Scaleable Computing Jim Gray Microsoft Corporation Gray@Microsoft
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Transcript of Scaleable Computing Jim Gray Microsoft Corporation Gray@Microsoft
Scaleable ComputingScaleable Computing
Jim GrayJim GrayMicrosoft CorporationMicrosoft Corporation
[email protected]@Microsoft.com
™
Thesis: Scaleable ServersThesis: Scaleable Servers Scaleable ServersScaleable Servers
Commodity hardware allows new applicationsCommodity hardware allows new applications New applications need huge serversNew applications need huge servers Clients and servers are built of the same “stuff”Clients and servers are built of the same “stuff”
Commodity software and Commodity software and Commodity hardwareCommodity hardware
Servers should be able to Servers should be able to Scale up Scale up (grow node by adding CPUs, disks, networks)(grow node by adding CPUs, disks, networks)
Scale out Scale out (grow by adding nodes)(grow by adding nodes)
Scale down Scale down (can start small)(can start small)
Key software technologiesKey software technologies Objects, Transactions, Clusters, ParallelismObjects, Transactions, Clusters, Parallelism
1987: 256 tps Benchmark 1987: 256 tps Benchmark 14 M$ computer (Tandem)14 M$ computer (Tandem) A dozen peopleA dozen people False floor, 2 rooms of machinesFalse floor, 2 rooms of machines
Simulate 25,600 clients
A 32 node processor array
A 40 GB disk array (80 drives)
OS expert
Network expert
DB expert
Performance expert
Hardware experts
Admin expert
Auditor
Manager
1988: DB2 + CICS Mainframe1988: DB2 + CICS Mainframe65 tps65 tps
IBM 4391 IBM 4391 Simulated network of 800 clientsSimulated network of 800 clients 2m$ computer2m$ computer Staff of 6 to do benchmarkStaff of 6 to do benchmark
2 x 3725 network controllers
16 GB disk farm4 x 8 x .5GB
Refrigerator-sizedCPU
1997: 10 years later1997: 10 years later1 Person and 1 box = 1250 tps1 Person and 1 box = 1250 tps
1 Breadbox ~ 5x 1987 machine room1 Breadbox ~ 5x 1987 machine room 23 GB is hand-held23 GB is hand-held One person does all the workOne person does all the work Cost/tps is 1,000x lessCost/tps is 1,000x less
25 micro dollars per transaction25 micro dollars per transaction4x200 Mhz cpu1/2 GB DRAM12 x 4GB disk
Hardware expertOS expertNet expertDB expertApp expert
3 x7 x 4GB disk arrays
What Happened?What Happened? Moore’s law: Moore’s law:
Things get 4x better every 3 yearsThings get 4x better every 3 years (applies to computers, storage, and networks)(applies to computers, storage, and networks)
New Economics: CommodityNew Economics: Commodityclassclass price/mips softwareprice/mips software $/mips k$/year $/mips k$/yearmainframe mainframe 10,000 10,000 100 100 minicomputerminicomputer 100 100 10 10microcomputer 10 microcomputer 10 1 1
GUI: Human - computer tradeoffGUI: Human - computer tradeoffoptimize for people, not computersoptimize for people, not computers
mainframeminimicro
time
pric
e
What Happens NextWhat Happens Next
Last 10 years: Last 10 years: 1000x improvement 1000x improvement
Next 10 years: Next 10 years: ????????
Today: Today: text and image servers are freetext and image servers are free
25 25 $/hit => advertising pays for $/hit => advertising pays for themthem
Future:Future:video, audio, … servers are freevideo, audio, … servers are free“You ain’t seen nothing yet!” “You ain’t seen nothing yet!”
