Maroš Anderko, Peter Hmira MFF UK 2013

Size: px
Start display at page:

Download "Maroš Anderko, Peter Hmira MFF UK 2013"

Transcription

1 Maroš Anderko, Peter Hmira MFF UK 2013

2 Obsah Problematika motivácia Súčasnosť, možnosti SQL Spreadsheet črty a možnosti Príklad

3 MO Excel Vynikajúce UI Ľahká manipulácia, vzorce, grafy.. 2D spracovanie, obmedzené rozsahom cca 64k x 200 Chýba paralelné spracovanie

4 Vízia

5 SQL Spreadsheet Relácia : n-rozmerné pole Zhusťovanie dát vypĺňanie medzier Zapúzdrenosť Výsledkom znovu relácia znovupoužitenosť Paralelné spracovanie Súčasť dopytu, žiadna zmena dát

6 SQL Spreadsheet klauzuly PARTITION (PBY) rozdelenie na disjunktné množiny DIMENSION (DBY) jedinečné riadky v každej z množín, bunky MEASURES (MEA) miery počítané spreadsheet-om

7 SQL Spreadsheet dopyt <existing parts of a query block > SPREADSHEET PBY(cols) DBY(cols) MEA(cols) <processing options> (<formula>,<formula>,...,<formula>) Vyhodnotenie po joinoch, agregácii, finálnej projekcii PRED ORDER BY Referencie na jednu bunku alebo ich rozsah

8 Príklad Obchod s elektronikou F (t,r,p,s,c) Dimenzie veličiny : čas t, región r, produkt p Miery predaj s, cena c

9 Dopyt SELECT r, p, t, s FROM f SPREADSHEET PBY(r) DBY (p, t) MEA (s) ( s[p= dvd,t=2002] =s[p= dvd,t=2001]*1.6, s[p= vcr,t=2002] =s[p= vcr,t=2000]+s[p= vcr,t=2001], s[p= tv, t=2002] =avg(s)[p= tv,1992<t<2002] ) Skrátené formy

10 Cv() funkcia a * operátor SPREADSHEET DBY (r, p, t) MEA (s) ( s[ west,*,t>2001] = 1.2*s[cv(r),cv(p),t=cv(t)-1] ) Existenčná formula, poradie spracovania

11 UPDATE Ignoruje neexistujúce bunky SPREADSHEET PBY(r) DBY (p, t) MEA (s) ( UPDATE s[ tv, 2000] = s[ black-tv,2000] + s[ white-tv,2000] )

12 UPSERT SPREADSHEET PBY(r) DBY (p, t) MEA (s) ( UPSERT s[ tv,*] = s[ black-tv,cv()]+s[ white-tv,cv()] )

13 Reference Spreadsheet Objekty rôznych veličín dimenzíí Predaj región, produkt, cena, čas Rozpočet - budget región, produkt SELECT r, t, s FROM f GROUP by r, t SPREADSHEET REFERENCE budget ON (SELECT r, p FROM budget) DBY(r) MEA(p) DBY (r, t) MEA (sum(s) s) ( s[ west,2002]= p[ west ]*s[ west,2001], s[ east,2002]= s[ east,2001]+s[ east,2000] )

14 Vyhodnocovanie formúl AUTOMATIC ORDER SPREADSHEET PBY(r) DBY (p, t) MEA (s) (s[ dvd,2002] = s[ dvd,2000] + s[ dvd,2001] s[ dvd,2001] = 1000) SEQUENTIAL ORDER SPREADSHEET DBY(r,p,t) MEA(s) SEQUENTIAL ORDER (...<formulas>...)

15 Cykly a rekurzia ITERATE (n) UNTIL <podmienka> SPREADSHEET DBY (x) MEA (s) ITERATE (10) UNTIL (PREVIOUS(s[1])-s[1] <= 1) (s[1] = s[1]/2)

16 Pr.1 predikcia predaja SELECT r, p, t, s FROM f SPREADSHEET PBY(r) DBY (p, t) MEA (s) ( F1: UPDATE s[ tv,2002] = s[ tv,2001] +slope(s,t)[ tv,1992<=t<=2001]*s[ tv,2001], Vnorený dopyt + join F2: UPDATE s[ vcr, 2002] = s[ vcr,2000]+s[ vcr,2001] Dvojitý join do tabuľky F3: UPDATE s[ dvd,2002] =(s[ dvd,1999]+ s[ dvd,2000]+s[ dvd,2001])/3, trojitý join F4: UPSERT s[ video, 2002] = s[ tv,2002]+s[ vcr,2002] ) UNION

17 Analýza Pokračování - osnova Optimalizácia Dátové štruktúry Evaluation

18 Analýza a optimalizácia Poradie vyhodnocovania formúl Nájdenie cyklov Orezávania formúl Prepisovanie Presun predikátov

19 Poradie formúl a závislostí Uvažujme formuly F1: s['video', 2000] = s['tv', 2000] + s['vcr',2000] F2:s['vcr', 2000] = s['vcr',1998] + s['vcr',1999] s[ tv, t^2 + t^3 + t^4 < t^5] Je náročné určiť prienik predikátov Predpokladáme, že výraz referencuje všetky bunky

20 Poradie formúl Ak sú formuly nezávislé (podľa grafu závislostí) môžu byť vyhodnotené paralelne za 1 scan Pre účely paralelného vyhodnocovania, formuly sú agregované do levelov, kde každý level obsahuje nezávislé formuly a formuly nižšie nezávisia na formulách vyššie Počet levelov určuje minimálny počet scanov

21 Pruning (orezávanie) Predpokladajme dotaz: SELECT * FROM ( SELECT r, p, t, s FROM f SPREADSHEET PBY(r) DBY (p, t) MEA (s) UPDATE ( F1: s['dvd', 2000] = s['dvd', 1999]*1.2, F2: s['vcr', 2000] = s['vcr',1998] + s['vcr', 1999], F3: s['tv', 2000] = avg(s)['tv', 1990 < 2000] ) ) WHERE p in ('dvd', 'vcr', 'video') Vonkajší dotaz odfiltruváva bunku, ktorú dotazuje F3 F3 môžeme odstrániť

