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Big Data Technology & Architecture
Big Data Technology & Architecture
Aug 7, 2021 · Big Data

Elasticsearch Optimization Practices and Performance Tuning Guide

This article presents a comprehensive guide on optimizing Elasticsearch for large‑scale data platforms, covering Lucene fundamentals, index and shard architecture, doc‑values usage, routing strategies, practical performance‑tuning techniques, and real‑world testing results to achieve sub‑second query responses on billions of records.

ElasticsearchIndex OptimizationPerformance tuning
0 likes · 12 min read
Elasticsearch Optimization Practices and Performance Tuning Guide
Architect
Architect
Aug 6, 2021 · Backend Development

Design of a High‑Throughput Messaging Center Architecture

This article outlines a backend messaging center architecture that targets 10,000 messages per second inbound via RocketMQ, 1,000 messages per second outbound to third‑party platforms, and ensures 100% high availability using Spring Cloud Gateway, Kubernetes, Elasticsearch, and related technologies.

DevOpsElasticsearchKubernetes
0 likes · 5 min read
Design of a High‑Throughput Messaging Center Architecture
Big Data Technology Architecture
Big Data Technology Architecture
Jul 27, 2021 · Big Data

Key Components of the Big Data Ecosystem: Hadoop, Hive, HBase, Spark, Kafka, and Elasticsearch

This article introduces the most important and still mainstream components of the big data ecosystem—including Hadoop’s storage and compute framework, Hive data warehouse, HBase NoSQL database, Spark unified engine, Kafka messaging platform, and Elasticsearch search engine—explaining their core concepts, architectures, and typical use cases.

Big DataElasticsearchHBase
0 likes · 9 min read
Key Components of the Big Data Ecosystem: Hadoop, Hive, HBase, Spark, Kafka, and Elasticsearch
Java Interview Crash Guide
Java Interview Crash Guide
Jul 21, 2021 · Big Data

Why ClickHouse Outperforms Elasticsearch in Log Search: A Practical Benchmark

This article compares Elasticsearch and ClickHouse for log analytics, detailing their architectures, presenting a Docker‑Compose test setup that streams synthetic syslog data to both stacks, executing equivalent queries, measuring response times, and concluding that ClickHouse generally delivers faster performance, especially for aggregations.

ClickHouseElasticsearchLog Analytics
0 likes · 10 min read
Why ClickHouse Outperforms Elasticsearch in Log Search: A Practical Benchmark
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Jul 19, 2021 · Backend Development

Technical Architecture of an E‑commerce Coupon System

This article explains the complete technical design of an e‑commerce coupon system, covering data models, product‑page exposure, coupon claiming rules, high‑concurrency caching, MQ‑driven expiration handling, order‑time coupon calculation, redemption flow, and search‑based coupon indexing.

CouponElasticsearche‑commerce
0 likes · 10 min read
Technical Architecture of an E‑commerce Coupon System
Baidu Geek Talk
Baidu Geek Talk
Jul 19, 2021 · Backend Development

How Baidu Scales Sensitive Word Detection to Tens of Millions with a Trie‑Based Service

This article explains the design and evolution of Baidu's word‑list service for content moderation, covering its background, multi‑layer architecture, management platform, strategy loading, matching workflow, performance optimizations for large texts, and future enhancements such as special‑character support and per‑business‑line deployment.

BOSBackend ArchitectureElasticsearch
0 likes · 16 min read
How Baidu Scales Sensitive Word Detection to Tens of Millions with a Trie‑Based Service
Java High-Performance Architecture
Java High-Performance Architecture
Jul 13, 2021 · Databases

Elasticsearch vs ClickHouse: Which Delivers Faster Log Search?

This article compares Elasticsearch and ClickHouse for log analytics, detailing their architectures, node roles, query capabilities, and performance through Docker‑Compose stacks and synthetic syslog data, concluding that ClickHouse generally outperforms Elasticsearch in speed and aggregation efficiency.

ClickHouseColumnar DatabaseElasticsearch
0 likes · 11 min read
Elasticsearch vs ClickHouse: Which Delivers Faster Log Search?
Architecture Digest
Architecture Digest
Jul 11, 2021 · Big Data

Performance Comparison of Elasticsearch and ClickHouse for Log Analytics

This article compares Elasticsearch and ClickHouse as log analytics solutions, detailing their architectures, deployment configurations, query capabilities, and performance benchmarks across various query types, and demonstrates that ClickHouse generally outperforms Elasticsearch in speed and aggregation efficiency.

ClickHouseDocker-ComposeElasticsearch
0 likes · 13 min read
Performance Comparison of Elasticsearch and ClickHouse for Log Analytics
dbaplus Community
dbaplus Community
Jul 8, 2021 · Databases

Why ClickHouse Outperforms Elasticsearch for Log Storage and Analytics

This article compares ClickHouse and Elasticsearch for API log storage, detailing development activity, schema handling, query performance, statistical functions, MySQL integration, new features, and practical drawbacks, while providing concrete SQL examples and migration tips.

