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Elasticsearch

1286 articles · Page 1 of 13
Java Architect Handbook
Java Architect Handbook
Sep 29, 2026 · Backend Development

DiDi Interview Deep-Dive: Solving Elasticsearch-MySQL Data Consistency

This article analyzes four patterns for keeping Elasticsearch synchronized with MySQL — synchronous dual-write, message-queue async, CDC via Canal/binlog, and scheduled reconciliation — explaining why CDC with version-based deduplication and periodic checksums is the production-grade choice for eventual consistency at scale.

CDCCanalElasticsearch
0 likes · 16 min read
DiDi Interview Deep-Dive: Solving Elasticsearch-MySQL Data Consistency
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Sep 24, 2026 · Artificial Intelligence

Alibaba Cloud Agentic Search: From Finding Answers to Completing Tasks

At the 2026 Yunqi Conference, Alibaba Cloud unveiled Agentic Search 2.0, a new AI search paradigm that evolves from answer generation to autonomous task execution via planning, tool use, and self-evolving memory, backed by a re-architected Elasticsearch engine delivering 60ms hot-query latency and 70% cost savings at hundred-billion-vector scale.

AI SearchAgentic SearchElasticsearch
0 likes · 13 min read
Alibaba Cloud Agentic Search: From Finding Answers to Completing Tasks
Xiaolin Talks Programming
Xiaolin Talks Programming
Sep 5, 2026 · Backend Development

Migrating Log Platform from Elasticsearch to ClickHouse: Table Design, Materialized Views & Tuning Lessons

The author details migrating a high-volume logging platform from Elasticsearch to ClickHouse, covering schema design with ReplicatedMergeTree, Spring Boot integration via JDBC and MyBatis, materialized views for pre-aggregation, and optimization techniques like skip indexes, batch inserts, and capacity planning.

ClickHouseElasticsearchKafka
0 likes · 21 min read
Migrating Log Platform from Elasticsearch to ClickHouse: Table Design, Materialized Views & Tuning Lessons
Java Architect Handbook
Java Architect Handbook
Sep 3, 2026 · Databases

Why ElasticSearch Is Blazing Fast: Inverted Indexes, FST, and Distributed Architecture Explained

This article breaks down ElasticSearch's performance advantages across three layers—data structures (inverted index, FST, compressed posting lists), storage (immutable segments, Doc Values), and architecture (shard parallelism, near-real-time writes, multi-level caching)—with concrete examples and interview-focused explanations.

CachingElasticsearchNear Real-Time
0 likes · 16 min read
Why ElasticSearch Is Blazing Fast: Inverted Indexes, FST, and Distributed Architecture Explained
IT Services Circle
IT Services Circle
Sep 3, 2026 · Backend Development

OpenSearch 3.0: Segment Replication, Read-Write Separation, and 9.5x Performance Boost

OpenSearch has evolved from an Elasticsearch fork into a Linux Foundation-governed Apache 2.0 platform with architectural innovations like segment replication and read-write separation, delivering 9.5x search performance gains in version 3.0, plus native GPU-accelerated vector indexing, hybrid search, and a growing ecosystem, making it a compelling alternative for license-sensitive, observability, and AI-driven search workloads.

Apache LuceneApache-2.0Elasticsearch
0 likes · 17 min read
OpenSearch 3.0: Segment Replication, Read-Write Separation, and 9.5x Performance Boost
Code Ape Tech Column
Code Ape Tech Column
Sep 3, 2026 · Databases

OpenSearch's Rise: 9.5x Faster Search, Read-Write Separation, and True Open Source

OpenSearch has evolved from an AWS fork of Elasticsearch into a Linux Foundation-hosted, Apache 2.0-licensed search platform with architectural innovations like segment replication, read-write separation, GPU-accelerated vector indexing, and native gRPC, delivering 9.5x query performance gains while offering full-stack free features and vendor-neutral governance.

Apache LuceneApache-2.0Elasticsearch
0 likes · 17 min read
OpenSearch's Rise: 9.5x Faster Search, Read-Write Separation, and True Open Source
Senior Tony
Senior Tony
Aug 31, 2026 · R&D Management

10 Core Competencies for High-Paid FDEs in AI Deployment

The article outlines ten critical capabilities required for Frontline Deployment Engineers (FDE) to successfully deliver AI projects, covering business research, problem breakdown, scenario judgment, solution design, rapid demo, data preparation, system integration, process orchestration, security governance, and impact review, emphasizing end-to-end delivery from vague requirements to measurable business value.

AI DeploymentAgentElasticsearch
0 likes · 10 min read
10 Core Competencies for High-Paid FDEs in AI Deployment
Java Architect Handbook
Java Architect Handbook
Aug 29, 2026 · Databases

Why Use ElasticSearch over MySQL? Key Differences for Interviews

The article explains why ElasticSearch excels at full‑text search and analytics while MySQL remains the reliable storage engine, compares their underlying data structures, outlines real‑time write behavior, lists scenarios where ES should not be used, and describes a production double‑store architecture with asynchronous sync.

