Technical Introduction to PostgreSQL and PPAS

A Technical introduction to PostgreSQL and PPASEnterprise Class PostgreSQL Database from EDB

10/6/2014

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• Introduction

• About Ashnik

• PostgreSQL and buzz it has created

• Postgres Plus Advanced Server

• Architecture

• Oracle Compatibility

• Performance Features

• Security Features

• High Availability Features

• DBA Tools

• User Stories

• What’s coming up in v9.3

• How to start adopting

Agenda

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• Independent & Thriving Development Community for over 20 years

• Thousands of active deployments worldwide in public and private sector organizations of all sizes

PostgreSQL and the Community

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Postgres’ IMPACT

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PostgreSQL – Postgres Plus Users, Globally

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Malaysia

Philippines

Singapore

Vietnam Thailand

Indonesia

PostgreSQL – Postgres Plus Users, across ASEAN

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EnterpriseDB – The Company

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• The Enterprise PostgreSQL company was founded in 2004,

first product GA in 2005

• 2,000+ customers across all market segments

• 70,000+ downloads/week of PostgreSQL and related products

• Enabling database consolidation using PostgreSQL and

advanced Oracle compatibility

• Saving customers millions through the power of open source

• Strong financial backing:

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Postgres Plus - Recognized

by Gartner’s Magic

Quadrant as a challenger

in the Database Market

The EnterpriseDB Advantage

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• Products and Tools

• Advanced database server software

• Deep Oracle compatibility

• Bundled development and management tools

• Technical Support and Services

• Around the clock support

• Expert consulting

• Oracle migration services

• Remote management and monitoring

• Professional Training

• Learn PostgreSQL from the experts

• Web and on-site training

• Training for developers and DBAs CO

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• Fast development cycles

• Thousands of developers

• Better code

• Lower cost

• 24/7 support

• Services and training

• Certification

• Indemnification

• Product strategy

Bringing the Advantage to Enterprises

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Open Source Software

CommercialSoftwareEnterpriseDB

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About PPAS

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Architectural Overview

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Process Architecture

Postmaster

BGWRITERBGWRITER STATS COLLECTOR

STATS COLLECTOR

ARCHIVERARCHIVERAUTO--VACUUMAUTO--VACUUM

BGWRITERBGWRITER STATS COLLECTOR

STATS COLLECTOR

Data Files

WALSegments

ArchivedWAL

Shared Memory

Shared Buffers Process ArrayWAL Buffers

WAL WriterWAL Writer LOG WRITERLOG WRITER

Error Log Files12

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Database Limitations

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• Limitations are generally defined by

• Operating System Limits

• Compile-Time Parameters

– Data Type Usage

General Database Limitations

Limit Value

Maximum Database Size Unlimited

Maximum Table Size 32 TB

Maximum Row Size 1.6 TB

Maximum Field Size 1 GB (4TB in v9.3 Beta)

Maximum Rows per Table Unlimited

Maximum Columns per Table 250-1600 (Depending on Column types)

Maximum Indexes per Table Unlimited

Oracle Compatibility

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• Run applications written for Oracle virtually unchanged

• No need to re-train Oracle DBAs and developers

• Support for PL/SQL language and OCI interoperability

• Replication for easy sharing of data

• Dramatic Cost Savings

• No Vendor Lock-in

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Survey: Re-Use of Oracle DBA Skills

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Compatibility Means

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• SQL Extension support• Decode, NVL, Substr, NVL2,replace,translate, table()

• Date/time functions: add_months, extract, next_day,months_between,trunc, current_date support

• Support for cascade option in drop table

• PL/SQL support• REF Cursors, Implicit and explicit cursors

• Looping, variable declarations, conditional statements

• Collections: Associative Arrays, Varrays, Nested tables

• Bulk binding

• Named parameters

• User Defined Exceptions

• Explicit Transaction Control - within a stored procedure

• Tools• EDB*Plus – SQL*Plus look-a-like

• EDB*Loader – SQL*Loader equivalent

• EDB*Wrap – similar to the PL/SQL wrapper CO

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Compatibility Means (cont.)

