INFO3404/3504 - Database Systems II

INFO3404/3504 - Database Systems II Week 1: Introduction to Database Systems II Dr. Uwe Röhm School of Information Technologies Example: Facebook Source: Facebook INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-2

Some Facebook Statistics In September 2011, Facebook reached over 750 million users worldwide. Over past two years: 7x growth in raw user data. Over Halloween weekend 2011: 1 billion photos were uploaded. Infrastructure: - data centers with nx10,000 servers - several specialised data stores - sharded MySQL database for actual user database http://en.wikipedia.org/wiki/facebook_statistics/ http://www.socialbakers.com/facebook-statistics/ http://gigaom.com/cloud/facebook-shares-some-secrets-on-making-mysql-scale/ INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-3 Example: Wikipedia INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-4

Wikipedia Hardware and Software! Wikipedia: (as of July 2012 - http://stats.wikimedia.org/en/sitemap.htm)! 271 languages, millions of articles (English: 4 million articles with more than 12GB data)! 21 million page views per hour (sum over all languages) 11.3 million article edits per month (all languages)! Software:! January 2001:! Wikipedia on UseModWiki (written in Perl) on Linux => articles in files! In 2002:! Development of own wiki platform: MediaWiki! PHP-based with either MySQL or PostgreSQL (since v1.8) as backend! As of 2011: MediaWiki v1.19.1! External text search engine (Apache Lucene)! 15 Jan 2011: 10 th birthday Sources: http://en.wikipedia.org/wiki/history_of_wikipedia INFO3404 "Database Systems II" - 2011 (U. Röhm and H. Jung) 12-5 Wikipedia Hardware! Hardware:! Clustered architecture, over 400 servers around the globe! As of 2012: Two global locations! Tampa, Florida! Amsterdam, Netherlands! (formerly also a third one in Korea)! commodity x86_64 Linux servers Source: http://meta.wikimedia.org/wiki/wikimedia_servers http://wikitech.wikimedia.org/view/server_roles INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-6

Example: News Websites! SPIEGEL online (big German news paper)! March 1994: 175,000 hits p.m.! July 2006: 437,018,954 hits p.m.! July 2011: 77million views per day! In Australia:! smh.com.au: 2.93 million visitors in April 2012! NineMSN: 1,558,776,000 page hits p.m. (May 2012) Source: www.spiegel.de (Source: Nielsen Online Ratings April 2012) INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-7 Example: Scale of Today s Workloads! Ebay (in 2005):! ca. 5 billion SQL/day! More than 100 back-end databases! VISA! In 2002, claimed 8 minutes downtime in past 5 years (uptime > 99.9999%) INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-8

The Scale of Today s Data! It is common now to deal in units of petabytes (10 15 )! Some examples from Wikipedia (July 2010)! Yahoo! claimed record with 1 Petabyte Database back in 2005! Google processes 24 petabytes/day! Teradata database has capacity of 50 petabytes of compressed data! World of Warcraft uses 1.3 petabytes of storage! Large Hadron Collider (LHC) will generate 15 petabytes per year.! Manage and access large data! Go to seek.com.au and search for the keyword data architect! This course will teach you to be a vendor-neutral data architect INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-9 Grand Theme of INFO3404/3504! How to efficiently deal with SCALE?! Large collections of data (hundreds of gigabytes)! both structured (tuples)! and unstructured (text or (key,value) pairs)! we are interested on cases where data does not fit into memory.! Shared access by large numbers of concurrent users (thousands)! Availability always ON! Questions:! How to efficiently manage large amounts of data?! How to efficiently find data in those collections?! How to efficiently serve thousands of concurrent users?! How to efficiently (and correct) execute concurrent updates and retrievals? INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-10