1985 20051995
perf
orm
ance
Kinds Of Kinds Of Information ProcessingInformation Processing
It’s ALL going electronicIt’s ALL going electronic
Immediate is being stored for analysis (so ALL database)Immediate is being stored for analysis (so ALL database)
Analysis and automatic processing are being addedAnalysis and automatic processing are being added
Point-to-pointPoint-to-point BroadcastBroadcast
ImmediateImmediate
Time-Time-shiftedshifted
ConversationConversationMoneyMoney
LectureLectureConcertConcert
MailMail BookBookNewspaperNewspaper
NetworkNetwork
DatabaseDatabase
Why Put EverythingWhy Put EverythingIn Cyberspace?In Cyberspace?
Low rent -Low rent -min $/bytemin $/byte
Shrinks time -Shrinks time -now or laternow or later
Shrinks space -Shrinks space -here or therehere or there
Automate processing -Automate processing -knowbotsknowbots
Point-to-point Point-to-point OR OR
broadcastbroadcast
Imm
ed
iate
OR
tim
e-d
ela
ye
dIm
me
dia
te O
R t
ime
-de
lay
ed
NetworkNetwork
DatabaseDatabase
LocateLocateProcessProcessAnalyzeAnalyzeSummarizeSummarize
Magnetic Storage Magnetic Storage Cheaper Than PaperCheaper Than Paper
File cabinetFile cabinet:: cabinet (four drawer)cabinet (four drawer) 250$250$paper (24,000 paper (24,000
sheets)sheets) 250$250$ space space (2x3 @ 10$/ft(2x3 @ 10$/ft22)) 180$180$ totaltotal
700$700$
3¢/sheet3¢/sheet DiskDisk:: disk (4 GB =)disk (4 GB =) 800$800$
ASCII: 2 mil ASCII: 2 mil pagespages
00..04¢/sheet04¢/sheet (80x cheaper)(80x cheaper)
ImageImage:: 200,000 pages200,000 pages
0.4¢/sheet0.4¢/sheet (8x cheaper)(8x cheaper)
Store everything on diskStore everything on disk
DatabasesDatabasesInformation at Your FingertipsInformation at Your Fingertips™™
Information Network Information Network™™
Knowledge NavigatorKnowledge Navigator™™
All information will be in anAll information will be in anonline database (somewhere)online database (somewhere)
You might record everything you You might record everything you Read: 10MB/day, 400 GB/lifetimeRead: 10MB/day, 400 GB/lifetime
(eight tapes (eight tapes todaytoday)) Hear: 400MB/day, 16 TB/lifetimeHear: 400MB/day, 16 TB/lifetime
(three tapes/year (three tapes/year todaytoday)) See: 1MB/s, 40GB/day, 1.6 PB/lifetime See: 1MB/s, 40GB/day, 1.6 PB/lifetime
(maybe someday)(maybe someday)
Database StoreDatabase StoreALL Data TypesALL Data Types
The new world:The new world: Billions of objectsBillions of objects Big objects (1 MB)Big objects (1 MB) Objects have Objects have
behavior (methods)behavior (methods)
The old world:The old world: Millions of objectsMillions of objects 100-byte objects100-byte objects
PeoplePeople
NameName AddressAddress
MikeMike
WonWon
DavidDavid NYNY
BerkBerk
AustinAustinPeoplePeople
NameName AddressAddress PapersPapers PicturePicture VoiceVoice
MikeMike
WonWon
DavidDavid NYNY
BerkBerk
AustinAustin
Paperless officePaperless office Library of Congress onlineLibrary of Congress online All information onlineAll information online
EntertainmentEntertainmentPublishingPublishingBusinessBusiness
WWW and InternetWWW and Internet
Billions Of Clients Billions Of Clients
Every device will be “intelligent”Every device will be “intelligent” Doors, rooms, cars…Doors, rooms, cars… Computing will be ubiquitousComputing will be ubiquitous
Billions Of ClientsBillions Of ClientsNeed Millions Of ServersNeed Millions Of Servers
MobileMobileclientsclients
FixedFixedclients clients
ServerServer
SuperSuperserverserver
ClientsClients
ServersServers
All clients networked All clients networked to serversto servers May be nomadicMay be nomadic
or on-demandor on-demand Fast clients wantFast clients wantfasterfaster servers servers
Servers provide Servers provide Shared DataShared Data ControlControl CoordinationCoordination CommunicationCommunication
ThesisThesisMany little beat few bigMany little beat few big
Smoking, hairy golf ballSmoking, hairy golf ball How to connect the many little parts?How to connect the many little parts? How to program the many little parts?How to program the many little parts? Fault tolerance?Fault tolerance?
