1. 1 Formal Models for Distributed Negotiations Commit Protocols Roberto Bruni Dipartimento di Informatica Università di Pisa XVII Escuela de Ciencias Informaticas (ECI 2003), Buenos Aires, July 21-26 2003

2. Formal Models for Distributed Negotiations2 Distributed DataBases Data can be inherently distributed e.g. customers accounts in different branches of the same bank Data are distributed to achieve failure independence e.g. replicated file systems Partial failures can lead to inconsistent results Commits have to be coordinated among participants to preserve data consistency

3. Formal Models for Distributed Negotiations3 Distributed DataBases DB user CentralizedDistributed

4. Formal Models for Distributed Negotiations4 Atomic Commitment Problem Reach a globally consistent state despite failures Each participant has two possible decision values commit All participants will make the transaction’s updates permanent abort All will roll-back Individual decisions are irreversible A commit decision requires unanimity of YES votes

5. Formal Models for Distributed Negotiations5 Atomic Commitment Properties Consensus All participants that decide reach the same decision If any participant decides commit, then all participants must have voted YES If all participants have voted YES and no failures occur, then commit is decided Irreversibility Each participant decides at most once

6. Formal Models for Distributed Negotiations6 Commitment Protocols Atomic commitment protocol satisfies all atomic commitment properties ensures that transactions terminate consistently at all participating sites of a distributed database, even in presence of failures Non-blocking if it permits transaction termination to proceed at correct participants despite failures of others is the activity of ensuring that Sw and Hw failures do not corrupt persistent data can limit time intervals of resource locking

7. Formal Models for Distributed Negotiations7 Some Assumptions One of the participants acts as unique coordinator (centralized version) At most one (if no failures, then there is one coordinator) A participant assumes the role of coordinator within a fixed time interval from the beginning of the transaction The transaction begins at a single participant called the invoker sends start messages to other participants Only undeliverable messages are dropped All participants can communicate (useful later)

8. Formal Models for Distributed Negotiations8 Generic ACP: Coordinator send VOTE-REQ[T id ] to all participants set-timeout wait-for vote[T id ] from all participants if (all votes are YES) then broadcast(commit[T id ], participants) else // at least one vote is NO broadcast(abort[T id ], participants) on-timeout: // escape blocking wait-for broadcast(abort[T id ], participants) Phase 1 Phase 2

9. Formal Models for Distributed Negotiations9 Generic ACP: Participants set-timeout wait-for VOTE-REQ[T id ] from coordinator // 1 send vote[T id ] to coordinator if (vote==NO) then // unilateral abort decide abort else set-timeout wait-for decision from coordinator // 2 if (decision==abort) then decide abort else decide commit on-timeout: termination-protocol // escape 2 on-timeout: decide abort //escape 1

10. Formal Models for Distributed Negotiations10 Simple Broadcast broadcast(m,S) // Broadcaster send m to all processes in S deliver m // other processes in S upon-receipt m // non-blocking deliver m This corresponds to the 2PC Protocol

11. Formal Models for Distributed Negotiations11 Timeout Actions Participants must wait VOTE_REQ from coordinator If this takes too long can just decide abort Coordinator collects votes No global decision is yet made Coordinator can decide abort commit / abort from coordinator The participants already took a decision (YES) It is now uncertain It must consult other participants according to the termination protocol

12. Formal Models for Distributed Negotiations12 Termination Protocol (TP) What if a participant that voted YES times out waiting for the response from coordinator? It invokes a termination protocol to contact: the coordinator other participants (cooperative TP) can have already voted or not yet voted There are failure scenarios for which no termination protocol can lead to a decision Blocking scenario: correct participants cannot decide e.g. coordinator crashes during broadcast all faulty participants deliver and crash all correct participants do not deliver the decision if faulty participants do not recover any decision could contradict the decision of a participant that crashed

13. Formal Models for Distributed Negotiations13 Non-Blocking ACP I set-timeout wait-for VOTE-REQ[T id ] from coordinator // 1 send vote[T id ] to coordinator if (vote==NO) then // unilateral abort decide abort else set-timeout wait-for decision from coordinator // 2 if (decision==abort) then decide abort else decide commit on-timeout: decide abort // escape 2 on-timeout: decide abort //escape 1

14. Formal Models for Distributed Negotiations14 Non-Blocking ACP II broadcast(m,S) // Broadcaster as before // other processes in S upon-first-receipt m send m to all processes in S // S can be sent along VOTE_REQ deliver m any process receiving m relays m to all others (if any correct process receives m, all correct process receive m, even if broadcaster crashes) m is delivered only after relaying

