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Scheduling

253 articles · Page 2 of 3
Architecture Digest
Architecture Digest
Oct 16, 2023 · Backend Development

Comparison of Delayed Task Implementation Strategies in Java: Database Polling, JDK DelayQueue, Time Wheel, Redis, and RabbitMQ

The article examines various delayed‑task solutions for order timeout handling in Java, including database polling with Quartz, JDK DelayQueue, Netty's HashedWheelTimer, Redis sorted‑set and key‑space notifications, and RabbitMQ delayed queues, analyzing their implementation steps, advantages, and drawbacks.

Delayed TasksRedisScheduling
0 likes · 18 min read
Comparison of Delayed Task Implementation Strategies in Java: Database Polling, JDK DelayQueue, Time Wheel, Redis, and RabbitMQ
vivo Internet Technology
vivo Internet Technology
Sep 6, 2023 · Cloud Native

Multi-Cluster Management in Kubernetes: Concepts, Practices, and Karmada Exploration

The article explains why enterprises adopt multi‑cluster Kubernetes architectures, reviews community solutions such as Karmada, Clusternet and OCM, and details vivo’s hybrid strategy that combines a unified UI for independent clusters with Karmada‑based federation for resource distribution, elastic scaling, cross‑cluster scheduling, and gray‑release migration.

KarmadaKubernetesMulti-Cluster
0 likes · 20 min read
Multi-Cluster Management in Kubernetes: Concepts, Practices, and Karmada Exploration
Python Programming Learning Circle
Python Programming Learning Circle
Aug 14, 2023 · Backend Development

Common Python Scheduling Techniques and Tools

This article reviews multiple ways to implement periodic tasks in Python, covering simple loops with sleep, libraries such as Timeloop, threading.Timer, sched, schedule, the APScheduler framework, as well as distributed solutions like Celery and Apache Airflow, and provides code examples for each method.

APSchedulerAirflowCron
0 likes · 23 min read
Common Python Scheduling Techniques and Tools
Volcano Engine Developer Services
Volcano Engine Developer Services
Jul 7, 2023 · Cloud Native

How KubeAdmiral Redefines Multi-Cluster Kubernetes Federation for Scale and Efficiency

Since Kubernetes became the de‑facto standard, ByteDance faced scaling limits with single‑cluster setups, prompting the adoption of KubeFed V2 and later the development of KubeAdmiral, a next‑generation multi‑cluster federation system that enhances scheduling, resource efficiency, native API support, and dynamic scaling across clouds.

FederationKubeAdmiralKubernetes
0 likes · 15 min read
How KubeAdmiral Redefines Multi-Cluster Kubernetes Federation for Scale and Efficiency
Ant R&D Efficiency
Ant R&D Efficiency
Jun 26, 2023 · Cloud Native

Serverless Function Compute for Mini Programs: Architecture, Security, and Performance Optimizations

Alipay’s serverless Function Compute platform empowers mini‑program developers with a four‑stage architecture—mini program, Alipay app, gateway, and function—offering automatic elastic scaling, sub‑20 ms scheduling, sub‑100 ms cold‑starts, multi‑layer isolation, DDoS protection, and the ability to sustain 10 k QPS for reliable, low‑latency user experiences.

Cloud NativeFunction ComputeMini Program
0 likes · 18 min read
Serverless Function Compute for Mini Programs: Architecture, Security, and Performance Optimizations
Snowball Engineer Team
Snowball Engineer Team
May 19, 2023 · Backend Development

Design and Implementation of a Rule Engine for Content Risk Control

This article details the design, architecture, and practical deployment of a scalable rule engine that separates logic from data, supports high‑concurrency execution, provides a visual DSL for business users, and enables rapid risk‑control strategy adjustments with improved performance and maintainability.

FeatureSchedulingrisk control
0 likes · 22 min read
Design and Implementation of a Rule Engine for Content Risk Control
Cloud Native Technology Community
Cloud Native Technology Community
May 17, 2023 · Cloud Native

Why Do You Need Kubernetes Multi‑Cluster? Core Challenges and Design Principles

This article explains the motivations behind Kubernetes multi‑cluster deployments, outlines common use cases such as isolation and high‑availability, and analyzes core management elements including deployment models, control‑plane architectures, network connectivity, service discovery, cross‑cluster scheduling, application model extensions, and treating clusters as resources.

Cloud NativeCluster ManagementKubernetes
0 likes · 23 min read
Why Do You Need Kubernetes Multi‑Cluster? Core Challenges and Design Principles
Python Programming Learning Circle
Python Programming Learning Circle
Apr 14, 2023 · Backend Development

Implementing Periodic Tasks in Python: while‑loop, Timeloop, sched, schedule, APScheduler, Celery, and Airflow

This article reviews several Python approaches for creating scheduled or periodic jobs—including a simple while‑True loop with sleep, the Timeloop library, the built‑in sched module, the schedule package, APScheduler, Celery, and Apache Airflow—explaining their usage, advantages, limitations, and providing ready‑to‑run code samples.

APSchedulerAirflowCron
0 likes · 15 min read
Implementing Periodic Tasks in Python: while‑loop, Timeloop, sched, schedule, APScheduler, Celery, and Airflow
DataFunSummit
DataFunSummit
Apr 10, 2023 · Big Data

Spark on Kubernetes: Practices and Optimizations at Eggplant Technology

This article explains how Spark can be effectively deployed on Kubernetes, covering its advantages over traditional Hadoop clusters, the principles of Spark on K8s, dynamic allocation, reuse PVC enhancements, scheduling optimizations, and real‑world performance results from Eggplant Technology's production use.