AnalyticsClickHouseElasticsearch
0 likes · 14 min read
Why ClickHouse Outperforms Elasticsearch for Log Storage and Analytics
MaGe Linux Operations
MaGe Linux Operations
Jul 4, 2021 · Databases

Why MySQL Queries Slow Down and How ES & HBase Can Help Optimize

This article explores common causes of MySQL slow queries such as index misuse and lock contention, explains indexing strategies like index pushdown and covering indexes, and then compares Elasticsearch and HBase as complementary solutions for large‑scale search and write‑intensive workloads, offering practical tips for performance optimization.

ElasticsearchHBaseMySQL
0 likes · 19 min read
Why MySQL Queries Slow Down and How ES & HBase Can Help Optimize
Java High-Performance Architecture
Java High-Performance Architecture
Jul 3, 2021 · Backend Development

Building a High‑Throughput, Highly Available Messaging Center with RocketMQ & Elasticsearch

This article outlines the technical, business, and product goals for a messaging center, presents a prototype and functional requirements, evaluates RocketMQ and Elasticsearch as core technologies, and details the architectural design, underlying frameworks, and DevOps strategies—including Spring Cloud Gateway, Kubernetes, and Docker—to achieve 10,000 msg/s upstream throughput, 1,000 msg/s downstream delivery, and 100 % high availability.

ElasticsearchKubernetesMessaging System
0 likes · 5 min read
Building a High‑Throughput, Highly Available Messaging Center with RocketMQ & Elasticsearch
Java Interview Crash Guide
Java Interview Crash Guide
Jul 2, 2021 · Databases

How Elasticsearch Achieves Lightning‑Fast Search with Inverted Indexes

This article explains how Elasticsearch leverages inverted indexes, term dictionaries, and advanced compression techniques like Frame of Reference and Roaring Bitmaps to enable rapid full‑text search, covering the underlying concepts, data structures, and query optimizations essential for high‑performance search applications.

ElasticsearchPostings Listcompression
0 likes · 17 min read
How Elasticsearch Achieves Lightning‑Fast Search with Inverted Indexes
Selected Java Interview Questions
Selected Java Interview Questions
Jul 1, 2021 · Fundamentals

Understanding Elasticsearch Inverted Index: Posting Lists, Term Dictionary, and Compression Techniques

This article explains how Elasticsearch achieves fast search by using inverted indexes, detailing the structure of posting lists, term dictionaries, term indexes, and compression methods such as Frame of Reference and Roaring Bitmaps, as well as techniques for efficient union and intersection queries.

ElasticsearchPostings ListTerm Dictionary
0 likes · 16 min read
Understanding Elasticsearch Inverted Index: Posting Lists, Term Dictionary, and Compression Techniques
Programmer DD
Programmer DD
Jul 1, 2021 · Operations

Why Loki Beats Elasticsearch: Low Index Overhead, Fast Queries, and Easy Setup

This article explains Loki's advantages over Elasticsearch, including low indexing overhead, concurrent query processing with caching, seamless integration with Prometheus and Grafana, detailed architecture components, installation steps, label handling, high‑cardinality challenges, and best practices for efficient log management.

ElasticsearchGrafanaLoki
0 likes · 15 min read
Why Loki Beats Elasticsearch: Low Index Overhead, Fast Queries, and Easy Setup
DataFunTalk
DataFunTalk
Jun 26, 2021 · Big Data

Building a Scalable Big Data Service System at Didi: Practices and Lessons

Zhang Liang shares Didi's four-stage journey of constructing and governing large‑scale open‑source big‑data engine services—including engine selection, hardware sizing, PaaS platform building, proxy architecture, and governance—highlighting practical challenges, solutions, and ROI‑driven best practices for Kafka, Elasticsearch, Flink, and related technologies.

Big DataData InfrastructureElasticsearch
0 likes · 16 min read
Building a Scalable Big Data Service System at Didi: Practices and Lessons
Efficient Ops
Efficient Ops
Jun 23, 2021 · Backend Development

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

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

ElasticsearchFull-Text Searchinverted index
0 likes · 13 min read
Why Can’t Elasticsearch Find My Logs? Uncovering Full‑Text Search Pitfalls and Tokenizer Tweaks
dbaplus Community
dbaplus Community
Jun 6, 2021 · Big Data

How to Build Near‑Real‑Time Elasticsearch Indexes for PB‑Scale Data

This article explains why traditional databases like MySQL struggle with petabyte‑scale queries, introduces Elasticsearch’s architecture and inverted‑index advantages, and details a practical pipeline using Hive, Canal, Otter, and a custom DTS service to achieve near‑real‑time indexing for massive data volumes.