$1 $1 millionmillion $100 K$100 K $10 K$10 K
MainframeMainframe MiniMiniMicroMicro NanoNano
14"14"9"9"
5.25"5.25" 3.5"3.5" 2.5"2.5" 1.8"1.8"1 M SPECmarks, 1TFLOP1 M SPECmarks, 1TFLOP
101066 clocks to bulk ram clocks to bulk ram
Event-horizon on chipEvent-horizon on chip
VM reincarnatedVM reincarnated
Multiprogram cache,Multiprogram cache,On-Chip SMPOn-Chip SMP
10 microsecond ram
10 millisecond disc
10 second tape archive
10 nano-second ram
Pico Processor
10 pico-second ram
1 MM 3
100 TB
1 TB
10 GB
1 MB
100 MB
Future Super Server:Future Super Server:4T Machine4T Machine
Array of 1,000 4B machinesArray of 1,000 4B machines1 bps processors1 bps processors1 BB DRAM 1 BB DRAM 10 BB disks 10 BB disks 1 Bbps comm lines1 Bbps comm lines1 TB tape robot1 TB tape robot
A few megabucksA few megabucks Challenge:Challenge:
ManageabilityManageabilityProgrammabilityProgrammabilitySecuritySecurityAvailabilityAvailabilityScaleabilityScaleabilityAffordabilityAffordability
As easy as a single systemAs easy as a single system
Future servers are CLUSTERSFuture servers are CLUSTERSof processors, discsof processors, discs
Distributed database techniquesDistributed database techniquesmake clusters workmake clusters work
CPU
50 GB Disc
5 GB RAM
Cyber BrickCyber Bricka 4B machinea 4B machine
The Hardware Is In Place…The Hardware Is In Place…And then a miracle occursAnd then a miracle occurs
? SNAP: scaleable networkSNAP: scaleable network
and platformsand platforms Commodity-distributedCommodity-distributed
OS built on:OS built on: Commodity platformsCommodity platforms Commodity networkCommodity network
interconnectinterconnect Enables parallel applicationsEnables parallel applications
Thesis: Scaleable ServersThesis: Scaleable Servers Scaleable ServersScaleable Servers
Commodity hardware allows new applicationsCommodity hardware allows new applications New applications need huge serversNew applications need huge servers Clients and servers are built of the same “stuff”Clients and servers are built of the same “stuff”
Commodity software and Commodity software and Commodity hardwareCommodity hardware
Servers should be able to Servers should be able to Scale up Scale up (grow node by adding CPUs, disks, networks)(grow node by adding CPUs, disks, networks)
Scale out Scale out (grow by adding nodes)(grow by adding nodes)
Scale down Scale down (can start small)(can start small)
Key software technologiesKey software technologies Objects, Transactions, Clusters, ParallelismObjects, Transactions, Clusters, Parallelism
Scaleable ServersScaleable ServersBOTH SMP And ClusterBOTH SMP And Cluster
Grow up with SMP; 4xP6Grow up with SMP; 4xP6is now standardis now standardGrow out with clusterGrow out with clusterCluster has inexpensive partsCluster has inexpensive parts
ClusterClusterof PCs of PCs
SMP superSMP superserverserver
DepartmentalDepartmentalserverserver
PersonalPersonalsystemsystem
SMPs Have AdvantagesSMPs Have Advantages
Single system image Single system image easier to manage, easier easier to manage, easier to program threads in to program threads in shared memory, disk, Netshared memory, disk, Net
