Do you ELT on z?

IBM INFORMATION ON DEMAND 2008© 2008 IBM Corporation

Do you ELT on z?

Mar 16. 2009

Information Management Software

© 2008 IBM Corporation

Agenda

• Design Studio Overview

• Development SQW Flows using Design Studio

• Physical Data Modeling

• Data Flows

• Control Flows

• Deployment & Runtime Management



Inhibitors to data warehousing on System z?

• DB2 functionality?

• DB2 V8 and V9 – great strides

• Costs?

• Specialty processors help – IIPs

• Lower cost licensing for new DB2 workloads – DB2 VUE

• Perception?

• Conventional wisdom over last decade: use distributed sytems for Data Warehouses

• A lot of shops defied conventional wisdom!

• Lack of skills and/or appropriate data warehouse building tooling on System z

• Fewer people have skills on System z?

• Recent graduates grew up using graphical tooling!• No green screen for them

• IBM recognizes this and is porting tooling to System z



Data Movement and Transformation

• Moving and transforming data is a key component to building a data warehouse

• What do you use on System z?

• Programs? COBOL? Rexx?

• Database utilities? Import, Export?

• SQL scripts?

• Stored procedures?

• FTPs?

• ????



Alphabet Soup for Tools

• ETL

• ELT

• ETLT

• TELT

• TETLT

• What???

• Just MarketingSpeak of stating how and where the data movement and transformation activities occur

• Leverage an stand-alone transformation engine

• Leverage a database engine for data transformations

E = Extract

T = Transform

L = Load



Extract Transform Load

ETL – Extract Transform Load

Usually a stand-alone server separate from any source or target systems

Referred to as an ETL Engine that performs all extracts and transformations

Database agnostic

Usually a procedural design slant

May push some processing to source databases

May invoke database utilities



ELT – Extract Load Transform

Turns the relational database engine into a data movement and transformation engine

The work is usually done at the target system

Can source from multiple database types but typically supports a specific target

By definition, has a set-based design slant

May push some processing to source databases

May invoke database utilities

Extract TransformLoad



Variations on a theme

• ETLT, TETLT

• ETL tools are now pushing some processing down into the source and/or target relational databases by generating SQL

• TELT, TETLT

• ELT tools can typically push SQL to remote databases

• ELT tools can do some limited non-relational processing – typically by calling executables or scripts



Reality…

• Don’t get caught up in the ETL vs ELT wars

• Advantages to doing some work outside the database

• Advantages go doing some work inside the database

• Don’t build an ETL or an ELT system

• Build an architected Population Subsystem

• Apply the appropriate tools to the appropriate function for the available (and future) skill level

• ETL tools when appropriate• ELT tools when appropriate• Other tools when appropriate



A Population Subsystem

• Consider using an architected model for building population subsystems

• Each logical layer performs a specific kind of function and processing is encapsulated to that layer

• Logical layers are grouped into physical components and a staging of data occurs between physical components

• Each physical component will be implemented with technical functions implemented by one or more technologies



Population Subsystem

• Consider using an architected model for building population subsystems

• Each logical layer performs a specific kind of function and processing is encapsulated to that layer

• Logical layers are grouped into physical components and a staging of data occurs between physical components

• Each physical component will be implemented with technical functions implemented by one or more technologies

From IBM course DW130



Tools on System z (z/OS or Linux on System z)

• Data Movement and Transformation

• ETL: InfoSphere DataStage for Linux on System z

• Data Cleansing: InfoSphere Quality Stage for Linux on System z

• ELT: InfoSphere Warehouse on System z – SQL Warehousing Tool

• Expanded Sources

• Heterogeneous data access: InfoSphere Federation Server

• Classic Data Sources: InfoSphere Classic Federation Server for z/OS

• Capturing Changes

• SQL and Q-based data replication: InfoSphere Replication Server for z/OS

• Classic data source replication: InfoSphere Classic Replication Server for z/OS

• DB2 event publishing: InfoSphere Data Event Publisher for z/OS

• Class event publishing: InfoSphere Classic Data Event Publisher for z/OS



ELT on System z

InfoSphere Warehouse on System z

SQL Warehousing Tool

(SQW)