Key Principles! Data Independence! Applications are decoupled from structure of data! Logical data model is decoupled from physical model! Declarative interface! Specify what rather than how.! Separate interface from implementation.! Space can be reused but not time! Speed-up lookups and joins! Transparent concurrency: Internal mechanisms to manage concurrency using transactions or groups of statements. INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-11 What is a DBMS?! A Database is a collection of data central to some organisation or enterprise! Essential to operation of enterprise! State of database mirrors state of enterprise! An improtant asset on its own! A Database Management System (DBMS) is a software package that manages a database:! Stores the database on some mass storage (+backup +recovery).! Supports a high-level access language (e.g. SQL).! Application describes database accesses using that language.! DBMS interprets statements of language to perform requested database access. INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-12

Levels of Abstraction! Many views, single conceptual (logical) schema and physical schema.! Views describe how users see the data.! Conceptual schema defines logical structure! Physical schema describes the files and indexes used. View 1 View 2 View 3 Conceptual Schema Physical Schema! In INFO3404/3504, we will look at! the physical layer! the translation between conceptual and physical schema, and! cross-layer aspects of DBMS. Knowledge of the database internals is the pre-requisite for effective performance tuning. INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-1 3 Data Independence! Applications are insulated from how data is structured and stored.! Logical data independence: Protection from changes in logical structure of data.! Physical data independence: Protection from changes in physical structure of data.! One of the most important benefits of using a DBMS!! INFO3404:! Which physical design choices do we have available?! What are the advantage / disadvantages of each structure? INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-15

The Nature of SQL! In the programming world new languages are constantly being invented Java, C#, Python, Ruby etc.! In the database world attempts to replace SQL with other languages have consistently failed SQL ends up being extended.! Why is SQL so versatile? => The declarative nature of SQL! In modern parlance SQL was probably the first widely accepted language to successfully decouple the interface design from the implementation.! SQL syntax is syntactic sugar for relational calculus. ( most practical thing is to have a good theory ) INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-16 SQL Example! Find all students that are enrolled in INFO3404.! SELECT s.sid, s.name FROM students s, enrolled e WHERE s.sid = e.sid AND e.cid = INFO3404! Given this formal description of what we want, how does a DBMS efficiently find the information?! Is there an index? Shall we use it? How to join the two tables?! Query Processing:! Translation into internal representation! Query optimization! Query execution INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-17

Query Optimization project sid,name project sid,name select cid= INFO3404 Are they all doing the same? join join Which is more efficient? students select cid= INFO3404 enrolled students enrolled project sid,name join select cid= INFO3404 project sid,name enrolled students INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-18 Example: Perl Script vs SQL #!perl use strict; my $in = shift or die; # illumina sequence file my $out = shift or die; # output file for binned sequences open (FH, "$in") or die; my @lines = <FH>; close FH; my %reads; for my $line (@lines) { chomp $line; my $read; if ($line =~ /\:([A T C G]+)\:/ $line =~ /^([A T G C]+)/) { $read = $1; if ($reads{$read}->{count}) { $reads{$read}->{count}++; } else { $reads{$read}->{count} = 1; } }} @lines = ""; open (OUT, ">$out") or warn; my $m =1; # for rank A relatively simple Perl script from a Bioinformatics project that processes a file (binning of unique short-reads ) for my $read (sort { $reads{$b}->{count} <=> $reads{$a}->{count} } keys %reads) { print OUT ">$reads{$read}->{count}\-$m\n$read\n"; # count, rank $m++; } close OUT; INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-19

The Same in SQL INSERT INTO UniqueRead SELECT ROW_NUMBER()OVER(ORDER BY COUNT(*)DESC), COUNT(*), r_sequence FROM ShortReads WHERE r_e_id=1 AND r_sg_id=2 AND r_s_id=1 AND CHARINDEX('N',r_sequence) = 0 GROUP BY r_sequence! Basically a group-by/aggregation query! Tricky part is to determine the rank of a result INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-20 Perl Script Performance Note that the CPU load is only 25% - Why? INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-21

SQL Query Performance SQL => automatic parallel query execution (4 cores available) INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-22 Concurrency Control! Concurrent execution of user programs is essential for good DBMS performance.! Because disk accesses are frequent, and relatively slow, it is important to keep the cpu humming by working on several user programs concurrently.! Interleaving actions of different user programs can lead to inconsistency: e.g., check is cleared while account balance is being computed.! DBMS ensures such problems don t arise: users can pretend they are using a single-user system.! How is this done?! What are the advantage / disadvantages of each approach? INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-23

