HBase | BestHub

Code Ape Tech Column

Oct 21, 2024 · Big Data

Design and Optimization of Querying 100k Records from Tens of Millions Using ClickHouse, Elasticsearch, HBase, and RediSearch

This article presents a business-driven requirement to extract no more than 100,000 records from a pool of tens of millions, evaluates four technical solutions—including multithreaded ClickHouse pagination, Elasticsearch scroll‑scan, an ES‑HBase hybrid, and RediSearch + RedisJSON—provides implementation details, performance measurements, and practical recommendations for large‑scale data querying.

Big DataClickHouseElasticsearch

0 likes · 11 min read

Design and Optimization of Querying 100k Records from Tens of Millions Using ClickHouse, Elasticsearch, HBase, and RediSearch

Efficient Ops

Oct 13, 2024 · Databases

Why Your MySQL Queries Are Slow and How to Fix Them with Indexes, ES & HBase

This article explains why MySQL queries become slow—covering index misuse, MDL locks, flush waits, large‑table bottlenecks, and read/write splitting—then shows how ElasticSearch’s inverted index and HBase’s column‑family design can complement MySQL for faster search and scalable storage.

Database OptimizationElasticsearchHBase

0 likes · 20 min read

Why Your MySQL Queries Are Slow and How to Fix Them with Indexes, ES & HBase

Wukong Talks Architecture

Sep 23, 2024 · Backend Development

Evolution of the Ctrip Travel Product Log System: Architecture, Challenges, and Solutions

This article describes the development trajectory of Ctrip's travel product log system, detailing its three major phases—from a single‑table DB approach to a platform‑based solution and finally an empowered version—while discussing technical challenges, design decisions, and the implementation of HBase, Elasticsearch, and related components to handle billions of log entries efficiently.

BackendBig DataElasticsearch

0 likes · 15 min read

Evolution of the Ctrip Travel Product Log System: Architecture, Challenges, and Solutions

DaTaobao Tech

Sep 20, 2024 · Databases

Database Technology Evolution: From Hierarchical to Vector Databases

The article chronicles the evolution of database technology from early hierarchical and network models through relational, column‑store, document, key‑value, graph, time‑series, HTAP, and finally vector databases, detailing each system’s architecture, strengths, limitations, typical uses, and future trends toward specialization, distributed cloud‑native designs, and AI‑driven applications.

HBaseHTAPInfluxDB

0 likes · 52 min read

Database Technology Evolution: From Hierarchical to Vector Databases

High Availability Architecture

Sep 11, 2024 · Backend Development

Evolution of Ctrip Vacation Product Log System: From Single‑Table DB to ES + HBase Platform

This article details the evolution of Ctrip's vacation product log system—from a simple single‑table DB in 2019, through a platformized ES + HBase architecture with custom RowKey design, to a V3.0 version that adds business and supplier empowerment, scalable storage, advanced search, and flexible data presentation for billions of daily change records.

BackendESHBase

0 likes · 13 min read

Evolution of Ctrip Vacation Product Log System: From Single‑Table DB to ES + HBase Platform

Ctrip Technology

Aug 22, 2024 · Backend Development

Evolution of Ctrip Vacation Product Log System: From Single‑Table DB to ES + HBase Platform

This article details the three‑stage evolution of Ctrip's vacation product log system—from a simple single‑table DB approach, through a platform‑based ES + HBase solution, to a scalable V3.0 architecture that improves storage, search, and business empowerment while handling billions of log entries.

BackendBig DataElasticsearch

0 likes · 16 min read

Architect

Aug 13, 2024 · Databases

Optimizing HBase for a Large‑Scale Content Platform: Selection, Performance Tuning, and Best Practices

This article examines why the unified content platform switched from MongoDB to HBase, outlines HBase’s high‑performance, scalability, and consistency features, and details four optimization techniques—including cluster upgrade, connection pooling, column‑read strategy, and compaction tuning—that significantly improved read/write latency and operational stability.

