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1 CS6320 – Performance L. Grewe 2 The Servlet Interface Java provides the interface Servlet Java provides the interface Servlet Specific Servlets implement.

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Presentation on theme: "1 CS6320 – Performance L. Grewe 2 The Servlet Interface Java provides the interface Servlet Java provides the interface Servlet Specific Servlets implement."— Presentation transcript:

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2 1 CS6320 – Performance L. Grewe

3 2 The Servlet Interface Java provides the interface Servlet Java provides the interface Servlet Specific Servlets implement this interface Specific Servlets implement this interface Whenever the Web server is asked to invoke a specific Servlet, it activates the method service() of an instance of this Servlet Whenever the Web server is asked to invoke a specific Servlet, it activates the method service() of an instance of this Servlet service(request,response) MyServlet (HTTP) request (HTTP) response

4 CS677: Distributed OS Consistency and Replication Today: Today: IntroductionIntroduction Consistency modelsConsistency models Data-centric consistency models Data-centric consistency models Client-centric consistency models Client-centric consistency models Thoughts for the mid-termThoughts for the mid-term

5 CS677: Distributed OS Why replicate? Data replication: common technique in distributed systems Data replication: common technique in distributed systems Reliability Reliability If one replica is unavailable or crashes, use anotherIf one replica is unavailable or crashes, use another Protect against corrupted dataProtect against corrupted data Performance Performance Scale with size of the distributed system (replicated web servers)Scale with size of the distributed system (replicated web servers) Scale in geographically distributed systems (web proxies)Scale in geographically distributed systems (web proxies) Key issue: need to maintain consistency of replicated data Key issue: need to maintain consistency of replicated data If one copy is modified, others become inconsistentIf one copy is modified, others become inconsistent

6 CS677: Distributed OS Object Replication Approach 1: application is responsible for replication Approach 1: application is responsible for replication Application needs to handle consistency issuesApplication needs to handle consistency issues Approach 2: system (middleware) handles replication Approach 2: system (middleware) handles replication Consistency issues are handled by the middlewareConsistency issues are handled by the middleware Simplifies application development but makes object-specific solutions harderSimplifies application development but makes object-specific solutions harder

7 CS677: Distributed OS Replication and Scaling Replication and caching used for system scalability Replication and caching used for system scalability Multiple copies: Multiple copies: Improves performance by reducing access latencyImproves performance by reducing access latency But higher network overheads of maintaining consistencyBut higher network overheads of maintaining consistency Example: object is replicated N timesExample: object is replicated N times Read frequency R, write frequency W Read frequency R, write frequency W If R<<W, high consistency overhead and wasted messages If R<<W, high consistency overhead and wasted messages Consistency maintenance is itself an issue Consistency maintenance is itself an issue What semantics to provide?What semantics to provide? Tight consistency requires globally synchronized clocks!Tight consistency requires globally synchronized clocks! Solution: loosen consistency requirements Solution: loosen consistency requirements Variety of consistency semantics possibleVariety of consistency semantics possible

8 CS677: Distributed OS Data-Centric Consistency Models Consistency model (aka consistency semantics) Consistency model (aka consistency semantics) Contract between processes and the data storeContract between processes and the data store If processes obey certain rules, data store will work correctly If processes obey certain rules, data store will work correctly All models attempt to return the results of the last write for a read operationAll models attempt to return the results of the last write for a read operation Differ in how “last” write is determined/defined Differ in how “last” write is determined/defined

9 CS677: Distributed OS Strict Consistency Any read always returns the result of the most recent write Any read always returns the result of the most recent write Implicitly assumes the presence of a global clockImplicitly assumes the presence of a global clock A write is immediately visible to all processesA write is immediately visible to all processes Difficult to achieve in real systems (network delays can be variable) Difficult to achieve in real systems (network delays can be variable)

10 CS677: Distributed OS Sequential Consistency Sequential consistency: weaker than strict consistency Sequential consistency: weaker than strict consistency Assumes all operations are executed in some sequential order and each process issues operations in program orderAssumes all operations are executed in some sequential order and each process issues operations in program order Any valid interleaving is allowed Any valid interleaving is allowed All agree on the same interleaving All agree on the same interleaving Each process preserves its program order Each process preserves its program order Nothing is said about “most recent write” Nothing is said about “most recent write”

11 CS677: Distributed OS Linearizability Assumes sequential consistency and Assumes sequential consistency and If TS(x) < TS(y) then OP(x) should precede OP(y) in the sequenceIf TS(x) < TS(y) then OP(x) should precede OP(y) in the sequence Stronger than sequential consistencyStronger than sequential consistency Difference between linearizability and serializbility?Difference between linearizability and serializbility? Granularity: reads/writes versus transactions Granularity: reads/writes versus transactions Example: Example: Process P1Process P2Process P3 x = 1; print ( y, z); y = 1; print (x, z); z = 1; print (x, y);

12 CS677: Distributed OS Linearizability Example Four valid execution sequences for the processes of the previous slide. The vertical axis is time. Four valid execution sequences for the processes of the previous slide. The vertical axis is time. x = 1; print ((y, z); y = 1; print (x, z); z = 1; print (x, y); Prints: 001011 Signature: 001011 (a) x = 1; y = 1; print (x,z); print(y, z); z = 1; print (x, y); Prints: 101011 Signature: 101011 (b) y = 1; z = 1; print (x, y); print (x, z); x = 1; print (y, z); Prints: 010111 Signature: 110101 (c) y = 1; x = 1; z = 1; print (x, z); print (y, z); print (x, y); Prints: 111111 Signature: 111111 (d)

