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SAP HANA 1.0Modeling fundamentals
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Agenda
Modeling Fundamentals & Best Practices
Analytical View & Calculation View Fundamentals
Design time vs. Runtime objects
General Modeling Principles
Modeling new functionality
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Attribute Views (Dimensions, Time, Hierarchy, Derived)
Analytical Views (Facts/Star Schemas)
Calculation Views (Composite views, Modeled or Script)
Transportable design time artifacts stored in the repository
Database objects (Column store views) are generated from these
development artifacts
L a n g
a u g e
Main procedural language of the SAP HANA database
Push data intensive operations into the database
Utilized in Calculation Views and Procedures
Read-Only procedures (Calculation views, highly optimized,
potential of parallelism)
Read-Write procedures (cursors, loops, conditions, transactions)
SQL
Script
SAP HANA Modeling Fundementals
M o d e l i n g
Views
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SAP HANA Modeling Best Practices
Analytical View Attribute View Column Table
Calculation View
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Agenda
Modeling Fundamentals & Best Practices
Analytical View & Calculation View Fundamentals
Design time vs. Runtime objects
General Modeling Principles
Modeling new functionality
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SAP HANA Analytical View
Star schema consist of one fact table
containing the key figures
Dimensions describe the key figures
and enrich the data
Slicing and dicing is a feature whereby
users can take out (slicing) a specificset of data and view (dicing) the slices
from different viewpoints
Cardinality in star schemas is generally
N:1 fact to dimension
Joins in star schemas are generally Left
Outer Joins
Analytical models are highly optimized
for aggregating mass data
Analyt ical View
Attr ibute View
Dimension
Left Outer
Fact Table
N N
1
11
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SAP HANA Calculation View
Several options available
Modeling using the Graphical Modeler
Write SQL Script and use CE Functions
Write SQL Script and using SQL
Suggested option = Graphical Modeler
No SQL or SQL Script knowledge required
Built-in Union Constant support
Graphical & SQL Script + CE Functions
Result in similar performance gains (e.g.
Field pruning, Parallelization, join
ommision)
Standard SQL
Does not provide field pruning and can be
less optimized. Useful for POCs and rapid
prototyping
Graphical
CE Functions
SQL
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Agenda
Modeling Fundamentals & Best Practices
Analytical View & Calculation View Fundamentals
Design time vs. Runtime objects
General Modeling Principles
Modeling new functionality
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SAP HANA Design Time vs. Runtime Time Objects
© SAP AG 2011
Column View
Activate
Activation of models creates an
executable, optimized Column
(database) view of the model
Front end’s queries column views and
as a result a specific execution plan is
instantiated based on fields requested
Un-used fields are pruned; un-usedtables joins are omitted; filters are
pushed down
Attributes are retrieved and Measures
are calculated in parallel
Design time Model
SELECT PERIO, VKORG, SUM(CM1)
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Agenda
Modeling Fundamentals & Best Practices
Analytical View & Calculation View Fundamentals
Design time vs. Runtime objects
General Modeling Principles
Modeling new functionality
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SAP HANA General Modeling Principles
Column
Store
Analytical
Views
Attribute
Views
Calculation Views
Client / Application
A B C D
A B C D G Y
A G Y
A G Y Z
Filter data amount as early as possible in the lower layers(CONSTRAINTS, WHERE Clause,Analytical Privileges..)
Aggregate data records (e.g usingGROUP BY, reducing Coulmns)
Avoid transfer data of large resultsets between the HANADB and client application
- Do calculation after aggregation.
- Avoid Complex expressions (IF, CASE, ... )
Join on Key Columns or IndexedColumns
Avoid calculations beforeaggregation on line item level
Reduce data transfer between views
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SPART MATNR WERKS KWMENG
ABC DPC1017 100 60
FILTERS pushed
down
SELECT SPART, MATNR, WERKS,
SUM(KWMENG) FROM VIEW WHEREWERKS = ? AND MATNR = ?
