Apache Hadoop 3.5.0 – Apache Hadoop 3.0.4 Release Notes

##### 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

# Apache Hadoop 3.0.4 Release Notes

These release notes cover new developer and user-facing incompatibilities, important issues, features, and major improvements.

- HADOOP-15252 | Major | Checkstyle version is not compatible with IDEA’s checkstyle plugin

Updated checkstyle to 8.8 and updated maven-checkstyle-plugin to 3.0.0.

- HADOOP-15506 | Minor | Upgrade Azure Storage Sdk version to 7.0.0 and update corresponding code blocks

WASB: Fix Spark process hang at shutdown due to use of non-daemon threads by updating Azure Storage Java SDK to 7.0

- HDFS-13174 | Major | hdfs mover -p /path times out after 20 min

Mover could have fail after 20+ minutes if a block move was enqueued for this long, between two DataNodes due to an internal constant that was introduced for Balancer, but affected Mover as well. The internal constant can be configured with the dfs.balancer.max-iteration-time parameter after the patch, and affects only the Balancer. Default is 20 minutes.

- HADOOP-15638 | Major | KMS Accept Queue Size default changed from 500 to 128 in Hadoop 3.x

Restore the KMS accept queue size to 500 in Hadoop 3.x, making it the same as in Hadoop 2.x.