Fundamentals of SAP HANA the begining

Fundamentals of SAP HANA

Version 1.0

February 1st 2013

Anubrat / Joseph / Deepthi / Karthik

Agenda


HANA modeling

Extract data from HANA

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Agenda - Fundamentals of SAP HANA

What is SAP HANA

Integrating HANA into existing SAP Landscape

Replicating Data to HANA (Data Provisioning)

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What is HANA?

Running Head

Real-time solutions

● New accelerators and analytic content for powerful

analysis and reporting on big data

● New applications for highly innovative processes and

business models

Benefits

● Make smarter and faster decisions with complete

insight on large volumes of granular data

● React quickly with real-time analysis and reporting

● Unlock new opportunities with state-of-the-art analysis

● Invent new data-driven business models and renew

differentiating processes enabled by real real-time

insight

● Ensure quick time-to-value with solutions that you can

deploy faster

A platform for innovative, real-time analytics and applications

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SAP HANA - In-Memory Strategy

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Innovations driving HANA

Running Head

• SAP has used the recent innovations in HW technology and economics to launch a platform that supports development of in-memory business applications.

CPU •Multicore architecture•Massive parallel processing capabilities

Memory (RAM)• 64 bit address space• 100 GB/s data throughput• Lower cost

Hardware Innovations

Row + Column Storage

Compression

Partitioning

Insert only on delta

SAP Software Innovations

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Columnar Table• Reduce database latency and storage• Faster Aggregation time

Partitioning

• Ability to process data from single table across multiple CPUs

Innovations driving HANA

Customer Product Amount

A AAA 10

A BBB 20

B BBB 30

C AAA 40

Columnar Table

Customer Product Amount

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Architecture Overview

Index Server: • Contains the actual data stores and

the engines for processing the data. • Processes incoming SQL or MDX

statements

Preprocessor Server:• Analyze text data and extract the

information on which the text search capabilities are based

Statistics Server• Collects information about status,

performance and resource consumption

Name Server• Information about HANA Topology• Critical for distributed landscape

Calculation Engine• Execute user defined functions• User defined functions are broken

into logical dataflow steps that can be executed in parallel

Languages Supported• SQL Script • Language R• Business Function Library• Predictive Analysis Library

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Integrating HANA into existing SAP Landscape

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Side by Side Scenario

SAP HANABusiness

WarehouseSAP Business

Suite

Traditional DB

Data Services (DS)

Direct Connector (DXC) DS / DXC

SAP Landscape Transformation (SLT)

ABAP Data Base Connector (ADBC)

• Agile Data Marts• Operational Data Marts• COPA Accelerators• SAP Sales and Operations Planning

Applications developed using Side by Side

Architecture

• HANA is used as a secondary database and used as an accelerator

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HANA is used as primary persistence

Business Warehouse

SAP Business Suite – ECC, CRM, SCM

HANA DB HANA DB

• SAP BW on HANA• Business suite on

HANA

Applications using HANA as Primary

Persistence

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SAP HANA Extended Application Service

Application logic directly built into HANA to develop Web Based Application using ODATA or XMLA interfaces or SAPUI5 with server side coding

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Data Provisioning

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SAP Landscape Transformation (SLT)

Application Tables

Application Tables

Trigger Based Recording

Replication Engine

HANA Studio

• SAP LT Replication Server (SLT) is positioned for real-time data replication from SAP and non-SAP sources (SAP supported data bases only).

• Mainly recommended for real-time data replication business scenarios.

