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  • Before we get into what Netezza appliances are, let’s agree on what appliances are in general Appliances—ie black-box solutions—are commonplace in the IT industry We are all familiar with how they have simplified operations and revolutionized entire markets With networking appliances, even the most incompetents when it comes to IT can create a multi-user network in their homes in a matter of minutes The iPod is a great example of an appliance that simplified and revolutionized digital entertainment instead of using a PC to do the same function These appliances have some common attributes that make them very attractive compared to the old way of doing things They do only one thing, but do it better than any alternative They are plug-and-play, with a simple interface that anyone can operate And they are generally much cheaper than the alternative
  • Constant 2TB per hour loads with little adverse impact on queries. Opportunity: move from overnight batch loads to trickle-feeds as events occur. Wide range of complementary vendors For Oracle customers – move from row-based PL/SQL to set-based Extract – Load – Transform in-place of ETL. AOL example replace Sun / Oracle ETL stages Saves more than 7 million dollars a year Data integration partners support this “push-down processing” technique.
  • Once loaded – data is available There are no indexes and aggregates to update before data can be queried Partnerships with all major BI vendors While SQL-based reports are common analytics using tools such as SAS and SPSS derive greater value from the same data. I’ll now investigate TwinFin’s in-database analytics
  • A key component of Netezza’s performance is the way in which its streaming architecture processes data. The Netezza architecture uniquely uses the FPGA as a turbocharger … a huge performance accelerator that not only allows the system to keep up with the data stream, but it actually accelerates the data stream through compression before processing it at line rates, ensuring no bottlenecks in the IO path. You can think of the way that data streaming works in the Netezza as similar to an assembly line. The Netezza assembly line has various stages in the FPGA and CPU cores. Each of these stages, along with the disk and network, operate concurrently, processing different chunks of the data stream at any given point in time. The concurrency within each data stream further increases performance relative to other architectures. Compressed data gets streamed from disk onto the assembly line at the fastest rate that the physics of the disk would allow. The data could also be cached, in which case it gets served right from memory instead of disk. The first stage in the assembly line, the Compress Engine within the FPGA core, picks up the data block and uncompresses it at wire speed, instantly transforming each block on disk into 4-8 blocks in memory. The result is a significant speedup of the slowest component in any data warehouse—the disk. The disk block is then passed on to the Project engine or stage, which filters out columns based on parameters specified in the SELECT clause of the SQL query being processed. The assembly line then moves the data block to the Restrict engine, which strips off rows that are not necessary to process the query, based on restrictions specified in the WHERE clause. The Visibility engine also feeds in additional parameters to the Restrict engine, to filter out rows that should not be “seen” by a query e.g. rows belonging to a transaction that is not committed yet. The Visibility engine is critical in maintaining ACID (Atomicity, Consistency, Isolation and Durability) compliance at streaming speeds in the Netezza. The processor core picks up the uncompressed, filtered data block and performs fundamental database operations such as sorts, joins and aggregations on it. It also applies complex algorithms that are embedded in the snippet code for advanced analytics processing. It finally assembles all the intermediate results together from the entire data stream and produces a result for the snippet. The result is then sent over the network fabric to other S-Blades or the host, as directed by the snippet code.
  • We do not have indexes. They are not an option, they simply do not exist. There is no disk administration or SA administraion. Day 2, the customer has a pool of disk performant ready. Upgrades are performed by Netezza as standard maintenance tech support call. Does Oracle help you go from 9i to 10g? Instead of spending time and effort on tedious DBA tasks, use the time for higher BUSINESS VALUE tasks: Bring on new applications and groups Quickly build out new data marts Provide more functionality to your end users
  • Traditional architectures are much more compicated then just Stoarge + HW + RDBMS. There are multiple hops for the data. Mutliple areas of tuning. Either the customer does this themselves or pays someone to do it.
  • As data volumes grow, oracle complexity increases. As new indexes are created in oracle, you break existing reports. All of this (indexes, partitioing) is an attempt to out guess the user’s data access. Netezza is database 101. This is as complicated as it gets.
  • Updates: 10/29/03: J. Feinsmith – System no longer chooses the first column by default.
  • Predictability
  • XO Communications offers a variety of communications services including voice over internet protocol (VoIP), data and internet services, network transport, broadband wireless access, and hosted and managed services. Its high capacity IP network and advanced transport network support more than 50 percent of the Fortune 500 and many of the world’s largest telecommunications companies.
  • This is a number we like to boast about A number that we hope you’ll come to cherish as well and help us maintain and grow in the future This is our win-rate against Oracle, both historic and current, as of last quarter … with and without Exadata! In fact, even when we lost deals, we lost them on business grounds … against Oracle ELAs and business relationships .. and not on the technical merits of their products Obviously our obsession has paid off very well Click to proceed The acquisition is naturally making Larry nervous He knows that the success of Exadata is key to his ambitions against IBM He also knows that if he couldn’t beat Netezza as a standalone company, he doesn’t stand a chance with the combination of Netezza and IBM When it comes to data warehousing, we have the right technology leadership, experience, proven customer successes and the right formula for winning … every single time!
