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IBM PureData System

for Analytics (Formerly known as, IBM Netezza)

- Ravi

Datawarehouse Appliance

H/W & S/W pre-bundled, pre-configured

What is Netezza?

Little configuration needed after deployment

Solves the traditional datawarehouse complexities!

Traditional DW Complexities!

Netezza Appliance: Datawarehousing simplified!

Netezza Architecture (major) Principles

Processing close to the data source

Balanced massively parallel architecture

Appliance Simplicity

Flexible configurations and extreme scalability

SELECT DISTRICT, PRODUCTGRP, SUM (NRX)

FROM MTHLY_PROD_DATA

WHERE PDATE=“20140401”

AND MARKET = “2014”

And SPECIALITY = “GASTRO”

Slice of table

MTHLY_PROD_DATA

(Compressed)

SELECT

DISTRICT,

PRODUCTGRP,

NRX

SU

M (

NR

X)

FPGA in Action!

S-Blade View

S-Blade: Where extreme performance happens

AMPP Architecture

What happens when you submit a query?

What happens when you submit a query?

Host compiles the query & divides into snippets

Optimizer creates a query execution plan by making intelligent decisions like join order/

redistribution/broadcast

Each snippet has two elements: Compiled code & FPGA parameters

Object Cache: Improves query performance. You can avoid code compilation

Scheduler: Maintains maximum utilization and throughput

S-Blades execute these snippets in parallel. Sends the results back to host

Host accumulates the results and results will be returned to Client …

Netezza TwinFin Specifications

Netezza TwinFin Specifications

Various Datawarehouse appliances in the market!

IBM (Netezza)

HP (Vertica)

EMC (Greenplum)

SAP (HANA-High Performance Analytics Appliance)

Oracle (Exadata)

Teradata (Teradata, Asterdata)

Microsoft (DATAllegro)

http://ybigdata.blogspot.com/2013/01/vertica-vs-aster-data-vs-greenplum-vs.html

Netezza Delivers …

• Speed: 10-100x faster than traditional custom systems

• Simplicity & Ease: Minimal tuning & administration and greater resilience

• Fast time to value: 5 TB/Hour load speed

• Smart: Complex algorithms in minutes. A rich library of integrated analytics

Data-In/Out of Netezza Appliance

Course Contents (Development)

• About Netezza Performance Server (NPS)

• NPS AMPP Architecture & Various Netezza appliance models

• Installing Netezza GUI client Interfaces

• ODBC/JDBC/OLEDB Client connectivity

• Installing Netezza Emulator for day-to-day practice

• Netezza Command Line Interface (CLI)

• Netezza SQL (NZSQL) language

• NZSQL DDL/DML/DCL/TCL statements

• NZSQL command line options & Internal slash commands

• Netezza Environment & System Variables

• Managing User Access to the Netezza Database

• Working with Databases & Tables (both from NZSQL & GUI interfaces)

• Netezza Data Types, Schemas, Users, Groups, Privileges

• Functions, Operators, Constraints, Sequences, & Synonyms

• Data Distribution (Hash, Random) & Best practices

• Transactions, Generate Statistics, Zone Maps, Materialized Views

• Groom Table, CBT, SQL Identifiers

• Data Loading/Unloading using External Tables, NZLOAD (CLI & GUI tools)

• Netezza system tables, views, user tables, Materialized views

• Netezza Joins, Sub queries, stored procedures, Aggregates, UDFs

• Netezza SQL Extensions & analytic functions

• Techniques to improve Netezza query performance

• Working with IBM Netezza support to resolve issues

Course Contents (DBA)

• About Netezza Performance Server (NPS)

• NPS AMPP Architecture & Various Netezza appliance models

• Netezza High Availability Architecture (Clustering, Mirroring, failover)

• Installing Netezza system and client softwares

• Installing Netezza Emulator for day-to-day practice

• NzAdmin: GUI Admin Tool (Installation & Setup)

• Netezza Command Line Interface (CLI)

• Manage NPS with CLI commands

• Manage User access to Netezza Databases

• Monitoring Netezza and Linux logs

• Netezza Events (Setup & Monitoring)

• Databases & Tables

• Data Distribution (Hash, Random), Cluster Base Tables, Table Skew

• Generate Statistics, Zone Maps, Materialized Views, Groom Table

• Backup & Restore (Host Level, Database Level, Table Level)

• Netezza Appliance/Database migration (For Example: 6.x to 7.x migration)

• Data Loading/Unloading using External Tables, NZLOAD, NZ_MIGRATE

• Data Loading/Unloading using GUI Tools

• Optimizer and query plans

• Query history collection & Reporting

• Workload management

• Netezza Replication/DR Architecture

• Techniques to improve Netezza performance

• Frequent DBA activities such as SPU replacements, Table Skew monitoring, etc

• Working with IBM Netezza Support to resolve issues

IBM Netezza Features

http://www-01.ibm.com/software/data/puredata/analytics/features.html