13 CS677: Distributed OS Causal consistency Causally related writes must be seen by all processes in the same order. Causally related writes must be seen by all processes in the same order. Concurrent writes may be seen in different orders on different machinesConcurrent writes may be seen in different orders on different machines Not permittedPermitted

14 CS677: Distributed OS Other models FIFO consistency: writes from a process are seen by others in the same order. Writes from different processes may be seen in different order (even if causally related) FIFO consistency: writes from a process are seen by others in the same order. Writes from different processes may be seen in different order (even if causally related) Relaxes causal consistencyRelaxes causal consistency Simple implementation: tag each write by (Proc ID, seq #)Simple implementation: tag each write by (Proc ID, seq #) Even FIFO consistency may be too strong! Even FIFO consistency may be too strong! Requires all writes from a process be seen in orderRequires all writes from a process be seen in order Assume use of critical sections for updates Assume use of critical sections for updates Send final result of critical section everywhereSend final result of critical section everywhere Do not worry about propagating intermediate resultsDo not worry about propagating intermediate results Assume presence of synchronization primitives to define semantics Assume presence of synchronization primitives to define semantics

15 CS677: Distributed OS Other Models Weak consistency Weak consistency Accesses to synchronization variables associated with a data store are sequentially consistentAccesses to synchronization variables associated with a data store are sequentially consistent No operation on a synchronization variable is allowed to be performed until all previous writes have been completed everywhereNo operation on a synchronization variable is allowed to be performed until all previous writes have been completed everywhere No read or write operation on data items are allowed to be performed until all previous operations to synchronization variables have been performed.No read or write operation on data items are allowed to be performed until all previous operations to synchronization variables have been performed. Entry and release consistency Entry and release consistency Assume shared data are made consistent at entry or exit points of critical sectionsAssume shared data are made consistent at entry or exit points of critical sections

16 CS677: Distributed OS Summary of Data-centric Consistency Models ConsistencyDescription StrictAbsolute time ordering of all shared accesses matters. Linearizability All processes must see all shared accesses in the same order. Accesses are furthermore ordered according to a (nonunique) global timestamp SequentialAll processes see all shared accesses in the same order. Accesses are not ordered in time CausalAll processes see causally-related shared accesses in the same order. FIFO All processes see writes from each other in the order they were used. Writes from different processes may not always be seen in that order (a) ConsistencyDescription WeakShared data can be counted on to be consistent only after a synchronization is done ReleaseShared data are made consistent when a critical region is exited EntryShared data pertaining to a critical region are made consistent when a critical region is entered. (b)

17 CS677: Distributed OS Caching in WWW: Case Study Dramatic growth in world wide web traffic Dramatic growth in world wide web traffic Web accesses are non-uniform in nature Web accesses are non-uniform in nature Create hot-spots of server and network load, increase latencyCreate hot-spots of server and network load, increase latency Solution: employ web proxy caches Solution: employ web proxy caches Reduces user response times, server load, network loadReduces user response times, server load, network load ProxiesEnd-hostsServers Network

18 CS677: Distributed OS Content Distribution Network Content distribution network (CDN) Content distribution network (CDN) Collection of proxies that act as intermediaries between servers and clientsCollection of proxies that act as intermediaries between servers and clients Service a client request from “closest” proxy with the objectService a client request from “closest” proxy with the object Similar benefits as single proxy environments, but larger scaleSimilar benefits as single proxy environments, but larger scale Example: Akamai CDN - 13,000+ proxiesExample: Akamai CDN - 13,000+ proxies Caching in CDN => must maintain cache consistency Caching in CDN => must maintain cache consistency End-hostsServers

19 CS677: Distributed OS Consistency Mechanisms Time-to-live (TTL) values Time-to-live (TTL) values Expiration time of cached documentExpiration time of cached document Proxy must refresh from server after expirationProxy must refresh from server after expiration Poll: Use if-modified-since (IMS) HTTP requests Poll: Use if-modified-since (IMS) HTTP requests Weaker guarantees: document can change before expirationWeaker guarantees: document can change before expiration Poll every time Poll every time Poll the server upon request for a cached objectPoll the server upon request for a cached object Increases response time of requestsIncreases response time of requests Provides stronger consistency guaranteesProvides stronger consistency guarantees

20 CS677: Distributed OS Consistency with Leases Lease: fixed duration contract between server and proxy Lease: fixed duration contract between server and proxy Server agrees to notify proxy of all updates to an object over duration d Server agrees to notify proxy of all updates to an object over duration d “d” is the lease duration“d” is the lease duration Lease may be renewed upon expiryLease may be renewed upon expiry Properties: Properties: Server needs to notify each proxy caching the object of an updateServer needs to notify each proxy caching the object of an update Excessive burden for popular objects Excessive burden for popular objects Leases requires a server to maintain stateLeases requires a server to maintain state Overhead can be excessive for large CDNs Overhead can be excessive for large CDNs Leases provide stronger consistency guaranteesLeases provide stronger consistency guarantees Push-based approach, server-initiated consistencyPush-based approach, server-initiated consistency

21 CS677: Distributed OS Mid-term Exam Comments Closed book, closed notes, 90 min Closed book, closed notes, 90 min Lectures 1-13 included on the test Lectures 1-13 included on the test Focus on things taught in class (lectures, in-class discussions)Focus on things taught in class (lectures, in-class discussions) Start with lecture notes, read corresponding sections from textStart with lecture notes, read corresponding sections from text Supplementary readings are not included on the test.Supplementary readings are not included on the test. Exam structure: few short answer questions, mix of subjective and “design” questions Exam structure: few short answer questions, mix of subjective and “design” questions Good luck! Good luck!


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