  • A Company is judged by the Company they keep. Those were just a few examples from over 500 Netezza customers Our customers span a variety of vertical industries and sizes

Netezza technicaloverviewportugues Netezza technicaloverviewportugues Presentation Transcript

  • IBM Netezza TwinFin ® Líder em Appliances para Data Warehouse Silvio Ferrari IBM Netezza Systems Engineer [email_address]
  • Conteúdo Integrate & Cleanses Dados Estruturados Analisar Integrar Governança Dados Aplicações Transacionais & Colaborativas Gerenciar Informação Streaming Aplicações Analíticas de Negócio Streams Big Data Data Warehouses Fontes de informação Externas www Qualidade Gerenciamento de Lifecycle Segurança & Privacidade Netezza, IM e BAO Data Warehouse Appliances Master Data
  • Verdadeiros Appliances
    • Dispositivos especializados
    • Otimizados para um propósito
    • Solução completa
    • Instalação rápida
    • Operação muito simples
    • Interfaces padrão de mercado
    • Baixo custo
    • Netezza anuncia servidor em 2002
    • Está no melhor quadrante do Gartner desde 2008
    • 2008 Data Warehouse Database Management Systems Magic Quadrant report released on December 23, 2008
  • A Simplicidade de um Appliance Netezza
  • Carregando dados no Appliance IBM Netezza Integração de dados Inserindo
      • Ab Initio
      • Business Objects/SAP
      • Composite Software
      • Expressor Software
      • GoldenGate Software (Oracle)
      • Informatica
      • IBM Information Server
      • Sunopsis (Oracle)
      • WisdomForce
      • ... e outras mais....
    SQL ODBC JDBC OLE-DB
  • Consultando o Appliance IBM Netezza Reporting e Análise
      • Actuate
      • Business Objects/SAP
      • Cognos (IBM)
      • Information Builders
      • Kalido
      • KXEN
      • MicroStrategy
      • Oracle OBIEE
      • QlikTech
      • Quest Software
      • SAS
      • SPSS (IBM)
      • Unica (IBM)
      • ... e outras mais....
    extraindo SQL ODBC JDBC OLE-DB
  • A arquitetura IBM Netezza AMPP™ ( parte de Hardware ) Analíticos Avançados Loader ETL BI Applicações FPGA Memory CPU FPGA Memory CPU FPGA Memory CPU Discos S-Blades™ Rede Interna Netezza Appliance Hosts Host
  • Servidores Blade CPUs Memória
  • Acelerador IBM Netezza Database CPUs Memória FPGA
  • Nosso segredo: FPGA CPU Descomprime Elimina colunas não usadas Restringe Visibilidade Operações complexas: ∑ Joins, Aggs, etc. select DISTRICT, PRODUCTGRP, sum(NRX) from MTHLY_RX_TERR_DATA where MONTH = '20091201' and MARKET = 509123 and SPECIALTY = 'GASTRO' Parte da tabela MTHLY_RX_TERR_DATA (comprimida) where MONTH = '20091201' and MARKET = 509123 and SPECIALTY = 'GASTRO' sum(NRX) select DISTRICT, PRODUCTGRP, sum(NRX)
  • O S-Blade™ IBM Netezza
  • Arquitetura IBM Netezza TwinFin™ Hardware+Software Otimizados Projetado (e não simplesmente adaptado) para tarefas analíticas de alta performance; Não necessita ajustes; Dados Streaming Aceleradores de query por Hardware, para resultados mais rápidos Verdadeiro MPP Todos os processadores totalmente utilizados para máxima eficiência e velocidade Analíticos avançados Analíticos complexos executados in-database
  • Simplicidade do Appliance IBM Netezza ( Software )
    • dbspace/tablespace: não há sizing ou configuração
    • redo/physical/Logical log: não há sizing ou configuração
    • page/block de tabelas: não há sizing ou configuração
    • extent para tabelas não há sizing ou configuração
    • Temp Space: não há alocação ou monitoração
    • dbspaces: não há decisões para nível RAID