Big DataSchedulingperformance-optimization
0 likes · 21 min read
Spark on Kubernetes: Practices and Optimizations at Eggplant Technology
StarRing Big Data Open Lab
StarRing Big Data Open Lab
Apr 7, 2023 · Cloud Native

How Cloud‑Native Scheduling Redesign Boosts Scalability and Efficiency

This article explains the concept of cloud‑native computing, its reliance on IaaS/PaaS/SaaS, the challenges of stateful services, and proposes a redesigned scheduling system—including storage‑aware, topology‑aware, label‑driven, and priority‑based mechanisms—to improve resource utilization, scalability, and multi‑tenant performance.

Schedulingmulti-tenantstorage-aware scheduling
0 likes · 20 min read
How Cloud‑Native Scheduling Redesign Boosts Scalability and Efficiency
DataFunSummit
DataFunSummit
Mar 28, 2023 · Big Data

Core Technologies, Performance Metrics, Challenges, and Future Trends of Cloud‑Native Big Data – Expert Interview

In this expert interview, a chief big‑data architect from NetEase explains the core technology layers, key performance indicators, major challenges and mitigation strategies, the business value, and emerging trends of cloud‑native big data platforms, highlighting scheduling, storage, and mixed‑deployment considerations.

Schedulingbig-datastorage
0 likes · 15 min read
Core Technologies, Performance Metrics, Challenges, and Future Trends of Cloud‑Native Big Data – Expert Interview
DeWu Technology
DeWu Technology
Mar 22, 2023 · Big Data

Analysis of Flink Scheduling Components and Slot Allocation

The article explains Flink’s post‑submission scheduling pipeline—from Dispatcher creating SchedulerNG and building the ExecutionGraph, through pipelined region construction and the PipelinedRegionSchedulingStrategy, to slot sharing allocation—identifying why slot and TaskManager overloads occur and proposing randomization or fine‑grained resource strategies to balance load.

DistributedSystemsExecutionGraphFlink
0 likes · 14 min read
Analysis of Flink Scheduling Components and Slot Allocation
DataFunTalk
DataFunTalk
Mar 15, 2023 · Big Data

Evolution of Next‑Generation Cloud Data Platform Architecture

This technical presentation reviews the historical development of big data platforms, outlines the four generations of cloud data platform architectures, details the modern cloud‑native stack—including unified metadata, scheduling, and integration systems—and showcases a real‑world industrial manufacturing case with a Q&A session.

Cloud Data PlatformMetadataScheduling
0 likes · 23 min read
Evolution of Next‑Generation Cloud Data Platform Architecture
Sanyou's Java Diary
Sanyou's Java Diary
Feb 27, 2023 · Backend Development

11 Ways to Implement Delayed Tasks in Java – From DelayQueue to Redis and MQ

This article surveys eleven practical techniques for implementing delayed tasks in Java, covering JDK utilities like DelayQueue, Timer, and ScheduledThreadPoolExecutor, as well as message‑queue solutions such as RocketMQ, RabbitMQ, Redis key‑expiration, Redisson, Netty, Hutool, Quartz, and simple polling, with code demos and implementation principles.

Delayed TasksMessage QueueRedis
0 likes · 26 min read
11 Ways to Implement Delayed Tasks in Java – From DelayQueue to Redis and MQ
Tencent Cloud Developer
Tencent Cloud Developer
Feb 8, 2023 · Backend Development

Design and Implementation of QQ Reminder Subscription Push System

Tencent’s QQ reminder subscription push system combines push‑pull prefetching, heterogeneous MySQL/Redis storage, delayed‑queue triggers, Redis‑based rate‑limiting, task scattering, message‑queue decoupling, at‑least‑once delivery, and dual‑replica disaster recovery within a dispatcher‑worker architecture to ensure reliable, controllable, low‑latency mass notifications.

At-Least-OncePush NotificationQQ
0 likes · 13 min read
Design and Implementation of QQ Reminder Subscription Push System
Data Thinking Notes
Data Thinking Notes
Jan 10, 2023 · Big Data

How Bilibili Built a Scalable Data Quality Platform for Billions of Events

This article describes Bilibili’s data quality platform, outlining its background, objectives, theoretical models, workflow stages (recording, checking, alerting), DSL for metrics, root‑cause analysis, scheduling strategies, heterogeneous source integration, rule coverage, intelligent monitoring, and future plans to achieve automated, real‑time, high‑reliability data assurance for massive daily workloads.

AutomationBig DataMonitoring
0 likes · 21 min read
How Bilibili Built a Scalable Data Quality Platform for Billions of Events
Spring Full-Stack Practical Cases
Spring Full-Stack Practical Cases
Jan 6, 2023 · Backend Development

Master Spring Boot Task Execution: Configure Executors, Schedulers, and Async

Learn how Spring Boot automatically configures ThreadPoolTaskExecutor and ThreadPoolTaskScheduler, customize them via spring.task.execution and spring.task.scheduling properties, and use @EnableAsync, @Scheduled, and @Async annotations—including advanced options like cron expressions, time units, executor qualifiers, and exception handling—to efficiently manage asynchronous and scheduled tasks.