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• Packages• Stored procedures• Functions• Triggers• Optimizer Hints• Database Links

• Hierarchical Queries• Synonyms – Public and

Private• Sequences• Materialized Views C

ON

FID

ENTI

AL

© 2

01

1 E

nte

rpri

seD

B. A

ll ri

ghts

res

erv

ed.

• Rownum• Object types

o Create type … as object

o Create type … as table

o Create type …as varray

o Constructor and collection methods

• PL/SQL like SUBTYPE, which inherits form base type

• Users/Roles• Dynamic SQL

• Features

Compatibility Means (cont.)

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• Data Types

• Integer, number, char, double precision, float, varchar2, blob, clob, xmltype, rowid, boolean

• Built-in Packages• DBMS_:

o SQL, LOB, JOB, PIPE, ALERT, OUTPUT, UTILITY, PROFILER, RLS

• UTL_:o FILE, MAIL, SMTP, ENCODE, TCP

• Oracle-like Data Dictionary• ALL_, DBA_, USER_ views

• Most commonly accessed views

• Diagnostics - DRITA• System and session waits

o Not exposed in PostgreSQL

o Part of Advanced Server

• Statspack-like reporting

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Flexible Partitioning Scheme in PostgreSQL

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• Partitioning Example in PostgreSQLo CREATE TABLE employees

o Create Child Tables

o create table emp_mgmt (check (job in (MANAGER'))) inherits (employees);

o create table emp_sales (check (job in ('SALESMAN'))) inherits (employees);

o Create the partitioning function

o CREATE OR REPLACE FUNCTION partition_emp();

o Create the trigger for partition

o CREATE TRIGGER employees_partition_trigger BEFORE INSERT ON employees

FOR EACH ROW EXECUTE PROCEDURE partition_emp();

• Advantages• Flexible

• Customize your Partitioning Policy

• Disadvantages• Complex

• Difficult to add/delete/split Partitions

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• Partitioning Example in PPASCREATE TABLE employees

(empno numeric(4,0),ename varchar(10),job varchar(9),hiredate timestamp)

PARTITION BY LIST (job)

(PARTITION emp_mgmt VALUES ('MANAGER', 'PRESIDENT') tablespace tbsp_1, PARTITION emp_sales VALUES ('SALESMAN') tablespace tbsp_2, PARTITION emp_ops VALUES ('CLERK') tablespace tbsp_3

);

• PPAS Offers• LIST and RANGE Partitioning Syntax

• Easy to manage and maintain partitions

• You can still take benefit of PostgreSQL syntax for complex partitioning e.g. Dynamic Partitions

• Easy to Add/Delete/Split/Swap/Detach/Attach partitions

• Brings the best of both the world!

Compatible and Flexible Partitioning Scheme in PPAS

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Scaling with Partitioning in PPAS v9.3

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0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000

100

250

500

1000

Time in Seconds

Nu

mb

er

of

Ta

ble

Pa

rtit

ion

s

Partitioning Performance: PPAS 9.3 v. PostgreSQL 9.3 v. PPAS 9.2 • Postgres Plus Advanced Server 9.3 is up to 460 times faster with rowinsertions into partitioned tables than PostgreSQL 9.3 or PPAS 9.2

• Better performance for bulk loading and disaster recovery

• Online Migration Toolkit enables point and click migration from Oracle

• Automatically Migrates:

Database Migration Toolkit

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• Data

• Schemas

• Stored Procedures

• Triggers

• Functions

• Sequences

• Packages

• Views

• Database Links

• Synonyms

• Developed for High Performance Transaction Environments (OLTP)

• DynaTune:

• Dynamic tuning of the database server to make the optimal usage of the system resources available on the host machine

• Index Advisor:

• Helps determine which columns you should index to improve performance in a given workload.

• Query Optimization Hints, Hi-Speed Bulk Loader, Multi-Threaded Replication

Performance enhancement in PPAS

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• Infinite Cache

• High performance horizontal scaling architecture for cache memory

• Cache expands with inexpensive commodity hardware

Scalability with Infinite Cache

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• Architecture: How it Works

• Disk access for data is slower than RAM access

• Infinite Cache puts disk data into the RAM cache

• Additional requests for that data are read from the faster cache

• The cache scales as needed with inexpensive hardware

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Ap

plicatio

n

High speed

pg_cache buffers in RAM

Slow speed disk

High Speed

Network

Updated Data Blocks

Update

Read

If not in buffer

Database Server

Infin

iteC

ache

RA

M b

lade

s

Highspeed


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• Single Machine Performance

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Advanced Server is 16X faster on a single machine with large amounts of memory (e.g. greater than 2 GB)

Infinite Cache can be usedon a single machine!