Source Systems

DB2 for z/OS

DB2 for z/OS IMS VSAM RDBMS

Data Warehouse Server

Cubing Services Engine

WebSphere App Server

Linux on System Z Partition / IFL

Design Studio

Admin Console

Windows / Linux

Application Server

Cognos 8 BI for System z

Excel

Third Parties / BPs

Client Layer•Design and admin client•BI / Reporting tools and apps

MQT Adviso

r

MQT Cube MetadataControl

DB

JDBC/DB2 Connect

JDBC/DB2 Connect

MDX

IE/Firefox

Eclipse

SQLJDBC/DB2 Connect

SQW Runtime

Administration



Design Studio



InfoSphere Warehouse Design Studio – Key features

• (IDE) Integrated Development Environment for DB2 Warehouse projects

• Integrated consistent and interoperable tools for:

• Connecting and browsing databases

• Exploring data

• Designing physical database models (reverse/forward engineering)

• Designing OLAP objects

• Designing data movement and transformation flows

• The platform is extensible (Eclipse based) and can be easily extended with third party or customer developed plug-ins



Getting Started – The Workspace

• A workspace is:

• A directory on the local file system where the projects (i.e. Metadata) created in the Design Studio are stored as XML files.

• The Design Studio GUI.

Metadata



The Business Intelligence Perspective• The Business Intelligence Perspective is the default perspective in the Design Studio.

• It contains the views which are useful during the development of a Data Warehousing project.

• Views can be moved/stacked by using drag and drop. They can be maximized by double-clicking on their title.

• View can be closed and reopened. To add a new view to the perspective, use the menu bar “Window -> Show View”

Data Project Explorer View

Data Source Explorer View

Outline View

Properties View

Data Output View

Problems View

Editor(s)

ObjectPalette



Data Source Explorer

• Define live jdbc connections to relational sources

• Could be nicknames if Federated Server installed

• Browse and work with objects in the live database

• Live connection required for many Design Studio operations• Reverse engineering data models• Test execution of flows• Sampling data



Team component• Version and configuration management

• Share resources with team via a repository

• The Design Studio includes a CVS repository provider

• Other repository providers can be used by installing the plugins provided by the repository vendors

• Rational Clearcase

• IBM CMVC

• Merant PVCS; Version Manager

• … see eclipse.org community page for a list of the available plugins.

RepositoryCheck in/out Check in/out



Integration with other IBM Tools – Eclipse Shell Sharing

• Share the core Eclipse components so that they are not duplicated between each Eclipse-based product. Shell sharing eliminates the need to install several Eclipse platforms for each product, thus saving disk space and eliminating duplication of components.

• Supported products that shell share with the Design Studio:

• Data Studio Developer (DSD) v2.1

• Data Studio Administrator (DSA) v2.1

• InfoSphere Developer Architect (IDA) v7.5.1

• Data Studio Optimization Expert for z/OS (DSOE) v2.1

• Rational Architect Developer (RAD) v7.5.1

• Rational Software Architect (RSA) v7.5.1



Physical Data Modeling



Data Models

• Two types of data models

• Logical – The “Business” representation of data without regard to underlying DBMS

• Physical – The representation of the data as it would appear in the DBMS

• Design Studio supports development of physical data models

• Metadata representation of actual objects that are present in the DBMS

• Create from scratch

• Reverse engineer from existing database or DDL

• Physical data model required to provide database metadata to other SQW components



Data modeling overview

• Design and modify database physical models (schema & storage design, as well as cubes, dimensions, hierarchies)

Key Features:

• Create a new DB design from scratch

• Reverse engineer from an existing Database Explorer connection or from DDL

• Create overview diagrams

• Modify the schema graphically or in the project tree

• Compare DB objects with each other or with objects existing in the database

• Analyze design (best practices, and dependencies), Validation

• Generate DDL script & Deploy

• Impact Analysis

• DB2 Storage Modeling: Table Space, Buffer Pool, Partition



Design Studio vs InfoSphere Data Architect• Design Studio includes a subset of functionality provided in InfoSphere Data Architect (IDA).

• Design Studio includes the physical data modeling and corresponding SQL generation capabilities to help you implement and modify to your physical model.