22 Pruning (cont.) Rozšírime dotaz o F4: SELECT * FROM ( SELECT r, p, t, s FROM f SPREADSHEET PBY(r) DBY (p, t) MEA (s) UPDATE ( F1: s['dvd', 2000] = s['dvd', 1999]*1.2, F2: s['vcr', 2000] = s['vcr',1998] + s['vcr', 1999], F3: s['tv', 2000] = avg(s)['tv', 1990 < 2000] F4: s['video', 2000] = s['tv',2000] + s['vcr',2000] ) ) WHERE p in ('dvd', 'vcr', 'video') F3 už nemôžeme odstrániť, lebo je referencované F4

23 Rewriing (prepisovanie) Predpokladajme dotaz : SELECT * FROM ( SELECT r, p, t, s FROM f SPREADSHEET PBY(r) DBY (p, t) MEA (s,c) UPDATE ( F1: s[*, 2002] = c[cv(p), 2002] * 2 ) ) WHERE p in ('dvd', 'vcr') and t >= 2000 Pruning nie je možné uplatniť, lebo vnútorná formula je potrebná vo vonkajšom dotaze Rewritingom sa môžeme vyhnúť zbytočným výpočtom

24 Rewriting (cont.) Zmenený dotaz : SELECT * FROM ( SELECT r, p, t, s FROM f SPREADSHEET PBY(r) DBY (p, t) MEA (s,c) UPDATE ( F1: s[p in ('dvd', 'vcr'), 2002] = c[cv(p), 2002] * 2 ) ) WHERE p in ('dvd', 'vcr') and t >= 2000 Rewriting sa implementuje jednoduchým rozšírením algoritmu orezávania

25 Pushing (predicates) Technika, pri ktorej presúvame predikáty z vonkajšieho do vnútorného dotazu Tri druhy : Presun u PBY a nezávislých DBY dimenzií Presun na základe analýzy hraničného obdĺžnika Presun cez referencie v spreadsheetoch

26 Presun u PBY Správa sa vždy korektne, lebo filtruje celé partitions SELECT * FROM ( SELECT r, p, t, s FROM f SPREADSHEET PBY(r) DBY (p, t) MEA (s) UPDATE ( F1: s['dvd', 2000] = s['dvd, 1999] + s['dvd', 1997], F2: s['vcr', 2000] = s['vcr', 1998] + s['vcr', 1999] ) ) WHERE r = 'east' and t = 2000 and p ='dvd' Predikát r = east presunieme do vnútorného dotazu

27 Presun založený na Boundary rectangle Zanalyzujeme boundary rectangle a rozšírime o predikát : SELECT * FROM ( SELECT r, p, t, s FROM f SPREADSHEET PBY(r) DBY (p, t) MEA (s) UPDATE ( F1: s['dvd', 2000] = s['dvd, 1999] + s['dvd', 1997], F2: s['vcr', 2000] = s['vcr', 1998] + s['vcr', 1999] ) ) WHERE r = 'east' and t = 2000 and p ='dvd' V tomto prípade t in (1997, 1998, 1999, 2000)

28 Presun cez funkčne nezávislé dimenzie Ref-sub-query pushing Vytvorenie poddotazu Extended pushing Vykonávanie referencovaného dotazu Formula unfolding Výsledok poddotazu vložíme do formúl

29 Spreadsheet execution Ak sú v spreadsheet klauzule referencie Spreadsheet operátor zoberie vstupné riadky pre každú referenciu a vyrobí hashovaciu tabuľku, aby mohli byť referencované počas vyhodnocovanie formúl Hashovacie tabuľky sú read-only a po výpočte zaniknú

30 Access structure Dvojúrovňová hašovacia prístupová štruktúra Prvá úroveň je hašovacia partícia na základe PBY stĺpcov Druhá úroveň je už na základ PBY a DBY stĺpcov v rámci partície na prvej úrovni Aby sme minimalizovali časové a pamäťové nároky, prístupovú štruktúru vytvoríme len nad riadkami dotazovanými formulami

31 Evaluation

32 Auto-acyklický algoritmus Funguje len vtedy, ak v grafe závislostí nie sú detekované žiadne cykly Pre každú spreadsheet partition vyhodnotí levely porade V každom leveli vyhodnotí agregáty až potom formuly

33 Auto acyklický algoritmus Najskôr vyhodnotíme formuly, ktoré nie sú obsiahnuté v silne-súvislej komponente grafu závislostí V silne-súvislých komponentác algoritmus iteruje, kým nedosiahne pevný bod po max N iteráciách N je počet buniek zmenených pri prvej iterácii

34 Sekvenčný algoritmus Formuly sú vyhodnotené v poradí v akom sú uvedené v spreadsheet klauzuli Analýza aj v tomto prípade agreguje formule do levelov, aby mohla zminimalizovať počet scanov

35 Zhrnutie : Problémy/motivácia na SQL Spreadsheet Výhody SQL Spreadsheet oproti konkurencii

36 Zdroje : WITKOWSKI, A., et al: Advanced SQL Modeling in RDBMS. ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003 TODS Volume 30 Issue 1, March 2005, p

Spájanie tabuliek. Jaroslav Porubän, Miroslav Biňas, Milan Nosáľ (c)

Spájanie tabuliek. Jaroslav Porubän, Miroslav Biňas, Milan Nosáľ (c) Spájanie tabuliek Jaroslav Porubän, Miroslav Biňas, Milan Nosáľ (c) 2011-2016 Úvod pri normalizácii rozdeľujeme databázu na viacero tabuliek prepojených cudzími kľúčmi SQL umožňuje tabuľky opäť spojiť

More information

Poradové a agregačné window funkcie. ROLLUP a CUBE

Poradové a agregačné window funkcie. ROLLUP a CUBE Poradové a agregačné window funkcie. ROLLUP a CUBE 1) Poradové a agregačné window funkcie 2) Extrémy pomocou DENSE_RANK(), TOP() - Príklady 3) Spriemernené poradia 4) Kumulatívne súčty 5) Group By a Datepart,

More information

Databázové systémy. SQL Window functions

Databázové systémy. SQL Window functions Databázové systémy SQL Window functions Scores Tabuľka s bodmi pre jednotlivých študentov id, name, score Chceme ku každému doplniť rozdiel voči priemeru 2 Demo data SELECT * FROM scores ORDER BY score