SchedulingSpring Bootasync
0 likes · 8 min read
Master Spring Boot Task Execution: Configure Executors, Schedulers, and Async
dbaplus Community
dbaplus Community
Dec 26, 2022 · Cloud Native

How Bilibili Boosted Server Utilization with Kubernetes Co‑Location Strategies

This article explains how Bilibili’s large‑scale Kubernetes cloud platform reduces costs and improves machine utilization by applying co‑location (mixed‑tenant) techniques, including resource‑aware scheduling, dynamic isolation, and a dedicated management console across online, offline, and idle‑machine scenarios.

Cloud NativeCo-locationKubernetes
0 likes · 17 min read
How Bilibili Boosted Server Utilization with Kubernetes Co‑Location Strategies
DataFunSummit
DataFunSummit
Dec 21, 2022 · Big Data

Big Data Platform Architecture: Expert Insights on Components, Challenges, and Trends

An expert interview series examines the architecture of big data platforms, detailing core modules such as data integration, storage, computation, scheduling, and query analysis, while highlighting current challenges, best‑practice tools, and future trends like cloud‑native, object storage, and real‑time processing.

Big DataDistributed ComputingQuery Engines
0 likes · 12 min read
Big Data Platform Architecture: Expert Insights on Components, Challenges, and Trends
Bilibili Tech
Bilibili Tech
Nov 22, 2022 · Big Data

Overview of the Berserker Big Data Platform and Its Data Development Architecture

The Berserker big‑data platform provides a one‑stop data development and governance solution built on over 40 micro‑services, featuring the Archer scheduler with CN and EN nodes, Raft‑based state management, Docker‑isolated task execution, smart routing, and plans to make EN stateless, migrate to Kubernetes, and unify batch and streaming services.

ArcherBig DataDocker
0 likes · 17 min read
Overview of the Berserker Big Data Platform and Its Data Development Architecture
ITPUB
ITPUB
Nov 5, 2022 · Big Data

How Bilibili Builds a Scalable, Automated, and Intelligent Data Quality Platform

This article explains how Bilibili’s data quality team designs a process‑driven, automated, and AI‑enhanced platform that monitors billions of records daily, defines quality metrics such as completeness and consistency, integrates heterogeneous data sources, and provides root‑cause analysis and real‑time alerting to ensure trustworthy data for its massive user base.

Root Cause AnalysisSchedulingdata quality
0 likes · 19 min read
How Bilibili Builds a Scalable, Automated, and Intelligent Data Quality Platform
IT Services Circle
IT Services Circle
Oct 21, 2022 · Fundamentals

Understanding Thread Blocking and Scheduling in Operating Systems

The article explains what thread blocking means in operating systems, how the OS moves blocked threads to wait queues and schedules other threads, discusses spin locks, and reflects on common misconceptions and community debates about callbacks versus polling.

AsynchronousSchedulingspin lock
0 likes · 5 min read
Understanding Thread Blocking and Scheduling in Operating Systems
StarRocks
StarRocks
Oct 13, 2022 · Databases

Inside StarRocks: How the Pipeline Execution Engine Boosts Query Performance

This article explains the core concepts, architecture, and code logic of StarRocks' Pipeline execution framework, covering ExecPlan, PlanFragment, Fragment Instance, ExecNode, SourceOperator, SinkOperator, PipelineDriver scheduling, asynchronous handling of blocking operations, and the roles of FE and BE in MPP scheduling.

Execution EngineMPPScheduling
0 likes · 13 min read
Inside StarRocks: How the Pipeline Execution Engine Boosts Query Performance
Alibaba Cloud Native
Alibaba Cloud Native
Oct 10, 2022 · Cloud Native

What’s New in Koordinator v0.7? Enhanced Coscheduling, ElasticQuota, and Fine‑Grained GPU Sharing

Koordinator v0.7 adds major cloud‑native scheduling features—including enhanced gang (coscheduling) with Strict/NonStrict modes, multi‑hierarchy ElasticQuota management, fine‑grained GPU resource protocols, richer diagnostic APIs, and safer descheduling—targeting machine‑learning and big‑data workloads on Kubernetes.

Cloud NativeCoschedulingElasticQuota
0 likes · 25 min read
What’s New in Koordinator v0.7? Enhanced Coscheduling, ElasticQuota, and Fine‑Grained GPU Sharing
Java Backend Technology
Java Backend Technology
Sep 3, 2022 · Backend Development

Mastering Java Scheduling: 10 Powerful Ways to Automate Your Tasks

This comprehensive guide explores ten practical Java scheduling techniques—from Linux crontab and JDK Thread/Timer to Spring Task, Quartz, and distributed solutions like XXL‑Job and Elastic‑Job—detailing their usage, code examples, advantages, and drawbacks for robust backend automation.

CronSchedulingSpring
0 likes · 21 min read
Mastering Java Scheduling: 10 Powerful Ways to Automate Your Tasks
Baidu Geek Talk
Baidu Geek Talk
Aug 22, 2022 · Mobile Development

How Baidu Optimized Low‑End Device Startup Performance: A Deep Dive

This article explains how Baidu's performance team tackled the slowdown of mobile internet growth by defining low‑end devices, building observability, creating high‑efficiency tooling, redesigning key components such as KV storage and locks, and introducing a smart scheduling framework that together reduced Android cold‑start TTI by over 50% and iOS cold‑start TTI by more than 40%, while establishing a continuous anti‑degradation pipeline.