Logical data modeling Naming model Glossary model Other non-LUW advanced physical data modeling Web publishing and report Mapping editor UML - LDM transformation

Data Project ExplorerDatabase ExplorerComplete Physical Data Modeling for DB2Basic Physical Data Modeling for othersImpact Analysis

IDA

DesignStudio



Design Studio - Physical Data Model

Physical data model Database – one per model

Schema

Diagrams logical folder – one per schema

Diagram

SQL statements logical folder – one per schema

Table

Primary key column

Column

Primary key constraint

Unique constraintIndex

Data Project



Physical Data Model - Diagram

Hide/show palette

Palette – select the element to create on diagram

Geometric shapes

Drawing area



Embedded Data MovementSQL Warehouse Tool

(SQW)



SQL warehousing tool (SQW)• Build and execute intra-warehouse (SQL-based) data movement and transformation services

• Integrated Development Environment and metadata system

• Model logical flows of higher-level operations

• Generate code and create execution plans

• Test and debug flows

• Package generated code and artifacts into a data warehouse application

• Integrate SQW Flows and DataStage jobs

• Generate DB2 z/OS specific optimized SQL code (Data Flows)

• DB2 z/OS specific operators

• DB2 z/OS specific code generation

• Across query optimization

• Predicates pushdown and move around

• Unnecessary column reduction

• Staging table handled automatically by the engine

• Integrate SQL based flows with non-database activities (Control Flows)

• Sequence and manage activity flow



Data Flows



Data flows• Data flows are flow models that represent data movement and transformation

requirements

• SQW Codegen translates the models into repeatable, SQL-based warehouse building processes

• Data from source files and tables moves through a series of transformation steps then loads or updates a target table or creates a file



Would you rather type this ?

……………………….SELECT SALES.OU_IP_ID AS STR_IP_ID, SALES.PD_ID AS PD_ID, SALES.MSR_PRD_ID AS TIME_ID, SALES.C_D_MKT_BSKT_TXN_ID AS NMBR_OF_MRKT_BSKTS, SALES.SUM_NBR_ITM AS NUMBER_OF_ITEMS, CASE WHEN SALES.M_BK_PD_SUB_DEPT_NM IN ('BATH AND SHOWER', 'CAMERAS') THEN SALES.BKP_SUM_NBR_ITMXPRC * DECIMAL(MARTS.RAND1N(5) + 123) / 100 ELSE SALES.BKP_SUM_NBR_ITMXPRC * DECIMAL(MARTS.RAND1N(5) + 102) / 100END AS PRDCT_BK_PRC_AMUNT, CASE WHEN SALES.MIN_CG_PD_DEPT_NM IN ('TEEN BOYS', 'TEEN BOYS JEANS', 'DRESS FORMAL','MEN SHOES') THEN (DECIMAL(68 - MARTS.RAND1N(5)) / 100) * SALES.SUM_CG_NBR_ITMX_PRC WHEN SALES.MIN_CG_PD_DEPT_NM IN ('ELECTRICAL APPLIANCES','ELECTRONICS','COLORED TELEVISIONS','WOMEN SHOES') THEN (DECIMAL(77 - MARTS.RAND1N(5)) / 100) * SALES.SUM_CG_NBR_ITMX_PRC WHEN SALES.MIN_CG_PD_DEPT_NM IN ('HEALTH AND BEAUTY') THEN (DECIMAL(65 - MARTS.RAND1N(5)) / 100) * SALES.SUM_CG_NBR_ITMX_PRC ELSE (DECIMAL(72 - MARTS.RAND1N(5)) / 100) * SALES.SUM_CG_NBR_ITMX_PRC END AS CST_OF_GDS_SLD_CGS, SALES.SUM_NBR_ITMXSTM_PRC AS SALES_AMOUNTFROM SALES) …………



A simple “Skills”Star schema

would you rather describe your logic at a higher-level ?



… and have optimized SQL generated for you?

