retail Technology
JD Retail Technology
Mar 25, 2026 · Databases

How JD.com Scaled POP Order Elasticsearch to Handle Billions of Orders

This article analyzes the challenges of JD.com's POP order Elasticsearch storage—including data skew, oversized shards, frequent updates, and high maintenance costs—and details the multi‑layered architectural redesign that introduced tenant isolation, dual‑hash routing, differentiated shard strategies, and a dual‑active physical foundation to achieve high performance, scalability, and availability.

Data PartitioningElasticsearchOrder Management
0 likes · 16 min read
How JD.com Scaled POP Order Elasticsearch to Handle Billions of Orders
DataFunSummit
DataFunSummit
Mar 24, 2026 · Artificial Intelligence

How to Build a Multimodal Product Search System with Embedding and Vector Retrieval

This article presents a comprehensive, end‑to‑end solution for multimodal product search, detailing the evolution from keyword to image‑based queries, the core embedding and vector retrieval technologies, practical Elasticsearch Serverless integration, quantization methods, and a complete demo workflow for building a high‑performance, low‑cost search platform.

AI search platformElasticsearchEmbedding
0 likes · 21 min read
How to Build a Multimodal Product Search System with Embedding and Vector Retrieval
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Mar 24, 2026 · Information Security

Easysearch Audit Log Walkthrough: Who’s Accessing Your Cluster?

This article guides you through enabling Easysearch's audit log, configuring the security.audit.type parameter, verifying settings in the management UI, and using the audit records to identify external IPs, failed logins, and SSL handshake failures in a production environment.

EasysearchElasticsearchSecurity
0 likes · 12 min read
Easysearch Audit Log Walkthrough: Who’s Accessing Your Cluster?
Wu Shixiong's Large Model Academy
Wu Shixiong's Large Model Academy
Mar 21, 2026 · Artificial Intelligence

Step‑by‑Step Guide to Implementing a Hybrid Retrieval Function with RRF Fusion

This article breaks down the end‑to‑end retrieval function used in a RAG system, detailing each of the five stages—from request construction, hybrid vector + BM25 search, RRF fusion, cross‑encoder reranking, to threshold filtering—and provides concrete Python code, parameter choices, and performance insights.

Cross-EncoderElasticsearchHybrid Retrieval
0 likes · 13 min read
Step‑by‑Step Guide to Implementing a Hybrid Retrieval Function with RRF Fusion
Coder Trainee
Coder Trainee
Mar 18, 2026 · Operations

How to Persist Zipkin Traces to MySQL or Elasticsearch

This guide explains why Zipkin loses trace data after a restart when using the default in‑memory storage and provides step‑by‑step instructions to configure persistent storage with MySQL or Elasticsearch, including database setup, SQL schema, startup commands, and verification.

Distributed TracingElasticsearchPersistence
0 likes · 7 min read
How to Persist Zipkin Traces to MySQL or Elasticsearch
ITPUB
ITPUB
Mar 2, 2026 · Backend Development

Eliminate Unstable Pagination Anchors: Reliable Cursor and Timestamp Strategies for Backend Systems

This article explains why traditional offset‑based pagination can cause duplicate or missing records when data changes, compares three practical solutions—including cursor pagination with timestamp + unique key, fixed‑window timestamp filtering, and Elasticsearch’s search_after/scroll methods—detailing their implementation, pros, cons, and suitable scenarios.

BackendCursorElasticsearch
0 likes · 14 min read
Eliminate Unstable Pagination Anchors: Reliable Cursor and Timestamp Strategies for Backend Systems
Su San Talks Tech
Su San Talks Tech
Feb 20, 2026 · Backend Development

How to Sync MySQL to Elasticsearch with DBSyncer: A Step‑by‑Step Guide

This guide introduces the open‑source DBSyncer tool, explains its key features, shows how to install it via Docker, and provides detailed step‑by‑step examples of synchronizing MySQL tables to another MySQL instance and to Elasticsearch, including configuration, field mapping, and verification.

DBSyncerDockerElasticsearch
0 likes · 6 min read
How to Sync MySQL to Elasticsearch with DBSyncer: A Step‑by‑Step Guide
dbaplus Community
dbaplus Community
Feb 10, 2026 · Backend Development

How to Eliminate Unstable Pagination Anchors and Data Duplication in Backend Systems

This article explains why offset‑based pagination can cause duplicate or missing records in backend list queries, illustrates real‑world cases, analyzes the root causes, and presents three practical solutions—including cursor pagination, timestamp windows, and Elasticsearch search_after—along with their trade‑offs and implementation details.