SchedulingStartup timeTTI
0 likes · 20 min read
How Baidu Optimized Low‑End Device Startup Performance: A Deep Dive
Selected Java Interview Questions
Selected Java Interview Questions
Aug 10, 2022 · Backend Development

Comparison of Java Scheduling Frameworks: Timer, ScheduledExecutorService, Spring, Quartz, TBSchedule, Elastic-Job, Saturn, XXL-Job

The article examines common business scenarios that require timed execution, explains why scheduled tasks are needed, lists single‑machine and distributed Java scheduling frameworks, and provides a detailed feature‑by‑feature comparison between two popular distributed schedulers, X‑Job and Elastic‑Job.

Elastic-JobQuartzScheduling
0 likes · 13 min read
Comparison of Java Scheduling Frameworks: Timer, ScheduledExecutorService, Spring, Quartz, TBSchedule, Elastic-Job, Saturn, XXL-Job
转转QA
转转QA
Aug 5, 2022 · Operations

How to Make Test Task Breakdown and Scheduling More Reasonable

This article explains how to improve overall delivery efficiency by systematically breaking down testing tasks, setting realistic schedules based on clear goals, preparation steps, granular time estimates, dependency considerations, and post‑execution reviews, while emphasizing a target testing effort not exceeding half of development time.

QASchedulingprocess improvement
0 likes · 7 min read
How to Make Test Task Breakdown and Scheduling More Reasonable
Big Data Technology & Architecture
Big Data Technology & Architecture
Aug 4, 2022 · Big Data

Comprehensive Guide to DataX: Introduction, Architecture, Usage, and Deployment

This article provides a detailed overview of DataX, covering its purpose, framework design, core architecture, scheduling process, practical examples of MySQL-to-MySQL synchronization, step‑by‑step installation and configuration of DataX‑WEB, UI usage, routing strategies, task types, and advanced task building techniques.

Big DataData IntegrationDataX
0 likes · 14 min read
Comprehensive Guide to DataX: Introduction, Architecture, Usage, and Deployment
Laiye Technology Team
Laiye Technology Team
Jul 22, 2022 · Cloud Native

Distributed Training Orchestration and Scheduling on Kubernetes: Architecture, Challenges, and Solutions

This article examines the pain points of distributed training orchestration and scheduling, presents a layered cloud‑native architecture built on Kubernetes, explains key components such as pipeline orchestrators, training job operators, schedulers, and topology managers, and discusses practical solutions using Argo, Kubeflow Pipelines, and the Volcano scheduler.

Distributed TrainingKubernetesML Platform
0 likes · 38 min read
Distributed Training Orchestration and Scheduling on Kubernetes: Architecture, Challenges, and Solutions
GuanYuan Data Tech Team
GuanYuan Data Tech Team
Jul 21, 2022 · Operations

Mastering Data Workflows with DAGs: Scheduling, Configurable UI, and Visual Design

This article explains how to abstract repetitive data‑report tasks into a standardized workflow, describes the core capabilities of scheduling and configuration, shows how to implement DAG‑based visual editors, and compares similar platforms such as n8n and Orange, offering practical code examples and design insights.

DAGData PipelineScheduling
0 likes · 20 min read
Mastering Data Workflows with DAGs: Scheduling, Configurable UI, and Visual Design
Alibaba Cloud Native
Alibaba Cloud Native
Jun 16, 2022 · Cloud Native

How Koordinator Improves Efficiency and Stability for Cloud‑Native Mixed Workloads

This article explains how Alibaba Cloud's open‑source Koordinator system tackles mixed‑workload challenges by introducing priority and QoS models, resource overcommit, load‑aware scheduling, fine‑grained CPU orchestration, and upcoming features such as GPU scheduling and resource recommendation, all illustrated with architecture diagrams and code examples.

Cloud NativeKoordinatorKubernetes
0 likes · 24 min read
How Koordinator Improves Efficiency and Stability for Cloud‑Native Mixed Workloads
Big Data Technology Architecture
Big Data Technology Architecture
Jun 14, 2022 · Big Data

Applying Apache DolphinScheduler in a Big Data Platform: Architecture, Migration, and Future Plans

This presentation details the background, redesign, and migration of a large‑scale data platform at Dangbei Network Technology, focusing on the adoption of Apache DolphinScheduler, ClickHouse migration, storage and compute separation, monitoring solutions, and the roadmap for future upgrades and open‑source involvement.

Apache DolphinSchedulerClickHouseHA
0 likes · 12 min read
Applying Apache DolphinScheduler in a Big Data Platform: Architecture, Migration, and Future Plans
Cognitive Technology Team
Cognitive Technology Team
Jun 10, 2022 · Backend Development

Understanding Spring's @Scheduled Annotation and Its Task Scheduling Mechanism

This article explains how Spring's @Scheduled annotation works, covering configuration options like cron, fixedDelay and fixedRate, the internal processing by ScheduledAnnotationBeanPostProcessor, method reflection, task registration with ScheduledTaskRegistrar, and the underlying execution using ThreadPoolTaskScheduler and ScheduledThreadPoolExecutor.

AnnotationSchedulingSpring
0 likes · 6 min read
Understanding Spring's @Scheduled Annotation and Its Task Scheduling Mechanism
IT Architects Alliance
IT Architects Alliance
Jun 3, 2022 · Backend Development

Which Delayed Task Strategy Wins? A Deep Dive into DB Polling, DelayQueue, Time Wheel, Redis, and RabbitMQ

The article compares five delayed‑task implementations—database polling, JDK DelayQueue, Netty time wheel, Redis sorted sets, and RabbitMQ dead‑letter queues—detailing their concepts, Java code examples, advantages, and drawbacks to help developers choose the most suitable approach for order‑timeout scenarios.