    • Logical Volume: não há criação de files
    • OS kernel: não há alterações
    • OS kernel: não há níveis de patch requeridos
    • Sessões JAD para configurar host/network/storage não requeridas
    Administração de storage desnecessária Sem índices ou ajustes Sem instalação de software Passos da instalação: - conectar energia elétrica - rodar testes (8h) - entregar servidor ao cliente DBAs se tornam Gerenciadores de Dados, em vez de administradores de banco de dados
  • Complexidade versus Simplicidade IBM Netezza Criando um database: 0. CREATE DATABASE TEST LOGFILE 'E:OraDataTESTLOG1TEST.ORA' SIZE 2M, 'E:OraDataTESTLOG2TEST.ORA' SIZE 2M, 'E:OraDataTESTLOG3TEST.ORA' SIZE 2M, 'E:OraDataTESTLOG4TEST.ORA' SIZE 2M, 'E:OraDataTESTLOG5TEST.ORA' SIZE 2M EXTENT MANAGEMENT LOCAL MAXDATAFILES 100 DATAFILE 'E:OraDataTESTSYS1TEST.ORA' SIZE 50 M DEFAULT TEMPORARY TABLESPACE temp TEMPFILE 'E:OraDataTESTTEMP.ORA' SIZE 50 M UNDO TABLESPACE undo DATAFILE 'E:OraDataTESTUNDO.ORA' SIZE 50 M NOARCHIVELOG CHARACTER SET WE8ISO8859P1; 1. Oracle* table and indexes   2. Oracle tablespace     3. Oracle datafile       4. Veritas file         5. Veritas file system            6. Veritas striped logical volume               7. Veritas mirror/plex                 8. Veritas sub-disk                   9. SunOS raw device                      10. Brocade SAN switch                        11. EMC Symmetrix volume                          12. EMC Symmetrix striped meta-volume                             13. EMC Symmetrix hyper-volume                                 14. EMC Symmetrix remote volume (replication)                                 15. Days/weeks of planning meetings Mudar pata 6data!!!!!!! IBM Netezza: ZERO parâmetros: CREATE DATABASE my_db;
    • ORACLE
    • CREATE TABLE "MRDWDDM"."RDWF_DDM_ROOMS_SOLD" ("ID_PROPERTY" NUMBER(5,
    • 0) NOT NULL ENABLE, "ID_DATE_STAY" NUMBER(5, 0) NOT NULL ENABLE,
    • "CD_ROOM_POOL" CHAR(4) NOT NULL ENABLE, "CD_RATE_PGM" CHAR(4) NOT
    • NULL ENABLE, "CD_RATE_TYPE" CHAR(1) NOT NULL ENABLE,
    • "CD_MARKET_SEGMENT" CHAR(2) NOT NULL ENABLE, "ID_CONFO_NUM_ORIG"
    • NUMBER(9, 0) NOT NULL ENABLE, "ID_CONFO_NUM_CUR" NUMBER(9, 0) NOT
    • NULL ENABLE, "ID_DATE_CREATE" NUMBER(5, 0) NOT NULL ENABLE,
    • "ID_DATE_ARRIVAL" NUMBER(5, 0) NOT NULL ENABLE, "ID_DATE_DEPART"
    • NUMBER(5, 0) NOT NULL ENABLE, "QY_ROOMS" NUMBER(5, 0) NOT NULL
    • ENABLE, "CU_REV_PROJ_NET_LOCAL" NUMBER(21, 3) NOT NULL ENABLE,
    • "CU_REV_PROJ_NET_USD" NUMBER(21, 3) NOT NULL ENABLE,
    • "QY_DAYS_STAY_CUR" NUMBER(3, 0) NOT NULL ENABLE, "CD_BOOK_SOURCE"
    • CHAR(1) NOT NULL ENABLE) PCTFREE 5 PCTUSED 95 INITRANS 4 MAXTRANS 255
    • STORAGE( FREELISTS 6) TABLESPACE "DDM_ROOMS_SOLD_DATA" NOLOGGING
    • PARTITION BY RANGE ("ID_PROPERTY" ) (PARTITION "PART1" VALUES LESS
    • THAN (600) PCTFREE 5 PCTUSED 95 INITRANS 4 MAXTRANS 255
    • STORAGE(INITIAL 16777216 FREELISTS 6 FREELIST GROUPS 1) TABLESPACE
    • "DDM_ROOMS_SOLD_DATA" NOLOGGING NOCOMPRESS, PARTITION "PART2" VALUES
    • LESS THAN (1200) PCTFREE 5 PCTUSED 95 INITRANS 4 MAXTRANS 255
    • STORAGE(INITIAL 16777216 FREELISTS 6 FREELIST GROUPS 1) TABLESPACE
    • "DDM_ROOMS_SOLD_DATA" NOLOGGING NOCOMPRESS, PARTITION "PART3" VALUES
    • LESS THAN (1800) PCTFREE 5 PCTUSED 95 INITRANS 4 MAXTRANS 255
    • STORAGE(INITIAL 16777216 FREELISTS 6 FREELIST GROUPS 1) TABLESPACE
    • "DDM_ROOMS_SOLD_DATA" NOLOGGING NOCOMPRESS, PARTITION "PART4" VALUES
    • LESS THAN (2400) PCTFREE 5 PCTUSED 95 INITRANS 4 MAXTRANS 255
