Hortonworks Data Platform

System Administration Guides

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Hortonworks Data Platform (HDP) and any of its components are not anticipated to be combined with any hardware, software or data, except as expressly recommended in this documentation.

The Hortonworks Data Platform, powered by Apache Hadoop, is a massively scalable and 100% open source platform for storing, processing and analyzing large volumes of data. It is designed to deal with data from many sources and formats in a very quick, easy and cost-effective manner. The Hortonworks Data Platform consists of the essential set of Apache Hadoop projects including MapReduce, Hadoop Distributed File System (HDFS), HCatalog, Pig, Hive, HBase, Zookeeper and Ambari. Hortonworks is the major contributor of code and patches to many of these projects. These projects have been integrated and tested as part of the Hortonworks Data Platform release process and installation and configuration tools have also been included.

Unlike other providers of platforms built using Apache Hadoop, Hortonworks contributes 100% of our code back to the Apache Software Foundation. The Hortonworks Data Platform is Apache-licensed and completely open source. We sell only expert technical support, training and partner-enablement services. All of our technology is, and will remain free and open source.

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Contents

1. ACLs on HDFS

1. Configuring ACLs on HDFS

2. Using CLI Commands to Create and List ACLs

3. ACLs Examples

3.1. Introduction: ACLs Versus Permission Bits
3.2. Example 1: Granting Access to Another Named Group
3.3. Example 2: Using a Default ACL for Automatic Application to New Children
3.4. Example 3: Blocking Access to a Sub-Tree for a Specific User

4. ACLS on HDFS Features

5. Use Cases for ACLs on HDFS

5.1. Multiple Users
5.2. Multiple Groups
5.3. Hive Partitioned Tables
5.4. Default ACLs
5.5. Minimal ACL/Permissions Only
5.6. Block Access to a Sub-Tree for a Specific User
5.7. ACLs with Sticky Bit

2. Capacity Scheduler

1. Introduction
2. Enabling Capacity Scheduler
3. Setting up Queues
4. Controlling Access to Queues with ACLs
5. Managing Cluster Capacity with Queues
6. Setting User Limits
7. Application Reservations
8. Starting and Stopping Queues
9. Setting Application Limits
10. Preemption (Technical Preview)
11. Scheduler User Interface

3. Centralized Cache Management in HDFS

1. Overview

2. Caching Use Cases

3. Caching Architecture

4. Caching Terminology

5. Configuring Centralized Caching

5.1. Native Libraries
5.2. Configuration Properties
5.3. OS Limits

6. Using Cache Pools and Directives

6.1. Cache Pool Commands
6.2. Cache Directive Commands

4. Configuring Rack Awareness on HDP

1. Create a Rack Topology Script
2. Add the Topology Script Property to core-site.xml
3. Restart HDFS and MapReduce
4. Verify Rack Awareness

5. Using DistCp to Copy Files

1. Using DistCp

2. Command Line Options

3. Update and Overwrite

4. DistCp and Security Settings

5. DistCp and HDP Version

6. DistCp Data Copy Matrix: HDP1/HDP2 to HDP2

7. Copying Data from HDP-2.x to HDP-1.x Clusters

8. DistCp Architecture

8.1. DistCp Driver
8.2. Copy-listing Generator
8.3. InputFormats and MapReduce Components

9. DistCp Frequently Asked Questions

10. Appendix

10.1. Map Sizing
10.2. Copying Between Versions of HDFS
10.3. MapReduce and Other Side-Effects
10.4. SSL Configurations for HSFTP Sources

6. Decommissioning Slave Nodes

1. Prerequisites

2. Decommission DataNodes or NodeManagers

2.1. Decommission DataNodes
2.2. Decommission NodeManagers

3. Decommission HBase RegionServers

7. Manually Add Slave Nodes to a HDP Cluster

1. Prerequisites
2. Add Slave Nodes
3. Add HBase RegionServer

8. NameNode High Availability for Hadoop

1. Architecture

2. Hardware Resources

3. Deploy NameNode HA Cluster

3.1. Configure NameNode HA Cluster
3.2. Deploy NameNode HA Cluster
3.3. Deploy Hue with an HA Cluster
3.4. Deploy Oozie with HA Cluster

4. Operating a NameNode HA cluster

5. Configure and Deploy NameNode Automatic Failover

5.1. Prerequisites
5.2. Instructions
5.3. Configuring Oozie Failover

6. Appendix: Administrative Commands

9. ResourceManager High Availability for Hadoop

1. Hardware Resources

2. Deploy ResourceManager HA Cluster

2.1. Configure Manual or Automatic ResourceManager Failover
2.2. Deploy the ResourceManager HA Cluster
2.3. Minimum Settings for Automatic ResourceManager HA Configuration

10. High Availability for Hive Metastore

1. Use Cases and Fail Over Scenarios

2. Software Configuration

2.1. Install HDP
2.2. Update the Hive Metastore
2.3. Validate configuration

11. Highly Available Reads with HBase

1. Understanding HBase Concepts

1.1. Region Servers and Secondary Mode
1.2. Timeline and Strong Data Consistency

2. Enabling HA Reads for HBase

3. Creating Highly-Available HBase Tables

3.1. Creating HA Tables with the HBase Java API
3.2. Creating HA Tables with the HBase Shell

4. Querying Secondary Region Servers

4.1. Querying HBase with the Java API
4.2. Querying HBase Interactively

5. Monitoring Secondary Region Servers

12. HBase Cluster Capacity and Region Sizing

1. Node Count and JVM Configuration

2. Region Count and Size

2.1. Increase Memstore Size for region server
2.2. Increase Size of the Region

3. Initial Configuration and Tuning

13. Timeline Server

1. Introduction
2. Configuring the Timeline Server
3. Configuring Generic Data Collection
4. Configuring Per-Framework Data Collection
5. Running the Timeline Server
6. Accessing Generic Data from the Command-Line
7. Publishing Per-Framework Data in Applications

14. WebHDFS Administrator Guide

List of Tables

8.1. Hue Configuration Properties
11.1.
12.1. HBase Concepts
12.2. Factors Affecting Physical Size of Data
12.3. Authentication Schemes in TCP Transport Mode

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