RFC DB Connection

Source System SAP or non-SAP System

SLT Server SAP HANA

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Replication from SAP sources system

Application LoggingTables Tables

Application Tables

Read ModuleStructure mapping &Transformation

SAP Source System

Write Module

DB Trigger

SLT Server SAP HANA

RFC

DB Connection

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Multi-system support

System A

Source System SAP HANA

System BSchema 1Schema 2

System A

System B

System A

System A

Schema 1

Schema 2Source System SAP HANA

System A

Source System SAP HANA

System B Schema 1

System ASystem A

System A

Schema 1

Schema 2SAP HANA SystemSource System

• SLT supports options to connect multiple source systems to single HANA or Multiple HANA

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Information Modeling with HANA

AgendaGraphical Modeling with HANA

When to use SQLSCRIPT

What is SQL SCRIPT

Purpose of SQLSCRIPT

SQLSCRIPT overviewDeclarative approach Data access operators ,CE functions, procedures

Integration with Hana Modeler

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Avoid Bottlenecks

Rethink Paradigms

ApplicationLayer

DatabaseLayer

Calculation

Calculation

Today Future

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Modeling for SAP HANA using SAP HANA Studio

Step 1: Attribute View

Separate Master Data Modeling from Fact Data

– Build the needed master data objects as ‘Attribute Views’

Step 2: Analytical ViewCreate Cube-like view by joining attributes view to Fact data Build a ‘Data Foundation’

based on transactional table Join attribute views to data

foundation

Step 3: Calculation ViewIf joins are not sufficient create a Calculation View that is something that looks like a View and has SQL Script inside Composite view of other views (tables,

re-use join, OLAP views) Consists of a Graphical & Script based

editor SQLScript is a HANA-specific functional

script language

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Calculation ViewGraphical Mode

– No SQL coding required

– Union, Join, Projection nodes provided

– Join Column Tables (Analytical Views)

The set of SQL extensions for the SAP HANA database which allow developers to push data intensive logic into the database is called SQLScript.

These extensions are keys to avoiding massive data copies to the application server and to leverage sophisticated parallel execution strategies of the database.

SQLScript supports stored procedures, which provides enhanced control flow capabilities and is positioned to be more suitable for pushing complex parts of application logic to the database.

It can meet some simple requirement for reporting, like join, aggregation, etc. When it comes to data mining and statistic analysis, SQLScript is not suitable for implementing complex algorithms.

SQL Script: Motivation and goals

For Internal Purpose Only

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Differences between SQL & SQLSCRIPT

SQLScript SQL

Bypass SQL processor interact with CE.

Yes (via CE functions) No

Consists of DDL & DML statements

Yes Mainly only this

functionality

Compilation One time only Every time

execution plan

Stored in memory in terms of calculation models

will be created at runtime

SQL

• extend SQL queries to contain high level calculations

• Conditional Evaluation• Scalar Expressions• Functional Loops• Declarative & Imperative features

SQLSCRIPT

• Data Definition Language DDL• Interactive Data Manipulation

Language (Interactive DML)

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SAP HANA: SQL Script

Compared to plain SQL queries, SQL Script has the following advantages:

Functions can return multiple results, while a SQL query returns only one result set.

Complex functions can be decomposed into smaller functions. This enables modular programming, reuse and a better understandability by functional abstraction. For structuring complex queries, standard SQL only allows the definition of SQL views. However, SQL views have no parameters.

SQL Scripts supports local variables for intermediate results with implicitly defined types. With standard SQL, it would be required to define globally visible views even for intermediate steps.

SQL Script has control logic such as if/else and throw/catch that is not available in SQL

SQL Script: Extensions Declarative Extension

Table Types.

Functional Extension, FSP.

SQL Script/CE Built in Functions.

Functional Extension

I

Imperative Extension

Control Structures, Cursor, Dynamic SQL.

Declarative-Logic


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Allows for the definition of new Table Types Similar to a database table but do not have an instance Used to define procedure parameters Created when the procedure is activated

SQLScript - Table types

Functional-Style Procedures

Procedures can have multiple input parameters and output parameters Side Effect free procedures – Declare a procedure as READ ONLY

READS SQL DATA Read-only procedures can only call other read-only procedures.

Advantages

calculation and transformations can be parameterized and reused.

define common sub expressions.

improves the readability of the SQLScript code.

Functional Extension – Concept


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CREATE PROCEDURE [schema.]name [({IN|OUT|IN OUT}

param_name data_type [,...])]

implementation language is by default SQLSCRIPT.

specify the security mode – SQL SECURITY.