    • STORAGE(INITIAL 16777216 FREELISTS 6 FREELIST GROUPS 1) TABLESPACE
    • "DDM_ROOMS_SOLD_DATA" NOLOGGING NOCOMPRESS, PARTITION "PART5" VALUES
    • LESS THAN (3000) PCTFREE 5 PCTUSED 95 INITRANS 4 MAXTRANS 255
    • STORAGE(INITIAL 16777216 FREELISTS 6 FREELIST GROUPS 1) TABLESPACE
    • "DDM_ROOMS_SOLD_DATA" NOLOGGING NOCOMPRESS, PARTITION "PART6" VALUES
    • LESS THAN (MAXVALUE) PCTFREE 5 PCTUSED 95 INITRANS 4 MAXTRANS 255
    • STORAGE(INITIAL 16777216 FREELISTS 6 FREELIST GROUPS 1) TABLESPACE
    • "DDM_ROOMS_SOLD_DATA" NOLOGGING NOCOMPRESS ) ;
    Simplicidade Netezza: criando uma tabela ORACLE Indexes CREATE INDEX "MRDWDDM"."RDWF_DDM_ROOMS_SOLD_IDX1" ON "RDWF_DDM_ROOMS_SOLD" ("ID_PROPERTY" , "ID_DATE_STAY" , "CD_ROOM_POOL" , "CD_RATE_PGM" , "CD_RATE_TYPE" , "CD_MARKET_SEGMENT" ) PCTFREE 10 INITRANS 6 MAXTRANS 255 STORAGE( FREELISTS 10) TABLESPACE "DDM_DATAMART_INDEX_L" NOLOGGING PARALLEL ( DEGREE 4 INSTANCES 1) LOCAL(PARTITION "PART1" PCTFREE 10 INITRANS 6 MAXTRANS 255 STORAGE(INITIAL 4194304 NEXT 4259840 MINEXTENTS 1 MAXEXTENTS 100000 PCTINCREASE 0 FREELISTS 10 FREELIST GROUPS 1 BUFFER_POOL DEFAULT) TABLESPACE "DDM_DATAMART_INDEX_L" NOLOGGING, PARTITION "PART2" PCTFREE 10 INITRANS 6 MAXTRANS 255 STORAGE(INITIAL 4194304 NEXT 4259840 MINEXTENTS 1 MAXEXTENTS 100000 PCTINCREASE 0 FREELISTS 10 FREELIST GROUPS 1 BUFFER_POOL DEFAULT) TABLESPACE "DDM_DATAMART_INDEX_L" NOLOGGING, PARTITION "PART3" PCTFREE 10 INITRANS 6 MAXTRANS 255 STORAGE(INITIAL 4194304 NEXT 4259840 MINEXTENTS 1 MAXEXTENTS 100000 PCTINCREASE 0 FREELISTS 10 FREELIST GROUPS 1 BUFFER_POOL DEFAULT) TABLESPACE "DDM_DATAMART_INDEX_L" NOLOGGING, PARTITION "PART4" PCTFREE 10 INITRANS 6 MAXTRANS 255 STORAGE(INITIAL 4194304 NEXT 4259840 MINEXTENTS 1 MAXEXTENTS 100000 PCTINCREASE 0 FREELISTS 10 FREELIST GROUPS 1 BUFFER_POOL DEFAULT) TABLESPACE "DDM_DATAMART_INDEX_L" NOLOGGING, PARTITION "PART5" PCTFREE 10 INITRANS 6 MAXTRANS 255 STORAGE(INITIAL 4194304 NEXT 4259840 MINEXTENTS 1 MAXEXTENTS 100000 PCTINCREASE 0 FREELISTS 10 FREELIST GROUPS 1 BUFFER_POOL DEFAULT) TABLESPACE "DDM_DATAMART_INDEX_L" NOLOGGING, PARTITION "PART6" PCTFREE 10 INITRANS 6 MAXTRANS 255 STORAGE(INITIAL 4194304 NEXT 4259840 MINEXTENTS 1 MAXEXTENTS 100000 PCTINCREASE 0 FREELISTS 10 FREELIST GROUPS 1 BUFFER_POOL DEFAULT) TABLESPACE "DDM_DATAMART_INDEX_L" NOLOGGING ) ; ORACLE Bitmap index CREATE BITMAP INDEX "CRDBO"."SNAPSHOT_MONTH_IDX13" ON "SNAPSHOT_OPPTY_MONTH_HIST" ("SNAPSHOT_YEAR" ) PCTFREE 10 INITRANS 2 MAXTRANS 255 STORAGE(INITIAL 4194304 NEXT 4194304 MINEXTENTS 2 MAXEXTENTS 2147483645 PCTINCREASE 0 FREELISTS 1 FREELIST GROUPS 1 BUFFER_POOL DEFAULT) TABLESPACE "SFA_DATAMART_INDEX" NOLOGGING ; ORACLE Table Clusters CREATE CLUSTER "MRDW"."CT_INTRMDRY_CAL" ("ID_YEAR_CAL" NUMBER(4, 0), "ID_MONTH_CAL" NUMBER(2, 0), "ID_PROPERTY" NUMBER(5, 0)) SIZE 16384 PCTFREE 10 PCTUSED 90 INITRANS 3 MAXTRANS 255 STORAGE(INITIAL 83886080 NEXT 41943040 MINEXTENTS 1 MAXEXTENTS 1017 PCTINCREASE 0 FREELISTS 4 FREELIST GROUPS 1 BUFFER_POOL RECYCLE) TABLESPACE "TSS_FACT" ; Netezza CREATE TABLE MRDWDDM.RDWF_DDM_ROOMS_SOLD ( ID_PROPERTY numeric(5, 0) NOT NULL , ID_DATE_STAY integer NOT NULL , CD_ROOM_POOL CHAR(4) NOT NULL , CD_RATE_PGM CHAR(4) NOT NULL , CD_RATE_TYPE CHAR(1) NOT NULL , CD_MARKET_SEGMENT CHAR(2) NOT NULL , ID_CONFO_NUM_ORIG integer NOT NULL , ID_CONFO_NUM_CUR integer NOT NULL , ID_DATE_CREATE integer NOT NULL , ID_DATE_ARRIVAL integer NOT NULL , ID_DATE_DEPART integer NOT NULL , QY_ROOMS integer NOT NULL , CU_REV_PROJ_NET_LOCAL numeric(21, 3) NOT NULL , CU_REV_PROJ_NET_USD numeric(21, 3) NOT NULL , QY_DAYS_STAY_CUR smallint NOT NULL , CD_BOOK_SOURCE CHAR(1) NOT NULL) distribute on random;
