CSC407: Software Architecture Winter 2007 Middleware

Transcription

1 CSC407: Software Architecture Winter 2007 Middleware Greg Wilson BA Overview The term middleware refers to the plumbing that holds applications together Provides proven ways to connect software components so they can exchange information relatively easily Completely hidden from end users At least, until something goes wrong 2 1

2 Roadmap Business Process Orchestrators Message Brokers Application Servers Transport ActiveBPEL SonicMQ J2EE,.NET Message-Oriented Middleware, Distributed Object Systems 3 The Layers Transport layer moves messages around Appliaction servers provide transactions, security, and directory services Message brokers define how to exchange, manipulate, and route messages between application components BPOs support workflow-style applications E.g., keep track of outstanding purchase orders 4 2

3 Distributed Object Systems Object-oriented programming across multiple machines Best-known example is CORBA Common Object Request Broker Architecture Client Object Reference request client ORB Network Server Servant reply server ORB 5 Implementation Object are represented remotely by proxies For X:A to call a method of Y:B A s ORB looks up (or creates) a proxy for Y:B X:A calls the proxy s method Request is routed to Y s ORB, which delivers it to B X:A is blocked until Y:B s response is returned So it looks like a local, synchronous call 6 3

4 The Details Usually specify object interfaces with IDL Interface Definition Language Compile it to create the proxy class Also create the interface (or abstract base class) from which the implementation class is derived module Fred { interface MyObject { string isalive(); } } class FredProxy interface IFred class FredImpl 7 A Closer Look Requests to remote servers are millions of times slower than local requests Build it local, then distribute turns out to be a bad design strategy Cannot pass by reference How deeply to copy lists of lists of lists? Have to cope with partial failure We ll return to this later 8 4

5 Message-Oriented Middleware MOM doesn t even try to hide the distinction between local and remote objects Inherently asynchronous Basic element is a message queue Any message a sender enqueues will eventually be dequeued and delivered, in order Can be implemented point-to-point, or by using a central server 9 Advantages Sender doesn t have to wait for a reply Send and forget E.g., logging systems Sender decides when to wait for a reply I.e., when to try to dequeue a reply message Is this another way of saying Every programmer has to figure it out herself? Handles intermittent connections more robustly 10 5

6 Message Delivery Message delivery must be reliable If MOM loses a credit card transaction, the customer may be happy, but the store will not But reliability costs performance Quality of Service options: Best effort (time out and discard) Persistent (costs 30-80% of performance) Transactional (persistent, with grouping) 11 Publish-Subscribe One-to-one messaging is tedious and inefficient Tedious: have to send the same message many times Inefficient: have to copy/send it many times Publish-subscribe extends MOM to support 1:N, N:N, and N:1 messaging Every message is associated with one or more topics Subscribers listen for messages on interesting topics Yes, it s observer/observable 12 6

7 Publish-Subscribe Decouples senders and receivers Many processes can create messages on a topic, while many are consuming New ones can appear and disappear at arbitrary times May organize topics hierarchically Newer systems use something like tagging Messages may be published with a time to live Stock quotes are only interesting for so long 13 Tuple Space Appeared in Linda in the early 1980s System consists of: Zero or more running processes A shared collection of tuples f(a, b) (1,2) (3,"blue") h("red") g(123) 14 7

8 Tuple Space out(val,...) creates a tuple E.g., out(1, 3) adds (1, 3) to tuple space in(val,...) blocks until a matching tuple can be found, then removes it If x and y are variables, in(?x,?y) blocks until a tuple with matching types exists, copies values into x and y, then removes the tuple Can mix values and variables at will rd() is like in(), but doesn't remove the tuple 15 Tuple Space eval(f,val,...) creates a process Executes function f on given parameters Turns into a tuple when execution terminates And that's it 16 8

9 Task Farm Example for i in num_jobs: eval(worker_func, job_data[i]) results = [] for i in num_jobs: in(?r) results.append(r) 17 Distributed Queue void put(str name, type val): int i; in(name, "tail",?i); i += 1; out(name, "tail", i); out(name, i, val); ("job", "tail", 9); type get(str name): int i; in(name, "head",?i); i += 1; out(name, "head", i); type val; in(name, i, val); return val; ("job", "head", 7); ("job", 7, data ); ("job", 8, data ); 18 9

10 JavaSpaces JavaSpaces is Sun's Java implementation of TS Adds the notion of a lease A process requesting access to resource must specify how long it wants to use it Resource owner grants access for no longer than that time Lease holder can renew or cancel leases When a lease expires, the grantor reclaims the resources and signals the lease holder 19 Service-Oriented Architecture SOA assembles an application from looselycoupled software services Application Front end Service Contract Implementation Business Logic SOA Service Repository Interface Data Service Bus 20 10

11 WSDL Web Services Description Language <message name="gettermrequest"> <part name="term" type="xs:string"/> </message> <message name="gettermresponse"> <part name="value" type="xs:string"/> </message> <porttype name="glossaryterms"> <operation name="getterm"> <input message="gettermrequest"/> <output message="gettermresponse"/> </operation> </porttype> 21 UDDI Universal Description Discovery and Integration Original idea was a yellow pages for web services, but in practice: Trust was an issue And so was lack of semantics In practice: Used on intranets Most of the possible metadata is ignored 22 11

12 Twin Challenges 1) How to test and debug? Model delays and partial failures when testing Few debuggers know how to track events across process boundaries (much less machines) 2) How to tune? Gathering performance data is hard enough on one machine Gathering it on many distorts the system being measured 23 12