4x SMP is commodity4x SMP is commodity Software capable of 16xSoftware capable of 16x Problems:Problems:
>4 not commodity>4 not commodity Scale-down problem Scale-down problem
(starter systems expensive)(starter systems expensive) There There isis a BIGGEST one a BIGGEST one
SMP superSMP superserverserver
DepartmentalDepartmentalserverserver
PersonalPersonalsystemsystem
Building the Largest NodeBuilding the Largest Node There is a biggest node (size grows over time)There is a biggest node (size grows over time) Today, with NT, it is probably 1TBToday, with NT, it is probably 1TB We are building itWe are building it (with help from DEC and SPIN2)(with help from DEC and SPIN2)
1 TB GeoSpatial SQL Server database1 TB GeoSpatial SQL Server database (1.4 TB of disks = 320 drives).(1.4 TB of disks = 320 drives). 30K BTU, 8 KVA, 1.5 metric tons.30K BTU, 8 KVA, 1.5 metric tons.
Will put it on the Web as a demo app.Will put it on the Web as a demo app. 10 meter image of the ENTIRE PLANET.10 meter image of the ENTIRE PLANET. 2 meter image of interesting parts 2 meter image of interesting parts (2% of land)(2% of land)
One pixel per meter = 500 TB One pixel per meter = 500 TB uncompressed.uncompressed.
Better resolution in US (courtesy of USGS).Better resolution in US (courtesy of USGS).
www.SQL.1TB.com
SupportSupportfilesfiles
1-TB SQL Server DB1-TB SQL Server DBSatellite and aerial Satellite and aerial
photosphotos
Todo loo da loo-rah, ta da ta-la la la
Todo loo da loo-rah, ta da ta-la la la
Todo loo da loo-rah, ta da ta-la la la
Todo loo da loo-rah, ta da ta-la la la
Todo loo da loo-rah, ta da ta-la la la
Todo loo da loo-rah, ta da ta-la la la
Todo loo da loo-rah, ta da ta-la la la
1-TB home page1-TB home page
TM
What’s TeraByte?What’s TeraByte? 1 Terabyte:1 Terabyte: 1,000,000,000 business letters 150 miles of book shelf1,000,000,000 business letters 150 miles of book shelf 100,000,000 book pages 100,000,000 book pages 15 miles of book shelf 15 miles of book shelf 50,000,000 FAX images50,000,000 FAX images 7 miles of book shelf 7 miles of book shelf 10,000,000 TV pictures (mpeg) 10 days of video 10,000,000 TV pictures (mpeg) 10 days of video
4,000 LandSat images 4,000 LandSat images 16 earth images (100m) 16 earth images (100m) 100,000,000 web page 10 copies of the web HTML100,000,000 web page 10 copies of the web HTML
Library of Congress (in ASCII) is 25 TBLibrary of Congress (in ASCII) is 25 TB 1980: $200 million of disc1980: $200 million of disc 10,000 discs 10,000 discs
$5 million of tape silo$5 million of tape silo 10,000 tapes 10,000 tapes
1997: $200 k$ of magnetic disc 48 discs1997: $200 k$ of magnetic disc 48 discs $30 k$ nearline tape 20 tapes$30 k$ nearline tape 20 tapes
Terror Byte !Terror Byte !
TB DB User InterfaceTB DB User Interface
+ +
+
Next
Tpc-C Web-Based BenchmarksTpc-C Web-Based Benchmarks Client is a Web browser Client is a Web browser
(7,500 of them!)(7,500 of them!) Submits Submits
OrderOrder InvoiceInvoice Query to server via Web Query to server via Web
page interfacepage interface
Web server translates to DBWeb server translates to DB SQL does DB workSQL does DB work Net: Net:
easy to implement easy to implement performance is GREAT!performance is GREAT!
