Netezza Online Training by in India
-
Upload
ravikumar-nandigam -
Category
Education
-
view
188 -
download
3
description
Transcript of Netezza Online Training by in India
Be Right back in 5 minutes!
Thank you for joining
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