READS SQL DATA - Read-only procedures can only call other read-only procedures.

Creating and Invoking PROCEDURES

Activated procedure can be called by other

procedures

Name of procedure:

“schema”.”<proc>”

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DemoProcedure

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Functional Extension - Implementing Functional logic

The declarative nature to define business logic might require some deeper thought when specifying an algorithm, but it gives the SAP HANA database freedom to optimize the data flow

A table variable is bound to tabular value when a procedure is called and a tabular IN parameter is bound to the value of its argument

Table variables are bound using the equality operator. recursion is not possible.

Each statement specifies a transformation of some data (e.g. by means of classical relational operators such as selection, projection) and binds the result to a variable

Sequence of statements

Data flow - Free of side effects

Table Variables

Binding of variables

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Binding of table type variables

lt_expensive_books = SELECT title, price, crcy FROM :it_books WHERE price > :minPrice AND crcy = :currency;

Bound

an IN parameter of a table type.

variables of type table in the FROM clause which were bound by an earlier statement

ot_sales = CE_UNION_ALL(:lt_on_sale, :lt_cheap_books);

Calculation engine plan operators can be used to assign variable as follows:

Bound

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SqlScriptCompiler

SQLScript - Code example

The SQL Script in the example above defines a table function which has two scalar input parameters and two output parameters of type table.

The first line contains a SQL query Q1 which identifies big publishers based on the number of books they have published (using the input parameter cnt).

Afterwards, detailed information about these publishers along with their corresponding books is determined in query Q2. Finally, this information is aggregated in two different ways in queries Q3 (aggregated per publisher) and Q4 (aggregated per year), respectively. The resulting tables constitute the output tables of the function.

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Select statements are executed in parallel unless: oLocal scalar parameters and variables are used in the procedureoRead/Write procedures or DML/DDL operations are executedo Imperative Logic is used within the procedureoSQL statements are used that are not assigned to a variable

The following 3 queries are processed in parallel:

BEGIN p_out1 = select * from <schema>.<TAB1>;

p_out2 = select * from <schema>.<TAB2>; p_out3 = select * from <schema>.<TAB3>;

END;

SQLScript - Parallel processing

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• bind a column table or a column view to a table variable

• CE_COLUMN_TABLE,CE_OLAP_VIEW

Data Source Access operators

• bypass the SQL processor during evaluation and to directly interact with the calculation engine.

• CE_JOIN,CE_LEFT_OUTER_JOIN,CE_PROJECTION,CE_UNION_ALL

Relational operators

• crucial business functions inside the database kernel.

• CE_VERTICAL_UNION,CE_CONVERSIONSpecial extensions

Calculation engine plan operatorsThey constitute an alternative to using SQL statements as their logic is directly implemented in the calculation engine, i.e. the execution environment of SQLScript.

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SQLScript CE Build In Functions Operators

SQL CE-Build In Function

SELECT on column table

out = SELECT A, B, C from "COLUMN_TABLE" out = CE_COLUMN_TABLE("COLUMN_TABLE", [A, B, C])

SELECT on attribute view

out = SELECT A, B, C from "ATTRIBUTE_VIEW"

out = CE_JOIN_VIEW("ATTRIBUTE_VIEW", [A, B, C])

SELECT on olap view out = SELECT A, B, C, SUM(D) from "ANALYTIC_VIEW" GROUP BY A, B, C

out = CE_OLAP_VIEW("ANALYTIC_VIEW", [A, B, C]);

WHERE HAVING out = SELECT A, B, C, SUM(D) from "ANALYTIC_VIEW" WHERE B = 'value' AND C = 'value'

col_tab= CE_COLUMN_TABLE("COLUMN_TABLE"); out = CE_PROJECTION(col_tab, [A, B, C], ' "B" = ''value'' AND "C" = ''value'' ');