HT
TP
HT
TP
OD
BC
OD
BC
SQL SQL
IISIIS= Web= Web
Grow UP and OUT Grow UP and OUT
1 billion 1 billion transactions transactions
per dayper day
SMP superSMP superserverserver
DepartmentalDepartmentalserverserver
PersonalPersonalsystemsystem
1 Terabyte DB1 Terabyte DB
Cluster: •a collection of nodes •as easy to program and manage as a single node
Clusters Have AdvantagesClusters Have Advantages
Clients and servers made from the same stuffClients and servers made from the same stuff Inexpensive: Inexpensive:
Built with commodity components Built with commodity components
Fault tolerance: Fault tolerance: Spare modules mask failuresSpare modules mask failures
Modular growthModular growth Grow by adding small modulesGrow by adding small modules
Unlimited growth: Unlimited growth: no biggest oneno biggest one
Windows NT ClustersWindows NT Clusters Microsoft & 60 vendors defining NT clustersMicrosoft & 60 vendors defining NT clusters
Almost all big hardware and software vendors involvedAlmost all big hardware and software vendors involved
No special hardware needed - but it may helpNo special hardware needed - but it may help Fault-tolerant first, scaleable secondFault-tolerant first, scaleable second
Microsoft, Oracle, SAP giving demos todayMicrosoft, Oracle, SAP giving demos today Enables Enables
Commodity fault-toleranceCommodity fault-tolerance Commodity parallelism (data mining, virtual reality…)Commodity parallelism (data mining, virtual reality…) Also great for workgroups!Also great for workgroups!
Billion Transactions per DayBillion Transactions per DayProjectProject
Building a 20-node Windows NT Building a 20-node Windows NT Cluster (with help from Intel)Cluster (with help from Intel)> 800 disks> 800 disks
All commodity partsAll commodity parts Using SQL Server & Using SQL Server &
DTC distributed transactionsDTC distributed transactions Each node has 1/20 th of the DB Each node has 1/20 th of the DB Each node does 1/20 th of the Each node does 1/20 th of the
workwork 15% of the transactions are 15% of the transactions are
“distributed”“distributed”
How Much Is 1 Billion How Much Is 1 Billion Transactions Per Day?Transactions Per Day?
Millions of transactions per dayMillions of transactions per day
0.10.1
1.1.
10.10.
100.100.
1,000.1,000.
1 B
tpd
1 B
tpd
Vis
aV
isa
AT
&T
AT
&T
Bo
fAB
ofA
NY
SE
NY
SE
Mtp
dM
tpd
1 Btpd = 11,574 tps 1 Btpd = 11,574 tps (transactions per second)(transactions per second) ~ 700,000 tpm ~ 700,000 tpm (transactions/minute)(transactions/minute)
AT&T AT&T 185 million calls 185 million calls
(peak day worldwide)(peak day worldwide) Visa ~20 M tpdVisa ~20 M tpd
400 M customers400 M customers 250,000 ATMs worldwide250,000 ATMs worldwide 7 billion transactions / year 7 billion transactions / year
(card+cheque) in 1994 (card+cheque) in 1994
ParallelismParallelismThe OTHER aspect of clustersThe OTHER aspect of clusters
Clusters of machines Clusters of machines allow two kinds allow two kinds of parallelismof parallelism Many little jobs: online Many little jobs: online
transaction processingtransaction processing TPC-A, B, C…TPC-A, B, C…
A few big jobs: data A few big jobs: data search and analysissearch and analysis TPC-D, DSS, OLAPTPC-D, DSS, OLAP
Both give Both give automatic parallelismautomatic parallelism
Jim Gray & Gordon Bell: VLDB 95 Parallel Database Systems Survey
Kinds of Parallel ExecutionKinds of Parallel Execution
Pipeline
Partition outputs split N ways inputs merge M ways
Any Sequential Program
Any Sequential Program
Any Sequential
Any Sequential Program Program
Jim Gray & Gordon Bell: VLDB 95 Parallel Database Systems Survey
Partitioned ExecutionPartitioned Execution
A...E F...J K...N O...S T...Z
A Table
Count Count Count Count Count
Count
Spreads computation and IO among processors
Partitioned data gives NATURAL parallelism
Jim Gray & Gordon Bell: VLDB 95 Parallel Database Systems Survey
N x M way ParallelismN x M way Parallelism
A...E F...J K...N O...S T...Z
Merge
Join
Sort
Join
Sort
Join
Sort
Join
Sort
Join
Sort
Merge Merge
N inputs, M outputs, no bottlenecks.