CursorElasticsearchSQL
0 likes · 12 min read
How to Eliminate Unstable Pagination Anchors and Data Duplication in Backend Systems
SpringMeng
SpringMeng
Feb 10, 2026 · Backend Development

Build a Fully Open‑Source Bilibili Clone with SpringBoot and Vue

It describes a fully open‑source Bilibili‑style video platform built with SpringBoot backend and Vue frontend, detailing system demo screenshots, functional requirements (video playback, upload, user, interaction, community), tech stack choices, video processing pipeline, deployment steps, and code acquisition instructions.

Bilibili cloneElasticsearchMicroservices
0 likes · 11 min read
Build a Fully Open‑Source Bilibili Clone with SpringBoot and Vue
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Jan 31, 2026 · Backend Development

How to Make a Python Project Support Both Elasticsearch and Easysearch – A Practical Walkthrough

This article explains how to configure a Python codebase to connect simultaneously to Elasticsearch (8.x/9.x) and Easysearch by selecting the elasticsearch‑7.13.1 client, handling product‑validation differences, applying NumPy 2.0 compatibility patches, and configuring HTTPS self‑signed certificates, while comparing three implementation options and recommending the most maintainable solution.

EasysearchElasticsearchHTTPS
0 likes · 8 min read
How to Make a Python Project Support Both Elasticsearch and Easysearch – A Practical Walkthrough
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Jan 30, 2026 · Backend Development

Text2DSL: Convert Natural Language to Precise Elasticsearch/Easysearch DSL

Text2DSL lets users describe search requirements in plain language, uses DeepSeek to generate Elasticsearch DSL, validates the DSL locally with Elasticsearch/Easysearch, iteratively refines it up to five times, and achieves over 95% first‑try accuracy while cutting query‑building time by at least threefold.

DSL generationDeepSeekEasysearch
0 likes · 12 min read
Text2DSL: Convert Natural Language to Precise Elasticsearch/Easysearch DSL
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Jan 23, 2026 · Backend Development

Why Elasticsearch’s 10,000 Hit Limit Slows Your Cluster and How to Fix It

Elasticsearch defaults to a total hit count of 10,000 after version 7.x, which many developers override with "track_total_hits": true to get exact numbers, but this seemingly harmless change can double CPU usage and increase query latency from 20 ms to 500 ms due to the underlying Block‑Max WAND algorithm and its interaction with aggregations, sorting, and scoring.

Block-Max WANDElasticsearchperformance
0 likes · 11 min read
Why Elasticsearch’s 10,000 Hit Limit Slows Your Cluster and How to Fix It
Ray's Galactic Tech
Ray's Galactic Tech
Jan 22, 2026 · Big Data

Export 1 Billion Elasticsearch Docs in 3 Hours Using PIT + Slice

This guide explains how to reliably export over a billion Elasticsearch documents within a few hours by using Point‑In‑Time (PIT) snapshots combined with parallel Slice processing, covering diagnostics, performance modeling, consistency levels, failure recovery, and resource isolation.

Big DataData ExportElasticsearch
0 likes · 7 min read
Export 1 Billion Elasticsearch Docs in 3 Hours Using PIT + Slice
Sohu Tech Products
Sohu Tech Products
Jan 14, 2026 · Artificial Intelligence

Build a Zero‑Cost Open‑Source RAG Smart Document Q&A System from Scratch

This guide walks through building an open‑source Retrieval‑Augmented Generation (RAG) system that indexes local files with Everything, uses hybrid BM25‑vector search via Elasticsearch, and answers questions with a local LLM, covering architecture, core techniques, deployment steps, performance tweaks, and common pitfalls.

ElasticsearchLLMPython
0 likes · 11 min read
Build a Zero‑Cost Open‑Source RAG Smart Document Q&A System from Scratch
DevOps Coach
DevOps Coach
Jan 11, 2026 · Databases

Is Elasticsearch Losing Its Edge? A Deep Dive into Its Decline and Alternatives

Elasticsearch, once hailed for speed and flexibility, now faces challenges from licensing changes, rising operational complexity, heavyweight architecture, and the surge of lightweight and vector‑based search solutions like OpenSearch, Meilisearch, and specialized vector databases, prompting developers to reassess its role as the default search engine.

ElasticsearchOpenSearchSolr
0 likes · 8 min read
Is Elasticsearch Losing Its Edge? A Deep Dive into Its Decline and Alternatives
Ray's Galactic Tech
Ray's Galactic Tech
Jan 4, 2026 · Fundamentals

Master Elasticsearch: From Core Concepts to Advanced Search and Scaling

This guide introduces Elasticsearch’s fundamental architecture, explains core concepts such as inverted indexes, analyzers, and mapping, demonstrates essential query types, aggregation techniques, performance optimizations, distributed design, and real‑world use cases like blog and e‑commerce search, while also covering monitoring and advanced features.