B+ TreeElasticsearchMySQL
0 likes · 14 min read
Why Use ElasticSearch over MySQL? Key Differences for Interviews
Random Bulletin
Random Bulletin
Aug 27, 2026 · Operations

Scaling Log Indexing: From Full‑Index to Selective Strategies for Million‑QPS Systems

Full‑text log indexing inflates storage, CPU and mapping costs for 99% of queries that never run, so the article breaks down the five cost walls of full indexing at TB‑scale and presents four selective indexing paths—ES field reduction, Loki tag indexing, ClickHouse column‑store with skip indexes, and hot‑warm‑cold tiering—to pay only for high‑frequency queries.

ClickHouseElasticsearchLoki
0 likes · 19 min read
Scaling Log Indexing: From Full‑Index to Selective Strategies for Million‑QPS Systems
Code Farming
Code Farming
Aug 26, 2026 · Databases

Tencent's 4 Kernel Optimizations for Trillion-Scale Elasticsearch

Tencent shares four kernel-level Elasticsearch optimizations: memory-based smooth rate limiting to prevent cluster avalanches, Rollup pre-aggregation cutting storage costs 10x, moving FST off-heap to manage 50TB per node, and metadata scalability improvements supporting million shards with sub-5-second index creation.

ElasticsearchRollupTencent
0 likes · 7 min read
Tencent's 4 Kernel Optimizations for Trillion-Scale Elasticsearch
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Aug 26, 2026 · Artificial Intelligence

How Alibaba Cloud Elasticsearch’s Cloud‑Native Vector Engine Tops VectorDBBench

Alibaba Cloud Elasticsearch on ES 9.4, using the FalconSeek HNSW engine, achieves 82,520 QPS at 0.98 recall with a 1.8 ms P99 latency in VectorDBBench, and the article explains the end‑to‑end architectural redesign—including quantized candidate recall, batch distance computation, hot‑data layout, on‑demand re‑ranking, and segment lifecycle integration—that makes these results possible.

AI SearchCloud NativeElasticsearch
0 likes · 17 min read
How Alibaba Cloud Elasticsearch’s Cloud‑Native Vector Engine Tops VectorDBBench
Random Bulletin
Random Bulletin
Aug 24, 2026 · Operations

Scaling Log Volumes from GB to TB at Ten‑Million QPS: Cost‑Effective Strategies and Architecture

At ten‑million QPS, log data can explode from a few gigabytes to terabytes or even petabytes, triggering storage blow‑up, pipeline saturation, slow queries, runaway costs, and poor signal‑to‑noise, and the article breaks down ingest, index, and store costs while presenting edge sampling, label‑based indexing, tiered storage, and log‑to‑metric rollup as mitigation tactics.

ElasticsearchLokiObservability
0 likes · 19 min read
Scaling Log Volumes from GB to TB at Ten‑Million QPS: Cost‑Effective Strategies and Architecture
Random Bulletin
Random Bulletin
Aug 21, 2026 · Operations

Scaling Link Tracing Storage: From Centralized Elasticsearch to Tiered Architecture

The article analyzes why storing massive tracing spans in a single Elasticsearch cluster fails at high QPS, outlines the four key challenges of trace data, and presents a three‑step engineering solution—sampling, hot‑warm‑cold tiered storage, and separating indexes from span payloads—while comparing major back‑ends such as Elasticsearch, Cassandra, ClickHouse, and Tempo.

ClickHouseElasticsearchObservability
0 likes · 19 min read
Scaling Link Tracing Storage: From Centralized Elasticsearch to Tiered Architecture
DataFunSummit
DataFunSummit
Aug 21, 2026 · Artificial Intelligence

Turning Search into Action: How Elasticsearch Agent Builder Makes Data Come Alive

The article analyzes how AI applications evolve from answering questions to executing tasks, outlines the data, context, and execution challenges, and explains how Elasticsearch Agent Builder integrates searchable data, tool capabilities, and governance into a verifiable execution chain, illustrated with a log‑analysis case study.

AI agentsElasticsearchRAG
0 likes · 12 min read
Turning Search into Action: How Elasticsearch Agent Builder Makes Data Come Alive
CodeSmart Hoops
CodeSmart Hoops
Aug 16, 2026 · Interview Experience

Elasticsearch Interview Self-Test: 8 ELK Questions & Answers Explained

This guide provides eight comprehensive Elasticsearch interview questions covering inverted indexes, shard sizing, ILM lifecycle, dynamic templates, processing pipelines, query DSL, scaling strategies, and high‑availability deployment, each accompanied by detailed answers, code examples, and best‑practice recommendations for ELK stack professionals.