More information

Databázy (1) Prednáška 11. Alexander Šimko

Databázy (1) Prednáška 11. Alexander Šimko Databázy (1) Prednáška 11 Alexander Šimko simko@fmph.uniba.sk Contents I Aktualizovanie štruktúry databázy Section 1 Aktualizovanie štruktúry databázy Aktualizácia štruktúry databázy Štruktúra databázy

More information

Testovanie bieleho šumu

Testovanie bieleho šumu Beáta Stehlíková FMFI UK Bratislava Opakovanie z prednášky Vygenerujeme dáta Vygenerujeme dáta: N

More information

Anycast. Ľubor Jurena CEO Michal Kolárik System Administrator

Anycast. Ľubor Jurena CEO Michal Kolárik System Administrator Anycast Ľubor Jurena CEO jurena@skhosting.eu Michal Kolárik System Administrator kolarik@skhosting.eu O nás Registrátor Webhosting Serverové riešenia Správa infraštruktúry Všetko sa dá :-) Index Čo je

More information

Databázy (1) Prednáška 08. Alexander Šimko

Databázy (1) Prednáška 08. Alexander Šimko Databázy (1) Prednáška 08 Alexander Šimko simko@fmph.uniba.sk Contents I Subqueries (poddopyty) konštrukcia WITH Section 1 Subqueries (poddopyty) Subquery (poddopyt) Použitie SELECTu na mieste, kde sme

More information

Constraint satisfaction problems (problémy s obmedzujúcimi podmienkami)

Constraint satisfaction problems (problémy s obmedzujúcimi podmienkami) I2AI: Lecture 04 Constraint satisfaction problems (problémy s obmedzujúcimi podmienkami) Lubica Benuskova Reading: AIMA 3 rd ed. chap. 6 ending with 6.3.2 1 Constraint satisfaction problems (CSP) We w

More information

1 Vytvorenie tabuľky

1 Vytvorenie tabuľky Základy jazyka SQL (Structured Query Language) - vyvinula IBM začiatkom 70-tych rokov - je to deklaratívny jazyk (popisuje čo urobiť, nie ako) - je súčasťou veľkých databázových systémov (Informix, Oracle,

More information

Data Reference Searcher. Documentation

Data Reference Searcher. Documentation Documentation Martin Dráb 8/19/2010 TABLE OF CONTENT Table of content... 1 Basic information... 2 Supported versions of Microsoft Dynamics AX... 2 Supported languages... 2 Installation... 3 User guide...

More information

Riešenia a technológie pre jednotnú správu používateľov

Riešenia a technológie pre jednotnú správu používateľov Riešenia a technológie pre jednotnú správu používateľov Radovan Semančík Agenda Úvod: Identity Crisis Technológie správy používateľov Postup nasadenia Záver Súčasný stav IT Security Nekonzistentné bezpečnostné

More information

Aplikačný dizajn manuál

Aplikačný dizajn manuál Aplikačný dizajn manuál Úvod Aplikačný dizajn manuál je súbor pravidiel vizuálnej komunikácie. Dodržiavaním jednotných štandardov, aplikácií loga, písma a farieb pri prezentácii sa vytvára jednotný dizajn,

More information

VYLEPŠOVANIE KONCEPTU TRIEDY

VYLEPŠOVANIE KONCEPTU TRIEDY VYLEPŠOVANIE KONCEPTU TRIEDY Typy tried class - definuje premenné a metódy (funkcie). Ak nie je špecifikovaná inak, viditeľnosť členov je private. struct - definuje premenné a metódy (funkcie). Ak nie

More information

NIKY a NIKY S. JEDNOFÁZOVÉ UPS od 600 do 3000 VA SVETOVÝ ŠPECIALISTA PRE ELEKTRICKÉ INŠTALÁCIE A DIGITÁLNE SYSTÉMY BUDOV

NIKY a NIKY S. JEDNOFÁZOVÉ UPS od 600 do 3000 VA SVETOVÝ ŠPECIALISTA PRE ELEKTRICKÉ INŠTALÁCIE A DIGITÁLNE SYSTÉMY BUDOV NIKY a NIKY S JEDNOFÁZOVÉ UPS od 600 do 3000 VA SVETOVÝ ŠPECIALISTA PRE ELEKTRICKÉ ŠTALÁCIE A DIGITÁLNE SYSTÉMY BUDOV Ideálna ochrana pre malé kancelárie a domáce kancelárske aplikácie. Tento rad ponúka

More information

Recipient Configuration. Štefan Pataky MCP, MCTS, MCITP

Recipient Configuration. Štefan Pataky MCP, MCTS, MCITP Recipient Configuration Štefan Pataky MCP, MCTS, MCITP Agenda Mailbox Mail Contact Distribution Groups Disconnected Mailbox Mailbox (vytvorenie nového účtu) Exchange Management Console New User Exchange

More information

kucharka exportu pro 9FFFIMU

kucharka exportu pro 9FFFIMU požiadavky na export kodek : Xvid 1.2.1 stable (MPEG-4 ASP) // výnimočne MPEG-2 bitrate : max. 10 Mbps pixely : štvorcové (Square pixels) rozlíšenie : 1920x1080, 768x432 pre 16:9 // výnimočne 1440x1080,

More information

Registrácia účtu Hik-Connect

Registrácia účtu Hik-Connect Registrácia účtu Hik-Connect Tento návod popisuje postup registrácie účtu služby Hik-Connect prostredníctvom mobilnej aplikácie a webového rozhrania na stránke www.hik-connect.comg contents in this document

More information

Rýchlosť Mbit/s (download/upload) 15 Mbit / 1 Mbit. 50 Mbit / 8 Mbit. 80 Mbit / 10 Mbit. 10 Mbit / 1 Mbit. 12 Mbit / 2 Mbit.