ElasticsearchQuery DSLaggregation
0 likes · 9 min read
Master Elasticsearch: From Core Concepts to Advanced Search and Scaling
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Jan 3, 2026 · Artificial Intelligence

Build Your Own AI Coding Assistant in 5 Minutes: A Hands‑On Guide

The article analyzes common pain points of traditional AI coding chats—repetitive context input, lengthy prompts, and generic answers—and demonstrates how to create a persistent, expert‑level AI coding assistant using Coco AI, with step‑by‑step configuration, example prompts, and future RAG enhancements.

AI AgentCoco AIDeepSeek
0 likes · 9 min read
Build Your Own AI Coding Assistant in 5 Minutes: A Hands‑On Guide
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Dec 29, 2025 · Cloud Native

How a Visual Platform Cut Search Costs by 60% with All‑in‑Elasticsearch

This case study details how a major internet visual platform consolidated its log, keyword, and vector search workloads onto Alibaba Cloud Elasticsearch, eliminating three separate pipelines, reducing write‑costs by 60%, cutting storage expenses over 60%, and achieving multi‑fold performance gains through serverless scaling, FalconSeek engine optimizations, and unified monitoring.

Cost OptimizationElasticsearchRAG
0 likes · 10 min read
How a Visual Platform Cut Search Costs by 60% with All‑in‑Elasticsearch
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Dec 28, 2025 · Artificial Intelligence

Building an Elasticsearch‑Powered RAG Q&A System: Theory and Full Code Walkthrough

This article walks through the principles of Retrieval‑Augmented Generation (RAG) and provides a complete Python implementation using Elasticsearch, covering document chunking, semantic embedding, bulk indexing, hybrid BM25‑vector search, RRF result fusion, prompt design, LLM invocation, and a practical demo.

ElasticsearchHybrid SearchPrompt Engineering
0 likes · 9 min read
Building an Elasticsearch‑Powered RAG Q&A System: Theory and Full Code Walkthrough
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Dec 28, 2025 · Big Data

Easysearch UI vs Kibana: Choosing the Right Visualization Tool

This guide compares Easysearch UI and Kibana across positioning, feature set, performance, resource usage, learning curve, and typical use cases, then provides concrete scenario‑based recommendations and a decision‑tree to help teams select the most suitable visualization solution for their Elasticsearch deployments.

Easysearch UIElasticsearchKibana
0 likes · 8 min read
Easysearch UI vs Kibana: Choosing the Right Visualization Tool
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Dec 26, 2025 · Databases

How to Enable Accurate Code Search in Elasticsearch with an NGram Analyzer

This article analyzes the shortcomings of standard Elasticsearch analyzers for code search, presents a custom NGram analyzer combined with match_phrase queries, shows configuration and query examples, compares performance of different query types, and offers best‑practice guidelines and pitfalls to avoid when building a reliable code‑search system.

ElasticsearchNGramPython
0 likes · 13 min read
How to Enable Accurate Code Search in Elasticsearch with an NGram Analyzer
JD Tech
JD Tech
Dec 24, 2025 · Databases

How to Eliminate 30‑Minute Master‑Slave Lag in High‑Volume Inventory Systems

This article analyzes why a warehouse management system’s master‑slave database replication lagged up to 30 minutes during nightly inventory snapshot generation, evaluates several mitigation strategies, and details the chosen big‑data‑driven solution that moved snapshots to Elasticsearch, reducing lag and disk usage.

Database ReplicationElasticsearchHive
0 likes · 8 min read
How to Eliminate 30‑Minute Master‑Slave Lag in High‑Volume Inventory Systems
Mike Chen's Internet Architecture
Mike Chen's Internet Architecture
Dec 21, 2025 · Backend Development

How Elasticsearch Scales to Billions of Queries: Sharding, Inverted Index, Distributed Execution, and Replication

Elasticsearch achieves billion‑scale search performance by combining horizontal sharding, immutable inverted‑index segments, a two‑stage distributed Query/FETCH model, and multiple replicas with a coordinator node to ensure high concurrency, scalability, and availability.

Distributed QueryElasticsearchReplication
0 likes · 4 min read
How Elasticsearch Scales to Billions of Queries: Sharding, Inverted Index, Distributed Execution, and Replication
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Dec 20, 2025 · Artificial Intelligence

How to Build an Enterprise‑Grade Intelligent Document QA System with Everything plus RAG

This article walks through the need for fast, accurate answers from massive document collections, compares plain keyword search and pure LLM chat, and presents a hybrid Retrieval‑Augmented Generation solution built with open‑source components, detailing architecture, hybrid retrieval, prompt engineering, deployment, performance tuning, and common pitfalls.