CanalElasticsearchMySQL
0 likes · 19 min read
How to Build Near‑Real‑Time Elasticsearch Indexes for PB‑Scale Data
Java High-Performance Architecture
Java High-Performance Architecture
Jun 4, 2021 · Operations

How JD.com Scaled Its Order Search with a Real-Time Dual Elasticsearch Cluster

JD.com’s order center faced massive query loads, prompting a migration from MySQL to Elasticsearch and a multi-stage evolution of its ES cluster—from a chaotic initial setup to isolated nodes, replica tuning, master‑slave dual clusters, and real‑time backup—culminating in a robust, high‑throughput, fault‑tolerant search architecture.

ElasticsearchJD.comdata synchronization
0 likes · 14 min read
How JD.com Scaled Its Order Search with a Real-Time Dual Elasticsearch Cluster
IT Architects Alliance
IT Architects Alliance
May 26, 2021 · Databases

Understanding MySQL Slow Queries, Elasticsearch, and HBase: Causes and Practical Solutions

This article explains why MySQL queries become slow, how indexes work and fail, the impact of MDL locks, large‑table challenges, sharding and read‑write splitting strategies, then introduces Elasticsearch’s search capabilities and HBase’s column‑family storage, offering practical guidance for each technology.

Database PerformanceElasticsearchHBase
0 likes · 17 min read
Understanding MySQL Slow Queries, Elasticsearch, and HBase: Causes and Practical Solutions
Wukong Talks Architecture
Wukong Talks Architecture
May 25, 2021 · Backend Development

Elasticsearch Performance Pitfalls and Optimization Strategies

This article examines common performance pitfalls in Elasticsearch—including slow queries, cluster architecture bottlenecks, and business‑scenario challenges—and provides practical guidance such as caching key fields, data pre‑heating, hot‑cold separation, avoiding joins, and using tribe nodes to improve accuracy and response time.

CachingClusterElasticsearch
0 likes · 9 min read
Elasticsearch Performance Pitfalls and Optimization Strategies
DataFunTalk
DataFunTalk
May 22, 2021 · Databases

Combining HBase and Elasticsearch: Challenges and the Lindorm Searchindex Solution

The article examines the strengths and weaknesses of combining HBase and Elasticsearch for massive data storage and retrieval, outlines three integration patterns and their challenges, and presents Alibaba Cloud's Lindorm Searchindex as a SQL‑driven, low‑cost, strongly consistent solution that simplifies development and improves performance.

Big DataElasticsearchHBase
0 likes · 11 min read
Combining HBase and Elasticsearch: Challenges and the Lindorm Searchindex Solution
Java High-Performance Architecture
Java High-Performance Architecture
May 22, 2021 · Backend Development

Boost Elasticsearch Query Speed: Simple Queries & OS Cache Tricks

This article explains how Elasticsearch processes queries across shards, identifies two key performance bottlenecks—query computation time and segment file I/O—and offers practical optimization strategies such as simplifying query logic, maximizing OS file cache usage, increasing memory, reducing stored data, and applying hot‑cold data separation.

ElasticsearchFile CacheI/O
0 likes · 7 min read
Boost Elasticsearch Query Speed: Simple Queries & OS Cache Tricks
Java Interview Crash Guide
Java Interview Crash Guide
May 21, 2021 · Backend Development

Mastering Elasticsearch: Core Concepts, Indexing, and Real‑Time Search Explained

This comprehensive guide walks through Elasticsearch fundamentals, including its architecture, core concepts like indices, shards, and replicas, the write and update processes, search workflow, consistency mechanisms, master election, performance tuning, and strategies for deep pagination and scroll searches.

Elasticsearchindexingreal-time search
0 likes · 17 min read
Mastering Elasticsearch: Core Concepts, Indexing, and Real‑Time Search Explained
Dada Group Technology
Dada Group Technology
May 21, 2021 · Backend Development

Implementing Data Heterogeneity for JD Daojia Order Fulfillment: Architecture, Canal Integration, and Lessons Learned

This article examines JD Daojia's order fulfillment system, detailing the challenges of high‑volume prompt‑sound queries, the division of responsibilities among Redis, MySQL, and Elasticsearch, the adoption of Canal for asynchronous data replication, deployment practices with Kafka and Zookeeper, and the key operational lessons learned.

Backend ArchitectureCanalElasticsearch
0 likes · 14 min read
Implementing Data Heterogeneity for JD Daojia Order Fulfillment: Architecture, Canal Integration, and Lessons Learned
Code Ape Tech Column
Code Ape Tech Column
May 21, 2021 · Databases

Why Your MySQL Queries Are Slow and How ElasticSearch & HBase Can Help

This article analyzes common causes of slow MySQL queries such as index misuse, MDL locks, and large‑table bottlenecks, then presents practical solutions like proper indexing, sharding, read/write splitting, and evaluates when to complement MySQL with ElasticSearch or HBase for better performance.