ELKElasticsearchFilebeat
0 likes · 25 min read
Elasticsearch Interview Self-Test: 8 ELK Questions & Answers Explained
CodeSmart Hoops
CodeSmart Hoops
Aug 11, 2026 · Operations

Scaling ELK from 1 GB to 1 TB Daily Logs: Full‑Stack Observability Guide

This comprehensive ELK tutorial walks through the journey of a company whose log volume grew from 1 GB to 1 TB per day, detailing the root causes of cluster failures and providing step‑by‑step guidance on index design, ILM policies, shard sizing, ingest pipelines, query optimization, high‑availability architecture, capacity planning, and security best practices.

ELKElasticsearchILM
0 likes · 35 min read
Scaling ELK from 1 GB to 1 TB Daily Logs: Full‑Stack Observability Guide
DataFunSummit
DataFunSummit
Aug 10, 2026 · Artificial Intelligence

How Elasticsearch 9.4 Powers Faster, More Accurate, Secure AI‑Agent Search

The article walks through the evolution of enterprise search from keyword‑based retrieval to Agentic AI, detailing Elasticsearch 9.4’s vector‑search optimizations, columnar metric engine, ES|QL pipeline, and Agent infrastructure, and shows benchmark‑backed speed and storage gains that make the platform a solid foundation for AI agents.

AI SearchAgent BuilderBBQ Quantization
0 likes · 15 min read
How Elasticsearch 9.4 Powers Faster, More Accurate, Secure AI‑Agent Search
ITPUB
ITPUB
Aug 9, 2026 · Big Data

Why a CK+Kafka+Filebeat Stack Beats ELK for Log Analytics

The article compares Elasticsearch and ClickHouse for log storage, analyzes cost and performance, and provides a step‑by‑step guide to deploying a Zookeeper‑Kafka‑Filebeat‑ClickHouse pipeline, including common pitfalls and their solutions, showing how the combo reduces server costs by up to half.

ClickHouseElasticsearchFilebeat
0 likes · 15 min read
Why a CK+Kafka+Filebeat Stack Beats ELK for Log Analytics
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Aug 7, 2026 · Backend Development

How to Turn Raw Text Data into an Interactive Searchable Dashboard in One Minute for Pre‑sales POCs

The article describes a fully automated pipeline that lets pre‑sales engineers upload a raw CSV/JSON sample, automatically infer mappings, mask sensitive fields, ingest data into Easysearch, generate a searchable, chart‑driven dashboard, and clean up the session with a single click, eliminating the tedious manual preparation that normally dominates POC demos.

Data IngestionEasysearchElasticsearch
0 likes · 14 min read
How to Turn Raw Text Data into an Interactive Searchable Dashboard in One Minute for Pre‑sales POCs
Cloud Architecture
Cloud Architecture
Aug 6, 2026 · Big Data

Exporting 10 Billion Elasticsearch Records: From Simple Script to Enterprise Offline Platform

The article analyses why exporting billions of Elasticsearch documents requires a full‑stack platform rather than a one‑off script, detailing the pitfalls of naive pagination, the benefits of PIT + search_after + slicing, and a complete architecture with Kafka, Redis, MySQL, Kubernetes and observability for reliable, scalable offline data export.

Data ExportElasticsearchJava
0 likes · 40 min read
Exporting 10 Billion Elasticsearch Records: From Simple Script to Enterprise Offline Platform
Code Farming
Code Farming
Jul 29, 2026 · Backend Development

Billions of Logs in Seconds: How Elasticsearch Makes It Possible

The article explains how Elasticsearch achieves sub‑second search over billions of log entries by combining sharding, immutable segment writes, a three‑layer inverted index, and a two‑phase query‑then‑fetch process that distributes work across nodes.

Distributed SearchElasticsearchinverted index
0 likes · 6 min read
Billions of Logs in Seconds: How Elasticsearch Makes It Possible
Top Architect
Top Architect
Jul 25, 2026 · Databases

Manticore Search: A High‑Performance Alternative That Could Overtake Elasticsearch

Manticore Search, a C++‑based open‑source search engine forked from Sphinx, claims to outperform Elasticsearch by up to 15× in various scenarios, offers modern multithreaded architecture, SQL compatibility, extensive client libraries, and easy Docker deployment, positioning itself as a fast, lightweight, full‑text search solution.

DockerElasticsearchManticore Search
0 likes · 8 min read
Manticore Search: A High‑Performance Alternative That Could Overtake Elasticsearch
Ops Community
Ops Community
Jul 24, 2026 · Operations

Comprehensive Filebeat Tuning Parameters to Reduce High Resource Usage

This guide walks through a systematic, evidence‑driven process for diagnosing and lowering Filebeat’s excessive CPU, memory, and file‑handle consumption—including version checks, process sampling, retry and queue analysis, registry handling, input configuration, parsing rules, queue sizing, output tuning, monitoring, and safe rollback procedures.