INSERT INTO OLAPANL.STAR_FACT_TABLE(ID, COMPANY_ID, TIME_ID, SKILL_DETAILS_ID, NB_SKILLS)WITH INPUT_04 (COMPANY_NAME, TIME, ID, SKILL_CAT, SKILL_DETAILS, SKILL_ID) AS (SELECT COMPANY_NAME AS COMPANY_NAME, TIME AS TIME, ID AS ID, SKILL_CAT AS SKILL_CAT, SKILL_DETAILS AS SKILL_DETAILS, SKILL_ID AS SKILL_IDFROM TXTANL.IT_SKILLS_ASKED INPUT_0281),IN4_07 (ID, SKILLS_PER_OFFER) AS (SELECT INPUT_04.ID AS ID, COUNT(*) AS SKILLS_PER_OFFERFROM INPUT_04 GROUP BY INPUT_04.ID)SELECT IN_07.ID AS ID, IN1_07.COMPANY_ID AS COMPANY_ID, IN2_07.TIME_ID AS TIME_ID, IN3_07.SKILL_DETAILS_ID AS SKILL_DETAILS_ID, DOUBLE(1) / DOUBLE(IN4_07.SKILLS_PER_OFFER) AS NB_SKILLSFROM TXTANL.IT_SKILLS_ASKED IN_07, OLAPANL.STAR_COMPANY IN1_07, OLAPANL.STAR_TIME IN2_07, OLAPANL.STAR_SKILL IN3_07, IN4_07WHERE (IN_07.SKILL_DETAILS = IN3_07.SKILL_DETAILS AND IN_07.COMPANY_NAME = IN1_07.COMPANY_NAME AND IN_07.TIME = IN2_07.TIME_DATE AND IN_07.ID = IN4_07.ID)



Data Flow Operators

Most operators same as in LUW versions but generate DB2 z/OS specific SQL

Sources & TargetsTable Source (Local and Remote)Table Target (Local and Remote)Data Set ImportData Set ExportSQL Query SourceData Station

SQL Transformation OperatorsSelect ListDistinctGroup ByOrder ByTable JoinWhere (Filter)Union

Warehouse OperatorsFact Key ReplaceKey LookupPivotUnpivotSplitter

Custom TranformationsCustom SQLDB2 Table FunctionsDB2 User Defined Functions



Data Flows that call DB2 z/OS utilities

Data Set Import Operator

Invokes the load utility to load data in a target table from a data set

Call DB2-Supplied stored procedure SYSPROC.DSNUTILU

Data Set Export Operator

Invokes the unload utility to unload data from a table to a BSAM sequential data set.


Cross Loader Operator

Invoke load utility to directly load the output of a dynamic SQL SELECT statement into a table




Execution Database

• The DB2 for z/OS subsystem to which the generated SQL of a dataflow is submitted

• Sources/Target tables are local when in the execution subsystem, otherwise remote

DB2A

DB2C

Linux

Admin Console/SQW Runtime

Execution database = DB2C

Distributed Database

Blue = Source TableGreen – Target Table

Control

Data



Local Source – Local Target

• Both Source and Target tables are in the same DB2 for z/OS subsystem

• SQL submitted to DB2C

• No data flows outside of DB2C

DB2A

DB2C

Linux





Control

Data

SQLprocessin

g



Remote Source Table via jdbc – Local Target

• Source table in remote database accessed as remote Table Source operator

• Java application runs on Linux connects to DB2A and DB2C

• Data flows throught Linux

DB2A

DB2C

Linux





Control

Data

SQLprocessin

g



Remote Source DB2 via Cross Loader – Local Target

• Source table in remote DB2 database accessed as remote Table Source operator but using Cross Loader Target operator

• Cross Load utility invoked at DB2C

• Uses DDF to access remote DB2 table over DRDA

DB2A

DB2C

Linux





Control

Data

SQLprocessin

g



Local Source Table– Remote Target via jdbc

• Source table in local DB2 z database and target is defined as remote Table Target operator


• Data flows throught Linux

DB2A

DB2C

Linux





Control

Data

SQLprocessin

g



Remote Source Table– Remote Target Table via jdbc

• Source and Target tables are remote


• Data flows through Linux

• All SQL processing is in DB2 z @ DB2C

DB2A

DB2C

Linux





Control

Data

SQLprocessin

g



Other data flow features

• Variables

• Variables can be used in Data Flows

• Defer the definition of certain properties until a later phase in the life cycle.• File Names• Table Names• Database Schema Names• Many more

• Generalize a Data Flow

• Subflows

• A subflow is a predefined set of operators that you can place inside a data flow.