DelayQueueDelayed TasksQuartz
0 likes · 16 min read
Which Delayed Task Strategy Wins? A Deep Dive into DB Polling, DelayQueue, Time Wheel, Redis, and RabbitMQ
Big Data Technology Architecture
Big Data Technology Architecture
Jun 3, 2022 · Operations

Understanding Apache Airflow DAGs, Operators, and Scheduling

This article explains Apache Airflow's core concepts, including DAG definitions, scheduling intervals, task dependencies, various operators such as BashOperator, PythonOperator, Branch operators, sensors, and custom operators, and provides code examples and configuration details for building robust data pipelines.

Apache AirflowDAGData pipelines
0 likes · 15 min read
Understanding Apache Airflow DAGs, Operators, and Scheduling
Programmer DD
Programmer DD
May 15, 2022 · Backend Development

How to Automate Gym Reservations with Selenium: A Google Engineer’s Design Doc

This article explains how a Google engineer designed and implemented an automated system using Python and Selenium to book gym slots two days in advance, detailing problem definition, requirements, architecture, code snippets, and operational workflow for reliable, headless execution on macOS.

AutomationPythonScheduling
0 likes · 11 min read
How to Automate Gym Reservations with Selenium: A Google Engineer’s Design Doc
Zhuanzhuan Tech
Zhuanzhuan Tech
May 11, 2022 · Backend Development

Evolution of Grouped Concurrency Scheduling and the Self‑Driven Concurrency Model for E‑commerce Backend Services

This article analyzes the challenges of aggregating multiple RPC calls in e‑commerce app backends, explains simple and complex concurrency scenarios, introduces grouped concurrency scheduling, and presents a self‑driven concurrency model that automates dependency handling to improve response latency and maintainability.

Schedulingbackendconcurrency
0 likes · 10 min read
Evolution of Grouped Concurrency Scheduling and the Self‑Driven Concurrency Model for E‑commerce Backend Services
IT Architects Alliance
IT Architects Alliance
Apr 5, 2022 · Backend Development

Understanding Java Timers, DelayQueue, ScheduledThreadPoolExecutor, and Time‑Wheel Algorithms

This article explains the concepts, use cases, and internal implementations of Java's Timer, DelayQueue, and ScheduledThreadPoolExecutor, compares their performance characteristics, and introduces the time‑wheel scheduling algorithm—including hierarchical wheels—to address scalability challenges in high‑volume timed‑task systems.

DelayQueueScheduledThreadPoolExecutorScheduling
0 likes · 12 min read
Understanding Java Timers, DelayQueue, ScheduledThreadPoolExecutor, and Time‑Wheel Algorithms
vivo Internet Technology
vivo Internet Technology
Mar 23, 2022 · Backend Development

Understanding the Time Wheel Mechanism in Dubbo and Redisson

The article explains why a time‑wheel scheduler outperforms traditional timers, describes single‑ and multi‑layer wheel designs, and walks through Apache Dubbo’s HashedWheelTimer implementation—including TimerTask, Timeout, bucket and worker components—showing its use in Dubbo heartbeats and Redisson lock renewal.

DubboRedissonScheduling
0 likes · 23 min read
Understanding the Time Wheel Mechanism in Dubbo and Redisson
IT Services Circle
IT Services Circle
Mar 23, 2022 · Operations

Understanding High‑Precision Timer Scheduling in Java and Linux Kernels

The article explores why absolute‑precision periodic tasks are hard to achieve, compares Java Timer and ScheduledExecutorService with Linux kernel mechanisms such as DelayedWorkQueue, futex, pthread_cond_timedwait, and high‑resolution hrtimers, and explains the underlying data structures and timing‑wheel algorithms.

Schedulinghigh precisiontimer
0 likes · 11 min read
Understanding High‑Precision Timer Scheduling in Java and Linux Kernels
Ops Development Stories
Ops Development Stories
Mar 22, 2022 · Operations

Optimize Kubernetes Resource Use with Requests, Limits, and Scheduling

This article explains common causes of resource waste in Kubernetes clusters, such as over‑provisioned requests and fluctuating workloads, and provides practical methods—including proper request/limit settings, ResourceQuota and LimitRange policies, node affinity, taints and tolerations, and HPA—to improve overall resource utilization and cluster stability.

KubernetesLimitRangeNode Affinity
0 likes · 16 min read
Optimize Kubernetes Resource Use with Requests, Limits, and Scheduling
Top Architect
Top Architect
Mar 11, 2022 · Fundamentals

Operating System Fundamentals: Concurrency, Process Management, Memory Management, and Deadlock

This article provides a comprehensive overview of operating system fundamentals, covering concepts such as concurrency, shared resources, virtual memory, process and thread management, synchronization mechanisms, classic synchronization problems, memory paging and replacement algorithms, device management, disk scheduling, and deadlock detection and prevention.

DeadlockProcess ManagementScheduling
0 likes · 33 min read
Operating System Fundamentals: Concurrency, Process Management, Memory Management, and Deadlock
DataFunTalk
DataFunTalk
Mar 3, 2022 · Big Data

Youzan Data Platform and DP Data Development Platform: Architecture, Core Modules, and Scheduling System Upgrade

This article presents an in‑depth overview of Youzan's data platform, introduces the DP data development platform with its key features and workflow, details the core module architecture—including service, scheduling, and component layers—and explains the migration from Airflow to DolphinScheduler to improve performance, stability, and scalability.