    • Sem indexes
    • Sem Admininstração ou ajustes
    • Distribua os dados aleatoriamente, ou por Colunas
  • Complexidade Tradicional versus a Simplicidade Netezza (RDBMS 101) CREATE TABLE EDW_PROD.EDW_RESPD_EXPSR_MIN_FACT ( RPT_PERIOD_DIM_ID NUMBER NOT NULL, SRVY_WEEK_DIM_ID NUMBER NOT NULL, DATE_DIM_ID NUMBER NOT NULL, SRVC_MKT_SEG_DIM_ID NUMBER NOT NULL, RESPD_HHLD_DIM_ID NUMBER NOT NULL, MDOTLT_DIM_ID NUMBER NOT NULL, LSTN_LOC_DIM_ID NUMBER NOT NULL, EXPSR_MIN_CNT NUMBER NOT NULL, RESPD_WGHT_NMBR NUMBER, PRELIM_DAILY_WGHT_NMBR NUMBER, FINAL_DAILY_WGHT_NMBR NUMBER, TIMESHIFT_SECOND_CNT NUMBER, BGN_EXPSR_UTC_TS DATE, END_EXPSR_UTC_TS DATE, BGN_EXPSR_LOCAL_TS DATE, END_EXPSR_LOCAL_TS DATE, BGN_BCST_UTC_TS DATE, END_BCST_UTC_TS DATE, BGN_BCST_LOCAL_TS DATE, END_BCST_LOCAL_TS DATE, SOURCE_ID VARCHAR2(50 BYTE), ACTIVE_IND CHAR(1 BYTE) DEFAULT 'Y‘ NOT NULL, INSERT_TS DATE NOT NULL, UPDATE_TS DATE NOT NULL, METADATA_ID NUMBER, MEDIA_CODE VARCHAR2(10 BYTE), MDOTLT_HIER_DIM_ID NUMBER, OUT_OF_MKT_IND CHAR(1 BYTE) ) CREATE TABLE EDW_PROD.EDW_RESPD_EXPSR_MIN_FACT ( RPT_PERIOD_DIM_ID INTEGER NOT NULL, SRVY_WEEK_DIM_ID INTEGER NOT NULL, DATE_DIM_ID INTEGER NOT NULL, SRVC_MKT_SEG_DIM_ID INTEGER NOT NULL, RESPD_HHLD_DIM_ID INTEGER NOT NULL, MDOTLT_DIM_ID INTEGER NOT NULL, LSTN_LOC_DIM_ID INTEGER NOT NULL, EXPSR_MIN_CNT NUMERIC(9,2) NOT NULL, RESPD_WGHT_NMBR NUMERIC(9,2), PRELIM_DAILY_WGHT_NMBR NUMERIC(9,2), FINAL_DAILY_WGHT_NMBR NUMERIC(9,2), TIMESHIFT_SECOND_CNT INTEGER, BGN_EXPSR_UTC_TS TIMESTAMP, END_EXPSR_UTC_TS TIMESTAMP, BGN_EXPSR_LOCAL_TS TIMESTAMP, END_EXPSR_LOCAL_TS TIMESTAMP, BGN_BCST_UTC_TS TIMESTAMP, END_BCST_UTC_TS TIMESTAMP, BGN_BCST_LOCAL_TS TIMESTAMP, END_BCST_LOCAL_TS TIMESTAMP, SOURCE_ID VARCHAR(50), ACTIVE_IND CHAR(1) DEFAULT 'Y‘ NOT NULL, INSERT_TS TIMESTAMP NOT NULL, UPDATE_TS TIMESTAMP NOT NULL, METADATA_ID INTEGER, MEDIA_CODE VARCHAR(10), MDOTLT_HIER_DIM_ID INTEGER, OUT_OF_MKT_IND CHAR(1) ) distribute on random; 516 BASE TABLE PARTITIONS… TABLESPACE AT_EDW_REXMIN PCTUSED 0 PCTFREE 10 INITRANS 1 MAXTRANS 255 LOGGING PARTITION BY RANGE (RPT_PERIOD_DIM_ID) ( PARTITION RP0000 VALUES LESS THAN (0) NOLOGGING NOCOMPRESS TABLESPACE AT_EDW_REXMIN PCTFREE 10 INITRANS 1 MAXTRANS 255 STORAGE ( INITIAL 96K NEXT 96K MINEXTENTS 1 MAXEXTENTS UNLIMITED PCTINCREASE 0 BUFFER_POOL DEFAULT ), PARTITION RP0001 VALUES LESS THAN (2) NOLOGGING NOCOMPRESS TABLESPACE AT_EDW_REXMIN PCTFREE 10 INITRANS 1 MAXTRANS 255 STORAGE ( INITIAL 96K NEXT 96K MINEXTENTS 1 MAXEXTENTS UNLIMITED PCTINCREASE 0 BUFFER_POOL DEFAULT ), PARTITION RP0002 VALUES LESS THAN (3) NOLOGGING NOCOMPRESS TABLESPACE AT_EDW_REXMIN PCTFREE 10 INITRANS 1 MAXTRANS 255 STORAGE ( INITIAL 96K NEXT 96K MINEXTENTS 1 MAXEXTENTS UNLIMITED PCTINCREASE 0 BUFFER_POOL DEFAULT ), … … PLUS DDL FOR 513 MORE PARTITIONS Index REXMIN_SOURCE_ID_I on 515 PARTITIONS… CREATE INDEX EDW_PROD.REXMIN_SOURCE_ID_I ON EDW_PROD.EDW_RESPD_EXPSR_MIN_FACT (SOURCE_ID) TABLESPACE AI_EDW_REXMIN INITRANS 2 MAXTRANS 255 LOGGING LOCAL ( PARTITION RP0000 NOLOGGING NOCOMPRESS TABLESPACE AI_EDW_REXMIN PCTFREE 10 INITRANS 2 MAXTRANS 255 STORAGE ( INITIAL 96K NEXT 96K MINEXTENTS 1 MAXEXTENTS UNLIMITED PCTINCREASE 0 BUFFER_POOL DEFAULT ), PARTITION RP0001 NOLOGGING NOCOMPRESS TABLESPACE AI_EDW_REXMIN PCTFREE 10 INITRANS 2 MAXTRANS 255 STORAGE ( INITIAL 96K NEXT 96K MINEXTENTS 1 MAXEXTENTS UNLIMITED