ElasticsearchHybrid RetrievalPrompt Engineering
0 likes · 12 min read
How to Build an Enterprise‑Grade Intelligent Document QA System with Everything plus RAG
Su San Talks Tech
Su San Talks Tech
Dec 18, 2025 · Backend Development

Which Elasticsearch Pagination Method Is Best? from/size, search_after, Scroll API & PIT

This guide compares Elasticsearch’s four common pagination techniques—`from/size`, `search_after`, Scroll API, and Point in Time—detailing their syntax, advantages, drawbacks, and ideal use‑cases, helping developers select the most efficient method based on pagination depth, consistency requirements, and resource constraints.

BackendElasticsearchpagination
0 likes · 10 min read
Which Elasticsearch Pagination Method Is Best? from/size, search_after, Scroll API & PIT
Ray's Galactic Tech
Ray's Galactic Tech
Dec 9, 2025 · Information Security

Master Elasticsearch Security: Complete Network, Auth, TLS & Hardening Guide

This comprehensive guide walks you through securing Elasticsearch by isolating the network, enabling authentication and role‑based access, encrypting traffic with TLS, upgrading legacy versions, configuring audit logging, setting up reverse‑proxy protection, and applying enterprise‑grade best practices to prevent data leaks.

AuthenticationElasticsearchHardening
0 likes · 10 min read
Master Elasticsearch Security: Complete Network, Auth, TLS & Hardening Guide
Raymond Ops
Raymond Ops
Dec 8, 2025 · Operations

Mastering EFK: Complete Guide to Building a Scalable Log Management Solution

This comprehensive guide walks you through building a scalable EFK log management solution, covering architecture components, high‑availability design, environment preparation, detailed Elasticsearch, Fluentd and Kibana deployment steps, index optimization, monitoring, alerting, security hardening, troubleshooting and best‑practice recommendations for modern cloud‑native operations.

EFKElasticsearchFluentd
0 likes · 19 min read
Mastering EFK: Complete Guide to Building a Scalable Log Management Solution
Code Ape Tech Column
Code Ape Tech Column
Dec 5, 2025 · Big Data

Optimizing 100K Record Retrieval from 10M‑Row Pools: ClickHouse, ES Scroll, ES+HBase, RediSearch

This article examines several engineering solutions for extracting up to 100,000 records from a ten‑million‑row pool, comparing multi‑threaded ClickHouse pagination, Elasticsearch scroll‑scan, an ES‑plus‑HBase hybrid, and RediSearch + RedisJSON, and presents performance measurements and practical trade‑offs.

Big DataClickHouseElasticsearch
0 likes · 12 min read
Optimizing 100K Record Retrieval from 10M‑Row Pools: ClickHouse, ES Scroll, ES+HBase, RediSearch
Java Architect Handbook
Java Architect Handbook
Nov 30, 2025 · Databases

When Sharding Fails: Debugging Pagination Bugs and Optimizing MySQL for Massive Tables

The article recounts a real‑world case where a massive device table (over 500 million rows) suffered from sharding and Elasticsearch integration issues, describes a pagination bug caused by Sharding‑JDBC, and presents a comprehensive set of hardware, software, and SQL optimization techniques—including MySQL configuration examples—to improve performance.

Database OptimizationElasticsearchSharding-JDBC
0 likes · 13 min read
When Sharding Fails: Debugging Pagination Bugs and Optimizing MySQL for Massive Tables
Architect
Architect
Nov 27, 2025 · Databases

How to Overcome Deep Pagination Bottlenecks with Cursor, Subqueries, and Elasticsearch Search After

This article explains why deep pagination hurts performance in large datasets, demonstrates the inefficiency of offset‑based SQL queries, and presents practical alternatives such as cursor pagination, sub‑query optimizations, delayed joins, caching, business limits, and the Elasticsearch Search After technique for stable, scalable paging.

Database OptimizationElasticsearchcursor pagination
0 likes · 10 min read
How to Overcome Deep Pagination Bottlenecks with Cursor, Subqueries, and Elasticsearch Search After
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Nov 24, 2025 · Backend Development

Mastering Easysearch CCR: A Hands‑On Guide to Auto‑Follow

This step‑by‑step tutorial shows how to set up two Easysearch clusters, configure Cross‑Cluster Replication (CCR), enable the Auto‑Follow feature, apply minimal‑privilege roles, tune performance parameters, and avoid common pitfalls, enabling seamless multi‑region data sync and zero‑downtime migrations.