• Useful as a plugin into multiple versions of the same or similar data flows

• Containers or building blocks for complex flows (division of labor)

• Blue ports represent subflow inputs and outputs



Control Flows



Definition and simple example

• A control flow is a flow model that sequences one or more data flows and integrates other data processing tasks and activities.

• Control flows are the unit of execution.

• This simple example processes two data flows in sequence. If they fail, e-mail is sent to an administrator:



Control Flow Operators• Task-oriented operators (Do things)

• Data flow

• Subprocess

• JCL Job

• Command (DB2 Shell/FTP)

• Secure Command

• Secure FTP

• Email

• Period row generator

• Load

• Unload

• Reorg

• Runstats

• Table Partition

• Stored procedure

• DataStage job sequence

• DataStage parallel job

• Custom SQL



Control Flow Operators

• Flow control operators (Manage things)

• Parallel Container

• Start

• End

• Iterator/End Iterator

• Continue

• Break

• Fail

• File wait

• Variable assignment

• Variable comparison

• File Write



CF Operator Introduction(1)

Exchange Operator

Switch the contents of a base table and its associated clone table.

Exchange operation is not supported when it runs against a DB2 z/OS version 8 database.

Table Partition Operator

Perform table partition operation

1. Adding a partition

2. Rotating partitions

3. Changing partition boundary

Runstats Operator

Update the system catalog statistics for DB2 for z/OS database through the DB2 RUNSTATS utility.





Reorg Operator

Reorganize a table space or an index for DB2 for z/OS database through the DB2 REORG utility.


Unload Operator

Unload data from an entire table space or select table, columns to the BSAM sequential data sets.


DB2 Online Utility Operator

Runs any DB2 for z/OS utility that can be invoked by the stored procedure DSNUTILU





Load Operator

Four load approaches1. Load from Z/OS data set

2. Load from cursor

3. Load from file on client side (Using FTP to transfer file to Z/OS data set)

4. Load from file on client side (Using FTP to transfer file to Z/OS BATCHPIPES data set)

Call DB2-Supplied stored procedure SYSPROC.DSNUTILU for 1,2,3 approaches, Call ADMIN_JOB_SUBMIT, ADMIN_JOB_QUERY, ADMIN_JOB_FETCH, ADMIN_JOB_CANCEL for 4 approach.

Command Operator (FTP)

Advanced Options Tab has been added ,user could specify following additional options for Z/OS file transfer:

1. Record length

2. Record format

3. Data transfer type




JCL Operator

JCL: a control language that is used to identify a job to an operating system and to describe the job's requirements.

JCL Operator works to submit a job, query the status of the job, fetch the output of a job and purge a job.

Support three scenarios

1. JCL on local machine

2. JCL on Z/OS side

3. New edited JCL

Call DB2-Supplied stored procedures :ADMIN_JOB_SUBMIT, ADMIN_JOB_QUERY, ADMIN_JOB_FETCH, ADMIN_JOB_CANCEL, ADMIN_DS_BROWSE



Deployment and Runtime



Deployment

Deploy / Install

Manage /

Execute

Production

DDL

Application Profile

EPG

Zip file

Design / TestPrepare

Application

Development

Deploy / Install

Manage /

Execute

Test

Deployment preparation is done in the Design Studio

Deployment is done via the Administration Console

The process of promoting a Warehouse Application from a development environment to Test and Production environments.




Administration Console – manage the runtime environment

• Deploy data movement applications

• Schedule, Execute, Monitor flows

• Define and manage cube servers

• Manage OLAP Metadata

• Assign cubes to cube servers

54



Admin Console - SQW

Manage database connections Deploy and manage SQW apps

Run and schedule Control Flows Monitor run instances



Contact Info – z Warehouse SWAT Team

• Mgr – Beth Hamel – [email protected]

• Andy Perkins – [email protected]

• Jonathan Sloan – [email protected]

• Sundari Voruganti – [email protected]

• Willie Favero – [email protected]

Documents

Do you ELT on z?