PCTINCREASE 0 BUFFER_POOL DEFAULT ), PARTITION RP0002 NOLOGGING TABLESPACE AI_EDW_REXMIN PCTFREE 10 INITRANS 2 MAXTRANS 255 STORAGE ( INITIAL 96K NEXT 96K MINEXTENTS 1 MAXEXTENTS UNLIMITED PCTINCREASE 0 BUFFER_POOL DEFAULT ), … … PLUS DDL FOR 512 MORE PARTITIONS Index REXMIN_LLOC_FK_BI on 515 PARTITIONS… CREATE BITMAP INDEX EDW_PROD.REXMIN_LLOC_FK_BI ON EDW_PROD.EDW_RESPD_EXPSR_MIN_FACT (LSTN_LOC_DIM_ID) TABLESPACE AI_EDW_REXMIN INITRANS 2 MAXTRANS 255 LOGGING LOCAL ( PARTITION RP0000 NOLOGGING TABLESPACE AI_EDW_REXMIN PCTFREE 10 INITRANS 2 MAXTRANS 255 STORAGE ( INITIAL 96K NEXT 96K MINEXTENTS 1 MAXEXTENTS UNLIMITED PCTINCREASE 0 BUFFER_POOL DEFAULT ), PARTITION RP0001 NOLOGGING TABLESPACE AI_EDW_REXMIN PCTFREE 10 INITRANS 2 MAXTRANS 255 STORAGE ( INITIAL 96K NEXT 96K MINEXTENTS 1 MAXEXTENTS UNLIMITED PCTINCREASE 0 BUFFER_POOL DEFAULT ), … … PLUS DDL FOR 513 MORE PARTITIONS Index REXMIN_REHH_FK_BI on 515 PARTITIONS… CREATE BITMAP INDEX EDW_PROD.REXMIN_REHH_FK_BI ON EDW_PROD.EDW_RESPD_EXPSR_MIN_FACT (RESPD_HHLD_DIM_ID) TABLESPACE AI_EDW_REXMIN INITRANS 2 MAXTRANS 255 LOGGING LOCAL ( PARTITION RP0000 NOLOGGING TABLESPACE AI_EDW_REXMIN PCTFREE 10 INITRANS 2 MAXTRANS 255 STORAGE ( INITIAL 96K NEXT 96K MINEXTENTS 1 MAXEXTENTS UNLIMITED PCTINCREASE 0 BUFFER_POOL DEFAULT ), PARTITION RP0001 NOLOGGING TABLESPACE AI_EDW_REXMIN PCTFREE 10 INITRANS 2 MAXTRANS 255 STORAGE ( INITIAL 96K NEXT 96K MINEXTENTS 1 MAXEXTENTS UNLIMITED PCTINCREASE 0 BUFFER_POOL DEFAULT ), … … PLUS DDL FOR 513 MORE PARTITIONS Index REXMIN_SMS_FK_BI on 515 PARTITIONS… CREATE BITMAP INDEX EDW_PROD.REXMIN_SMS_FK_BI ON EDW_PROD.EDW_RESPD_EXPSR_MIN_FACT (SRVC_MKT_SEG_DIM_ID) TABLESPACE AI_EDW_REXMIN INITRANS 2 MAXTRANS 255 LOGGING LOCAL ( PARTITION RP0000 NOLOGGING TABLESPACE AI_EDW_REXMIN PCTFREE 10 INITRANS 2 MAXTRANS 255 STORAGE ( INITIAL 96K NEXT 96K MINEXTENTS 1 MAXEXTENTS UNLIMITED PCTINCREASE 0 BUFFER_POOL DEFAULT ), … … PLUS DDL FOR 514 MORE PARTITIONS Index REXMIN_SRWK_FK_BI on 515 PARTITIONS… CREATE BITMAP INDEX EDW_PROD.REXMIN_SRWK_FK_BI ON EDW_PROD.EDW_RESPD_EXPSR_MIN_FACT (SRVY_WEEK_DIM_ID) TABLESPACE AI_EDW_REXMIN INITRANS 2 MAXTRANS 255 LOGGING LOCAL ( PARTITION RP0000 NOLOGGING TABLESPACE AI_EDW_REXMIN PCTFREE 10 INITRANS 2 MAXTRANS 255 STORAGE ( INITIAL 96K NEXT 96K MINEXTENTS 1 MAXEXTENTS UNLIMITED PCTINCREASE 0 BUFFER_POOL DEFAULT ), … … PLUS DDL FOR 514 MORE PARTITIONS Index REXMIN_RP_FK_BI on 515 PARTITIONS… CREATE BITMAP INDEX EDW_PROD.REXMIN_SRWK_FK_BI ON EDW_PROD.EDW_RESPD_EXPSR_MIN_FACT (SRVY_WEEK_DIM_ID) TABLESPACE AI_EDW_REXMIN INITRANS 2 MAXTRANS 255 LOGGING LOCAL ( … … PLUS DDL FOR 515 PARTITIONS Index REXMIN_DATE_FK_BI on 515 PARTITIONS… CREATE BITMAP INDEX EDW_PROD.REXMIN_DATE_FK_BI ON EDW_PROD.EDW_RESPD_EXPSR_MIN_FACT (DATE_DIM_ID) TABLESPACE AI_EDW_REXMIN INITRANS 2 MAXTRANS 255 LOGGING LOCAL ( … … PLUS DDL FOR 515 PARTITIONS Index REXMIN_MEDO_FK_BI on 515 PARTITIONS… CREATE BITMAP INDEX EDW_PROD.REXMIN_MEDO_FK_BI ON EDW_PROD.EDW_RESPD_EXPSR_MIN_FACT (MDOTLT_DIM_ID)… … PLUS DDL FOR TABLESPACE + 515 PARTITIONS Oracle: 34,500 KB de DDLs Netezza: 250 KB de DDLs
  • Comparação de requerimentos de redes (internas e externas) Total: 9 endereços IP Total: 90 endereços IP 4 network drops 10 network drops minimum (with 50+ reported as being typical 5 IP addresses 68 IP addresses for Ethernet (for a single cluster) - 22 IP addresses for the InfiniBand network TwinFin12 (full rack) Exadata (full rack)
  • Monitorando a distribuição dos dados com NzAdmin
    • Uma má distribuição.