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• Infinite Cache - Features• Expands and Distributes buffer cache across multiple machines• Designed for Read-Mostly applications (e.g. Content Management, Query Intensive, Business

Intelligence, Data Warehouse)• Cache is transparent to client applications (no cache coding needed)• Compression feature enables caching entire databases (e.g. put a 250 GB database into 32 GB

RAM Cache)• Cache can be pre-warmed for immediate results• Cache scales using inexpensive commodity hardware• Infinite Cache can be run to boost single machine performance!

• Created For• DBAs and data managers overseeing large amounts of data requiring fast response times for

queries and reporting loads• Developers who don’t want to write specialized caching code16

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• Red Hat Reference Architecture Series:

Comparing BenchmarkSQL Performance

on Red Hat Enterprise Linux 5 to Windows

Server Enterprise (2010)

Performance Benchmark to SQL Server

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Scalability MySQL Vs PostgreSQL

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Security

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• Object level privileges assigned to roles and users

• Virtual Private Database

• Kerberos and LDAP authentication

• Host base authentication

• SSL communication

• Data Level Encryption (AES, 3DES, etc)

• Ability to utilize 3rd party Key Stores in a full PKI Infrastructure

• Foundation for full compliance with the strictest of security standards (PCI Data Security Standard)

• Flexible field level encryption and row level security

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“By default, PostgreSQL is probably the most

security-aware database available ...”

Database Hacker's Handbook- David Litchfield

PL/Secure and EDB*Wrap

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• Encrypt your Pl/pgsql stored programs with PL/Secure

• Encrypt your SPL procedures with EDB*Wrap

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SQL/Protect

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• DBA Managed SQL Injection Protection

a) Preventing attacks is normally the responsibility of the application developer, but with SQL/Protect, DBAs can now provide another layer of protection to prevent corruption or co-opting of the database.

• Multiple Prevention Techniques

a) Unauthorized Relations

b) Utility Commands (e.g. DDL)

c) SQL Tautology

d) Unbounded DML

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• Multi-Master Replication – Active-Active Technology

• Near real-time Replication

• Multi-Version Concurrency Control (MVCC)

• Point-in-Time Recovery

• Log Shipping for Standby (~ Oracle® Data Guard)

High Availability

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Availability

Backup and Recovery Options

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• Physical and Logical Backup

• Logical Backup using pg_dump

• Instance level logical backup using pg_dumpall

• Table level, Schema level or DB level logical backup

• pg_restore

• Physical Backups

• pg_basebackup

• Compressed backup

• Recovery with WAL and archived WAL

• Point in Time Recover

• Using OS Clustering

• Using a shared disk for data

Active – Passive OS HA Clustering

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• Uses WAL (Write Ahead Log)

• WAL is continuously shipped through an opened TCP channel to Hot Standby Node

• Hot Standby node can be used for read scalability

Hot Streaming Replication (Hot Standby Mode)

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• Uses WAL (Write Ahead Log)

• Archived WAL is shipped to Hot Standby Node


Log Shipping Replication (Hot Standby Mode)

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EnterpriseDB Postgres Plus Failover Manager

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Agent Agent

• Using pg-pool

• Using redundant disk for data


HA with read scaling (with pg-pool)

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• Trigger based replication

• Publication – Subscription

• Snapshot and Continuous

• Cascaded Replication

• Read Scalability

• Master/Slave DB can be:

• Oracle

• MSSQL

• Postgres Plus Advanced Server

• Either Master or Slave should be PPAS/PostgreSQL

xDB Single Master Replication (SMR)

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• High Availability uses

• Geographic distribution of load

• For creation of Testing/staging env using snapshot replication

• Segregate OLTP and reporting

xDB Replication Use Cases

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Replication

xDB Single-Master Replication (SMR)

