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2. IBM PureData System
for Analytics
(Formerly known as, IBM Netezza)
- Ravi

3. Datawarehouse Appliance
What is Netezza?
H/W & S/W pre-bundled, pre-configured
Little configuration needed after deployment
Solves the traditional datawarehouse complexities!

4. Traditional DW Complexities!

5. Netezza Appliance: Datawarehousing simplified!

8. Netezza Architecture (major) Principles
Processing close to the data source
Balanced massively parallel architecture
Appliance Simplicity
Flexible configurations and extreme scalability

9. 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
SUM (NRX)
FPGA in Action!

10. S-Blade View
S-Blade: Where extreme performance happens

11. AMPP Architecture

12. What happens when you submit a query?

13. 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 …

14. Netezza TwinFin Specifications

15. Netezza TwinFin Specifications

16. 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

17. 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

18. Data-In/Out of Netezza Appliance

20. 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

21. 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

22. IBM Netezza Features
http://www-01.ibm.com/software/data/puredata/analytics/features.html