AutoFollowCCRCluster Configuration
0 likes · 10 min read
Mastering Easysearch CCR: A Hands‑On Guide to Auto‑Follow
Java Companion
Java Companion
Nov 22, 2025 · Databases

Why ShardingJDBC Can Be a Trap: Rethinking Sharding‑Based Database Optimization

The article recounts a real‑world case where using ShardingJDBC, Elasticsearch and Logstash dramatically increased system complexity and caused a pagination bug, then walks through hardware, software and SQL‑level optimization techniques and suggests more balanced alternatives to blind sharding.

Database OptimizationElasticsearchLogstash
0 likes · 12 min read
Why ShardingJDBC Can Be a Trap: Rethinking Sharding‑Based Database Optimization
Java Companion
Java Companion
Nov 21, 2025 · Databases

How to Query Phone Number Suffix in Milliseconds on 50 Million Records

When faced with 50 million user rows, using LIKE '%1234' triggers a full table scan, but adding a suffix column, reversing the phone number, leveraging function indexes, or integrating Elasticsearch can reduce query time from minutes to a few milliseconds, each with its own trade‑offs.

Database designElasticsearchindexing
0 likes · 12 min read
How to Query Phone Number Suffix in Milliseconds on 50 Million Records
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Nov 19, 2025 · Backend Development

Master Elasticsearch: Index Design, Field Types, and Cluster Management Tips

An experienced engineer shares practical Elasticsearch insights covering index design with aliases and routing, field type choices, query optimization techniques, pagination strategies, real‑time refresh settings, memory limits, and cluster management, offering concrete examples and actionable recommendations for robust search implementations.

Cluster ManagementElasticsearchfield types
0 likes · 12 min read
Master Elasticsearch: Index Design, Field Types, and Cluster Management Tips
Zhuanzhuan Tech
Zhuanzhuan Tech
Nov 17, 2025 · Backend Development

How to Eliminate Duplicate and Missing Data in Backend Pagination

This article explains why offset‑based pagination can cause duplicate or missing records when data changes, compares three practical solutions—including cursor pagination with timestamps and IDs, fixed‑window timestamp filtering, and Elasticsearch search_after—and provides concrete SQL and code examples along with their trade‑offs and suitable scenarios.

BackendCursorElasticsearch
0 likes · 12 min read
How to Eliminate Duplicate and Missing Data in Backend Pagination
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Nov 16, 2025 · Databases

Elasticsearch vs Open Distro vs OpenSearch vs Easysearch: A Complete Comparison

This article systematically compares Elasticsearch, Open Distro, OpenSearch, and Easysearch, covering their origins, licensing, feature sets, performance benchmarks, Chinese‑language support, deployment and operational considerations, and provides guidance on which solution fits different business and compliance scenarios.

EasysearchElasticsearchOpen Distro
0 likes · 17 min read
Elasticsearch vs Open Distro vs OpenSearch vs Easysearch: A Complete Comparison
ITPUB
ITPUB
Nov 12, 2025 · Backend Development

Where Did Elasticsearch Docs Move? A Quick Guide to the New 9.x URLs

The article outlines the major changes introduced in Elasticsearch 9.x documentation, including the new elastic.co/docs domain, unified version handling, reorganized navigation by use case, separate release‑notes location, versioned API paths, and practical tips for updating bookmarks and finding the right guides.

APIBackendDocumentation
0 likes · 6 min read
Where Did Elasticsearch Docs Move? A Quick Guide to the New 9.x URLs
DataFunTalk
DataFunTalk
Nov 11, 2025 · Artificial Intelligence

How Alibaba Cloud’s AI Search Redefines Vector Retrieval and RAG

This article outlines Alibaba Cloud AI Search’s evolution, detailing its dual product lines—enhanced Elasticsearch and self‑developed OpenSearch—key Agentic RAG technologies, serverless architecture, vector and LLM‑driven search capabilities, and future directions in AI‑powered search.

AI searchAlibaba CloudElasticsearch
0 likes · 4 min read
How Alibaba Cloud’s AI Search Redefines Vector Retrieval and RAG
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Nov 7, 2025 · Backend Development

How to Achieve MySQL‑LIKE Style Fuzzy Search in Elasticsearch 8.x

This article walks through the challenge of implementing MySQL‑LIKE style front‑and‑back wildcard searches in Elasticsearch, comparing match, match_phrase, n‑gram, legacy wildcard queries, and the new wildcard field type introduced in ES 7.9+, with code samples, performance benchmarks, and practical recommendations for choosing the optimal solution.