GROUP BY out = SELECT A, B, C, SUM(D) FROM"COLUMN_TABLE" GROUP BY A, B, C

col_tab= CE_COLUMN_TABLE("COLUMN_TABLE"); out = CE_AGGREGATION( (col_tab, SUM(D), [A, B, C]);

INNER JOIN out = SELECT A, B, Y, SUM(D) from "COLTAB1" INNER JOIN "COLTAB2" WHERE "COLTAB1"."KEY1" = "COLTAB2"."KEY1" AND "COLTAB1"."KEY2" = "COLTAB2"."KEY2"

out = CE_JOIN("COLTAB1","COLTAB2", [KEY1, KEY2], [A, B, Y, D])

LEFT OUTER JOIN out = SELECT A, B, Y, SUM(D) from "COLTAB1" LEFT OUTER JOIN "COLTAB2" WHERE "COLTAB1"."KEY1" = "COLTAB2"."KEY1" AND "COLTAB1"."KEY2" = "COLTAB2"."KEY2"

out = CE_LEFT_OUTER_JOIN("COLTAB1","COLTAB2", [KEY1, KEY2], [A, B, Y, D])

SQL Expressions out = SELECT A, B, C, SUBSTRING(D,2,5) FROM "COLUMN_TABLE"

proj_tab = CE_COLUMN_TABLE("COLUMN_TABLE"); out = CE_PROJECTION( :proj_tab, ["A", "B", "C", CE_CALC('midstr("D",2,5)', string) ]);

UNION ALL col_tab1 = SELECT A, B, C, D FROM "COLUMN_TABLE1"; col_tab2 = SELECT A, B, C, D FROM "COLUMN_TABLE2"; out = SELECT * FROM :col_tab1 UNION ALL SELECT * FROM :col_tab2;

col_tab1 = CE_COLUMN_TABLE("COLUMN_TABLE1",[A,B,C,D]); col_tab2 = CE_COLUMN_TABLE("COLUMN_TABLE2",[A,B,C,D]); out = CE_UNION_ALL(:col_tab1,:col_tab2);

Integration with ModelerCalculation View

Procedures

Declarative-Logic


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Read-only procedure can be created

Following restrictions will apply for the procedures created in the SAP HANA Modeler

– IN (Input) parameters can be of scalar or table type

– OUT (Output) parameters must have table type

– Tables types required for the signature are generated automatically

Modeling: ProceduresIntegration with SAP HANA Modeler

Activated procedure can be called by other procedures

Name of procedure:

“_SYS_BIC”.”<package-name>/<proc>”

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DemoCalculation View – SQLScript (CE Operators)

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RecommendationsHow to build content

1: Column Table 2: Analytical View 3: Calculation View (SQL)

4: Calculation View (CE Functions)

UsageUsed for simple applications and showcases.

Used for analytical purposes where reading operations on mass data is required.

Used for simple calculations where only a few fields are used.

Used for analytical purposes that cannot be expressed using Attribute or Analytical views. Perform statements against existing Attribute & Analytical Views.

ProsNo additional modeling required. For most clients easy to consume.

Very high performance on SELECT. Supported by modeling. Well optimized.

Building calculation views via SQL syntax is easy.

Client queries can be well optimized and parallelized. Usually better performance results than SQL.

Cons

No support for analytical privileges, multi language and client handling. Complex calculation and logic shifted to client side. In general low performance.

Limitations in regards to functions.

Client queries can be less optimized and could significantly be slower compared to other models.

Syntax is different in compared to well-known SQL Language.

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Extract data from HANA

Agenda Application Accelerator

ABAP Database Connectivity (ADBC)

SAP HANA Extended Application Services (XS Engine)

HANA Full Text Search Capabilities

Application Accelerator - Scenario

Application Accelerator - Features Side-by-side scenario where SAP HANA data base act as a secondary data base along with the

traditional data base

Instrumented application server can run ERP application without modifications

Applications areas that need performance improvement is continuously replicated in to the HANA data base with the help of SLT. Tables, DB views, main program and batch jobs can be configured for replication.