Database PerformanceElasticsearchHBase
0 likes · 19 min read
Why Your MySQL Queries Are Slow and How ElasticSearch & HBase Can Help
Java Tech Enthusiast
Java Tech Enthusiast
May 18, 2021 · Backend Development

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

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

Advanced QueriesElasticsearchInstallation
0 likes · 18 min read
Master ElasticSearch: Install, Index, and Run Advanced Java Queries
dbaplus Community
dbaplus Community
May 17, 2021 · Databases

How Migrating from Elasticsearch to MongoDB Cut Costs 10‑Fold and Boosted Latency

This article presents a detailed case study of moving a 2‑petabyte smart‑product data workload from Elasticsearch to MongoDB, covering business background, source cluster architecture, MongoDB design and resource planning, step‑by‑step performance optimizations, latency and cost comparisons, and guidance on when each database is appropriate.

Database ArchitectureElasticsearchMongoDB
0 likes · 21 min read
How Migrating from Elasticsearch to MongoDB Cut Costs 10‑Fold and Boosted Latency
MaGe Linux Operations
MaGe Linux Operations
May 14, 2021 · Big Data

Build a Billion-Scale ELK Logging Platform with Filebeat, Kafka, Elasticsearch

This guide walks through the complete architecture and step‑by‑step deployment of a billion‑scale ELK logging system, covering Filebeat agents, Kafka buffering, Logstash processing, Elasticsearch indexing, and Kibana visualization, including configuration files, version details, and best‑practice tips for scaling and security.

ELKElasticsearchFilebeat
0 likes · 12 min read
Build a Billion-Scale ELK Logging Platform with Filebeat, Kafka, Elasticsearch
dbaplus Community
dbaplus Community
May 10, 2021 · Backend Development

How JD.com’s Order Fulfillment Scales: Data Heterogeneity & Complexity‑Driven Architecture

This talk explains JD.com’s order‑fulfillment workflow, the underlying storage stack of Redis, MySQL and Elasticsearch, the challenges of high‑traffic alert‑sound queries, the adoption of Canal for data heterogeneity, and a 4R‑based complexity‑oriented design methodology for building resilient backend systems.

Backend ArchitectureCanalElasticsearch
0 likes · 18 min read
How JD.com’s Order Fulfillment Scales: Data Heterogeneity & Complexity‑Driven Architecture
Big Data Technology Architecture
Big Data Technology Architecture
May 6, 2021 · Databases

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

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

ElasticsearchSearchbackend
0 likes · 13 min read
Elasticsearch Pagination: From+size, search_after, and Scroll – Differences, Advantages, and Use Cases
IT Architects Alliance
IT Architects Alliance
May 1, 2021 · Big Data

Comprehensive Guide to ELK Stack (Elasticsearch, Logstash, Kibana) Installation, Configuration, and Architecture

This article provides a detailed overview of the ELK stack—including Elasticsearch, Logstash, Kibana, and Beats—explaining its components, why to use it for centralized log management, various deployment architectures, system tuning, security setup, and step‑by‑step installation and configuration commands for a production‑grade environment.

Big DataELKElasticsearch
0 likes · 22 min read
Comprehensive Guide to ELK Stack (Elasticsearch, Logstash, Kibana) Installation, Configuration, and Architecture
dbaplus Community
dbaplus Community
Apr 29, 2021 · Operations

How 58.com Scaled Elasticsearch: Cluster Optimization, Automation, and Real‑World Practices

This article details 58.com’s journey with Elasticsearch, covering the challenges of disparate deployments, common problems like disk exhaustion and write slowdown, the governance and automation platform they built, development standards, service architecture, real‑world application cases, and future plans for version upgrades and intelligent diagnostics.

Cluster ManagementElasticsearchIndex Lifecycle
0 likes · 19 min read
How 58.com Scaled Elasticsearch: Cluster Optimization, Automation, and Real‑World Practices
Architect
Architect
Apr 29, 2021 · Big Data

ELK Stack (Elasticsearch, Logstash, Kibana) Overview, Architecture, Installation, and Configuration Guide (Version 7.7.0)

This article provides a comprehensive introduction to the ELK stack—including component descriptions, architectural diagrams, reasons for adoption, and step‑by‑step installation and configuration of Filebeat, Logstash, Elasticsearch, and Kibana on Linux, with optional Kafka integration for advanced pipelines.