Big DataData DevelopmentDolphinScheduler
0 likes · 14 min read
Youzan Data Platform and DP Data Development Platform: Architecture, Core Modules, and Scheduling System Upgrade
OPPO Kernel Craftsman
OPPO Kernel Craftsman
Feb 25, 2022 · Fundamentals

Inside Linux’s fork: How the Kernel Creates a New Process

This article dissects the Linux kernel’s fork implementation, explaining why the child receives a return value of 0, how parent and child share code execution, the internal steps of sys_fork, kernel_clone, copy_process, thread handling, scheduling initialization, and the final insertion of the new task into the run‑queue.

LinuxSchedulingfork
0 likes · 10 min read
Inside Linux’s fork: How the Kernel Creates a New Process
Code Ape Tech Column
Code Ape Tech Column
Nov 27, 2021 · Backend Development

A Comprehensive Guide to 10 Practical Scheduling Solutions for Java and Linux

This article reviews ten widely used scheduling methods—from Linux crontab and Java Thread/Timer to Spring Task, Spring Quartz, and distributed frameworks like XXL‑Job and Elastic‑Job—explaining their configuration, code examples, and advantages and disadvantages for various backend scenarios.

CronDistributed TasksScheduling
0 likes · 22 min read
A Comprehensive Guide to 10 Practical Scheduling Solutions for Java and Linux
dbaplus Community
dbaplus Community
Nov 27, 2021 · Big Data

How Vipshop’s Hera Data Service Boosts Big Data Access and Performance

The article details the design, architecture, core features, scheduling logic, and performance gains of Vipshop’s self‑built Hera data service, which unifies data‑warehouse access, supports multiple engines, adapts SQL execution, and dramatically improves SLA for both B‑to‑B and B‑to‑C workloads.

Big DataData ServiceDistributed Computing
0 likes · 22 min read
How Vipshop’s Hera Data Service Boosts Big Data Access and Performance
DataFunTalk
DataFunTalk
Nov 20, 2021 · Big Data

How to Build a Big Data Platform from Zero to One: Architecture, Components, and Best Practices

This article provides a comprehensive guide to designing and implementing a big‑data platform, covering architecture overview, data ingestion with Flume, storage on HDFS/Hive/HBase, processing engines such as Hive, Spark and Flink, scheduling solutions like Azkaban and Airflow, and the construction of self‑service analytics systems.

Big DataData EngineeringETL
0 likes · 29 min read
How to Build a Big Data Platform from Zero to One: Architecture, Components, and Best Practices
Liangxu Linux
Liangxu Linux
Nov 18, 2021 · Fundamentals

Why Does Linux Use Preemptible Kernels? A Deep Dive into Kernel Preemption Mechanics

This article explains the technical details of Linux kernel preemption, covering the difference between preemptible and non‑preemptible kernels, the role of the reschedule flag and preempt count, scheduling checkpoints and preempt points, low‑latency handling in non‑preemptible kernels, and the voluntary preemption model.

ARM64CFSLinux
0 likes · 20 min read
Why Does Linux Use Preemptible Kernels? A Deep Dive into Kernel Preemption Mechanics
Alibaba Cloud Native
Alibaba Cloud Native
Nov 2, 2021 · Cloud Native

How to Spot Load‑Balancing, Scheduling, and Hotspot Issues with Kubernetes Monitoring

This article explains how to use Kubernetes monitoring features such as service details, topology maps, and pod metrics to quickly identify load‑balancing imbalances, cluster scheduling bottlenecks, and resource hotspot problems, providing practical steps and visual examples for improving system reliability and performance.

Cloud NativeKubernetesLoad Balancing
0 likes · 10 min read
How to Spot Load‑Balancing, Scheduling, and Hotspot Issues with Kubernetes Monitoring
macrozheng
macrozheng
Oct 29, 2021 · Backend Development

Mastering Delayed Tasks: From Database Polling to Redis and RabbitMQ

This article explains the concept of delayed tasks in payment systems, distinguishes them from scheduled tasks, and evaluates five practical implementation approaches—including database polling, Java DelayQueue, time‑wheel algorithms, Redis, and RabbitMQ—highlighting each method's advantages and drawbacks.

Message QueueScheduling
0 likes · 18 min read
Mastering Delayed Tasks: From Database Polling to Redis and RabbitMQ
Top Architect
Top Architect
Oct 27, 2021 · Backend Development

Implementation Strategies for Delayed Tasks in Java Applications

The article explains the concept of delayed tasks, distinguishes them from scheduled tasks, and evaluates five practical implementation approaches—including database polling, JDK DelayQueue, Netty time‑wheel, Redis sorted‑set and key‑space notifications, and RabbitMQ delayed queues—while providing code samples, performance pros and cons, and deployment considerations.

Delayed TasksQuartzRedis
0 likes · 20 min read
Implementation Strategies for Delayed Tasks in Java Applications
IT Architects Alliance
IT Architects Alliance
Sep 26, 2021 · Backend Development

Mastering Delayed Tasks in Java: From Quartz to Redis and RabbitMQ

This article examines the concept of delayed tasks versus scheduled tasks, outlines their differences, and presents five practical implementation strategies—including database polling with Quartz, JDK DelayQueue, Netty’s HashedWheelTimer, Redis ZSET and keyspace notifications, and RabbitMQ delayed queues—complete with code samples, performance pros and cons, and scalability considerations.