Partitioned DataPartitioned and Pipelined Data Flows
The Parallel Law The Parallel Law Of ComputingOf Computing
Grosch's Law: Grosch's Law:
Parallel Law:Parallel Law:Needs:Needs:
Linear speedup and linear scale-upLinear speedup and linear scale-upNot always possibleNot always possible 1 MIPS 1 MIPS
1 $1 $
1,000 MIPS1,000 MIPS1,000 $1,000 $
2x $ is2x performance
1 MIPS1 MIPS1 $1 $
1,000 MIPS1,000 MIPS 32 $32 $.03$/MIPS.03$/MIPS
2x $ is 4x performance
Thesis: Scaleable ServersThesis: Scaleable Servers Scaleable ServersScaleable Servers
Commodity hardware allows new applicationsCommodity hardware allows new applications New applications need huge serversNew applications need huge servers Clients and servers are built of the same “stuff”Clients and servers are built of the same “stuff”
Commodity software and Commodity software and Commodity hardwareCommodity hardware
Servers should be able to Servers should be able to Scale up Scale up (grow node by adding CPUs, disks, networks)(grow node by adding CPUs, disks, networks)
Scale out Scale out (grow by adding nodes)(grow by adding nodes)
Scale down Scale down (can start small)(can start small)
Key software technologiesKey software technologies Objects, Transactions, Clusters, ParallelismObjects, Transactions, Clusters, Parallelism
The BIG PictureThe BIG PictureComponents and transactionsComponents and transactions
Software modules are objects Software modules are objects Object Request Broker (a.k.a., Transaction Object Request Broker (a.k.a., Transaction
Processing Monitor) connects objectsProcessing Monitor) connects objects(clients to servers)(clients to servers)
Standard interfaces allow software plug-insStandard interfaces allow software plug-ins Transaction ties execution of a “job” into an Transaction ties execution of a “job” into an
atomic unit: all-or-nothing, durable, isolatedatomic unit: all-or-nothing, durable, isolated
Object Request BrokerObject Request Broker
Linking And EmbeddingLinking And EmbeddingObjects are data modules;Objects are data modules;
transactions are execution modulestransactions are execution modules
Link: pointer to object Link: pointer to object somewhere elsesomewhere else Think URL in InternetThink URL in Internet
Embed: bytesEmbed: bytesare hereare here
Objects may be Objects may be activeactive; ; can callback to subscriberscan callback to subscribers
Objects Meet DatabasesObjects Meet DatabasesThe basis for The basis for universaluniversal
data servers, access, & integrationdata servers, access, & integration
DBMSDBMSengineengine
object-oriented (COM oriented) object-oriented (COM oriented) programming interface to dataprogramming interface to data
Breaks DBMS into componentsBreaks DBMS into components Anything can be a data sourceAnything can be a data source Optimization/navigation “on top Optimization/navigation “on top
of” other data sourcesof” other data sources A way to componentized a A way to componentized a
DBMSDBMS Makes an RDBMS and O-RMakes an RDBMS and O-R
DBMS (assumes optimizer DBMS (assumes optimizer understands objects)understands objects)
DatabaseDatabase
SpreadsheetSpreadsheet
PhotosPhotos
MailMail
MapMap
DocumentDocument
43
The Three The Three TiersTiers
Web Client
HTML
VB or Java Script Engine
VB or Java Virt Machine
VBscritptJavaScrpt
VB Javaplug-ins
InternetORB
HTTP+DCOM
ObjectserverPool
MiddlewareORB
TP MonitorWeb Server...