Big DataELKElasticsearch
0 likes · 22 min read
ELK Stack (Elasticsearch, Logstash, Kibana) Overview, Architecture, Installation, and Configuration Guide (Version 7.7.0)
IT Architects Alliance
IT Architects Alliance
Apr 20, 2021 · Big Data

Real-time Log Processing System Based on Flink and Drools

This article describes a real-time log processing platform that integrates Kafka, Flink, Drools rule engine, Redis, and Elasticsearch to unify heterogeneous log formats, extract business metrics, and provide configurable, dynamic data processing for large‑scale logging scenarios.

DroolsElasticsearchFlink
0 likes · 6 min read
Real-time Log Processing System Based on Flink and Drools
Huolala Tech
Huolala Tech
Apr 16, 2021 · Cloud Native

How to Build a Scalable Kubernetes Logging Pipeline with EFK and Fluentd

This article explains how to collect, process, and visualize Flink job logs on Kubernetes using an EFK stack with Fluentd, covering logging architectures, deployment of Elasticsearch, Kibana, and Fluentd, and the backend logic for querying and displaying logs in a feature platform.

EFKElasticsearchFlink
0 likes · 20 min read
How to Build a Scalable Kubernetes Logging Pipeline with EFK and Fluentd
JD Retail Technology
JD Retail Technology
Apr 15, 2021 · Backend Development

How We Scaled JD’s UGC Platform with Elasticsearch: A Backend Architecture Deep Dive

This case study details how JD’s "Browse" UGC project evolved from rapid agile delivery to a performance bottleneck as data grew, and how introducing Elasticsearch, redesigning the query flow, and refactoring storage components restored fast, flexible searches for both front‑end and operations users.

Backend ArchitectureElasticsearchJD UGC Platform
0 likes · 9 min read
How We Scaled JD’s UGC Platform with Elasticsearch: A Backend Architecture Deep Dive
Programmer DD
Programmer DD
Apr 14, 2021 · Databases

AWS Launches OpenSearch: A True Open‑Source Alternative to Elasticsearch

AWS introduced OpenSearch, an Apache‑licensed, fully open‑source fork of Elasticsearch and Kibana that removes commercial restrictions, offers advanced features like security and machine‑learning, and promises seamless migration for existing users while gaining broad industry support.

ElasticsearchOpenSearchOpenSource
0 likes · 5 min read
AWS Launches OpenSearch: A True Open‑Source Alternative to Elasticsearch
Wukong Talks Architecture
Wukong Talks Architecture
Apr 8, 2021 · Backend Development

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

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

ElasticsearchFull-Text SearchJava
0 likes · 21 min read
Integrating Elasticsearch with Spring Boot for Full‑Text Search in a Microservice Architecture
Architecture Digest
Architecture Digest
Apr 6, 2021 · Backend Development

Integrating Spring Boot with Elasticsearch Using Java API

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

ElasticsearchJavaREST API
0 likes · 18 min read
Integrating Spring Boot with Elasticsearch Using Java API
Wukong Talks Architecture
Wukong Talks Architecture
Mar 31, 2021 · Backend Development

How to Install and Use the IK Chinese Analyzer Plugin in Elasticsearch

This article explains why Elasticsearch's built‑in tokenizers struggle with Chinese text, introduces the IK analyzer plugin, provides step‑by‑step Docker and file‑based installation methods, shows how to configure custom dictionaries via Nginx, and demonstrates smart and max‑word tokenization queries.

Chinese TokenizationCustom DictionaryDocker
0 likes · 12 min read
How to Install and Use the IK Chinese Analyzer Plugin in Elasticsearch
HelloTech
HelloTech
Mar 26, 2021 · Big Data

Data Quality and Interface Semantic Monitoring for Algorithm Testing Platform

The article describes how algorithm testing teams tackled data‑quality and interface‑semantic monitoring problems by building a unified business monitoring platform that checks table, storage and service consistency, validates response semantics, and, through dashboards, alerts and correction tools, quickly identified dozens of offline and online issues, guiding future reliability enhancements.

AIBig DataElasticsearch
0 likes · 26 min read
Data Quality and Interface Semantic Monitoring for Algorithm Testing Platform
Wukong Talks Architecture
Wukong Talks Architecture
Mar 23, 2021 · Databases

MongoDB vs MySQL: Interview Insights on NoSQL, Relational Databases, and Search Engines

This article shares an interview experience that compares MongoDB and MySQL, explains the advantages and disadvantages of document‑oriented and relational databases, introduces other NoSQL solutions such as Elasticsearch, and offers guidance on choosing the right storage technology based on workload characteristics.

ElasticsearchMongoDBMySQL
0 likes · 13 min read
MongoDB vs MySQL: Interview Insights on NoSQL, Relational Databases, and Search Engines
MaGe Linux Operations
MaGe Linux Operations
Mar 20, 2021 · Backend Development

Mastering Elasticsearch Distributed Search: Performance Tips & Pagination Strategies

This article examines Elasticsearch’s distributed search architecture, explains the two‑phase query and fetch process, identifies performance and relevance scoring challenges, and presents optimization techniques such as Search After with point‑in‑time, Scroll API usage, and DFS query‑then‑fetch for accurate scoring.