Rýchlosť Mbit/s (download/upload) 15 Mbit / 1 Mbit. 50 Mbit / 8 Mbit. 80 Mbit / 10 Mbit. 10 Mbit / 1 Mbit. 12 Mbit / 2 Mbit. Fiber 5 Mbit ** 5 Mbit / Mbit 5,90 Fiber 50 Mbit * 50 Mbit / 8 Mbit 9,90 Fiber 80 Mbit * 80 Mbit / Mbit 5,90 Mini Mbit* Mbit / Mbit 9,90 Klasik 2 Mbit* 2 Mbit / 2 Mbit Standard 8 Mbit* 8 Mbit / 3Mbit Expert

More information

Workbooks (File) and Worksheet Handling

Workbooks (File) and Worksheet Handling Workbooks (File) and Worksheet Handling Excel Limitation Excel shortcut use and benefits Excel setting and custom list creation Excel Template and File location system Advanced Paste Special Calculation

More information

Algoritmy deterministickej a stochastickej optimalizácie a ich počítačová realizácia

Algoritmy deterministickej a stochastickej optimalizácie a ich počítačová realizácia Algoritmy deterministickej a stochastickej optimalizácie a ich počítačová realizácia ESF 2007 D. Ševčovič Katedra aplikovanej matematiky a štatistiky, Univerzita Komenského, 842 48 Bratislava http://www.iam.fmph.uniba.sk/institute/sevcovic

More information

Lesson 21: Surface Area

Lesson 21: Surface Area Lesson 21: Surface Area Classwork Opening Exercise: Surface Area of a Right Rectangular Prism On the provided grid, draw a net representing the surfaces of the right rectangular prism (assume each grid

More information

Wolverine ESP Cradle System User Manual Version 1.0 August, 2006

Wolverine ESP Cradle System User Manual Version 1.0 August, 2006 Wolverine ESP Cradle System User Manual Version 1.0 August, 2006 FEATURES Use the ESP Cradle system to record directly from TV, DVD Player, VCR or any video source and watch them anywhere, anytime Record

More information

Obsah. SOA REST REST princípy REST výhody prest. Otázky

Obsah. SOA REST REST princípy REST výhody prest. Otázky REST Peter Rybár Obsah SOA REST REST princípy REST výhody prest Otázky SOA implementácie WEB (1990) CORBA (1991) XML-RPC (1998) WS-* (1998) SOAP RPC/literal SOAP Document/literal (2001) REST (2000) SOA

More information

Entity Framework: Úvod

Entity Framework: Úvod Entity Framework: Úvod Martin Macák Fakulta informatiky, Masarykova univerzita, Brno 29. 9. 2016 Osnova prednášky 1. Základy Entity Frameworku 2. Návrh databázy (detailnejšie Code First prístup) 3. Migrácie

More information

Copyright 2016 by Martin Krug. All rights reserved.

Copyright 2016 by Martin Krug. All rights reserved. MS Managed Service Copyright 2016 by Martin Krug. All rights reserved. Reproduction, or translation of materials without the author's written permission is prohibited. No content may be reproduced without

More information

Desatinné čísla #1a. Decimal numbers #1b. How much larger is 21,8 than 1,8? Desatinné čísla #2a. Decimal numbers #2b. 14 divided by 0,5 equals...

Desatinné čísla #1a. Decimal numbers #1b. How much larger is 21,8 than 1,8? Desatinné čísla #2a. Decimal numbers #2b. 14 divided by 0,5 equals... Desatinné čísla #1a Mravec išiel 5,5 cm presne na sever, potom 3,4 cm na východ, 1,8 cm na juh, 14,3 cm na západ, 1,3 cm na sever a 10,9 cm na východ. Najmenej koľko cm musí teraz prejsť, aby sa dostal

More information

No Bikinis? Working with SQL s Model

No Bikinis? Working with SQL s Model No Bikinis? Working with SQL s Model Presented to: RMOUG Training Days February 9, 2005 John Jay King King Training Resources john@kingtraining.com Download this paper and code examples from: http://www.kingtraining.com

More information

High Speed ETL on Low Budget

High Speed ETL on Low Budget High Speed ETL on Low Budget Introduction Data Acquisition & populating it in a warehouse has traditionally been carried out using dedicated ETL tools available in the market. An enterprise-wide Data Warehousing

More information

Excel Manual Updating Formula Auto 2010 Does Not

Excel Manual Updating Formula Auto 2010 Does Not Excel Manual Updating Formula Auto 2010 Does Not How can I make the formula result to update automatically when I open it after each If it still not update, please try to use VBA or manually update the

More information

NÁKLADY ŽIVOTNÉHO CYKLU LIFE CYCLE COSTS

NÁKLADY ŽIVOTNÉHO CYKLU LIFE CYCLE COSTS NÁKLADY ŽIVOTNÉHO CYKLU LIFE CYCLE COSTS Jaroslav Lexa Apuen SK Kritériá ekonomicky najvýhodnejšej ponuky Most economically advantageous tender criteria Najlepší pomer ceny a kvality Best price-quality

More information

Ochrana proti DDoS za použitia open-source software. Katarína Ďurechová

Ochrana proti DDoS za použitia open-source software. Katarína Ďurechová Ochrana proti DDoS za použitia open-source software Katarína Ďurechová katarina.durechova@nic.cz 30.11.2013 Distributed Denial of Service odopretie služby dosiahnutím limitu pripojenia sieťovej karty CPU

More information

AUTOMATIC CLUSTERING PRASANNA RAJAPERUMAL I MARCH Snowflake Computing Inc. All Rights Reserved

AUTOMATIC CLUSTERING PRASANNA RAJAPERUMAL I MARCH Snowflake Computing Inc. All Rights Reserved AUTOMATIC CLUSTERING PRASANNA RAJAPERUMAL I MARCH 2019 SNOWFLAKE Our vision Allow our customers to access all their data in one place so they can make actionable decisions anytime, anywhere, with any number

More information

Advanced Database Systems

Advanced Database Systems Lecture IV Query Processing Kyumars Sheykh Esmaili Basic Steps in Query Processing 2 Query Optimization Many equivalent execution plans Choosing the best one Based on Heuristics, Cost Will be discussed

More information

Copyright 2016 Ramez Elmasri and Shamkant B. Navathe

Copyright 2016 Ramez Elmasri and Shamkant B. Navathe CHAPTER 19 Query Optimization Introduction Query optimization Conducted by a query optimizer in a DBMS Goal: select best available strategy for executing query Based on information available Most RDBMSs

More information

Query Processing & Optimization

Query Processing & Optimization Query Processing & Optimization 1 Roadmap of This Lecture Overview of query processing Measures of Query Cost Selection Operation Sorting Join Operation Other Operations Evaluation of Expressions Introduction

More information

Principles of Data Management. Lecture #9 (Query Processing Overview)

Principles of Data Management. Lecture #9 (Query Processing Overview) Principles of Data Management Lecture #9 (Query Processing Overview) Instructor: Mike Carey mjcarey@ics.uci.edu Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke 1 Today s Notable News v Midterm

More information

Programming the Polaroid Universal Remote Control Following are two sets of instructions for programming your Polaroid Universal Remote Control to work with other devices in addition to your Polaroid TV.