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TableD

TableC

TableB

TableA

TableC

TableD

ProcsObjects

ReportsQueries

Continuousor Scheduled----------------

Filteredor All Rows

TransactionReplication

ImprovedOLTP

Performance

InexpensiveQuery /

Reporting

Oracle Server Postgres Plus Advanced Server

xDB SMR Heterogeneous Replication Support

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Source/Target Oracle MS SQL

Server

2005/2008

PostgreSQL

Advanced

Server

(Oracle

mode)

Advanced

Server

(PostgreSQL

mode)

Oracle No No Yes Yes Yes

MS SQL

Server

2005/2008

No No Yes Yes Yes

PostgreSQL No Yes Yes Yes Yes

Advanced

Server (Oracle

mode)Yes Yes No

YesNo

Advanced

Server

(PostgreSQL

mode)

No Yes Yes Yes Yes

• Trigger based replication

• 2 or more Masters can be Sync

• Auto Conflict Detection & Resolution

• Read & Write Scalability

xDB Multi Master Replication (MMR)

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• Java-based Replication Server and Replication Console• Delta changes recorded in shadow tables via post Insert/Update/Delete triggers• Data Replication through JDBC channel

xDB MMR Architecture

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Remotely Manage, Monitor And Tune

• Management En-Mass Design

• Enterprise Performance Monitoring

• Proactive Alert Management

• Graphical Administration

• SQL Workload Profiling

• Simplified Capacity Planning

• Full SQL IDE

Postgres Enterprise Manager

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• Performance Monitoring Dashboards

• Capacity Manager

• Postgres Expert

• Alert Management

• Browser based console and dashboard

• Audit Manager

• Team Support

• Distributed Architecture

• Convenient Access

PEM For DBAs: Centralized Tool

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Helps you apply patches and updates for all the products under PPAS:

Stackbuilder Plus

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• A solution to aid in the creation of highly available configurations of Postgres

• Monitors the health of a Postgres HA configuration

• Automates the failover process in the event of a failure

• Used in conjunction with Streaming Replication

Postgres Plus Failover Manager

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Slave

Witness

Master

Failover Manager Architecture

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Agent Agent

• Automatic Failover from master to replica node

• Configurable fencing operation

1. By default uses VIP

2. Parameter to specify alternative operation

a) Ex: reconfigure a load balancer

• Manual failover configuration possible

• Email notifications when cluster status changes

• Witness node provides protection against ‘split brain’ scenarios

• User configurable wait times

• Built on PPCD/JGroups technology

Failover Manager Features

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Replicate below objects from MS SQL Server to

Postgres Plus Advanced Server:

• Schemas

• Tables

• Constraints

• Indexes

• Table data

• Views

Replicating & Migrating Microsoft SQL Server

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• Split input files into multiple files

• Load single tables in parallel

• Magnitudes better load time performance

• Parallel load capabilities also in Migration Toolkit and Migration Studio

Parallel Data Loader

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FTD Replicates Oracle Data for Volume Peaks

Background

FTD is the world’s leading provider of floral-related products and services

Processes 15M+ orders annually through 20,000 retail florists in the US

The ARGO System Project

FTD deployed new shipping administration system (ARGO)

ARGO’s performance deteriorated during peak holiday loads

Oracle-based system couldn’t handle peak reporting volumes

Off-load reporting data form Oracle to Postgres using Postgres Plus Replication Server

Why Postgres

No major changes required to run Oracle apps on Postgres

Project completed in 6 weeks (Valentines Day Mother’s Day)

Out of the Box Compatibility with existing database

Improved Vendor Service – response times decreased dramatically

Performance of order processing systems improved 400% by offloading reporting to Postgres

“When someone comes in at a sixth of the cost [of Oracle]

and 500 times the customer service, that makes it very easy.”