ConfigurationElasticsearchFilebeat
0 likes · 16 min read
Comprehensive Filebeat Tuning Parameters to Reduce High Resource Usage
Cloud Architecture
Cloud Architecture
Jul 17, 2026 · Backend Development

Elasticsearch Cluster: Inverted Index, Mechanics, Architecture for 100M+ Queries

This article provides a comprehensive, production‑grade guide to Elasticsearch clusters, covering the fundamentals of inverted indexes and Lucene segments, near‑real‑time write mechanics, shard routing, indexing pipelines, query execution flow, scaling strategies, and practical tips to avoid common pitfalls in high‑traffic search systems.

ElasticsearchJavaindexing
0 likes · 37 min read
Elasticsearch Cluster: Inverted Index, Mechanics, Architecture for 100M+ Queries
ITPUB
ITPUB
Jul 17, 2026 · Backend Development

Cutting 50 M‑record Deep Paging from 10 min to 1 s – 600× Faster with ES Search‑After & Redis

This article details how a photo‑contest backend migrated from MySQL to Elasticsearch and, through three rounds of optimization—including multi‑level Redis anchor caching, recent‑anchor positioning, and a large‑interval‑plus‑small‑page‑anchor strategy—reduced arbitrary deep‑page response time from ten minutes to about one second, achieving a 600‑fold speedup while exposing remaining data‑drift challenges.

CachingDeep PaginationElasticsearch
0 likes · 14 min read
Cutting 50 M‑record Deep Paging from 10 min to 1 s – 600× Faster with ES Search‑After & Redis
Niu Liu
Niu Liu
Jul 13, 2026 · Artificial Intelligence

Building a Real‑Time Recommendation Engine with Flink: A Complete Example Project

The article walks through constructing a full‑stack real‑time recommendation system—from user‑behavior collection via Kafka, through Flink streaming jobs for hot‑list, user and item profiling, to storage in Redis, HBase and Elasticsearch, and finally a React/Ant Design console that visualizes the pipeline and enables debugging.

ElasticsearchFlinkHBase
0 likes · 12 min read
Building a Real‑Time Recommendation Engine with Flink: A Complete Example Project
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Jul 11, 2026 · Backend Development

Elasticsearch Introduces True Columnar Mode: What It Means for Storage and Analytics

Elasticsearch adds a new Columnar Mode in the 9.5 tech preview and 9.6 GA, storing data once in a columnar layout with on‑demand indexing, which cuts storage costs, speeds analytical queries, keeps the existing document mode intact, and offers a migration path for append‑only log and security workloads.

Analytics QueriesColumnar ModeElasticsearch
0 likes · 6 min read
Elasticsearch Introduces True Columnar Mode: What It Means for Storage and Analytics
Architect Chen
Architect Chen
Jul 9, 2026 · Databases

Essential Elasticsearch Commands (2026 Edition)

This guide walks through the most important Elasticsearch commands, covering cluster health checks, index listing, creation with mappings, deletion, mapping inspection, document insertion (with and without IDs), various query types, updates, deletions, pagination, sorting, and bulk operations, each illustrated with concrete examples and usage notes.

ElasticsearchMappingbulk
0 likes · 5 min read
Essential Elasticsearch Commands (2026 Edition)
Cloud Architecture
Cloud Architecture
Jul 8, 2026 · Backend Development

High‑Concurrency Order System Architecture: How Redis, MySQL, and Elasticsearch Collaborate Without Overstepping

This article presents a production‑grade, high‑concurrency order system design that separates responsibilities among Redis for traffic control, MySQL as the single source of truth, Kafka for event propagation, and Elasticsearch for search, while detailing state‑machine modeling, outbox patterns, seckill flow, and comprehensive observability and deployment practices.

ElasticsearchMySQLOutbox
0 likes · 31 min read
High‑Concurrency Order System Architecture: How Redis, MySQL, and Elasticsearch Collaborate Without Overstepping
DataFunSummit
DataFunSummit
Jul 6, 2026 · Artificial Intelligence

From Text to Images: Building Multi‑Modal Product Search with Elasticsearch Serverless

The article explains how modern e‑commerce search is evolving from simple keyword matching to multi‑modal retrieval, outlines a generic architecture that combines text and image embeddings, describes vector similarity metrics and quantization techniques, and demonstrates how Elasticsearch Serverless and Alibaba Cloud AI Search Platform enable a low‑cost, fully managed end‑to‑end multi‑modal product search solution.