Distributed SearchElasticsearchPerformance Optimization
0 likes · 9 min read
Mastering Elasticsearch Distributed Search: Performance Tips & Pagination Strategies
ITPUB
ITPUB
Mar 12, 2021 · Backend Development

How to Sync MySQL Data to Elasticsearch in Real-Time Using Binlog and Kafka

This article explains how a growing e‑commerce platform replaced a heavyweight MySQL intermediate table with a binlog‑driven pipeline that streams changes to Elasticsearch via Kafka, detailing the architecture, modules, customizations, monitoring, and performance results.

ElasticsearchKafkaMySQL
0 likes · 13 min read
How to Sync MySQL Data to Elasticsearch in Real-Time Using Binlog and Kafka
Open Source Linux
Open Source Linux
Mar 11, 2021 · Operations

Master Filebeat 7.7: What It Is, How It Works, and How to Deploy It

This article explains Filebeat's role as a lightweight log shipper, its relationship to the Beats family, internal architecture, installation steps, configuration of inputs, outputs, keystore usage, module activation, and practical examples for sending logs to Logstash or Elasticsearch.

BeatsElasticsearchFilebeat
0 likes · 19 min read
Master Filebeat 7.7: What It Is, How It Works, and How to Deploy It
Sohu Tech Products
Sohu Tech Products
Mar 10, 2021 · Databases

Elasticsearch Deployment Best Practices: Memory, CPU, Sharding, Replicas, Hot/Warm Architecture, Node Roles, Monitoring and Troubleshooting

This article presents practical best‑practice guidelines for configuring Elasticsearch in production, covering heap memory sizing, CPU considerations, shard and replica planning, hot‑warm node architecture, node role settings, common pitfalls, monitoring APIs, and troubleshooting tips.

Cluster TuningElasticsearchNode Roles
0 likes · 15 min read
Elasticsearch Deployment Best Practices: Memory, CPU, Sharding, Replicas, Hot/Warm Architecture, Node Roles, Monitoring and Troubleshooting
Top Architect
Top Architect
Mar 5, 2021 · Big Data

Elasticsearch Indexing and Search Optimization: Principles, Lucene Internals, and Performance Tuning

This article explains the architecture and core concepts of Elasticsearch and Lucene, outlines the requirements for cross‑month and high‑speed queries on massive datasets, and provides detailed index and search performance tuning techniques—including bulk writes, shard routing, doc‑values management, and pagination strategies—to achieve sub‑second response times on billions of records.

Big DataElasticsearchIndex Optimization
0 likes · 13 min read
Elasticsearch Indexing and Search Optimization: Principles, Lucene Internals, and Performance Tuning
dbaplus Community
dbaplus Community
Feb 24, 2021 · Operations

Building ESPaaS: Real‑Time Elasticsearch Monitoring and Alerting at Scale

Zhongtong’s ESPaaS platform automates deployment, unified monitoring, real‑time alerting, and diagnostic analysis for over 40 Elasticsearch clusters, leveraging custom exporters, Prometheus, Grafana, and DingTalk integrations to track resource, cluster, and node metrics, reduce noise, and prevent production incidents.

ElasticsearchGrafanadiagnostics
0 likes · 9 min read
Building ESPaaS: Real‑Time Elasticsearch Monitoring and Alerting at Scale
Big Data Technology & Architecture
Big Data Technology & Architecture
Feb 24, 2021 · Big Data

Gairos: Uber’s Real‑Time Data Processing, Storage and Query Platform and Its Scalability Optimizations

The article describes Uber’s Gairos platform—a unified real‑time data ingestion, storage, and query system built on Kafka, Elasticsearch and RT‑Gairos—detailing its architecture, Uber use cases such as dynamic pricing, the scalability and reliability challenges faced, and the suite of optimization techniques (sharding, query routing, caching, index merging, template tuning, and data‑pruning) applied to achieve low latency and high throughput.

ElasticsearchShardingUber
0 likes · 26 min read
Gairos: Uber’s Real‑Time Data Processing, Storage and Query Platform and Its Scalability Optimizations
MaGe Linux Operations
MaGe Linux Operations
Feb 20, 2021 · Operations

Master Filebeat 7.7: From Basics to Advanced Log Shipping

This guide explains what Filebeat is, how it fits into the Beats ecosystem, its architecture and processing flow, installation steps, key configuration options, keystore usage, and practical examples of sending logs to Logstash or Elasticsearch, helping you set up reliable log collection on Linux.