ElasticsearchN-gramfuzzy-search
0 likes · 10 min read
How to Achieve MySQL‑LIKE Style Fuzzy Search in Elasticsearch 8.x
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Nov 5, 2025 · Backend Development

Complete Easysearch.yml Field Guide and Security Configuration Walkthrough

This article answers a WeChat query by providing the official documentation link, demonstrating how to disable HTTP TLS, testing TCP TLS, and offering a line‑by‑line walkthrough of easysearch.yml’s core settings—including cluster basics, security options, TLS certificates, password policies, and critical risk warnings for production deployments.

ClusterEasysearchElasticsearch
0 likes · 8 min read
Complete Easysearch.yml Field Guide and Security Configuration Walkthrough
Architecture Digest
Architecture Digest
Nov 5, 2025 · Backend Development

Why Deep Pagination Breaks Elasticsearch and How to Fix It

This article explains how deep pagination in Elasticsearch triggers costly scatter‑gather queries that overload CPU, memory, and network, and it presents practical alternatives such as the scroll API and search_after to achieve efficient, real‑time pagination for large datasets.

Elasticsearchdeep paginationperformance
0 likes · 10 min read
Why Deep Pagination Breaks Elasticsearch and How to Fix It
Tech Freedom Circle
Tech Freedom Circle
Nov 5, 2025 · Artificial Intelligence

Elasticsearch: BM25, TF‑IDF, Dense Vectors, kNN, L2 & Cosine Distances, RRF

This article provides a comprehensive technical guide to Elasticsearch’s core retrieval models—BM25 and TF‑IDF—while detailing modern vector‑based search using dense_vector, kNN, L2 and cosine distances, and demonstrates how to combine keyword and semantic results through hybrid search and Reciprocal Rank Fusion (RRF) with practical configuration examples.

BM25ElasticsearchRRF
0 likes · 42 min read
Elasticsearch: BM25, TF‑IDF, Dense Vectors, kNN, L2 & Cosine Distances, RRF
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Nov 2, 2025 · Backend Development

What’s New in the Elasticsearch 9.x Documentation?

The Elasticsearch 9.x documentation has moved to a new URL, unified version handling, reorganized by solution use‑cases, separated release notes, added versioned API paths, and introduced client library navigation and versioning guides, all aimed at improving discoverability and developer efficiency.

APIDocumentationElasticsearch
0 likes · 7 min read
What’s New in the Elasticsearch 9.x Documentation?
Architect
Architect
Oct 29, 2025 · Big Data

Master Kibana: Install, Configure, and Visualize Elasticsearch Data

This guide walks you through installing Kibana, configuring its connection to Elasticsearch, exploring data via Discover, creating visualizations and dashboards, and monitoring cluster health, while also covering advanced query syntax, time filters, and practical tips for effective data analysis and visualization.

Data visualizationElasticsearchKibana
0 likes · 13 min read
Master Kibana: Install, Configure, and Visualize Elasticsearch Data
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Oct 28, 2025 · Big Data

How Huolala Scaled Elasticsearch to 40B Records with Serverless Cloud Architecture

Huolala, a leading smart logistics platform serving over 14 markets and millions of users, detailed its massive Elasticsearch deployment—over 1.5 万 CPU cores, 40 billion records, 4 PB data—highlighting multi‑AZ design, serverless migration, and a comprehensive management platform that boosted performance, reduced costs, and enabled AI‑driven services.

AI searchBig DataElasticsearch
0 likes · 10 min read
How Huolala Scaled Elasticsearch to 40B Records with Serverless Cloud Architecture
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Oct 28, 2025 · Operations

elasticdumpWeb: A New Web Tool for Cross‑Cluster Elasticsearch to Easysearch Index Migration

elasticdumpWeb is a web‑based utility that automates cross‑cluster index migration between Elasticsearch (including version 9.0.0) and Easysearch, handling version compatibility, field type conversion, data validation, performance tuning, and SSL issues while providing visual progress and detailed reports.

EasysearchElasticsearchbulk API
0 likes · 6 min read
elasticdumpWeb: A New Web Tool for Cross‑Cluster Elasticsearch to Easysearch Index Migration
Raymond Ops
Raymond Ops
Oct 15, 2025 · Operations

Step‑by‑Step Guide: Deploying an ELK Log Analysis Stack on CentOS

This comprehensive tutorial walks you through installing and configuring the ELK stack (Elasticsearch, Logstash, Kibana) on CentOS, covering environment setup, component installation, node configuration, plugin integration, index creation, and log visualization with code snippets and screenshots.

CentOSELKElasticsearch
0 likes · 14 min read
Step‑by‑Step Guide: Deploying an ELK Log Analysis Stack on CentOS
Su San Talks Tech
Su San Talks Tech
Oct 13, 2025 · Backend Development

Essential Microservice Architecture Components Explained

This article outlines the key building blocks of a microservice architecture—including Nginx as the traffic entry, Spring Cloud Gateway, service registration, Redis caching, MySQL persistence, Elasticsearch, message queues, ELK logging, distributed scheduling, and object storage—providing practical guidance on design choices and high‑availability setups.