    • O usuário escolheu a(s) coluna(s) errada(s) para a distribuição dos dados.
    • Nota: Neste caso, o usuário escolheu a primeira coluna da tabela como a coluna de distrubuição. Uma decisão incorreta.
  • Uma boa Distribuição: 2.2 Trilhões de Registros
  • Monitoração: Distribuição homogênea dos dados no sistema
    • Análise de SKEW com relação ao sistema
    Deve haver uma carga de utilização equivalente entre as SPUs
  • Backup e Restore
    • Integração e certificação com ferramentas líderes de mercado:
      • Simplifica integração com as principais ferramentas de backup e restore
      • Suporte a X/Open Backup Services API (XBSA)
      • Certificação IBM Tivoli Storage Manager (TSM)
      • Certificação Veritas NetBackup™ da Symantec
    • Backup and Restore Incremental
      • Diminui significativamente os tempos de backup comparados ao backup Full
      • Disponível no utilitário NZBACKUP
      • Restores tipo Full ou parcial
    Dom Seg Ter Qua Qui Sex Sab Full Dif Dif Cumulativo Dif Dif Dif
  • The IBM Netezza TwinFin™ - Expansão Em caso de expansão: - um novo sistema completo é enviado - dados migrados ONLINE - IPs são redirecionados - servidor original é desligado e devolvido
  • i-Class: Analytics Without Constraints
    • Analyze wider and deeper data
      • Additional dimensions
      • Richer history
    Big Data Big Math
    • Increase computational intensity
      • More complex models
      • Faster execution for results
  • Advanced Analytics with TwinFin i-Class SAS, SPSS R, S+ SQL SQL Fraud Detection Demand Forecasting
  • Simples de Instalar e Operar
    • Operações
      • Simplesmente carregue e use… é um appliance!
      • Instalação em ~2 dias!
      • Fácil de avaliar e funciona como anunciado!
    • Desenvolvedores BI & DBAs – mais ágeis
      • Sem configuração ou modelagem física
      • Sem índices ou ajustes – performance imediata
      • Agnóstico a modelos de dados
      • Data Architects / DBA focam nos negócios, não na modelagem física
    • Desenvolvedores ETL
      • Tabelas de agregação não necessárias – lógica de ETL simplificada
      • Cargas e transformações mais rápidas
    • Analistas de Negócio
      • Análise “Linha de Pensamento”– 10 a 100x mais rápida
      • Consultas ad hoc – sem ajustes, sem índices
      • Consultas complexas a grandes datasets
      • Menor latencia – cargas e consultas simultâneas
      • processamento OnStream a centenas de nodes
  • Família de Appliances para todo o ciclo de gerenciamento: Skimmer Sistemas de Desenvolvimento e Testes 1 TB to 10 TB TwinFin Data Warehouse Analítico de alta Performance 1 TB to 1.5 PB Cruiser Archiving acessível por SQL, Back-up / DR 100 TB to 10 PB
  • 15,000 users running 800,000+ queries per day 50X faster than before Speed Source: http:// www.youtube.com/watch?v =yOwnX14nLrE&feature= player_embedded “… when something took 24 hours I could only do so much with it, but when something takes 10 seconds, I may be able to completely rethink the business process…” - SVP Application Development, Nielsen
  • Simplicity 200X faster than Oracle system ROI in less than 3 months Up and running 6 months before having any training DAYS WEEKS MONTHS “ Allowing the business users access to the Netezza box was what sold it.” Steve Taff, Executive Dir. of IT Services
  • Scalability Source: http://www.computerweekly.com/Articles/2008/04/14/230265/NYSE-improves-data-management-with-datawarehousing.htm 1 PB on Netezza 7 years of historical data 100-200% annual data growth “ NYSE … has replaced an Oracle IO relational database with a data warehousing appliance from Netezza, allowing it to conduct rapid searches of 650 terabytes of data.” ComputerWeekly.com
  • Smart Coupon redemption rates as high as 25% Predicts what shoppers are likely to buy in future visits “ Because of (Netezza’s) in-database technology, we believe we'll be able to do 600 predictive models per year (10X as many as before) with the same staff." Eric Williams, CIO and executive VP
  • Todos prometem, mas... nós provamos!