ElasticsearchFilebeatLinux
0 likes · 20 min read
Master Filebeat 7.7: From Basics to Advanced Log Shipping
Architecture Digest
Architecture Digest
Feb 18, 2021 · Big Data

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

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

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

Elasticsearch Optimization Practices for Large-Scale Data Queries

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

Big DataElasticsearchOptimization
0 likes · 14 min read
Elasticsearch Optimization Practices for Large-Scale Data Queries
Architecture Digest
Architecture Digest
Feb 15, 2021 · Operations

ELK Stack Overview, Architecture, Installation and Configuration Guide (Version 7.7.0)

This article provides a comprehensive introduction to the ELK stack—Elasticsearch, Logstash, Kibana, and Filebeat—including its components, why it’s used for centralized log management, detailed architecture diagrams, step‑by‑step installation commands, configuration examples, and a practical Kafka‑based data pipeline demonstration.

Big DataELKElasticsearch
0 likes · 22 min read
ELK Stack Overview, Architecture, Installation and Configuration Guide (Version 7.7.0)
21CTO
21CTO
Feb 6, 2021 · Backend Development

From a Cooking App to Elasticsearch: The Story Behind the Search Engine

This article recounts how Shay Banon’s early cooking‑app project led to the creation of Compass, the evolution into Elasticsearch, and the pivotal role of Apache Lucene, distributed testing, and visionary design in building today’s powerful search platform.

Apache LuceneDistributed TestingElasticsearch
0 likes · 9 min read
From a Cooking App to Elasticsearch: The Story Behind the Search Engine
Top Architect
Top Architect
Feb 1, 2021 · Big Data

Kibana Tutorial: Installation, Configuration, and Usage Guide

This guide provides a comprehensive walkthrough of Kibana, covering installation, connection to Elasticsearch, data discovery, query syntax, visualizations, dashboards, and monitoring, with step‑by‑step instructions and screenshots to help users effectively explore and visualize their Elasticsearch data.

Data visualizationElasticsearchKibana
0 likes · 12 min read
Kibana Tutorial: Installation, Configuration, and Usage Guide
Programmer DD
Programmer DD
Jan 28, 2021 · Databases

How Elasticsearch Writes, Reads, and Searches Data: Inside the Engine

This article explains Elasticsearch's internal mechanisms for writing, reading, and searching data, covering the roles of coordinating nodes, primary and replica shards, buffers, translog, segment files, refresh cycles, commit and flush operations, as well as Lucene's inverted index and how deletions and updates are handled.

ElasticsearchSegmentinverted index
0 likes · 10 min read
How Elasticsearch Writes, Reads, and Searches Data: Inside the Engine
Architect's Journey
Architect's Journey
Jan 26, 2021 · Backend Development

Three Storage Solutions for Cross-Database Aggregated Full-Text Search

The article compares three approaches—synchronous dual write, asynchronous dual write with a message queue, and CDC via Canal—to keep Elasticsearch and a relational database consistent for cross‑database aggregated full‑text search, outlining their steps, advantages, and drawbacks.

Backend ArchitectureCDCData Consistency
0 likes · 6 min read
Three Storage Solutions for Cross-Database Aggregated Full-Text Search
Programmer DD
Programmer DD
Jan 25, 2021 · Cloud Computing

Why Is AWS Forking Elasticsearch After Elastic’s License Shift?

The article explains Elastic's switch to SSPL/Elastic License for Elasticsearch and Kibana, Logz.io's criticism, AWS's fork under Apache 2.0, and the broader open‑source licensing battle between cloud providers and the original vendor.

Cloud ServicesElasticsearchaws
0 likes · 4 min read
Why Is AWS Forking Elasticsearch After Elastic’s License Shift?
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Jan 9, 2021 · Big Data

Performance Optimization of Elasticsearch in an ELK Log Architecture

This article summarizes a year‑long performance tuning of an ELK logging system, analyzing bottlenecks such as write thread pool saturation, JVM heap and GC settings, refresh intervals, translog durability, merge threads, shard and replica counts, and provides concrete configuration changes that reduced latency, eliminated data loss, and stabilized node resource usage.

ELKElasticsearchJVM
0 likes · 20 min read
Performance Optimization of Elasticsearch in an ELK Log Architecture
Java Interview Crash Guide
Java Interview Crash Guide
Jan 9, 2021 · Databases

Master Elasticsearch Performance: Practical Tuning Tips for Faster Clusters

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

Cluster OptimizationElasticsearchScalability
0 likes · 18 min read
Master Elasticsearch Performance: Practical Tuning Tips for Faster Clusters
MaGe Linux Operations
MaGe Linux Operations
Dec 28, 2020 · Backend Development

Mastering Elasticsearch: Core Concepts and Indexing Workflow Explained

This article introduces Elasticsearch’s core concepts—including clusters, node roles, documents, mappings, and shards—and walks through the complete indexing workflow from client request to replica synchronization, highlighting key settings, routing calculations, and the role of refresh and flush operations.

