SAP HANA. José González Seco SAP AG Junio 2013

Transcripción

1 SAP HANA José González Seco SAP AG Junio 2013

2 Cláusula de exención de responsabilidad legal Esta presentación resume la orientación general de nuestro producto y no debe servir como base para tomar una decisión de compra. Esta presentación no está sujeta al acuerdo de licencia ni a cualquier otro acuerdo con SAP. SAP no tiene ninguna obligación de conseguir ningún tipo de negocio descrito en esta presentación ni de desarrollar ni lanzar ninguna funcionalidad mencionada en esta presentación. Esta presentación, la estrategia de SAP y los posibles desarrollos futuros están sujetos a cambios y pueden ser modificados por SAP en cualquier momento y por cualquier motivo sin aviso previo. Este documento se proporciona sin garantía de ninguna clase, ni expresa ni implícita, incluyendo pero sin limitarse a las garantías implícitas de comerciabilidad, idoneidad para un determinado propósito, o cumplimiento. SAP declina toda responsabilidad por errores u omisiones en este documento, excepto si han sido causados por SAP de forma intencionada o por negligencia grave SAP AG. All rights reserved. 2

11 SAP HANA Estructuras de Datos Order Country Product Sales 456 France corn Italy wheat Italy corn Spain rice France corn Italy wheat Italy corn Spain rice 800 Base de Datos tradicional France Italy Italy Spain corn wheat corn rice SELECT Country, SUM(sales) FROM SalesOrders WHERE Product = corn GROUP BY Country SAP HANA: orden por columnas 2013 SAP AG. All rights reserved. 12

12 SAP HANA Compresión basada en Diccionario Column Name (uncompressed) Miller Jones Millman Zsuwalski Baker Miller John Miller Johnson Jones Column Name (dictionary compressed) Value-ID sequence One element for each row in column N Value IDs point into dictionary Dictionary N Baker Jones John Johnson Miller Millman Zsuwalski sorted Value ID implicitly given by sequence in which values are stored Value 2013 SAP AG. All rights reserved. 13

14 SAP HANA Paralelismo a todos los niveles Multiple sesiones de usuarios Operaciones paralelas dentro de un query ( T1.A T2.B ) Particionamiento de los datos en uno o más hosts Segmentación horizontal (en columnas) y agregación en paralelo Multi-threading a nivel del procesador core de Intel Vector Processing host 1 host 2 host SAP AG. All rights reserved. 15

16 SAP HANA Database Components Servidor de Índices: Contiene los datos y los motores Servidores adicionales Preprocessor: Análisis de datos de texto Estadísticas: Recoge el estatus, el rendimiento y el consumo de recursos Servidor de nombres: Contiene la información sobre la topología del sistema Sistema XS: Facilita a otras aplicaciones el acceso a los modelo internos de la base de datos 2013 SAP AG. All rights reserved. 17

17 SAP HANA Database Multi-Engine for Different Application Needs Business Applications Connection and Session Management SQL SQL Script MDX WIPE (Graphs) FOX (Planning) Authorization Manager Calculation Engine Optimizer and Plan Generator In-Memory Processing Engines Execution Engine Transaction Manager Metadata Manager Relational Engine (Row and Column Store) Graph Engine Text Engine Persistency Layer Logging and Recovery Page Management 2013 SAP AG. All rights reserved. 18

19 Usage Scenarios Escenarios de uso Cómo aprovechar SAP HANA

20 Modelos Analíticos en HANA Experiencia en Clientes Data Compression with SAP HANA Traditional DB HANA 41,9 6, Data Volume (GB) Cliente en el secto Banca Aceleración de Queries Sin cambios en el Schema Los mismos datos El mismo SQL Beneficios inmmediatos Query Run-Time Comparison Query 3 Query 2 Query , , , Query Run-Time (seconds) 6.3x Compresión de Datos 369x Mejora en la velocidad media de los Query Traditional DB HANA 2013 SAP AG. All rights reserved. 21

21 Data Mart Operacional Experiencia en Clientes We use about 140,000 different materials, which creates several million records per year which have to be analyzed to determine which materials should go to which locations. The possibility to work directly with operational data in a real time mode with large volumes of our data is a tremendous opportunity. CIO, Oil and Gas Company 16 horas antes de HANA 2 minutos Con HANA (HANA processing time 3 sec) 2013 SAP AG. All rights reserved. 22

22 Acelerador CO/PA Experiencia en Clientes SAP CO/PA Accelerator ERP w/o HANA ERP with HANA Acceleration factor vs. ERP EBIT with commodity sales initial report EBIT with commodity sales drilldown by alphacode Cost allocation initial report Cost allocation drilldown by sending cost center 280 sec 7 sec (DB 2,8 sec)* 620 sec 5 sec (DB 2,9 sec)* 45 sec 5 sec (DB 3,4 sec)* 260 sec 7 sec (DB 3,3 sec)* Drilldowns adicionales son ahora posibles por ejemplo por cliente y artículo El rendimiento del drilldown no depende de la disponibilidad de un nivel de agregación concreto porque cada selección se hace siempre a nivel de item Reports de ERP reports mejoran sus prestaciones sin cambios en la definición del report *DB measurements show the selection runtime on HANA. Non-DB time is likely to decrease if the application server runs on production hardware SAP AG. All rights reserved. 23

23 Rendimiento de BW on HANA ,39 Data Load Improvement Loading speed improvement DSO Activation Factor 4, DSO Activation Factor Query Performance Factor 8 26, Query Performance factor 2013 SAP AG. All rights reserved. 24

26 Acelera los procesos de negocio Mejora el rendimiento a través de la operaciones en memoria Tradicional Cálculo Nivel de aplicación Real-Time Platform Nivel de la base de datos Cálculo SAP HANA Los cálculas son transferidos a la base de datos Agregación dinámica Extensibilidad dinámica 2013 SAP AG. All rights reserved. 27

27 La mejor suite sobre la plataforma con mejor rendimiento Unificación de procesos OLAP y OLTP: de la visión a la realidad Multi-channel Unified User Experience SAP Business Suite SAP Business Warehouse New SAP Apps Partner Apps SAP HANA Application Services App Server I Planning & Calculation Rules I Business Function Libraries Streams Processing Database Services Virtual Data Model Operational (OLTP) I Analytics (OLAP) I Predictive Text Search Synchronization Services Replication Services I ETL I Hadoop, R 2013 SAP AG. All rights reserved. 28

37 Gracias! Contact information: José González Seco SAP AG

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