More information

CMPT 354: Database System I. Lecture 7. Basics of Query Optimization

CMPT 354: Database System I. Lecture 7. Basics of Query Optimization CMPT 354: Database System I Lecture 7. Basics of Query Optimization 1 Why should you care? https://databricks.com/glossary/catalyst-optimizer https://sigmod.org/sigmod-awards/people/goetz-graefe-2017-sigmod-edgar-f-codd-innovations-award/

More information

Figure 1 Map of US Coast Guard Districts... 2 Figure 2 CGD Zip File Size... 3 Figure 3 NOAA Zip File Size By State...

Figure 1 Map of US Coast Guard Districts... 2 Figure 2 CGD Zip File Size... 3 Figure 3 NOAA Zip File Size By State... Table of Contents NOAA RNC Charts (By Coast Guard District, NOAA Regions & States) Overview... 1 NOAA RNC Chart File Locations... 2 NOAA RNC by Coast Guard Districts(CGD)... 2 NOAA RNC By States... 3 NOAA

More information

Quick-Sort. Quick-Sort 1

Quick-Sort. Quick-Sort 1 Quick-Sort 7 4 9 6 2 2 4 6 7 9 4 2 2 4 7 9 7 9 2 2 9 9 Quick-Sort 1 Outline and Reading Quick-sort ( 4.3) Algorithm Partition step Quick-sort tree Execution example Analysis of quick-sort (4.3.1) In-place

More information

Horizontal Aggregations for Mining Relational Databases

Horizontal Aggregations for Mining Relational Databases Horizontal Aggregations for Mining Relational Databases Dontu.Jagannadh, T.Gayathri, M.V.S.S Nagendranadh. Department of CSE Sasi Institute of Technology And Engineering,Tadepalligudem, Andhrapradesh,

More information

UNIVERZITA KOMENSKÉHO FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY. Katedra Informatiky DIPLOMOVÁ PRÁCA. Branislav Belas Programové a počítačové systémy

UNIVERZITA KOMENSKÉHO FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY. Katedra Informatiky DIPLOMOVÁ PRÁCA. Branislav Belas Programové a počítačové systémy UNIVERZITA KOMENSKÉHO FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY Katedra Informatiky DIPLOMOVÁ PRÁCA Meno: Odbor: Vedúci dipl. práce: Branislav Belas Programové a počítačové systémy RNDr. Ján Šturc, CSc.

More information

Parallel DBMS. Parallel Database Systems. PDBS vs Distributed DBS. Types of Parallelism. Goals and Metrics Speedup. Types of Parallelism

Parallel DBMS. Parallel Database Systems. PDBS vs Distributed DBS. Types of Parallelism. Goals and Metrics Speedup. Types of Parallelism Parallel DBMS Parallel Database Systems CS5225 Parallel DB 1 Uniprocessor technology has reached its limit Difficult to build machines powerful enough to meet the CPU and I/O demands of DBMS serving large

More information

Princípy tvorby softvéru Dizajnové princípy

Princípy tvorby softvéru Dizajnové princípy Robert Luko ka lukotka@dcs.fmph.uniba.sk www.dcs.fmph.uniba.sk/~lukotka M-255 Analýza a dizajn - úrovne Architektúra Vysokoúrov ový analytický model... Nízkoúrov ový analytický model Implementa ný model

More information

COMPUTER TECHNOLOGY SPREADSHEETS BASIC TERMINOLOGY. A workbook is the file Excel creates to store your data.

COMPUTER TECHNOLOGY SPREADSHEETS BASIC TERMINOLOGY. A workbook is the file Excel creates to store your data. SPREADSHEETS BASIC TERMINOLOGY A Spreadsheet is a grid of rows and columns containing numbers, text, and formulas. A workbook is the file Excel creates to store your data. A worksheet is an individual

More information

Computer Applications Data Processing FA 14

Computer Applications Data Processing FA 14 Lesson 7: Combining Multiple Data Sources Microsoft Excel 2016 IN THIS CHAPTER, YOU WILL LEARN HOW TO: Use workbooks as templates for other workbooks. Link to data in other worksheets and workbooks. Consolidate

More information

Manual Version DC

Manual Version DC Manual Version DC20060609-1 2 Table of Contents Cart Setup...4 Laptop Instructions...6 AMX Panel Command Flow...7 AMX Panel Verification Page...8 Source Selection...9 VCR Controls...10 Laptop...11 Presenter

More information

TECHNICKÁ UNIVERZITA V KOŠICIACH. MULTIDIMENZIONÁLNE SPRACOVANIE DÁT Zadanie z predmetu Manažérske informačné systémy

TECHNICKÁ UNIVERZITA V KOŠICIACH. MULTIDIMENZIONÁLNE SPRACOVANIE DÁT Zadanie z predmetu Manažérske informačné systémy TECHNICKÁ UNIVERZITA V KOŠICIACH FAKULTA ELEKTROTECHNIKY A INFORMATIKY KATEDRA KYBERNETIKY A UMELEJ INTELIGENCIE MULTIDIMENZIONÁLNE SPRACOVANIE DÁT Zadanie z predmetu Manažérske informačné systémy 2014/2015

More information

COUNTING AND PROBABILITY

COUNTING AND PROBABILITY CHAPTER 9 COUNTING AND PROBABILITY Copyright Cengage Learning. All rights reserved. SECTION 9.3 Counting Elements of Disjoint Sets: The Addition Rule Copyright Cengage Learning. All rights reserved. Counting