Big DataDatabase OptimizationHBase

0 likes · 15 min read

Optimizing HBase for a Large‑Scale Content Platform: Selection, Performance Tuning, and Best Practices

360 Zhihui Cloud Developer

Aug 8, 2024 · Big Data

How to Migrate HBase and HDFS Clusters Safely Without Downtime

This guide details a step‑by‑step migration plan for HBase and HDFS clusters, covering background, high‑availability architecture, role assignments, expansion and shrinkage of ZooKeeper and JournalNode, NameNode and DataNode migration, rolling restarts, and common upgrade pitfalls.

Big DataCluster MigrationHBase

0 likes · 12 min read

How to Migrate HBase and HDFS Clusters Safely Without Downtime

58 Tech

Jul 29, 2024 · Databases

HBase Cloud Migration: Architecture, Challenges, and Solutions

This technical report details the background, architecture, construction, core issues, migration plans, and future roadmap of moving 58's HBase clusters to a cloud‑native environment, highlighting cost reduction, operational automation, and performance optimizations.

Big DataHBasecloud migration

0 likes · 22 min read

HBase Cloud Migration: Architecture, Challenges, and Solutions

JD Tech Talk

Jul 17, 2024 · Databases

A Comprehensive Guide to 9 Database Types and Polyglot Persistence

This article provides an in‑depth overview of nine major database categories—including relational, key‑value, columnar, document, graph, time‑series, and vector databases—detailing their strengths, weaknesses, best practices, and typical application scenarios, and explains how polyglot persistence combines multiple databases for optimal performance and scalability.

ClickHouseElasticsearchHBase

0 likes · 41 min read

A Comprehensive Guide to 9 Database Types and Polyglot Persistence

JD Tech

Jul 15, 2024 · Databases

A Comprehensive Overview of Nine Database Types and Polyglot Persistence Practices

This article provides an in‑depth survey of nine database categories—including relational, key‑value, columnar, document, graph, time‑series, and vector databases—detailing their architectures, advantages, disadvantages, best‑practice recommendations, typical use cases, and how they can be combined in polyglot persistence solutions.

ClickHouseDatabase TypesElasticsearch

0 likes · 41 min read

A Comprehensive Overview of Nine Database Types and Polyglot Persistence Practices

vivo Internet Technology

Jul 10, 2024 · Databases

HBase Optimization Practice in Vivo's Unified Content Platform

Vivo's unified content platform replaced its unwieldy 60 TB MongoDB store with HBase, then upgraded the cluster, introduced table‑specific connection pools, column‑only reads, tuned compaction, and leveraged multi‑version cells, cutting response times from seconds to under ten milliseconds and dramatically lowering operational costs while boosting read/write performance.

Compaction OptimizationDatabase OptimizationDistributed Database

0 likes · 16 min read

HBase Optimization Practice in Vivo's Unified Content Platform

vivo Internet Technology

May 8, 2024 · Databases

Troubleshooting and Repairing HBase Meta Table Issues

The article explains how HBase’s meta table stores region metadata, outlines common failures such as slow startup, RIT, region holes and overlaps, and provides step‑by‑step online and offline repair procedures—including command‑line tools and configuration tweaks—for both HBase 1.x and 2.x clusters.

HBCKHBaseMeta Table

0 likes · 20 min read

Troubleshooting and Repairing HBase Meta Table Issues

vivo Internet Technology

Jan 24, 2024 · Big Data

Evolution of Vivo's Trillions-Scale Data Architecture: Dual-Active Real-Time and Offline Computing

Vivo’s trillion‑scale data platform evolved into a dual‑active real‑time and offline architecture that leverages multi‑datacenter clusters, Kafka/Pulsar caching, a unified sorting layer, HBase‑backed dimension tables, and micro‑batch Spark jobs to deliver low‑cost, high‑performance processing, 99.9% availability, and 99.9995% data‑integrity.