ElasticsearchMulti-modal SearchServerless
0 likes · 21 min read
From Text to Images: Building Multi‑Modal Product Search with Elasticsearch Serverless
Cloud Architecture
Cloud Architecture
Jul 5, 2026 · Databases

Production‑grade Elasticsearch: From Lucene Internals to Billion‑scale Search Architecture

This article explains why running Elasticsearch in production is far more complex than a simple API tutorial, covering Lucene fundamentals, mapping design, shard planning, write‑path architecture, query optimization, hot‑warm‑cold tiering, ILM policies, capacity planning, monitoring, incident handling, and a step‑by‑step evolution roadmap for building a reliable, scalable search system.

ElasticsearchIndex ModelingLucene
0 likes · 54 min read
Production‑grade Elasticsearch: From Lucene Internals to Billion‑scale Search Architecture
Java Tech Enthusiast
Java Tech Enthusiast
Jul 3, 2026 · Backend Development

Why RediSearch Can Outperform Elasticsearch: Low Memory, High Speed

The article introduces Redis's official search module RediSearch, compares its memory usage and query performance against Elasticsearch, presents benchmark results showing faster indexing and four‑times higher throughput, and provides step‑by‑step installation, index commands, and Java integration examples.

ElasticsearchJavaJedis
0 likes · 10 min read
Why RediSearch Can Outperform Elasticsearch: Low Memory, High Speed
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Jul 2, 2026 · Artificial Intelligence

AI Search + ES Agent Builder: Best Practices for Deploying Enterprise AI Assistants

This guide explains why enterprise data is hard for large language models, introduces ES Agent Builder as a solution, outlines three high‑value use cases, details the three‑layer architecture and four core components, and provides practical best‑practice recommendations with concrete examples and visualizations.

AI SearchAgent BuilderData Integration
0 likes · 15 min read
AI Search + ES Agent Builder: Best Practices for Deploying Enterprise AI Assistants
vivo Internet Technology
vivo Internet Technology
Jul 1, 2026 · Backend Development

From 10 Minutes to 1 Second: Three‑Stage Elasticsearch Deep‑Pagination Jump Optimization

This article details how a photo‑contest backend migrated from MySQL to Elasticsearch and, through three iterative optimizations—segment pre‑warming, recent‑anchor positioning with Redis ZSet, and a large‑region‑plus‑small‑page cache—reduced arbitrary deep‑page response time on 500 k records from ten minutes to under one second.

Deep PaginationElasticsearchPerformance Optimization
0 likes · 15 min read
From 10 Minutes to 1 Second: Three‑Stage Elasticsearch Deep‑Pagination Jump Optimization
Subtle Storm
Subtle Storm
Jun 30, 2026 · Databases

Elasticsearch vs Traditional Relational Databases: Core Differences and When to Use Each

The article contrasts Elasticsearch’s search‑oriented design—using inverted indexes, near‑real‑time BASE consistency, schema‑free JSON documents, and horizontal scaling—with relational databases’ precise row‑based storage, ACID guarantees, strict schemas, B+‑tree indexes, and vertical scaling, showing how they complement rather than compete.

ACIDElasticsearchRelational Database
0 likes · 5 min read
Elasticsearch vs Traditional Relational Databases: Core Differences and When to Use Each
Linyb Geek Road
Linyb Geek Road
Jun 30, 2026 · Databases

Implementing Efficient Pagination Across Sharded Databases

The article analyzes why traditional LIMIT/OFFSET pagination fails when data is split across multiple databases, presents a global query approach with its trade‑offs, and proposes an optimized "no‑skip" method plus practical tips using ShardingSphere and Elasticsearch.

ElasticsearchShardingSpheredatabase
0 likes · 7 min read
Implementing Efficient Pagination Across Sharded Databases
ITPUB
ITPUB
Jun 27, 2026 · Databases

Why Does Database Master‑Slave Replication Lag Every Day at 5‑7 AM?

The article investigates why master‑slave replication delay spikes each morning between 05:00 and 07:00, tracing it to the inventory‑snapshot worker that floods binlog traffic, evaluates five mitigation strategies, implements a big‑data extraction pipeline to Elasticsearch, and reports that the nightly delay disappeared and disk utilization improved.

BDPDatabase ReplicationElasticsearch
0 likes · 9 min read
Why Does Database Master‑Slave Replication Lag Every Day at 5‑7 AM?
DeepNoMind
DeepNoMind
Jun 27, 2026 · Backend Development

Designing a Production‑Grade Distributed Logging and Metrics Platform

This article presents an end‑to‑end design of a production‑grade observability platform that ingests millions of real‑time logs, metrics, and events, detailing functional and non‑functional requirements, capacity planning, component choices such as Kafka, Flink, Elasticsearch, object‑storage data lakes, and the trade‑offs involved.