More information

7. Query Processing and Optimization

7. Query Processing and Optimization 7. Query Processing and Optimization Processing a Query 103 Indexing for Performance Simple (individual) index B + -tree index Matching index scan vs nonmatching index scan Unique index one entry and one

More information

Functions in Excel. Structure of a function: Basic Mathematical Functions. Arithmetic operators: Comparison Operators:

Functions in Excel. Structure of a function: Basic Mathematical Functions. Arithmetic operators: Comparison Operators: Page1 Functions in Excel Formulas (functions) are equations that perform calculations on values in your spreadsheet. A formula always starts with an equal sign (=). Example: =5+2*7 This formula multiples

More information

DW Performance Optimization (II)

DW Performance Optimization (II) DW Performance Optimization (II) Overview Data Cube in ROLAP and MOLAP ROLAP Technique(s) Efficient Data Cube Computation MOLAP Technique(s) Prefix Sum Array Multiway Augmented Tree Aalborg University

More information

Programovatelné obvody a SoC. PI-PSC

Programovatelné obvody a SoC. PI-PSC Evropský sociální fond Praha & EU: Investujeme do vaší budoucnosti Programovatelné obvody a SoC. PI-PSC doc. Ing. Hana Kubátová, CSc. Katedra číslicového návrhu Fakulta informačních technologií ČVUT v

More information

MS Exchange 2010 Prechod Ing. Peter Záhradník

MS Exchange 2010 Prechod Ing. Peter Záhradník MS Exchange 2010 Prechod Ing. Peter Záhradník Gratex Support Center support@gratex.com Exchange 2010 o com to bude? Tato prezentacia bude pre ludi co uvazuju nad prechodom na novy Exchange zopar otazok

More information

Jazyk SQL. Jaroslav Porubän, Miroslav Biňas, Milan Nosáľ (c)

Jazyk SQL. Jaroslav Porubän, Miroslav Biňas, Milan Nosáľ (c) Jazyk SQL Jaroslav Porubän, Miroslav Biňas, Milan Nosáľ (c) 2011-2016 Jazyk SQL - Structured Query Language SQL je počítačový jazyk určený na komunikáciu s relačným SRBD neprocedurálny (deklaratívny) jazyk

More information

Parser: SQL parse tree

Parser: SQL parse tree Jinze Liu Parser: SQL parse tree Good old lex & yacc Detect and reject syntax errors Validator: parse tree logical plan Detect and reject semantic errors Nonexistent tables/views/columns? Insufficient

More information

Module 9: Selectivity Estimation

Module 9: Selectivity Estimation Module 9: Selectivity Estimation Module Outline 9.1 Query Cost and Selectivity Estimation 9.2 Database profiles 9.3 Sampling 9.4 Statistics maintained by commercial DBMS Web Forms Transaction Manager Lock

More information

Presentation for use with the textbook, Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, 2015

Presentation for use with the textbook, Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, 2015 Presentation for use with the textbook, Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, 2015 Quick-Sort 7 4 9 6 2 2 4 6 7 9 4 2 2 4 7 9 7 9 2 2 9 9 2015 Goodrich and Tamassia

More information

ÚVOD. NorStone design kombinuje praktické a estetické hľadisko s výnimočnou precíznosťou výroby.

ÚVOD. NorStone design kombinuje praktické a estetické hľadisko s výnimočnou precíznosťou výroby. ÚVOD NorStone design kombinuje praktické a estetické hľadisko s výnimočnou precíznosťou výroby. Každý detail je pozorne navrhnutý tak, aby poskytol najvyššiu odolnosť a trvácnosť. NorStone navrhuje a vyrába

More information

Advanced Excel Reporting

Advanced Excel Reporting SedonaOffice Users Conference San Francisco, CA January 21 24, 2018 Advanced Excel Reporting Presented by: Matt Howe This Page Intentionally Left Blank Page 2 of 20 Table of Contents Overview... 4 Making

More information

ÚRAD VEREJNÉHO ZDRAVOTNÍCTVA SLOVENSKEJ REPUBLIKY Trnavská cesta 52 P.O.BOX Bratislava

ÚRAD VEREJNÉHO ZDRAVOTNÍCTVA SLOVENSKEJ REPUBLIKY Trnavská cesta 52 P.O.BOX Bratislava ÚRAD VEREJNÉHO ZDRAVOTNÍCTVA SLOVENSKEJ REPUBLIKY Trnavská cesta 52 P.O.BOX 45 826 45 Bratislava Úrad verejného zdravotníctva Slovenskej republiky upozorňuje na výskyt nebezpečných výrobkov farby na tetovanie

More information

Crestron Mercury. Univerzálny Videokonferenčný a Kolaboračný systém

Crestron Mercury. Univerzálny Videokonferenčný a Kolaboračný systém Crestron Mercury Univerzálny Videokonferenčný a Kolaboračný systém Tradičná malá zasadacia miestnosť CRESTRON Mercury Videokonferenčná miestnosť Možnosť rezervácie miestnosti: Prostredníctvom MS Outlook

More information

Sorting Goodrich, Tamassia Sorting 1

Sorting Goodrich, Tamassia Sorting 1 Sorting Put array A of n numbers in increasing order. A core algorithm with many applications. Simple algorithms are O(n 2 ). Optimal algorithms are O(n log n). We will see O(n) for restricted input in

More information

Oracle In-Memory and all that

Oracle In-Memory and all that Oracle In-Memory and all that Paolo Kreth, DBA, Head of team Datamanagement, paolo.kreth@mobiliar.ch Andreas Wyssenbach, Senior DBA andreas.wyssenbach@mobiliar.ch July 2017 1 Agenda 1. Swiss Mobiliar in

More information

About Codefrux While the current trends around the world are based on the internet, mobile and its applications, we try to make the most out of it. As for us, we are a well established IT professionals

More information

Quick-Sort fi fi fi 7 9. Quick-Sort Goodrich, Tamassia

Quick-Sort fi fi fi 7 9. Quick-Sort Goodrich, Tamassia Quick-Sort 7 4 9 6 2 fi 2 4 6 7 9 4 2 fi 2 4 7 9 fi 7 9 2 fi 2 9 fi 9 Quick-Sort 1 Quick-Sort ( 10.2 text book) Quick-sort is a randomized sorting algorithm based on the divide-and-conquer paradigm: x