Jason Weiss, Software Architect

InMobi Delivers Mobile Ads with Postgres

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Background

• One of the fastest growing mobile advertising networks

• Huge scalability and performance requirements, billions of ads per month

• Uses HP Proliant server

Mobile Ad Platform Project

• Postgres the best fit for a scalable open-source

database

• Community support not sufficient to meet business

requirements, EnterpriseDB a partner

• Initial database install supported organic growth

• 25 instances across 4 data centers with replication

• Database sizes upwards of 600 GB

• 200K txns/minute with 3 ms response time

Why Postgres

• Most scalable open-source database

• Lower cost than traditional databases

• Performance and reliability up to the task at internet scale, supporting the most extreme workloads

• Customizations by EnterpriseDB rapidly incorporated into the product ensuring costly customization maintenance is avoided

Sony Reduces TCO of database environment by 80%

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.Free Realms Project

• Lower TCO and improve licensing flexibility

• Leverage existing Oracle DBA and Developer talent

• Migrate key Oracle apps to Postgres

• Commercial-grade quality and reliability, including backup and recovery standards, to support mission-critical applications

• Scalable, high performance execution

Why Postgres

• Reduced TCO by 80%

• East of Migration – majority of Oracle apps could run unmodified on Postgres Plus

• Skills re-use – Oracle – trained staff could immediately work with Postgres Plus

• Exceptional technical support from EnterpriseDB

“Postgres Plus has proven to be a cost-effective database that can accommodate Free Realms’ massive growth.”

- Andy Sites, Free Realms Senior Producer, SOE

Background

• Free Realms massively multiplayer online game

• >9M registered players since April 2009

• IT Oracle scale-up was cost-prohibitive

Background

• Multi-terabyte Oracle DB and needed to reduce DB costs

• Running old, unsupported version of Oracle and had to pay to upgrade

The EPBS Project

• Engaged EnterpriseDB consulting services to migrate

• Unique migration process developed and implemented

Why Postgres

• 2.2 TeraByte system migrated and now running on Postgres Plus Advanced Server

• Current performance is comparable to Oracle

• Costs reduced significantly by migrating to EnterpriseDB solutions

Achieved Comparable Performance Replacing Oracle

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ToT, Thailand plans to replace Oracle Exadata-TimesTen In-memory database with HP-EnterpriseDB stack

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Background

• Largest public sector company in telecom in Thailand

• Has very stringent response time SLA (20ms response time for user requests ~ 3-5 read queries)

• Current setup has Oracle Exadata and four TimeTen In-memory databases

Current Challenges in Oracle Stack

• Issues in sync of Exadata with In-memory databases

• Full refresh locks the tables

• Current system can go upto 1500 tps

• Dynamic Partitioning for huge table

• Current system load is 750 TPS with write operations

• 5000 user requests (16.5K read queries) per second with 4 servers

HP-EnterpriseDB Stack Proposed to be DR for Exadata• HP DL-980 (4 CPU * 10 cores, 256GB RAM)

• 1TB VMA Disks for faster access

• Simulation tests show 2800 write-TPS achieved

• Flexible Partitioning scheme in PPAS (add partition on the fly for

each new date, no manual intervention)

• Currently this server is being tested as DR for Exadata

• Replication using xDB near-relatime replication for 1000 tps

• Scalability achieved using cascaded replication and Infinite Cache

• Setup can handle 5500 user requests (18K queries per second)

with 1.5-2.5ms response time per query

v.9.3

• Switch master without archive logs in cascaded replication

• Faster recovery

• Enhanced partitioning feature- Better performance

• More extended JSON support

• Materialized Views

• Updatable Views

• Recursive Views

• Replication between Heterogeneous System Architectures – Facilitates central backup server

• pg_xlogdump to decode WAL

• 4TB Large Object Support

• Better memory managements

What’s New?

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v.9.4

• Logical Replication

• Time Lagging DR

• Enhanced JSON features

• Enhancements in Materialized Views

• Moving aggregates

• Pg_prewarm to warm up the cache

• Backup throttle

• ALTER SYSTEM command to set parameters

What’s Coming up?

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How to start adoption

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REPLICATION SERVER

BACKUP / DR SERVER

NEW APPLICATION

MIGRATION

You have a ‘Real’ alternative to Oracle or other

conventional proprietary Databases

Conclusion

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EconomicalTechnically

Sound

Easy to

Adopt

Technical Introduction to PostgreSQL and PPAS

Technology

Transcript of Technical Introduction to PostgreSQL and PPAS