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PostgreSQL 9 High Availability Cookbook

PostgreSQL 9 High Availability Cookbook

By : Shaun Thomas
4.7 (6)
Buy this Book
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PostgreSQL 9 High Availability Cookbook

PostgreSQL 9 High Availability Cookbook

4.7 (6)
By: Shaun Thomas
Buy this Book

Overview of this book

A comprehensive series of dependable recipes to design, build, and implement a PostgreSQL server architecture free of common pitfalls that can operate for years to come. Each chapter is packed with instructions and examples to simplify even highly complex database operations. If you are a PostgreSQL DBA working on Linux systems who want a database that never gives up, this book is for you. If you've ever experienced a database outage, restored from a backup, spent hours trying to repair a malfunctioning cluster, or simply want to guarantee system stability, this book is definitely for you.
Table of Contents (12 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Sections
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Conventions
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Reader feedback
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Customer support
Lock Free Chapter
1
1. Hardware Planning
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1. Hardware Planning
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Introduction
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Planning for redundancy
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Having enough IOPS
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Sizing storage
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Investing in a RAID
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Picking a processor
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Making the most of memory
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Exploring nimble networking
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Managing motherboards
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Selecting a chassis
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Saddling up to a SAN
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Tallying up
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Protecting your eggs
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2. Handling and Avoiding Downtime
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2. Handling and Avoiding Downtime
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Introduction
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Determining acceptable losses
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Configuration – getting it right the first time
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Configuration – managing scary settings
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Identifying important tables
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Defusing cache poisoning
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Exploring the magic of virtual IPs
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Terminating rogue connections
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Reducing contention with concurrent indexes
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Managing system migrations
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Managing software upgrades
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Mitigating the impact of hardware failure
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Applying bonus kernel tweaks
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3. Pooling Resources
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3. Pooling Resources
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Introduction
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Determining connection costs and limits
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Installing PgBouncer
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Configuring PgBouncer safely
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Connecting to PgBouncer
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Listing PgBouncer server connections
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Listing PgBouncer client connections
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Evaluating PgBouncer pool health
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Installing pgpool
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Configuring pgpool for master/slave mode
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Testing a write query on pgpool
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Swapping active nodes with pgpool
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Combining the power of PgBouncer and pgpool
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4. Troubleshooting
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4. Troubleshooting
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Introduction
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Performing triage
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Installing common statistics packages
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Evaluating the current disk performance with iostat
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Tracking I/O-heavy processes with iotop
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Viewing past performance with sar
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Correlating performance with dstat
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Interpreting /proc/meminfo
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Examining /proc/net/bonding/bond0
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Checking the pg_stat_activity view
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Checking the pg_stat_statements view
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Debugging with strace
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Logging checkpoints properly
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5. Monitoring
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5. Monitoring
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Introduction
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Figuring out what to monitor
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Installing and configuring Nagios
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Configuring Nagios to monitor a database host
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Enhancing Nagios with check_mk
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Getting to know check_postgres
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Installing and configuring collectd
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Adding a custom PostgreSQL monitor to collectd
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Installing and configuring Graphite
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Adding collectd data to Graphite
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Building a graph in Graphite
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Customizing a Graphite graph
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Creating a Graphite dashboard
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6. Replication
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6. Replication
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Introduction
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Deciding what to copy
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Securing the WAL stream
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Setting up a hot standby
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Upgrading to asynchronous replication
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Bulletproofing with synchronous replication
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Faking replication with pg_receivexlog
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Setting up Slony
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Copying a few tables with Slony
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Setting up Bucardo
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Copying a few tables with Bucardo
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Setting up Londiste
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Copying a few tables with Londiste
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7. Replication Management Tools
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7. Replication Management Tools
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Introduction
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Deciding when to use third-party tools
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Installing and configuring Barman
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Backing up a database with Barman
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Restoring a database with Barman
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Installing and configuring OmniPITR
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Managing WAL files with OmniPITR
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Installing and configuring repmgr
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Cloning a database with repmgr
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Swapping active nodes with repmgr
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Installing and configuring walctl
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Cloning a database with walctl
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Managing WAL files with walctl
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8. Advanced Stack
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8. Advanced Stack
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Introduction
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Preparing systems for the stack
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Getting started with the Linux Volume Manager
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Adding block-level replication
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Incorporating the second LVM layer
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Verifying a DRBD filesystem
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Correcting a DRBD split brain
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Formatting an XFS filesystem
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Tweaking XFS performance
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Maintaining an XFS filesystem
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Using LVM snapshots
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Switching live stack systems
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Detaching a problematic node
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9. Cluster Control
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9. Cluster Control
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Introduction
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Installing the components
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Configuring Corosync
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Preparing startup services
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Starting with base options
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Adding DRBD to cluster management
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Adding LVM to cluster management
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Adding XFS to cluster management
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Adding PostgreSQL to cluster management
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Adding a virtual IP to hide the cluster
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Adding an e-mail alert
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Grouping associated resources
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Combining and ordering related actions
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Performing a managed resource migration
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Using an outage to test migration
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10. Data Distribution
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10. Data Distribution
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Introduction
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Identifying horizontal candidates
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Setting up a foreign PostgreSQL server
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Mapping a remote user
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Creating a foreign table
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Using a foreign table in a query
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Optimizing foreign table access
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Transforming foreign tables into local tables
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Creating a scalable nextval replacement
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Building a sharding API
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Talking to the right shard
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Moving a shard to another server
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Index
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Index

Introduction

Every business has the goal of being successful. The consequence of having a successful business when there's a database involved is increasingly high volume. This volume can be composed of query activity, data accumulation, or both. A PostgreSQL database that is not prepared for vast amounts of data or transaction load will slowly falter until the platform suffers.

Customers notice bad performance just as readily as outages. If our database is struggling to service queries, we have three options:

  • Spend time optimizing the platform to reduce database interaction
  • Buy a more capable database server
  • Store data on several PostgreSQL servers

Indeed, we should probably always implement step one in any case. Yet, there is a limit to candidates for optimization. If the platform is using an ORM, making query changes can be difficult. Frontend caching can prevent a vast amount of database accesses, but we need to consider cold caches, refreshes, and write volume. Writes must touch the...

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