Delayed TasksQuartzRedis
0 likes · 19 min read
Mastering Delayed Tasks in Java: From Quartz to Redis and RabbitMQ
Python Programming Learning Circle
Python Programming Learning Circle
Sep 9, 2021 · Backend Development

Common Python Scheduling Techniques and Libraries

This article provides a comprehensive overview of various Python approaches for implementing periodic tasks, including simple loops with sleep, third‑party libraries such as Timeloop, schedule, APScheduler, as well as distributed solutions like Celery and Apache Airflow, complete with code examples and architectural explanations.

APSchedulerAirflowCron
0 likes · 24 min read
Common Python Scheduling Techniques and Libraries
Architecture Digest
Architecture Digest
Sep 9, 2021 · Backend Development

Design and Implementation of Delayed Task Processing in Java: Database Polling, DelayQueue, Time Wheel, Redis, and RabbitMQ

The article explains the concept of delayed tasks versus scheduled tasks and presents five practical Java implementations—database polling with Quartz, JDK DelayQueue, Netty's HashedWheelTimer, Redis sorted sets and keyspace notifications, and RabbitMQ delayed queues—detailing their code, advantages, and drawbacks.

DelayQueueDelayed TasksQuartz
0 likes · 18 min read
Design and Implementation of Delayed Task Processing in Java: Database Polling, DelayQueue, Time Wheel, Redis, and RabbitMQ
IT Architects Alliance
IT Architects Alliance
Sep 7, 2021 · Backend Development

Implementing Delayed Tasks: Strategies, Code Samples, and Trade‑offs

This article explains various approaches to implementing delayed tasks in backend systems, comparing database polling, Java's DelayQueue, Netty's time wheel, Redis sorted sets and keyspace notifications, and RabbitMQ delayed queues, with detailed code examples and analysis of each method's pros and cons.

Delayed TasksNettyRedis
0 likes · 17 min read
Implementing Delayed Tasks: Strategies, Code Samples, and Trade‑offs
Programmer DD
Programmer DD
Sep 5, 2021 · Backend Development

Mastering Delayed Tasks in Java: From Quartz to Redis and RabbitMQ

This article compares delayed and scheduled tasks, explains their differences, and presents five practical Java implementations—including database polling with Quartz, JDK DelayQueue, Netty's HashedWheelTimer, Redis sorted sets, and RabbitMQ—highlighting each method's advantages and drawbacks.

Delayed TasksRedisScheduling
0 likes · 19 min read
Mastering Delayed Tasks in Java: From Quartz to Redis and RabbitMQ
Top Architect
Top Architect
Sep 4, 2021 · Backend Development

Various Implementations of Delayed Task Scheduling in Java: Quartz, DelayQueue, HashedWheelTimer, Redis, and RabbitMQ

This article compares delayed tasks with scheduled tasks and presents five practical Java implementations—database polling with Quartz, JDK DelayQueue, Netty's HashedWheelTimer, Redis sorted sets and keyspace notifications, and RabbitMQ delayed queues—detailing their code, advantages, and drawbacks.

DelayQueueDelayed TasksQuartz
0 likes · 18 min read
Various Implementations of Delayed Task Scheduling in Java: Quartz, DelayQueue, HashedWheelTimer, Redis, and RabbitMQ
Java Backend Technology
Java Backend Technology
Aug 26, 2021 · Backend Development

How to Implement Reliable Delayed Tasks in Java: From Quartz to Redis and RabbitMQ

This article compares several Java-based delayed‑task solutions—including database polling with Quartz, JDK DelayQueue, Netty’s HashedWheelTimer, Redis sorted‑set or key‑space notifications, and RabbitMQ delayed queues—detailing their implementations, advantages, drawbacks, and practical code examples for reliable order‑timeout handling.

Delayed TasksQuartzRedis
0 likes · 19 min read
How to Implement Reliable Delayed Tasks in Java: From Quartz to Redis and RabbitMQ
Open Source Linux
Open Source Linux
Jul 25, 2021 · Cloud Native

Demystifying Kubernetes: Core Components and How They Work Together

This article provides a concise, question‑driven overview of Kubernetes, explaining the roles of master and worker nodes, pod networking, scheduling, storage with etcd, service exposure, scaling mechanisms, and how the various controllers collaborate to manage a cloud‑native cluster.

Cloud NativeKubernetesPods
0 likes · 10 min read
Demystifying Kubernetes: Core Components and How They Work Together
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Jul 18, 2021 · Backend Development

Implementing Delayed Tasks in E‑commerce Systems: Techniques, Code Samples, and Trade‑offs

This article explains the concept of delayed tasks versus scheduled tasks, presents common e‑commerce scenarios, and provides multiple implementation approaches—including JDK DelayQueue, ScheduledExecutorService, database polling, Redis sorted sets, Pulsar, ActiveMQ, and Netty time‑wheel—along with code examples and practical considerations.

Delayed TasksScheduling
0 likes · 14 min read
Implementing Delayed Tasks in E‑commerce Systems: Techniques, Code Samples, and Trade‑offs
macrozheng
macrozheng
May 20, 2021 · Backend Development

10 Powerful Java Scheduling Techniques for Every Scenario

This article walks through ten practical scheduling solutions—from Linux crontab and JDK utilities to Spring Task, Spring Quartz, and distributed frameworks like XXL‑Job and Elastic‑Job—explaining their usage, configuration, code examples, and pros and cons so developers can pick the right tool for any business need.

