CPS 216: Advanced Database Systems Shivnath Babu

Outline for Today What this class is about: Data management What we will cover in this class Logistics What does a Database System mean to you? (Hint: What are they used for? Give examples)

Data Management Data Query User/Application DataBase Management System (DBMS)

Example: At a Company IDNameDeptIDSalary… 10Nemo12120K… 20Dory15679K… 40Gill8976K… 52Ray3485K… …………… IDName… 12IT… 34Accounts… 89HR… 156Marketing… ……… EmployeeDepartment Query 1: Is there an employee named “Nemo”? Query 2: What is “Nemo’s” salary? Query 3: How many departments are there in the company? Query 4: What is the name of “Nemo’s” department? Query 5: How many employees are there in the “Accounts” department?

DataBase Management System (DBMS)High-level Query Q DBMS Data Answer Translates Q into best execution plan for current conditions, runs plan

Example: Store that Sells Cars MakeModelOwnerID HondaAccord12 ToyotaCamry34 MiniCooper89 HondaAccord156 ……… IDNameAge 12Nemo22 34Ray42 89Gill36 156Dory21 ……… Cars Owners Filter (Make = Honda and Model = Accord) Join (Cars.OwnerID = Owners.ID) MakeModelOwnerIDIDNameAge HondaAccord12 Nemo22 HondaAccord156 Dory21 Owners of Honda Accords who are <= 23 years old Filter (Age <= 23)

DataBase Management System (DBMS)High-level Query Q DBMS Data Answer Translates Q into best execution plan for current conditions, runs plan Keeps data safe and correct despite failures, concurrent updates, online processing, etc.

DBMS is multi-user Example Get account balance from database; If balance > amount of withdrawal then balance = balance - amount of withdrawal; dispense cash; store new balance into database; Homer at ATM1 withdraws $100 Marge at ATM2 withdraws $50 Initial balance = $400, final balance = ? –Should be $250 no matter who goes first

Final balance = $250 read balance; $400 if balance > amount then balance = balance - amount; $300 write balance; $300 read balance; $300 if balance > amount then balance = balance - amount; $250 write balance; $250 Homer withdraws $100: Marge withdraws $50:

Final balance = $300 read balance; $400 if balance > amount then balance = balance - amount; $300 write balance; $300 read balance; $400 If balance > amount then balance = balance - amount; $350 write balance; $350 Homer withdraws $100: Marge withdraws $50:

Final balance = $350 read balance; $400 if balance > amount then balance = balance - amount; $300 write balance; $300 read balance; $400 if balance > amount then balance = balance - amount; $350 write balance; $350 Homer withdraws $100: Marge withdraws $50:

Concurrency control in DBMS Similar to concurrent programming problems –But data is not all in main-memory Appears similar to file system concurrent access? –Approach taken by MySQL initially; now MySQL offers better alternatives But want to control at much finer granularity Or else one withdrawal would lock up all accounts!

Recovery in DBMS Example: balance transfer decrement the balance of account X by $100; increment the balance of account Y by $100; Scenario 1: Power goes out after the first instruction Scenario 2: DBMS buffers and updates data in memory (for efficiency); before they are written back to disk, power goes out Log updates; undo/redo during recovery

DataBase Management System (DBMS)High-level Query Q DBMS Data Answer Translates Q into best execution plan for current conditions, runs plan Keeps data safe and correct despite failures, concurrent updates, online processing, etc.

Summary of modern DBMS features Persistent storage of data Logical data model; declarative queries and updates ! physical data independence Multi-user concurrent access Safety from system failures Performance, performance, performance –Massive amounts of data (terabytes ~ petabytes) –High throughput (thousands ~ millions transactions per minute) –High availability (¸ % uptime)

Modern DBMS Architecture Disk(s) Applications OS Parser Query Optimizer Query Executor Storage Manager Logical query plan Physical query plan Access method API calls SQL File system API calls Storage system API calls DBMS

World of “Big Data” Numbers reported by Google from 2007: –Data processed per month is 400 PB (PetaBytes) –Average job size is 180 GB For 180 GB of data, it takes: –30 minutes to read from disk MB/s) –600 minutes to download at 5 MB/s Big data is hard to move (but easy to store – few cents per GB) Can throw parallelism at the problem

Word Count over a Given Set of Web Pages see bob throw see1 bob1 throw 1 see 1 spot 1 run 1 bob1 run 1 see 2 spot 1 throw1 see spot run Can we do word count in parallel?

The MapReduce Framework (pioneered by Google)

Automatic Parallel Execution in MapReduce Handles failures automatically, e.g., restarts tasks if a node fails; runs multiples copies of the same task to avoid a slow task slowing down the whole job

Course Outline Principles of query processing (25%) –Indexes –Query execution plans and operators –Query optimization Data storage (15%) –Databases Vs. filesystems (Google FileSystem, Hadoop Distributed FileSystem) –Row-oriented Vs. column-oriented storage –Flash memory and Solid State Drives Scalable data processing (30%) –Parallel query plans and operators –Systems based on MapReduce –Scalable key-value stores Concurrency control and recovery (15%) –Consistency models for data (ACID, BASE, Serializability) –Write-ahead logging Information retrieval and Data mining (15%) –Web search (Google PageRank, inverted indexes) –Association rules and clustering

Course Logistics Useful reference: Database Systems: The Complete Book, by H. Garcia-Molina, J. D. Ullman, and J. Widom Web site: Grading: –Project 40% –Homework Assignments 15% –Midterm 20% –Final 25%

Summary: Data Management is Important Core aspect of most sciences and engineering today Core need in industry (esp., “big data”) Cool mix of theory and systems Chances are you will find something interesting even if you primary interest is elsewhere