ELKElasticsearchMinio
0 likes · 9 min read
Essential Microservice Architecture Components Explained
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Oct 12, 2025 · Backend Development

5 Practical Ways to Migrate Elasticsearch Data to Easysearch

This article evaluates five common methods for moving data from cloud Elasticsearch to on‑premise INFINI Easysearch, details three viable solutions—Logstash, Elasticdump, and custom Python scripts—explains why reindex and snapshot restore fail, and provides a decision matrix and practical migration guidelines.

Data MigrationEasysearchElasticdump
0 likes · 7 min read
5 Practical Ways to Migrate Elasticsearch Data to Easysearch
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Oct 11, 2025 · Operations

Where to Find Easysearch’s Initial Password and How to Retrieve It

Easysearch 1.15.x no longer saves the initial password in initialize.log for security reasons, so the article explains two ways to obtain it—checking the startup log for the bootstrap credential or resetting it with the reset_admin_password.sh script—and shows how to verify the password with curl.

DeploymentEasysearchElasticsearch
0 likes · 4 min read
Where to Find Easysearch’s Initial Password and How to Retrieve It
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Oct 8, 2025 · Operations

Step‑by‑Step Logstash Migration from Elasticsearch 9.0 to Easysearch with Zero Downtime

This guide walks through a zero‑downtime migration from Elasticsearch 9.0 to the Easysearch compatible branch using Logstash, covering project goals, solution selection, detailed input/filter/output configurations, SSL handling, batch tuning, execution steps, and verification to ensure data integrity and ID consistency.

Data MigrationEasysearchElasticsearch
0 likes · 6 min read
Step‑by‑Step Logstash Migration from Elasticsearch 9.0 to Easysearch with Zero Downtime
Tech Freedom Circle
Tech Freedom Circle
Sep 25, 2025 · Artificial Intelligence

Inside RAGFlow: How Its Microservice Architecture Powers an Enterprise‑Grade Retrieval‑Augmented Generation Platform

This article provides a detailed technical walkthrough of RAGFlow's architecture, covering its microservice design, directory layout, layered structure, cloud‑native deployment, core modules such as DeepDoc, RAG engine, Agent system, and web UI, as well as multi‑tenant isolation, streaming responses, asynchronous task handling, concurrency controls, scalability strategies, and a complete request‑lifecycle example for document upload.

AI ArchitectureDeepDocDocker Compose
0 likes · 26 min read
Inside RAGFlow: How Its Microservice Architecture Powers an Enterprise‑Grade Retrieval‑Augmented Generation Platform
Tech Freedom Circle
Tech Freedom Circle
Sep 25, 2025 · Artificial Intelligence

RAGFlow Deep Dive: Data Parsing and Knowledge Graph Construction

This article examines RAGFlow's end‑to‑end pipeline for turning diverse documents into structured knowledge, detailing the TaskExecutor factory, the DeepDoc layout‑aware parser, chunking strategies, embedding and storage mechanisms, and the GraphRAG‑based knowledge‑graph extraction that together enable high‑precision retrieval and reasoning.

Data ParsingDeepDocElasticsearch
0 likes · 15 min read
RAGFlow Deep Dive: Data Parsing and Knowledge Graph Construction
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Sep 24, 2025 · Big Data

How 3 Simple Tweaks Doubled Elasticsearch Scan Performance on 40M Docs

The article details a real‑world case of scanning over 40 million Elasticsearch documents, identifies four performance bottlenecks, and presents three concrete optimizations—_source filtering, precise index targeting, and batch‑size tuning—that together cut processing time in half and raise CPU utilization from 25% to 85%.

Batch Size TuningElasticsearchIncremental Sync
0 likes · 8 min read
How 3 Simple Tweaks Doubled Elasticsearch Scan Performance on 40M Docs
macrozheng
macrozheng
Sep 19, 2025 · Databases

Master Database Sharding: Solving Read Diffusion with Range and Modulo Strategies

This article explains why large MySQL tables degrade performance, introduces vertical and horizontal sharding techniques—including range‑based and modulo‑based partitioning—covers the read‑diffusion problem caused by non‑sharding keys, and presents practical solutions such as auxiliary index tables, Elasticsearch integration, and TiDB as a distributed alternative.