Data LakeElasticsearchFlink
0 likes · 21 min read
Designing a Production‑Grade Distributed Logging and Metrics Platform
DataFunSummit
DataFunSummit
Jun 25, 2026 · Cloud Computing

From Text to Images: Building Multi‑Modal Product Search with Elasticsearch Serverless

The article walks through the evolution of e‑commerce search from simple keyword matching to multi‑modal retrieval, explains a generic architecture that fuses text and image embeddings, details core techniques such as dense, sparse and hybrid models, vector similarity metrics, quantization methods like SQ and BBQ, and demonstrates how Elasticsearch Serverless provides a server‑less, cost‑effective platform to implement the end‑to‑end solution.

AIElasticsearchMulti-modal Search
0 likes · 21 min read
From Text to Images: Building Multi‑Modal Product Search with Elasticsearch Serverless
Xiaolin Talks Programming
Xiaolin Talks Programming
Jun 25, 2026 · Backend Development

Building a Production-Grade Search Engine with Spring Boot & Elasticsearch

This article details how to replace MySQL complex queries with Elasticsearch in production, covering data sync via Canal/Kafka, mapping design with IK analyzer, Spring Data ES query builders, deep pagination with Search After, and consistency guarantees through reconciliation and dead-letter queues.

Consistency PatternsDeep PaginationElasticsearch
0 likes · 21 min read
Building a Production-Grade Search Engine with Spring Boot & Elasticsearch
Mingyi World Elasticsearch
Mingyi World Elasticsearch
Jun 24, 2026 · Databases

How Two Mapping Tweaks Cut Easysearch Index Size by One‑Third

A storage audit of an Easysearch cluster revealed that overly generic field mappings caused the index to bloat to 500‑600 GB, and by correcting two mapping mistakes—using text + autocomplete only where needed and storing numeric IDs as long types—the index size shrank by over 200 GB, roughly one‑third, without data loss or functional changes.

Dynamic TemplatesEasysearchElasticsearch
0 likes · 10 min read
How Two Mapping Tweaks Cut Easysearch Index Size by One‑Third
dbaplus Community
dbaplus Community
Jun 21, 2026 · Databases

Why Master‑Slave Replication Lags 5‑7 AM and How a Big‑Data Snapshot Fixes It

The article analyzes why the master‑slave database replication experiences 30‑minute delays each morning between 5 AM and 7 AM, traces the cause to massive inventory‑snapshot jobs, evaluates several mitigation options, and details a big‑data extraction workflow that eliminates the lag while reducing disk usage.

Database ReplicationElasticsearchHive
0 likes · 8 min read
Why Master‑Slave Replication Lags 5‑7 AM and How a Big‑Data Snapshot Fixes It
Architect Chen
Architect Chen
Jun 20, 2026 · Databases

Comprehensive ElasticSearch Command Guide (2026 Edition)

This article provides a step‑by‑step reference of essential ElasticSearch REST commands—including cluster health checks, node information, index management, document CRUD operations, and various search queries with examples and expected responses—helping practitioners efficiently manage and troubleshoot large ElasticSearch deployments.

AggregationDocument CRUDElasticsearch
0 likes · 5 min read
Comprehensive ElasticSearch Command Guide (2026 Edition)
Architect Chen
Architect Chen
Jun 13, 2026 · Databases

Essential ElasticSearch Commands (2026 Edition)

This guide walks through the most common ElasticSearch commands, covering cluster health checks, index management, document CRUD operations, mapping inspection, full‑text and filtered searches, aggregations, and bulk inserts, while explaining each step with concrete examples and performance tips.

Elasticsearchbulkcluster health
0 likes · 6 min read
Essential ElasticSearch Commands (2026 Edition)
Qunar Tech Salon
Qunar Tech Salon
Jun 9, 2026 · Operations

Mastering Elasticsearch Shard Management: From Fundamentals to 100k‑Shard Scale

This article explains Elasticsearch shard fundamentals, primary and replica roles, allocation rules, recovery and rebalance mechanisms, tuning parameters, best‑practice sizing, and presents real‑world production cases—including a 100,000‑shard cluster—along with concrete API commands for effective shard operations.

Cluster OperationsElasticsearchShard Management
0 likes · 28 min read
Mastering Elasticsearch Shard Management: From Fundamentals to 100k‑Shard Scale
DataFunSummit
DataFunSummit
Jun 8, 2026 · Artificial Intelligence

Agent Architecture in Action: Building Next‑Gen Recommendation and Search Systems

The article reviews cutting‑edge technical practices for next‑generation recommendation and search, covering Alibaba Cloud AI Search's Agentic RAG multi‑agent design, Huawei Noah's LLM‑enhanced recommendation evolution, Baidu's generative ranking (GRAB) for ads, and Elasticsearch‑based vector RAG implementations, with concrete architecture details and performance results.

