CSE 562 Database Systems

UB CSE Database Courses

CSE 562 Database Systems

CSE 462 Database Concepts

Introduction

CSE 562 Database Systems

Some slides are based or modified from originals by Database Systems: The Complete Book, Pearson Prentice Hall 2nd Edition ©2008 Garcia-Molina, Ullman, and Widom

CSE 636 Data Integration

UB CSE 562 Spring 2010

•  Study key DBMS design issues:

Tue & Thu @ 2-3pm 210 Bell Hall

–  Query Languages, Indexing, Query Compilation, Query Execution, Query Optimization –  Recovery, Concurrency and other transaction management issues

•  TA: Xinglei Zhu Wednesday @ 12-2pm 329 Bell Hall

–  Data warehousing, Column-Oriented DBMS –  Database as a Service (DaaS), Cloud DBMS

•  Web Page http://www.cse.buffalo.edu/~mpetropo/CSE562-SP10/

•  Ensure that:

•  Newsgroup

–  You are comfortable using a DBMS –  You acquire hands-on experience by implementing the internal components of a relational database engine

sunyab.cse.562


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Goals of the Course

•  Instructor: Dr. Michalis Petropoulos

Office Hours: Location:

CSE 7xx Dr. Petropoulos’ Seminar


Resources

Office Hours: Location:

CSE 7xx Dr. Chomicki’s Seminar

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Course Evaluation •  •  •  • 

Reading Material

Homework Assignments: 15% Midterm Exam: 20% (in class) Final Exam: 30% (in class) Project: 35%

Textbook •  Database Systems: The Complete Book (2nd Edition) –  by Garcia-Molina, Ullman and Widom

Also Recommended •  Database System Concepts (5th Edition)

–  Teams of 2

–  by Avi Silberschatz, Henry F. Korth and S. Sudarshan

•  Database Management Systems (3rd Edition) –  by Ramakrishnan and Gehrke

•  Late Submission Policy:

•  Foundations of Databases

–  Submissions less than 24 hours late will be penalized 10% –  Submissions more than 24 hours but less than 48 hours late will be penalized 25%


–  by Abiteboul, Hull and Vianu

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Prerequisites

Let’s Get Started!

•  Chapters 2 through 8 of the textbook: –  –  –  – 

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•  Isn’t Implementing a Database System Simple?

Relational Model, Entity/Relationship (E/R) Model Constraints, Functional Dependencies Views, Triggers Database query languages (Relational Algebra, SQL)

Relations

Statements

Results

•  Solid background in Data Structures and Algorithms •  Significant programming experience in Java •  Some knowledge of Compilers •  Curiosity! You should ask a lot of questions!


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Let’s Get Started!

Megatron 3000 Implementation Details •  Relations stored in files (ASCII) –  e.g., relation Movie Wild # Lynch # Winger Sky # Berto # Winger Reds # Beatty # Beatty …

•  Directory file (ASCII) Movie # Title # STR # Director # STR # Actor # STR … Schedule # Theater # STR # Title # STR … …


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Megatron 3000 Sample Sessions

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% MEGATRON3000 Welcome to MEGATRON 3000! &

& select * from Movie # Title Wild Sky Reds Tango Tango Tango

… & quit %

Director Lynch Berto Beatty Berto Berto Berto

Actor Winger Winger Beatty Brando Winger Snyder

&


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Megatron 3000 •  To execute select * from Movie where condition (1) Read dictionary to get Movie attributes (2) Read Movie file, for each line: (a) Check condition (b) If OK, display

& select Theater, Movie.Title from Movie, Schedule where Movie.Title = Schedule.Title AND Actor = “Winger” # Theater Title Odeon Wild Forum Sky &


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What’s wrong with the Megatron 3000 DBMS?

Megatron 3000

•  Tuple layout on disk

•  To execute select Theater, Movie.Title from Movie, Schedule where Movie.Title = Schedule.Title AND Actor = “Winger” (1) Read dictionary to get Movie, Schedule attributes (2) Read Movie file, for each line: (a) Read Schedule file, for each line: (i) Create join tuple (ii) Check condition (iii) Display if OK



–  Change string from ‘Cat’ to ‘Cats’ and we have to rewrite file –  Deletions are expensive

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What’s wrong with the Megatron 3000 DBMS? •  Brute force query processing For example:

•  Search expensive; no indexes –  Cannot find tuple with given key quickly –  Always have to read full relation

select Theater, Movie.Title from Movie, Schedule where Movie.Title=Schedule.Title and Actor = “Winger”

•  Much better if –  Use index to select tuples with “Winger” first –  Use index to find theaters where qualified titles play

•  Or –  Sort both relations on Title and merge-join

•  Exploit cache and buffers


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•  Concurrency control & recovery •  No reliability

•  Security •  Interoperation with other systems •  Consistency enforcement

–  Can lose data –  Can leave operations half done



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Course Topics

Course Topics

•  Hardware Aspects •  Physical Organization Structure

•  Concurrency Control Correctness, locks, deadlocks…

•  On-Line Analytical Processing

Records in blocks, dictionary, buffer management,…

Map-Reduce,…

•  Indexing

•  Database as a Service (DaaS) •  Cloud DBMS

B-Trees, hashing,…

•  Query Processing parsing, rewriting, logical/physical operators, algebraic and cost-based optimization, semantic optimization…

•  Crash Recovery Failures, stable storage,…

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Database System Architecture Query Processing

Example Journey of a Query

Transaction Management

SQL Query

SELECT Theater FROM Movie M, Schedule S WHERE M.Title = S.Title AND M.Actor=“Winger”

Calls from Transactions (read,write)

Parser Transaction Manager

relational algebra

Query Rewriter and Optimizer query execution plan

Execution Engine

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View Definitions Statistics & Catalogs & System Data

Buffer Manager

Concurrency Controller

Yet Another logical query plan

Lock Table

Parse/ Convert

Initial logical query plan

Query Rewriter applies Algebraic Rewriting Another logical query plan

Recovery Manager

Query Rewriter

Log Data + Indexes UB CSE 562 Spring 2010

Cont’d 23


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Example Journey of a Query (cont’d)

The Journey of a Query (cont’d) ActorIndex

Algebraic Optimization

Winger TitleIndex Cost-based Optimization

What are the rules used for the transformation of the query? How do we evaluate the cost of a possible execution plan?

EXECUTION ENGINE Query Execution Plan

find “Winger” tuples using ActorIndex for each “Winger” tuple find tuples t with the same title using TitleIndex project the attribute Actor of t

Index on Actor and Title Unsorted tables Tables >> Memory


Title Wild Sky Reds Tango Tango Tango

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Director Lynch Berto Beatty Berto Berto Berto

Actor Winger Winger Beatty Brando Winger Snyder

How is the table arranged on the disk? Are tuples with the same Actor value clustered? What is the exact structure of the index (tree, hash,…)? 26

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