ElasticsearchRange ShardingTiDB
0 likes · 15 min read
Master Database Sharding: Solving Read Diffusion with Range and Modulo Strategies
macrozheng
macrozheng
Sep 16, 2025 · Backend Development

Simplify Elasticsearch with Easy-Es: MyBatis‑Plus‑Style ORM Tutorial

This article introduces Easy-Es, an Elasticsearch ORM that mimics MyBatis‑Plus syntax, walks through its core features, integration steps, entity annotations, mapper and service implementations, and demonstrates simple, advanced, and recommendation search scenarios, highlighting the reduction in boilerplate code.

Easy-EsElasticsearchJava
0 likes · 17 min read
Simplify Elasticsearch with Easy-Es: MyBatis‑Plus‑Style ORM Tutorial
Su San Talks Tech
Su San Talks Tech
Sep 15, 2025 · Databases

5 Proven Ways to Sync MySQL Data to Elasticsearch

This article explains why synchronizing MySQL with Elasticsearch is beneficial and compares five practical solutions—dual‑write, scheduled tasks, binlog, Canal, and MQ asynchronous—detailing their implementation, advantages, disadvantages, and suitable scenarios for each.

Backend DevelopmentElasticsearchdata synchronization
0 likes · 14 min read
5 Proven Ways to Sync MySQL Data to Elasticsearch
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Sep 10, 2025 · Operations

Visualize Elasticsearch Core Metrics Without Kibana Using Easysearch UI Plugin

This guide walks through installing the Easysearch UI plugin (v1.15.0) on a Linux host to replace Kibana and Console, showing how to download the package, deploy it with required security authentication, verify port 9200, and explore built‑in visualizations such as global, node, index, alias, dev‑tool, and security views.

EasysearchElasticsearchKibana alternative
0 likes · 4 min read
Visualize Elasticsearch Core Metrics Without Kibana Using Easysearch UI Plugin
Top Architect
Top Architect
Sep 7, 2025 · Databases

Mastering MySQL‑Elasticsearch Sync: Strategies, Pros, Cons, and Real‑World Use Cases

This article explores why MySQL alone struggles with large‑scale queries, introduces Elasticsearch as a complementary search engine, and compares several synchronization methods—including synchronous and asynchronous dual‑write, Logstash, binlog‑based, Canal, and Alibaba Cloud DTS—detailing their advantages, drawbacks, and typical application scenarios.

BinlogCanalDTS
0 likes · 18 min read
Mastering MySQL‑Elasticsearch Sync: Strategies, Pros, Cons, and Real‑World Use Cases
Java Tech Enthusiast
Java Tech Enthusiast
Sep 5, 2025 · Big Data

Master Kibana: Install, Configure, and Visualize Elasticsearch Data

Learn how to install Kibana, connect it to Elasticsearch, explore data with Discover, craft queries using Lucene syntax, create visualizations and dashboards, and monitor your stack, all with detailed step‑by‑step instructions and screenshots to help you master this powerful analytics platform.

ElasticsearchKibanaLog Monitoring
0 likes · 14 min read
Master Kibana: Install, Configure, and Visualize Elasticsearch Data
Tech Freedom Circle
Tech Freedom Circle
Sep 4, 2025 · Backend Development

How to Solve ES Latency in MySQL‑Canal Sync and Indexing Scenarios?

The article dissects the interview question about ES latency in a MySQL‑Canal‑to‑Elasticsearch pipeline, explains the root causes across four system layers, and presents a comprehensive four‑layer optimization, end‑to‑end observability, routing‑based degradation, and a Java‑based LatencyProbe component to measure and control delay.

CanalElasticsearchKafka
0 likes · 17 min read
How to Solve ES Latency in MySQL‑Canal Sync and Indexing Scenarios?
DataFunSummit
DataFunSummit
Sep 4, 2025 · Artificial Intelligence

Unlocking Elasticsearch Vector Search: From Basics to RAG Implementation

This article explores the evolving search demands of the intelligent era, explains dense and sparse vector concepts, details Elasticsearch's vector search capabilities and recent performance breakthroughs, introduces hybrid and relevance‑tuning techniques, and demonstrates RAG principles and real‑world enterprise use cases.

AIElasticsearchHybrid Search
0 likes · 14 min read
Unlocking Elasticsearch Vector Search: From Basics to RAG Implementation
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Aug 30, 2025 · Operations

INFINI Console FAQ: Enterprise‑Grade Unified Elasticsearch Management

The article introduces INFINI Console, an open‑source, lightweight platform for unified, multi‑cluster and cross‑version Elasticsearch governance, compares it with Kibana, details deployment options, enterprise‑level features such as monitoring, alerting and security, and analyzes cost advantages and practical migration scenarios.

Cluster ManagementCost OptimizationElasticsearch
0 likes · 13 min read
INFINI Console FAQ: Enterprise‑Grade Unified Elasticsearch Management