Big DataData IntegrityHBase

0 likes · 16 min read

Evolution of Vivo's Trillions-Scale Data Architecture: Dual-Active Real-Time and Offline Computing

Sohu Tech Products

Aug 16, 2023 · Big Data

Understanding HBase Compaction: Principles, Process, Throttling Strategies and Real‑World Optimizations

This article explains HBase’s LSM‑Tree compaction fundamentals—including minor and major compaction triggers, file‑selection policies, dynamic throughput throttling, and practical tuning examples that show how adjusting size limits, thread pools, and off‑peak settings can dramatically improve read latency and cluster stability.

Big DataCompactionHBase

0 likes · 35 min read

Understanding HBase Compaction: Principles, Process, Throttling Strategies and Real‑World Optimizations

vivo Internet Technology

Jul 26, 2023 · Big Data

Understanding HBase Compaction: Principles, Process, Throttling Strategies, and Optimization Cases

Understanding HBase compaction involves knowing its minor and major merge types, trigger mechanisms, file‑selection policies such as RatioBased and Exploring, throttling controls based on file count, and practical tuning of key parameters to avoid latency spikes, as illustrated by real‑world production cases.

Big DataCompactionHBase

0 likes · 36 min read

Understanding HBase Compaction: Principles, Process, Throttling Strategies, and Optimization Cases

Selected Java Interview Questions

Mar 12, 2023 · Big Data

Design and Optimization of Querying 100K Records from Tens of Millions of Data Using ClickHouse, Elasticsearch, HBase, and RediSearch

This article presents a comprehensive design and performance‑optimization study for extracting up to 100 000 records from a pool of tens of millions, comparing multithreaded ClickHouse pagination, Elasticsearch scroll‑scan, ES + HBase, and RediSearch + RedisJSON solutions, and provides practical recommendations based on measured latency and throughput.

Big DataClickHouseElasticsearch

0 likes · 11 min read

Design and Optimization of Querying 100K Records from Tens of Millions of Data Using ClickHouse, Elasticsearch, HBase, and RediSearch

DataFunTalk

Feb 18, 2023 · Big Data

Xiaomi Data Governance Evolution: Cost Governance Practices for HDFS and HBase

The article outlines Xiaomi's data governance journey, focusing on storage‑service cost governance, describing the transition from simple cost‑centered governance to big‑data‑driven asset management, and detailing concrete HDFS and HBase practices that achieved significant resource and cost reductions.

Big DataCost OptimizationHBase

0 likes · 15 min read

Xiaomi Data Governance Evolution: Cost Governance Practices for HDFS and HBase

Java Architect Essentials

Jan 31, 2023 · Big Data

Optimizing Large-Scale Data Retrieval: ClickHouse Pagination, Elasticsearch Scroll Scan, ES+HBase, and RediSearch + RedisJSON Solutions

This article examines a business requirement to filter and rank up to 100,000 records from a pool of tens of millions, presenting and evaluating four technical solutions—multithreaded ClickHouse pagination, Elasticsearch scroll‑scan deep paging, an ES‑HBase combined query, and a RediSearch + RedisJSON approach—along with performance data and code examples.

BigDataClickHouseElasticsearch

0 likes · 12 min read

Optimizing Large-Scale Data Retrieval: ClickHouse Pagination, Elasticsearch Scroll Scan, ES+HBase, and RediSearch + RedisJSON Solutions

Selected Java Interview Questions

Dec 29, 2022 · Backend Development

Optimizing Large‑Scale Data Retrieval with ClickHouse, Elasticsearch Scroll Scan, ES+HBase, and RediSearch+RedisJSON

This article examines a business requirement to filter up to 100 000 records from a pool of tens of millions, presenting and evaluating four backend solutions—multithreaded ClickHouse pagination, Elasticsearch scroll‑scan, an ES‑HBase hybrid, and RediSearch + RedisJSON—along with performance data and implementation details.

BackendClickHouseData Retrieval

0 likes · 11 min read

Optimizing Large‑Scale Data Retrieval with ClickHouse, Elasticsearch Scroll Scan, ES+HBase, and RediSearch+RedisJSON