DCOM (oleDB, ODBC,...)
Object & Dataserver.
LU6.2
IBMLegacy Gateways
47
Server Side ObjectsServer Side Objects Easy Server-Side ExecutionEasy Server-Side Execution
Give simple execution Give simple execution environmentenvironment
Object gets Object gets startstart invokeinvoke shutdownshutdown
Everything else is Everything else is automaticautomatic
Drag & Drop Business Drag & Drop Business ObjectsObjects
NetworkNetwork
Thread PoolThread Pool
QueueQueue
ConnectionsConnections
ContextContext SecuritySecurity
Shared Data
ReceiverReceiver
SynchronizationSynchronization
Service logic
Co
nfig
ura
tion
Co
nfig
ura
tion
Ma
na
ge
me
nt
Ma
na
ge
me
nt
A Server
A new programming paradigm Develop object on the desktopDevelop object on the desktop Better yet: download them from the NetBetter yet: download them from the Net Script work flows as method invocations Script work flows as method invocations All on desktopAll on desktop Then, move work flows and objects to server(s)Then, move work flows and objects to server(s) GivesGives
desktop development desktop development three-tier deploymentthree-tier deploymentSoftware CyberbricksSoftware Cyberbricks
Transactions Coordinate Transactions Coordinate Components (ACID)Components (ACID)
Transaction propertiesTransaction properties Atomic: all or nothingAtomic: all or nothing Consistent: old and new valuesConsistent: old and new values Isolated: automatic locking or versioningIsolated: automatic locking or versioning Durable: once committed, effects surviveDurable: once committed, effects survive Transactions are built into modern OSsTransactions are built into modern OSs
MVS/TM Tandem TMF, VMS DEC-DTM, NT-DTCMVS/TM Tandem TMF, VMS DEC-DTM, NT-DTC
Transactions & ObjectsTransactions & Objects Application requests transaction Application requests transaction
identifier (XID)identifier (XID) XID flows with method invocationsXID flows with method invocations Object Managers join (enlist)Object Managers join (enlist)
in transactionin transaction Distributed Transaction Manager Distributed Transaction Manager
coordinates commit/abortcoordinates commit/abort
Distributed TransactionsDistributed Transactions Enable Huge Throughput Enable Huge Throughput
Each node capable of 7 KtmpC Each node capable of 7 KtmpC (7,000 (7,000 activeactive users!) users!) Can add nodes to cluster Can add nodes to cluster (to support 100,000 users)(to support 100,000 users)
Transactions coordinate nodesTransactions coordinate nodes ORB / TP monitor spreads work among nodesORB / TP monitor spreads work among nodes
Distributed TransactionsDistributed Transactions Enable Huge DBs Enable Huge DBs
Distributed database technology Distributed database technology spreads data among nodesspreads data among nodes
Transaction processing technology Transaction processing technology manages nodesmanages nodes
Thesis: Scaleable ServersThesis: Scaleable Servers Scaleable Servers Built from CyberbricksScaleable Servers Built from Cyberbricks
Allow new applicationsAllow new applications
Servers should be able to Servers should be able to Scale up, out, downScale up, out, down
Key software technologiesKey software technologies Clusters (ties the hardware together)Clusters (ties the hardware together) Parallelism: (Parallelism: (uses the independent cpus, stores, wiresuses the independent cpus, stores, wires
Objects (software CyberBricks) Objects (software CyberBricks) Transactions: masks errors.Transactions: masks errors.