    • Nós provamos que somos simples
    • Nós provamos que entregamos performance
    • Nós provamos dentro do seu ambiente
    • Nós provamos que nos integramos com suas ferramentas
    • Nós provamos que somos “ fáceis de fazer negócio ”
    • Nós provamos que temos o menor TCO
    • Nós provamos Business Value
  • Listar os passos de uma PoC
    • 1- Definir com cliente, os testes a serem realizados
    • 2- Obter as queries e as DDLs a serem usadas na PoC
    • 3- Criar as tabelas
    • 4- Testes de carga, leitura, atualização e concorrência
    • 5- Comparar as consultas no sistema atual e no Netezza
    • 6- Duração de 1 semana (2 semanas no máximo)
  • Indice de sucesso nas PoCs: 86% One of “ The five most important M&A Deals of 2010 ” - Wall Street Journal
  • Page Digital Media Financial Services Governo Health & Life Sciences Retail / Consumer Products Telecom Other
  • Obrigado! (slides backup)
  • Oracle Exadata Oracle Exadata Results In Netezza TwinFin Netezza’s Competitive Advantage Architecture
    • Two layer:
      • Clustered SMP DB Layer (RAC)
      • Shared disk MPP Storage Layer
    Compromised Performance
    • True MPP with FPGA acceleration of processing in each MPP node
    • Best architecture for DW and advanced analytics due to minimization of contention/bottlenecks
    Speed
    • Tuned for OLTP (e.g. FlashCache)
    • RAC unfit for DW workloads
    Poor DW Performance
    • Appliance tuned for DW and advanced analytics
    • Highest DW performance
    • Operational Simplicity
    Simplicity
    • Complexity of Oracle Real Application Clusters (RAC)
    • Constant tuning for performance
    Complex Administration
    • True Appliance with HW/SW created to provide high performance for DW
    • No tuning
    • More time spent delivering business value rather than tuning for acceptable performance
    Smart
    • Very limited push-down of analytics
    • RAC bottleneck for analytic performance
    Poor Analytic Performance
    • Push down of many diverse analytics (SAS, R, Gnu, etc.) through iClass
    • Ability to accelerate the analytics used by many prospects
    Costs
    • Acquisition cost can exceed $7M per rack
      • Hardware $1M
      • Software is more than $6M!
    • High maintenance and software subscription
    • Continuing high admin costs
    High Total Cost of Ownership
    • Low, transparent initial cost
    • Simple install requires no additional professional services
    • Standard maintenance includes hw /sw support and sw upgrades
    • Easily understood, predictable costs
    • Minimal “extra” services so easier to budget for Netezza
  • Analysis Summary: Oracle Exadata Database Machine
    • Exadata is Limited in the Processing It Does. Won’t Handle:
      • Complex joins
      • Distinct aggregation
      • Analytical functions
    • Most Work Still Done on Oracle Database Server
      • Lots of movement of data
      • Loss of Performance
    • Oracle Says Exadata Can Do OLTP or DW or Both At the Same Time
      • Vastly different workloads requiring vastly different tuning
      • Netezza customers report that Exadata poor at DW and analytic
  • Query Throughput ≠ Scan Rate
    • Oracle Exadata throws together the very fast hardware and hopes it produces fast results.
    • Exadata offers very fast scan rates but that just means it can get data off the disks quickly.
    • Overall query throughput also relies on the speed of all the other components, including the software
    • Oracle Exadata can be very fast for simple queries but gets slower with increasing complexity
    • Netezza is designed for balance – it works fast for all query types
  • Netezza’s Advantages over Oracle
    • Oracle RAC is still Oracle RAC. It is still:
      • Complex – needs to be tuned
      • Temperamental – needs retuning for different configurations
      • Difficult – needs specialized skills and constant maintenance
    • Netezza is much easier. With hardware and software optimized for data warehouse applications, there is:
      • No need for labor-intensive tuning
      • No requirements for partitioning, indexing or building cubes
    • Database Machine is a Resource Hog
      • For a full rack Oracle Exadata Database Machine, you will need to supply at least 90 IP addresses (22 IP addresses for the InfiniBand network, 68 IP addresses for Ethernet, assuming a single cluster), and a minimum of 10 network drops (with 50+ reported as being typical ).
    • In contrast, a Netezza TwinFin-12 requires 5 IP addresses and 4 network drops. The core Netezza theme of simplicity is reflected in installation as in operation.
  • TwinFin™ 24 Specification
    • 16 (8*2) Disk Enclosures
    • 192 (96*2) 1TB SAS Drives
    • (8 hot spares)
    • RAID 1 Mirroring
    • 24 Netezza S-Blades:
    • 192 Core’s ( Intel Quad-Core 2.5 GHz)
    • 192 FPGA’s ( 125 MHz )
    • 384 GB DDR2 RAM (1+TB compressed)
    • Linux 64-bit Kernel
    • 2 Hosts (Active-Passive):
    • 24 Cores (Quad-Core Intel 2.6 GHz)
    • 96 GB Memory
    • 4x146 GB SAS Drives
    • Red Hat Linux 5 64-bit
    • 10G Internal Network
    • User Data Capacity: 250 TB
    • Data Scan Speed: 290 TB/hr
    • Load Speed (per system): 2.0 TB/hr
    • Power/Rack: 7,400 Watts
    • Cooling/Rack: 25,500 BTU/Hour
  • Compress Engine in Action
    • On Data Load
    • Rows separated into columnar streams
    • Each stream independently compiled
    • Field instructions applied to block headers
    • Compressed data maintains row-based structure
    • On Data Scan/Query
    • FPGA executes field instructions to decompile at wire speed
    • Data re-assembled into rows for other FAST Engines processing
  • Workload Management Controls: Guaranteed Resource Allocation
  • Default Workload Management: Short Query Bias
    • Short Query Bias (SQB)
      • Short queries prioritized ahead of longer running queries
      • Real-time responses to users performing short queries
      • Invaluable feature for large mixed-workload environments
    8 Items or Less Full Carts Here Full Carts Here
  • GRA Test: Fidelity to User Settings