AI SearchAgentic RAGElasticsearch
0 likes · 6 min read
Agent Architecture in Action: Building Next‑Gen Recommendation and Search Systems
Su San Talks Tech
Su San Talks Tech
Jun 8, 2026 · Backend Development

Building an Enterprise Log MCP: A Hands‑On Guide

The article explains why AI alone cannot reliably analyze logs, proposes wrapping an enterprise Loki or Elasticsearch log system with a custom MCP that separates discovery and query layers, discusses transport and authentication choices, provides complete Python implementation, and shares three production lessons to ensure safe, scalable log querying.

AI-assisted debuggingElasticsearchLogQL
0 likes · 24 min read
Building an Enterprise Log MCP: A Hands‑On Guide
Spring Full-Stack Practical Cases
Spring Full-Stack Practical Cases
Jun 2, 2026 · Big Data

Millisecond‑Level Real‑Time Sync from MySQL to Elasticsearch with Flink CDC

This guide walks through setting up a Spring Boot 3.5 environment, configuring Flink 1.20 and Flink CDC 3.5, preparing MySQL tables, and using both the Flink CDC CLI and SQL client to achieve near‑millisecond synchronization of data from MySQL to Elasticsearch, including custom sink programming and real‑time monitoring via the Flink Web UI.

Apache FlinkElasticsearchFlink CDC
0 likes · 14 min read
Millisecond‑Level Real‑Time Sync from MySQL to Elasticsearch with Flink CDC
Mingyi World Elasticsearch
Mingyi World Elasticsearch
May 31, 2026 · Operations

How to Collect Easysearch Logs with Filebeat OSS: A Step‑by‑Step Guide

This guide walks through selecting Filebeat OSS 7.10.2, preparing Ubuntu 20.04, uploading and extracting the package, configuring filebeat.yml for Easysearch log paths, creating an index template, starting Filebeat, verifying data ingestion, and applying production‑grade recommendations such as systemd service setup and ILM policies.

EasysearchElasticsearchFilebeat
0 likes · 11 min read
How to Collect Easysearch Logs with Filebeat OSS: A Step‑by‑Step Guide
Mingyi World Elasticsearch
Mingyi World Elasticsearch
May 31, 2026 · Operations

Automating Easysearch Cluster Alerts and Root‑Cause Analysis with AIOps – Full Implementation Guide

This article walks through a practical AIOps solution that replaces brittle keyword rules for Easysearch Elasticsearch clusters with a three‑step pipeline—Filebeat log ingestion, Flask‑driven LLM analysis, and automated email alerts plus ES feedback—detailing configuration, code, pitfalls, and suitability.

AIOpsDeepSeekElasticsearch
0 likes · 12 min read
Automating Easysearch Cluster Alerts and Root‑Cause Analysis with AIOps – Full Implementation Guide
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
May 27, 2026 · Artificial Intelligence

Building a Multimodal Search with Alibaba Cloud Elasticsearch and Qwen‑VL

This article demonstrates how to integrate Alibaba Cloud Elasticsearch with the Qwen‑VL large model and DashScope Embedding API to extract image features and perform multimodal vector search, covering text‑to‑image, text‑to‑text, image‑to‑image, and image‑to‑text queries, with step‑by‑step code, environment setup, data loading, indexing, and a Streamlit demo.

AI EmbeddingDashScopeElasticsearch
0 likes · 8 min read
Building a Multimodal Search with Alibaba Cloud Elasticsearch and Qwen‑VL
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
May 22, 2026 · Artificial Intelligence

Step-by-Step Guide to Building AI Assistants with Alibaba Cloud Elasticsearch Agent Builder

This article introduces Elastic Agent Builder on Alibaba Cloud, outlines the required Elasticsearch version, walks through creating an agent and AI connector in Kibana, configures model details and API keys, and demonstrates using natural‑language queries to analyze API logs with generated ES|QL statements.

AI assistantAgent BuilderConnector
0 likes · 8 min read
Step-by-Step Guide to Building AI Assistants with Alibaba Cloud Elasticsearch Agent Builder
Cloud Architecture
Cloud Architecture
May 21, 2026 · Information Security

Production-Ready Elasticsearch Security Hardening: TLS, Authentication, and High‑Concurrency Architecture with INFINI Gateway

This guide walks through why Elasticsearch should sit behind a gateway, compares native security with INFINI Gateway, presents a layered security model, and provides concrete configuration, Kubernetes deployment, high‑availability, high‑concurrency, and observability patterns to turn a runnable setup into a production‑grade, continuously‑evolvable Elasticsearch security solution.

AuthenticationElasticsearchINFINI Gateway
0 likes · 30 min read
Production-Ready Elasticsearch Security Hardening: TLS, Authentication, and High‑Concurrency Architecture with INFINI Gateway
DataFunSummit
DataFunSummit
May 21, 2026 · Artificial Intelligence

Designing Next‑Gen Recommendation and Search with Intelligent Agent Architecture

The article reviews a collection of technical chapters that analyze how multi‑agent AI architectures, large‑language‑model‑enhanced recommendation pipelines, generative ranking for ads, and Elasticsearch‑based vector RAG are applied to build next‑generation recommendation and search systems, citing concrete designs, performance numbers and real‑world deployments.