More information

c. Typically results in an intractably large set of test cases even for small programs

c. Typically results in an intractably large set of test cases even for small programs Multiple-Choice Questions: 1. True or false? Generally, in practice, developers exhaustively test software. a. True b. False 2. True or false? All real software contains bugs. a. True b. False 3. Which

More information

SQL Server Analysis Services

SQL Server Analysis Services DataBase and Data Mining Group of DataBase and Data Mining Group of Database and data mining group, SQL Server 2005 Analysis Services SQL Server 2005 Analysis Services - 1 Analysis Services Database and

More information

Query Optimization in Distributed Databases. Dilşat ABDULLAH

Query Optimization in Distributed Databases. Dilşat ABDULLAH Query Optimization in Distributed Databases Dilşat ABDULLAH 1302108 Department of Computer Engineering Middle East Technical University December 2003 ABSTRACT Query optimization refers to the process of

More information

Parallel Nested Loops

Parallel Nested Loops Parallel Nested Loops For each tuple s i in S For each tuple t j in T If s i =t j, then add (s i,t j ) to output Create partitions S 1, S 2, T 1, and T 2 Have processors work on (S 1,T 1 ), (S 1,T 2 ),

More information

Parallel Partition-Based. Parallel Nested Loops. Median. More Join Thoughts. Parallel Office Tools 9/15/2011

Parallel Partition-Based. Parallel Nested Loops. Median. More Join Thoughts. Parallel Office Tools 9/15/2011 Parallel Nested Loops Parallel Partition-Based For each tuple s i in S For each tuple t j in T If s i =t j, then add (s i,t j ) to output Create partitions S 1, S 2, T 1, and T 2 Have processors work on

More information

1) Merge the cells that contain the title and center the title

1) Merge the cells that contain the title and center the title Supplies: You will need a storage location to save your spreadsheet for use in Session 2. You will need the 2 handouts pertaining to Session 1 Instructions: Follow the directions below to create a budget

More information

Query Optimizer MySQL vs. PostgreSQL

Query Optimizer MySQL vs. PostgreSQL Percona Live, Santa Clara (USA), 24 April 2018 Christian Antognini @ChrisAntognini antognini.ch/blog BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN LAUSANNE MUNICH

More information

Ďakujem pánovi RNDr. Tomášovi Skopalovi Ph.D. za odborné vedenie, za ochotu a čas, ktorý mi venoval počas písania tejto bakalárskej práce.

Ďakujem pánovi RNDr. Tomášovi Skopalovi Ph.D. za odborné vedenie, za ochotu a čas, ktorý mi venoval počas písania tejto bakalárskej práce. Univerzita Karlova v Praze Matematicko-fyzikální fakulta BAKALÁŘSKÁ PRÁCE Viliam Sabol Demonstrační aplikace vyhodnocování dotazu v relačním kalkulu Katedra softwarového inženýrství Vedoucí bakalářské

More information

Unit 3 Fill Series, Functions, Sorting

Unit 3 Fill Series, Functions, Sorting Unit 3 Fill Series, Functions, Sorting Fill enter repetitive values or formulas in an indicated direction Using the Fill command is much faster than using copy and paste you can do entire operation in

More information

Developing SQL Data Models(768)

Developing SQL Data Models(768) Developing SQL Data Models(768) Design a multidimensional business intelligence (BI) semantic model Create a multidimensional database by using Microsoft SQL Server Analysis Services (SSAS) Design, develop,

More information

Unit 3 Functions Review, Fill Series, Sorting, Merge & Center

Unit 3 Functions Review, Fill Series, Sorting, Merge & Center Unit 3 Functions Review, Fill Series, Sorting, Merge & Center Function built-in formula that performs simple or complex calculations automatically names a function instead of using operators (+, -, *,

More information

REPORT DESIGNER 1 VYTVORENIE A ÚPRAVA FORMULÁRA. úprava formulárov v Money S4 / Money S Vytvorenie formulára

REPORT DESIGNER 1 VYTVORENIE A ÚPRAVA FORMULÁRA. úprava formulárov v Money S4 / Money S Vytvorenie formulára REPORT DESIGNER úprava formulárov v Money S4 / Money S5 Informačný systém Money S4/S5 umožňuje upraviť tlačové zostavy tak, aby plne vyhovovali potrebám používateľa. Na úpravu tlačových zostáv slúži doplnkový

More information

Implementing Table Operations Using Structured Query Language (SQL) Using Multiple Operations. SQL: Structured Query Language

Implementing Table Operations Using Structured Query Language (SQL) Using Multiple Operations. SQL: Structured Query Language Implementing Table Operations Using Structured Query Language (SQL) Using Multiple Operations Show Only certain columns and rows from the join of Table A with Table B The implementation of table operations

More information

General Ledger Integration

General Ledger Integration General Ledger Integration for Microsoft Dynamics GP 9, 10 & 2010 Install and User Guide Peter Boniface C o n t e n t s Overview... 4 Installation... 4 Software In stallation (Server and Clients)... 4

More information

SURFACE AREA OF A RECTANGULAR PRISM

SURFACE AREA OF A RECTANGULAR PRISM SURFACE AREA OF A RECANGULAR PRISM Objective: Find the surface area of a rectangular prism Review Find the area of the following plane figures. notebook. Write your answers on your 1. A = 5 dm 12 dm 2.

More information

CSE 190D Spring 2017 Final Exam Answers

CSE 190D Spring 2017 Final Exam Answers CSE 190D Spring 2017 Final Exam Answers Q 1. [20pts] For the following questions, clearly circle True or False. 1. The hash join algorithm always has fewer page I/Os compared to the block nested loop join

More information

CMSC424: Database Design. Instructor: Amol Deshpande

CMSC424: Database Design. Instructor: Amol Deshpande CMSC424: Database Design Instructor: Amol Deshpande amol@cs.umd.edu Databases Data Models Conceptual representa1on of the data Data Retrieval How to ask ques1ons of the database How to answer those ques1ons

More information

Page 1. Oracle9i OLAP. Agenda. Mary Rehus Sales Consultant Patrick Larkin Vice President, Oracle Consulting. Oracle Corporation. Business Intelligence

Page 1. Oracle9i OLAP. Agenda. Mary Rehus Sales Consultant Patrick Larkin Vice President, Oracle Consulting. Oracle Corporation. Business Intelligence Oracle9i OLAP A Scalable Web-Base Business Intelligence Platform Mary Rehus Sales Consultant Patrick Larkin Vice President, Oracle Consulting Agenda Business Intelligence Market Oracle9i OLAP Business

More information

4.2 and 4.6 filled in notes.notebook. December 08, Integration. Copyright Cengage Learning. All rights reserved.