SELECT
SPART
SUM(KWMENGA)
SUM(KWMENGB)
SUM(KWMENGC)
SUM(TOTAL)
FROM CALCVIEWWHERE MATNR =
DPC1017
GROUP BY SPART
OLAP AOLAP AOLAP A
SPART PLANT A PLANT B PLANT C TOTAL
ABC 60 60 0 120
SPART MATNR KWMENGA KWMENGB KWMENGC
ABC DPC1017 60 0 0
ABC DOC1017 0 60 0
SPART MATNR WERKS KWMENG
ABC DPC1017 1000 60
SPART MATNR WERKS KWMENG
- - - -
SAP HANA Basic Modeling Principle (Aggregate, filter, pushdown)
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Agenda
Modeling Fundamentals & Best Practices
Analytical View & Calculation View Fundamentals
Design time vs. Runtime objects
General Modeling Principles
Modeling new functionality
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SAP HANA – Variables & input parameters
Variables and Parameters are usually entered
manually by the user using UI Prompts
Variables are bound to attributes and used to filter
using WHERE clauses (Single, Interval, Range)
Input Parameters are passed by Placeholders and
used in Formulas (Attribute, Currency, Date,
Static List) It is the task of the client to convert the user input
into either WHERE clause or Placeholders when
accessing the data
Devine Variable
Use Variable as a Prompt
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SAP HANA - Aggregation Node
A new Aggregated Columns folder is visible in the output of a Graphical Calculation View
The definition of the specific aggregation type is maintained in the property view
Only columns of numerical & date data types are allowed (like for measures)
The calculation and filtering occurs after the aggregation
Aggregation
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SAP HANA - Exceptional Aggregation
A new Counters folder is visible in the output view of a Graphical Calculation view
Ability to define Count Distinct functions based on specific Dimensions (1..N)
Count
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SAP HANA - Optional Measures
Within Calculation views measures can now be made optional
The output node instead will be a projection node
Models should be simple SQL views that do not automatically aggregate the measures
Multidimensional
Reporting Flag
The output node does not offer any measures
(or hierarches) but just attributes
The Calculation view is not consumable via
MDX (Explorer / AAO)
The Calculation view is only consumable via
SQL
To disable measures set the Multidimensional
Reporting flag accordingly within the
properties view
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SAP HANA - Join Suggestions
The goal is to simplify modeling by proposing tables and suggesting joins
This features is available in both Attribute and Analytical Views
Prerequisite: table DD08L needs to exist in HANA
Select Propose Tables, then choose the required tables
Highlight all the tables and select Suggest Joins
Propose Tables
Suggest Joins
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SAP HANA - Analytical Privi leges
In addition to equal and between SP4 provides GE (greater equal), LE (less equal) and
CP (contains pattern), GT (Greater Than) and LT (Less Than)
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SAP HANA - Intellisense
Intellisence assistance provided in SQL editor and function editors
Provides both the function Syntax details and code Examples
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SAP HANA - Multi User Support
The same object will not exist in the inactive workspace of several users
Only one inactive version of any object is allowed
In addition there is now functionality to discard an inactive version and to return it to the
active status
System Privileges - REPO.WORK_IN_FOREIGN_WORKSPACE required
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SAP HANA - Union
Constant Union enhancement
Allow to add unmapped columns that
only have a constant mapping
Additionally it is required to specify a
data type
Example. The Planned vs. Actual
indicator can now be set in the Unioninstead of defining the flag within a
Projection node
Constant Union
Manage Mapping
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SAP HANA – Intermediate Data Preview
Calculation View enhancement
Allows easier design and prototyping
Requires that the View has been
activated
Example: Data Preview before and
after filtering a Join
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SAP HANA – Decision Tables
SQLScript Enhancement
Graphical user interface to simplify
changing data
Supports Tables and Analytical Views
Example: Updating prices based on
attribute and measure conditions
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SAP HANA – Attribute views
Table Al iases
Add the same table to an Attribute View multiple times with the assignment of an alias.
Upon selecting a table twice the system will prompt for an alias.
Hide attributes
Functionality to hide attributes has
been extended to attribute views
from within the context of an
analytic view.
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SAP HANA - Auto Documentation
Generate the metadata documentation for information models and packages created on
SAP HANA systems
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