AI agentsElasticsearchGenerative Ranking
0 likes · 6 min read
Designing Next‑Gen Recommendation and Search with Intelligent Agent Architecture
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
Cloud Architecture
Cloud Architecture
May 16, 2026 · Databases

MySQL 8.x Large Pagination Guide: From OFFSET Performance Pitfalls to Production‑Ready Cursor Pagination

This article explains why deep OFFSET pagination in MySQL 8.x forces the database to scan, sort and discard massive rows, outlines four categories of pagination bottlenecks, and presents a step‑by‑step engineering roadmap—including covering indexes, delayed joins, cursor pagination, Elasticsearch integration, API contracts, and production‑grade Spring Boot/MyBatis code—to eliminate the performance black‑hole and build a scalable pagination architecture.

CursorElasticsearchMySQL
0 likes · 35 min read
MySQL 8.x Large Pagination Guide: From OFFSET Performance Pitfalls to Production‑Ready Cursor Pagination
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 SearchElasticsearchServerless
0 likes · 20 min read
From Text to Images: Building Multimodal Product Search with Elasticsearch Serverless
Cloud Architecture
Cloud Architecture
May 13, 2026 · Backend Development

Mastering Spring Boot Data Access: From ORM and Caching to Search and Distributed Consistency

This extensive guide redesigns Spring Boot data‑access for high‑traffic e‑commerce, explaining why traditional JPA‑Redis‑Elasticsearch thinking fails, then detailing a multimodal architecture that assigns strong‑consistency, hot‑read, document, and search responsibilities to MySQL, Redis, MongoDB and Elasticsearch, with production‑grade code, CDC pipelines, distributed‑transaction patterns, caching strategies, observability, and cloud‑native deployment.

CDCCachingDistributed Transactions
0 likes · 49 min read
Mastering Spring Boot Data Access: From ORM and Caching to Search and Distributed Consistency
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
Cloud Architecture
Cloud Architecture
May 11, 2026 · Operations

3 Billion Products, 500 Million Daily Queries: How I Boosted a Failing Elasticsearch Cluster 5×

A large‑scale e‑commerce search system handling 3 billion product documents and 500 million daily queries was on the brink of collapse, but a systematic overhaul across query modeling, index design, write pipelines, cluster topology, and application‑level governance lifted throughput five‑fold while cutting P99 latency from 3.2 seconds to 180 ms.

ElasticsearchJavabulk processing
0 likes · 30 min read
3 Billion Products, 500 Million Daily Queries: How I Boosted a Failing Elasticsearch Cluster 5×
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 SearchElasticsearchServerless
0 likes · 22 min read
From Text to Images: Building Multimodal Product Search with Elasticsearch Serverless
Cloud Architecture
Cloud Architecture
May 3, 2026 · Big Data

Cutting Log Storage Costs 70% for 100 Billion Daily Logs: A Full Guide to Hot‑Cold Separation Architecture

This article explains why massive log systems must adopt hot‑cold separation, walks through the problem analysis, SLO definition, component design, Kafka partition planning, Elasticsearch and ClickHouse tuning, Parquet archiving, a unified query gateway with async cold queries, governance practices, cost modeling, common pitfalls, and a roadmap for evolving the platform.

ElasticsearchKafkaLog Storage
0 likes · 40 min read
Cutting Log Storage Costs 70% for 100 Billion Daily Logs: A Full Guide to Hot‑Cold Separation Architecture
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
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.

Data SkewElasticsearchbackend architecture
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 ArchitectureCloud Computing
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.

ElasticStackElasticsearchMCP
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.

AIElasticsearchServerless
0 likes · 20 min read
How to Build a Multimodal Product Search Engine with Embedding and Vector Retrieval on Elasticsearch Serverless
Java Tech Workshop
Java Tech Workshop
Apr 5, 2026 · Backend Development

Spring Boot + Elasticsearch: Full‑Text Search Integration Guide

This article walks through integrating Spring Boot with Elasticsearch to enable fuzzy search, keyword highlighting, tokenized queries, and real‑time data sync, covering environment setup, Maven dependencies, application.yml configuration, entity annotations, CRUD via Repository, advanced queries with RestTemplate, IK analyzer usage, common pitfalls, and synchronization strategies.

ElasticsearchIK analyzerRepository
0 likes · 10 min read
Spring Boot + Elasticsearch: Full‑Text Search Integration Guide
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.

AIElasticsearchVector Retrieval
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.

C++ElasticsearchIngest 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 platformElasticsearchHNSW
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.

EasysearchElasticsearchaudit log
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-EncoderElasticsearchMilvus
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.

ElasticsearchMySQLPersistence
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