4.2 and 4.6 filled in notes.notebook. December 08, Integration. Copyright Cengage Learning. All rights reserved. 4 Integration Copyright Cengage Learning. All rights reserved. 1 4.2 Area Copyright Cengage Learning. All rights reserved. 2 Objectives Use sigma notation to write and evaluate a sum. Understand the concept

More information

CSci 231 Final Review

CSci 231 Final Review CSci 231 Final Review Here is a list of topics for the final. Generally you are responsible for anything discussed in class (except topics that appear italicized), and anything appearing on the homeworks.

More information

Excel 2016: Part 2 Functions/Formulas/Charts

Excel 2016: Part 2 Functions/Formulas/Charts Excel 2016: Part 2 Functions/Formulas/Charts Updated: March 2018 Copy cost: $1.30 Getting Started This class requires a basic understanding of Microsoft Excel skills. Please take our introductory class,

More information

Database Applications (15-415)

Database Applications (15-415) Database Applications (15-415) DBMS Internals- Part VIII Lecture 16, March 19, 2014 Mohammad Hammoud Today Last Session: DBMS Internals- Part VII Algorithms for Relational Operations (Cont d) Today s Session:

More information

Query Processing. Debapriyo Majumdar Indian Sta4s4cal Ins4tute Kolkata DBMS PGDBA 2016

Query Processing. Debapriyo Majumdar Indian Sta4s4cal Ins4tute Kolkata DBMS PGDBA 2016 Query Processing Debapriyo Majumdar Indian Sta4s4cal Ins4tute Kolkata DBMS PGDBA 2016 Slides re-used with some modification from www.db-book.com Reference: Database System Concepts, 6 th Ed. By Silberschatz,

More information

IVIT Inštitút vzdelávania informačných technológií Excel 2013/2016 pre pokročilých. Obsah

IVIT Inštitút vzdelávania informačných technológií Excel 2013/2016 pre pokročilých. Obsah Obsah 1 Nastavenie užívateľského prostredia... 3 1.1 Ovládanie je sústredené do panela nástrojov... 3 1.2 Vytvorenie vlastnej karty, export a import nastavenia Excelu... 3 1.3 Možnosti nastavenia zobrazenia

More information

Exploring extreme weather with Excel - The basics

Exploring extreme weather with Excel - The basics Exploring extreme weather with Excel - The basics These activities will help to develop your data skills using Excel and explore extreme weather in the UK. This activity introduces the basics of using

More information

BGP - duálne prepojenie AS. (primary + backup spoj), s IBGP, cez virtuální L2 linky

BGP - duálne prepojenie AS. (primary + backup spoj), s IBGP, cez virtuální L2 linky BGP - duálne prepojenie AS (primary + backup spoj), s IBGP, cez virtuální L2 linky Peter Jašica Abstrakt: Cieľom tohto projektu je zhotoviť a otestovať funkčnosť BGP s dvojitým prepojením Autonómnych systémov.

More information

Module 9: Query Optimization

Module 9: Query Optimization Module 9: Query Optimization Module Outline Web Forms Applications SQL Interface 9.1 Outline of Query Optimization 9.2 Motivating Example 9.3 Equivalences in the relational algebra 9.4 Heuristic optimization

More information

Mining Association Rules with Composite Items *

Mining Association Rules with Composite Items * Mining Association Rules with Composite Items *. Xiiifeng Ye, Department of Computer Science, University of Auckland, New Zealand. John A. Keane, Department of Computation, UMIST, Manchester, UK. Abstract

More information

CS317 File and Database Systems

CS317 File and Database Systems CS317 File and Database Systems http://dilbert.com/strips/comic/2010-08-24/ Lecture 8 Introduction to Normalization October 17, 2017 Sam Siewert Exam #1 Questions? Reminders Working on Grading Ex #3 -

More information

(Complete Package) We are ready to serve Latest Testing Trends, Are you ready to learn? New Batches Info

(Complete Package) We are ready to serve Latest Testing Trends, Are you ready to learn? New Batches Info (Complete Package) WEB APP TESTING DB TESTING We are ready to serve Latest Testing Trends, Are you ready to learn? New Batches Info START DATE : TIMINGS : DURATION : TYPE OF BATCH : FEE : FACULTY NAME

More information

Oracle Big Data SQL High Performance Data Virtualization Explained

Oracle Big Data SQL High Performance Data Virtualization Explained Keywords: Oracle Big Data SQL High Performance Data Virtualization Explained Jean-Pierre Dijcks Oracle Redwood City, CA, USA Big Data SQL, SQL, Big Data, Hadoop, NoSQL Databases, Relational Databases,

More information

Suppose that some packets are to be sent from nodes in the top layer to the bottom layer. For example:

Suppose that some packets are to be sent from nodes in the top layer to the bottom layer. For example: 18. The DSCO System Peter Revesz 18.1 ntroduction DSCO, short for DATALOG with nteger Set COnstraints, is a constraint database system that implements DATALOG with Boolean constraints (see Chapter 7) on

More information

Parallel Query Optimisation

Parallel Query Optimisation Parallel Query Optimisation Contents Objectives of parallel query optimisation Parallel query optimisation Two-Phase optimisation One-Phase optimisation Inter-operator parallelism oriented optimisation

More information

Query Evaluation Overview, cont.

Query Evaluation Overview, cont. Query Evaluation Overview, cont. Lecture 9 Feb. 29, 2016 Slides based on Database Management Systems 3 rd ed, Ramakrishnan and Gehrke Architecture of a DBMS Query Compiler Execution Engine Index/File/Record

More information