Backend DevelopmentClusterDistributed Systems
0 likes · 13 min read
Mastering Elasticsearch: Core Concepts and Indexing Workflow Explained
Programmer DD
Programmer DD
Dec 28, 2020 · Operations

How to Install and Use Cerebro for Easy Elasticsearch Cluster Management

This guide explains what Cerebro is, how to install it (including binary and Docker options), how to run it on Linux, macOS, and Windows, and how to use its UI to connect to an Elasticsearch node, view cluster overviews, manage shards, and execute DSL queries.

AngularJSCerebroCluster Management
0 likes · 5 min read
How to Install and Use Cerebro for Easy Elasticsearch Cluster Management
vivo Internet Technology
vivo Internet Technology
Dec 23, 2020 · Backend Development

How Vivo Scaled Its Order System: Sharding, Migration, and Real‑World Lessons

This article details how Vivo transformed its monolithic e‑commerce order service into a scalable, service‑oriented system by applying data archiving, sharding‑JDBC based sharding, MySQL‑to‑Elasticsearch sync, zero‑downtime migration, and distributed‑transaction techniques, while sharing practical pitfalls and performance results.

Distributed SystemsElasticsearchMySQL
0 likes · 17 min read
How Vivo Scaled Its Order System: Sharding, Migration, and Real‑World Lessons
Tencent Cloud Developer
Tencent Cloud Developer
Dec 18, 2020 · Cloud Computing

Multi-AZ Deployment and High Availability Practices for Tencent Cloud Elasticsearch

The guide explains how to configure Tencent Cloud Elasticsearch clusters for multi‑AZ high availability by using zone‑aware node attributes, deploying data nodes in multiples of AZs, assigning three dedicated masters across zones, setting replica shards and force‑awareness rules, and safely upgrading single‑AZ clusters without service interruption.

Cloud ComputingCluster DeploymentElasticsearch
0 likes · 11 min read
Multi-AZ Deployment and High Availability Practices for Tencent Cloud Elasticsearch
Efficient Ops
Efficient Ops
Dec 16, 2020 · Operations

Build a Secure, Scalable ELK + Kafka Logging Architecture on CentOS

This step‑by‑step guide shows how to deploy a production‑grade log collection pipeline by installing Filebeat on log sources, forwarding logs to a hardened Kafka cluster, processing them with Logstash, storing them in an Elasticsearch 7.2.0 cluster secured with X‑Pack, and visualizing the data in Kibana, all on CentOS 7.6 with detailed security hardening, configuration scripts, and verification commands.

ELKElasticsearchFilebeat
0 likes · 29 min read
Build a Secure, Scalable ELK + Kafka Logging Architecture on CentOS
Big Data Technology & Architecture
Big Data Technology & Architecture
Dec 13, 2020 · Big Data

Elasticsearch Write, Read, Search Processes and Performance Tuning Guide

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

Cluster ConfigurationElasticsearchPerformance tuning
0 likes · 20 min read
Elasticsearch Write, Read, Search Processes and Performance Tuning Guide
DeWu Technology
DeWu Technology
Dec 11, 2020 · Big Data

Data Synchronization from MySQL to Elasticsearch using DataX and Canal

The article explains how to improve query performance by flattening multi‑table MySQL data and synchronizing it to Elasticsearch—using DataX for one‑time bulk loading and Canal (with Canal‑Adapter) for real‑time binlog‑driven incremental updates—while detailing configuration steps, job examples, and common pitfalls.

CanalDataXETL
0 likes · 14 min read
Data Synchronization from MySQL to Elasticsearch using DataX and Canal
Programmer DD
Programmer DD
Dec 9, 2020 · Operations

Step-by-Step Guide to Installing Apache SkyWalking with Elasticsearch and InfluxDB

This tutorial walks through installing and configuring Apache SkyWalking, an open‑source APM system for micro‑services and cloud‑native environments, covering its architecture, Elasticsearch and InfluxDB storage setup, agent deployment, service startup, alarm integration, and essential documentation links.

APMDockerElasticsearch
0 likes · 12 min read
Step-by-Step Guide to Installing Apache SkyWalking with Elasticsearch and InfluxDB
Tencent Cloud Developer
Tencent Cloud Developer
Dec 7, 2020 · Big Data

Searchable Snapshots in Elasticsearch 7.10: Features, Usage, and Future Outlook

Elasticsearch 7.10 adds searchable snapshots, letting users query indices stored directly in remote repositories such as S3 or COS, which halves storage costs, decouples storage from compute, supports manual mounting and ILM cold‑phase policies, and promises future full storage‑compute separation without local caching.

Big DataData TieringElasticsearch
0 likes · 12 min read
Searchable Snapshots in Elasticsearch 7.10: Features, Usage, and Future Outlook