Transactions! Key concept is transaction, which is an atomic sequence of database actions (reads/writes).! Each transaction, executed completely, must leave the DB in a consistent state if DB is consistent when the transaction begins.! Atomicity : either all statements of a transaction take effect or none.! Consistency: If a database starts in a consistent state and each individual transaction is consistent, then database ends in a consistent state after transactions are executed.! Isolation: A Transaction executes as if it were the only one active in the system.! Durability: Transactions should survive system and media failure. INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-24 Transaction Example! T1 (John): 1. Read(x) from DB 2. If x >= 50 Then x := x -50 3. Dispense cash 4. Write(x) to DB! T2 (Jane): 1. Read(x) from DB 2. Read(y) from DB 3. If x >= 100 Then x := x-100 4. y := y +100 5. Write(x) to DB 6. Write(y) to DB X=200 -> T1 -> T2 -> X=50 X=200 -> T1.1 -> T2.1 -> T2.2 -> T2.3 -> T2.5 -> T1.2 -> T1.4 -> X=150 Ups INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-25

Challenge: Multi-Core CPUs! For example, some latest toy :! 4 x eight-core Opteron CPUs (2GHz)! 128 GB RAM! 4 TB HDDs! 2 x 250GB SDDs! 2 x Gigabit Ethernet! Servers with 64 cores and more are available already! These systems can execute multiple transactions and queries in parallel on different CPU cores! But we have to synchronize them when they access shared data!! The challenge: How to do this fast and correctly at the same time? INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-26 Internal Structure of a DBMS! A typical DBMS has a layered architecture Web Forms Application Front Ends SQL Interface SQL Commands! This is one of several possible architectures; each system has its own variations Transaction Manager Lock Manager Concurrency Control Parser Plan Executor Optimizer Operator Evaluator File and Access Methods Buffer Manager Disk Space Manager Query Evaluation Engine Recovery Manager DBMS DATABASE Index Files Data Files System Catalog INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) Source: Ramakrishnan,Gehrke, 2003." 1-2 7

All DBMS Have the Same Architecture? INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-28 Excurse: Operating System Process Model! Operating System Process! Program execution unit! Own private address space! Own resource handles (e.g. open files, network connections)! Unit of OS scheduling! Operating System Thread! Program execution unit without private address space! Address space and OS resource handles are shared among all threads of the same multi-threaded process! Scheduled by OS ( kernel threads )! Lightweight Thread Package! an application-level construct that supports multiple threads within a single OS process; scheduled by application-own scheduler! Advantage: faster thread switching as done in user space! Disadvantage: Any blocking operation blocks all lightweight threads INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-29

Mapping of DBMS Functionality to OS Process Model! DBMS Client! software component that communicates with a DBMS! Either in-process (DBMS is just a linked library, eg. BerkeleyDB or SQLite)! or via network or IPC to separate DBMS server! DBMS Worker Thread! thread of execution in DBMS side to does work on behalf of a DBMS client: executes SQL and returns result to client! 1:1 mapping between DBMS client and one Worker Thread! DBMS Internal Threads! Several housekeeping tasks that need independent execution! Typically: decoupled writing of updated data and snapshot creation! Question: How to map DBMS Threads to OS Threads? INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-30 Classification of DB Servers DB Server Monolithic Server single DB process thread per DBMS worker Multiple Server multiple DB processes process per DBMS worker Symmetric per client one DB process Asymmetric dynamic assignment of client to DB processes process pool INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-31

Monolithic Server! Exactly one server process for all clients ( One-to-many )! DBMS server process typically prioritised by operating system! Server uses multi-threading! Own DBMS resource management! Examples: Sybase, MS SQL Server, Oracle on Windows Client 1 CL Client i CL Client k CL multi-threaded DBMS Server operating system 1 operating system n network INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-32 Multiple Server! DBMS consists of several processes! Scheduling done by the operating system! Communication between! server processes: via shared memory! clients and servers: via operating system or network! Two variants:! Symmetric - each client is mapped to exactly one server process: static mapping with a certain number of n servers pre-generated " maximal degree of parallelism is n! Asymmetric / process pool - a dispatcher connects a client to a server process. Again, a certain number of servers are instantiated beforehand, but degree of parallelism can be higher! Examples: Oracle, Informix, DB2 INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-33