Configuration is done via program RDA_MAINTAIN in table RDA_CONFIG.

Application Accelerator - Configuration

RDA_CONFIG table maintenance

RDA_CONFIG table sample entries

Application Accelerator – Installation Procedure

• SAP Business Application Accelerator – User Documentation - SAP note 1694697.

• Add On package needs to be installed (SAP Note 1713986 and 1716826)

• Upgrade SAP Kernel of AS to 7.2.1

• Activation of SAP Business Application Accelerator need to be done by enabling the profile parameter as rsdb/rda = on in transaction RZ11.

• Data needs to be replication from SAP Business suite system to HANA environment – SLT is the replication mechanism suggested by SAP here.

• Set secondary database connection for the scenario using report RDA_MAINTAIN

ABAP Database Connectivity (ADBC)• Object-based ABAP API for programming relational database access

• Access to entire SQL functionality of underlying DB system

• Dynamic creation and execution of native SQL statements via respective API methods

• Clean concept for multiple DB connections (connections are associated to connection objects)

• ADBC is the mechanism to connect to any secondary data base and is not specific to the HANA DB

• Exception handling – API methods have well-defined exceptions that can be handled

ADBC – Features

ADBC – Configuration

Data base table DBCON

Transaction DBCO to maintain table DBCON

Transaction DBA_COCKPIT to maintain table DBCON and test the secondary data base connection

ADBC – Your Tools

CL_SQL_CONNECTION GET_CONNECTION – Opens a Connection to a Database CLOSE – Closes an Open Database Connection GET_CON_NAME – Returns the Connection Name Entered in the DBCON ROLLBACK and COMMIT

CL_SQL_PREPARED_STATEMENT / CL_SQL_STATEMENT EXECUTE_DDL – Execute a DDL Operation (For Example, CREATE TABLE) EXECUTE_QUERY – Execute an SQL Query EXECUTE_UPDATE – Execute a DML Operation (INSERT, UPDATE, DELETE) PREPARE / CLOSE – Prepare / release an SQL Statement SET_PARAM - Set an Input/Output Parameter (variants for CLOB, BLOB, STRUCT) PREPARED_QUERY, PREPARED_UPDATE - Execute a Prepared Query / DML Operation

CL_SQL_RESULT_SET SET_PARAM – Set reference to output parameter (variants for CLOB, BLOB, STRUCT, TABLE) NEXT – Read next record in the resulting set NEXT_PACKAGE – Read next set of records for internal tables

Go through the classes in class builder SE24

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Demo

Calling SQL Procedure using ADBC

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Demo

SAP HANA Extended Application Services (XS Engine) A light weight application server that is deeply integrated in to the HANA DB

Web based data access via http

Build stand alone applications (mobile, browser) without the need of an additional application server in the landscape

Lower TCO

Enables better performance due to the tight integration with data

Data Access from SAP HANAODATA Services

for building light weight stand alone web applications on SAP HANA

a REST based web protocol for querying and updating data

defines operations on data using HTTP commands (for example, GET, PUT, POST, and DELETE)

data is transferred over HTTP using the Atom or JSON format

XMLA Interface for building light weight stand alone web applications on SAP HANA

for OLAP processing using Multi Dimensional Expression (MDX) Queries

uses SOAP based XML APIs to exchange analytical data between a web based application and the Hana database

Server-Side JavaScript make use of a powerful set of specially developed API functions

interact with Sap HANA XS runtime environment

directly access SAP HANA database capabilities

unlike OData services and xmla, server side java scripts not only enables you to expose, but also to update, insert and delete data

Full Text Search Capabilities One major benefit of the column store technique in SAP HANA is fast search

access to character based columns.

Text search is integrated in to HANA SQL using ‘CONTAINS’, which can be used in the WHERE clause of a select statement.

Types of text search in SAP HANA Linguistic search Multi column search Fuzzy search

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Demo

Fundamentals of SAP HANA the begining

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Transcript of Fundamentals of SAP HANA the begining