Apache Hadoop 3.5.0 – Concepts

##### General

- Overview
- Single Node Setup
- Cluster Setup
- Commands Reference
- FileSystem Shell
- Compatibility Specification
- Downstream Developer's Guide
- Admin Compatibility Guide
- Interface Classification
- FileSystem Specification

##### Common

- CLI Mini Cluster
- Fair Call Queue
- Native Libraries
- Proxy User
- Rack Awareness
- Secure Mode
- Service Level Authorization
- HTTP Authentication
- Credential Provider API
- Hadoop KMS
- Tracing
- Unix Shell Guide
- Registry
- Async Profiler

##### HDFS

- Architecture
- User Guide
- Commands Reference
- NameNode HA With QJM
- NameNode HA With NFS
- Observer NameNode
- Federation
- ViewFs
- ViewFsOverloadScheme
- Snapshots
- Edits Viewer
- Image Viewer
- Permissions and HDFS
- Quotas and HDFS
- libhdfs (C API)
- WebHDFS (REST API)
- HttpFS
- Short Circuit Local Reads
- Centralized Cache Management
- NFS Gateway
- Rolling Upgrade
- Extended Attributes
- Transparent Encryption
- Multihoming
- Storage Policies
- Memory Storage Support
- Synthetic Load Generator
- Erasure Coding
- Disk Balancer
- Upgrade Domain
- DataNode Admin
- Router Federation
- Provided Storage

##### MapReduce

- Tutorial
- Commands Reference
- Encrypted Shuffle
- Pluggable Shuffle/Sort
- Distributed Cache Deploy
- Support for YARN Shared Cache

##### MapReduce REST APIs

- MR Application Master
- MR History Server

##### YARN

- Architecture
- Commands Reference
- Capacity Scheduler
- Fair Scheduler
- ResourceManager Restart
- ResourceManager HA
- Resource Model
- Node Labels
- Node Attributes
- Web Application Proxy
- Timeline Server
- Timeline Service V.2
- Writing YARN Applications
- YARN Application Security
- NodeManager
- Running Applications in Docker Containers
- Running Applications in runC Containers
- Using CGroups
- Secure Containers
- Reservation System
- Graceful Decommission
- Opportunistic Containers
- YARN Federation
- Shared Cache
- Using GPU
- Using FPGA
- Placement Constraints
- YARN UI2

##### YARN REST APIs

- Introduction
- Resource Manager
- Node Manager
- Timeline Server
- Timeline Service V.2

##### YARN Service

- Overview
- QuickStart
- Concepts
- Yarn Service API
- Service Discovery
- System Services

##### Hadoop Compatible File Systems

- Aliyun OSS
- Amazon S3
- Azure Blob Storage
- Azure Data Lake Storage
- Tencent COS
- Huaweicloud OBS
- VolcanoEngine TOS

##### Auth

- Overview
- Examples
- Configuration
- Building

##### Tools

- Hadoop Streaming
- Hadoop Archives
- Hadoop Archive Logs
- DistCp
- HDFS Federation Balance
- GridMix
- Rumen
- Resource Estimator Service
- Scheduler Load Simulator
- Hadoop Benchmarking
- Dynamometer

##### Reference

- Changelog and Release Notes
- Java API docs
- Unix Shell API
- Metrics

##### Configuration

- core-default.xml
- hdfs-default.xml
- hdfs-rbf-default.xml
- mapred-default.xml
- yarn-default.xml
- kms-default.xml
- httpfs-default.xml
- Deprecated Properties

# Concepts

This document describes some key concepts and features that makes YARN as a first-class platform in order to natively support long running services on YARN.

### Service Framework (ApplicationMaster) on YARN

A container orchestration framework is implemented to help deploying services on YARN. In a nutshell, the framework is an ApplicationMaster that requests containers from ResourceManager based on service definition provided by the user and launch the containers across the cluster adhering to placement policies. It also does all the heavy lifting work such as resolving the service definition and configurations, managing component life cycles such as automatically restarting failed containers, monitoring components’ healthiness and readiness, ensuring dependency start order across components, flexing up/down components, upgrading components etc. The end goal of the framework is to make sure the service is up and running as the state that user desired.

In addition, it leverages a lot of features in YARN core to accomplish scheduling constraints, such as affinity and anti-affinity scheduling, log aggregation for services, automatically restart a container if it fails, and do in-place upgrade of a container.

### A Restful API-Server for deploying/managing services on YARN

A restful API server is developed to allow users to deploy/manage their services on YARN via a simple JSON spec. This avoids users from dealing with the low-level APIs, writing complex code to bring their services onto YARN. The REST layer acts as a unified REST based entry for creation and lifecycle management of YARN services. Services here can range from simple single-component apps to the most complex, multi-component applications needing special orchestration needs. Please refer to this API doc for detailed API documentations.

The API-server is stateless, which means users can simply spin up multiple instances, and have a load balancer fronting them to support HA, distribute the load etc.

### Service Discovery

A DNS server is implemented to enable discovering services on YARN via the standard mechanism: DNS lookup.

The framework posts container information such as hostname and ip into the YARN service registry. And the DNS server essentially exposes the information in YARN service registry by translating them into DNS records such as A record and SRV record. Clients can then discover the IPs of containers via standard DNS lookup.

The previous read mechanisms of YARN Service Registry were limited to a registry specific (java) API and a REST interface and are difficult to wireup existing clients and services. The DNS based service discovery eliminates this gap. Please refer to this Service Discovery doc for more details.