Example: Asymmetric Multiple Server AP Client 1 CL AP Client i CL AP Client m CL Dispatcher DBMS Server 1 shared mem DBMS Server k Operating system 1 Operating system n network INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-34 Examples: Sybase and Oracle! Sybase: Monolithic Server! single server process! own lightweight thread-scheduling! less shared memory! Oracle: Multiple Server! Configurable as either symmetric or asymmetric! dedicated server! shared server with dispatcher! DB processes with different tasks:! Recoverer, Process Monitor,System Monitor, Database Writer, Log Writer, Archiver, Checkpoint, Dispatcher, Lock INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-35

Example: Oracle Process Overview LCKn RECO PMON SMON System Global Area Database Buffer Cache Redo Log Buffer User Shared Dedicated Server Server D000 DBW0 User CKPT LGWR ARC0 Offline Storage Control Data Redo Log INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-36 Oracle Process Overview (cont d)! User - user clients (JDBC programs, Oracle tools, etc.)! LCKn - Lock Process (Parallel Server Option)! RECO - Recoverer (deals with hanging distributed transactions)! PMON - Process Monitor (cleans up after process failure)! SMON - System Monitor (startup recovery, garbage collection)! D000 - Dispatcher (responsible for communication with clients)! Snnn - Share Server Processes! DBWn - Database Writer (writes db buffer blocks back to disk)! CKPT - Checkpoint! LGWR - Logwriter (writes Redo information to the disk)! ARCn - Archiver (copies Redo-logfiles onto the backup medium) INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-37

Information Retrieval (IR)! While DBMS focus on structured data (set of tuples), Information Retrieval work with (unstructured) text documents! Search and Rank Queries! Keyword Search Database Internals! Questions: 1. How should data be organized to answer the query efficiently. 2. In what order should the results be displayed.! Challenge: again Scale! large document collections, large texts! e.g. Wikipedia, USYD library, library of congress etc. INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-38 IR Example! Find all information about DBMS Internals! SQL: SELECT * FROM books WHERE content like %DBMS%Internals% (title?) ORDER BY???! IR: keyword query DBMS internals! Result: 1. DBMS.DBMS Internals DBMS Internals 2. DB Systems DBMS Internals of DBMS 3. My Book DBMS Internals INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-39

IR versus DBMS! Seem like very different beasts: IR Imprecise Semantics Keyword search Unstructured data format Read-Mostly. Add docs occasionally Page through top k results DBMS Precise Semantics SQL Structured data Expect reasonable number of updates Generate full answer! Both support queries over large datasets, use indexing.! In practice, you currently have to choose between the two. INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-40 Summary! DBMS used to maintain & query large datasets! Main Benefits:! Program-Data Independence! Controlled Data Redundancy! Declarative Queries! Transactions! DBMS internals not only of interest to DBAs, but for every SW developer facing large-scale data problems! Big Challenges: Internet-Scale and latest hardware developments (multi-core CPUs and SSDs) INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-41

! Storage Layer! Disks, Blocks and Pages! Buffer Management! Row and page structures! Data Compression Next Week! Row Store vs. Column Store! Readings:! Ramakrishnan/Gehrke, Chapter 9! Kifer/Bernstein/Lewis, Chapter 9 INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-42! INFO3404:! Check for elearning updates Tasks for this week! INFO3504:! Check for elearning and Timetable updates! Read Chapters 1 and 2 of Architecture of a Database System by Joe Hellerstein, Michael Stonebraker and James Hamilton (available on course website)! Download PostgreSQL 9.1 source code (latest stable version) from postgresql.org and try to compile/make INFO3404/3504 "Database Systems II" - 2012 (U. Röhm) 1-43