CronSchedulingSpring
0 likes · 24 min read
10 Powerful Java Scheduling Techniques for Every Scenario
Youzan Coder
Youzan Coder
May 12, 2021 · Frontend Development

Understanding React Fiber Architecture, Work Units, and Scheduling

React Fiber rewrites React’s core algorithm by breaking the diff phase into small, interruptible fiber units, scheduling them during browser idle time with requestIdleCallback, using double‑buffered trees and effect lists to pause, resume, and efficiently commit DOM updates, thereby improving UI responsiveness in large applications.

Front-endJavaScriptReAct
0 likes · 28 min read
Understanding React Fiber Architecture, Work Units, and Scheduling
iQIYI Technical Product Team
iQIYI Technical Product Team
Apr 23, 2021 · Cloud Native

ByteDance Stateful Application Cloud‑Native Practices

ByteDance’s cloud‑native migration of stateful services uses a custom SolarService extending StatefulSet with Budset CRD to handle versioned data, shard‑aware routing, NUMA‑aware scheduling, advanced storage, eBPF monitoring, and automated PDB eviction, delivering efficiency, cost savings, and reliable rolling upgrades.

AutomationKubernetesMonitoring
0 likes · 18 min read
ByteDance Stateful Application Cloud‑Native Practices
JD Tech
JD Tech
Apr 16, 2021 · Backend Development

Using java.util.Timer for Scheduled and Delayed Tasks in Java

This article explains how to use java.util.Timer for one‑time and periodic task scheduling, covering constructors, instance methods, daemon‑thread behavior, handling past dates, negative delays, multiple tasks, and proper shutdown, with complete code examples and execution results.

Schedulingbackendconcurrency
0 likes · 24 min read
Using java.util.Timer for Scheduled and Delayed Tasks in Java
Su San Talks Tech
Su San Talks Tech
Apr 10, 2021 · Backend Development

Mastering Java Scheduling: 10 Essential Timers and Distributed Task Solutions

Explore ten practical Java scheduling options—from Linux crontab and JDK Thread/Timer to Spring Task, Quartz, and distributed frameworks like XXL‑Job, Elastic‑Job, Saturn and TBSchedule—detailing setup, code examples, advantages, drawbacks, and best‑fit scenarios for reliable task automation.

CronQuartzScheduling
0 likes · 22 min read
Mastering Java Scheduling: 10 Essential Timers and Distributed Task Solutions
ITPUB
ITPUB
Mar 2, 2021 · Fundamentals

Master OS Interview Questions: From Basics to Advanced Concepts

This comprehensive guide covers over forty operating system interview questions, explaining core concepts such as OS fundamentals, process and thread management, memory handling, file systems, I/O mechanisms, scheduling algorithms, and deadlock prevention, providing detailed answers and diagrams to help candidates excel in technical interviews.

Interview QuestionsMemory ManagementProcess Management
0 likes · 65 min read
Master OS Interview Questions: From Basics to Advanced Concepts
Tencent IMWeb Frontend Team
Tencent IMWeb Frontend Team
Jan 4, 2021 · Backend Development

How I Optimized a Node.js Enterprise WeChat Sync Service: Lessons & Solutions

This article walks through the design, pitfalls, and deep optimizations of a Node.js + TypeScript backend that periodically syncs enterprise WeChat organization data to a MySQL store and provides a phone‑number lookup API, offering practical solutions for rate limits, process management, database conflicts, and error recovery.

MySQLNode.jsRedis
0 likes · 10 min read
How I Optimized a Node.js Enterprise WeChat Sync Service: Lessons & Solutions
Liangxu Linux
Liangxu Linux
Dec 22, 2020 · Fundamentals

Mastering Processes and Threads: 19 Essential OS Concepts Explained

This comprehensive guide covers the fundamentals of processes and threads, their definitions, relationships, creation, lifecycle, scheduling strategies, context switching, inter‑process communication methods, and practical C/C++ examples, providing a deep dive into operating‑system concepts for developers and interview preparation.

C++IPCLinux
0 likes · 41 min read
Mastering Processes and Threads: 19 Essential OS Concepts Explained
Qunar Tech Salon
Qunar Tech Salon
Dec 9, 2020 · Backend Development

Improving L‑D Stage Smoothness and Refactoring the Rebuild System for International Hotel Pricing

This article details how the L‑D stage of international hotel pricing was optimized through a new offline‑fetch scheduling mechanism, cache‑freshness calculations, and a comprehensive refactor of the rebuild system, resulting in lower latency, higher throughput, and a smoother user experience.

SchedulingSystem Designbackend
0 likes · 11 min read
Improving L‑D Stage Smoothness and Refactoring the Rebuild System for International Hotel Pricing
Meituan Technology Team
Meituan Technology Team
Nov 26, 2020 · Artificial Intelligence

Meituan Autonomous Vehicle Engine: Architecture, Challenges, and Resource Optimization

Meituan’s autonomous vehicle engine abstracts communication, scheduling, data handling, and tooling into three layers to ensure deterministic behavior across on‑vehicle and simulation environments, tackling consistency, scheduling, and resource‑utilization challenges by using unified computation models, distributed graph deployment, caching, and remote model serving, thereby accelerating autonomous delivery vehicle development.

AIDistributed ComputingResource Optimization
0 likes · 14 min read
Meituan Autonomous Vehicle Engine: Architecture, Challenges, and Resource Optimization