15. Formal Models for Distributed Negotiations15 Recovery Participant p is recovering from a failure Must reach a consistent decision Suppose p remembers its state at the time it failed Before voting it can unilaterally abort After deciding abort it can unilaterally abort After receiving commit / abort from coordinator it had already decided and must behave accordingly During the uncertainty period (voted YES) Independent recovery is not possible! Termination protocol is needed

16. Formal Models for Distributed Negotiations16 Distributed Transaction Log DTL is kept in stable storage at each site Its content must survive failures Coordinators and participants at that site can record information about transactions Before/after sending VOTE_REQ, the coordinator C writes start2PC(S,T id ) Before voting YES, a participant writes yes(C,S,T id ) Before/after voting NO, a participant writes abort(T id ) Before C sends commit, it writes commit(T id ) Before/after C sends abort, it writes abort(T id ) After receiving the decision, participant writes commit/abort

17. Formal Models for Distributed Negotiations17 Recovery From DTL If DTL contains start2PC (the site hosted the coordinator) If it also contains commit/abort The coordinator decided before failure Otherwise The coordinator can decide abort (and record it in DTL) Otherwise It contains commit/abort The participant has reached decision before the failure Does not contain yes Either failed before voting or voted no The participant can unilaterally abort Otherwise (it contains yes but not commit/abort) The participant failed in its uncertainty period Must use the termination protocol

18. Formal Models for Distributed Negotiations18 Cooperative TP: Initiator send DECISION_REQ[T id ] to all processes in S wait-for decision[T id ] from any process if (decision==commit) then write commit in DTL else // decision==abort write abort in DTL

19. Formal Models for Distributed Negotiations19 Cooperative TP: Responder wait-for decision[T id ] from any process p if (abort(T id ) in DTL) then send abort to p else if (commit(T id ) in DTL) then send commit to p

20. Formal Models for Distributed Negotiations20 Evaluation of 2PC Criteria: Reliability vs Efficiency Resiliency What failures can be tolerated? Blocking Can processes be blocked? Under which conditions? Time Complexity How long does it take to reach a decision? Message Complexity How many messages are exchanged to reach a decision? What are their dimensions?

21. Formal Models for Distributed Negotiations21 Balancing Reliability and Efficiency are conflicting goals each can be achieved at the expenses of the other The choice of protocol depends on which goal is more important for a specific application Whatever protocol is chosen, we should optimize for the case with no failures Hopefully the normal operating state of the system

22. Formal Models for Distributed Negotiations22 Measuring Time Complexity A round is the max time for a message to reach its destination Timeouts are based on the assumption that such a delay is known Note that many messages can be sent in a single round Two messages must belong to different rounds iff one cannot be sent before the other is received Rounds are taken as time units We count the number of rounds needed for unblocked sites to reach a decision, in the worst case This neglects the time needed to process messages Reasonable: messages delays usually exceed processing delays Other two factors can be relevant: DTL management (on stable storage) Broadcasting preparation (to a large number of processes)

23. Formal Models for Distributed Negotiations23 Measuring Message Complexity Number of messages sent during the whole protocol Reasonable measure if individual messages are not very large Otherwise we should measure the length of messages, not merely their number Here messages are short, so we abstract away from their lengths

24. Formal Models for Distributed Negotiations24 Reliability of 2PC Resiliency 2PC is resilient to site failures communication failures In fact, the cause of timeouts is not important Blocking 2PC is subject to blocking Probabilistic analysis can be performed depending on the probabilistic distribution of failures

25. Formal Models for Distributed Negotiations25 Time Complexity of 2PC In absence of failure, 2PC requires 3 rounds Broadcast VOTE-REQ Collect votes Broadcast global decision If failures happen, The TP may need 2 additional rounds Broadcast DECISION_REQ Reply from a process outside its uncertainty period Note that several TPs can be initiated separately in the same round Up to 5 rounds, independently from the number of failures! But processes may remain blocked for an unbounded period of time

26. Formal Models for Distributed Negotiations26 Message Complexity of 2PC Let N+1 be the number of participants, including the coordinator In each round of 2PC, there are N messages sent Hence, in absence of failures 2PC uses 3N messages Cooperative TP is invoked by all participants that voted YES but did not receive commit / abort Let there be M such participants M initiators, each sending N DECISION_REQ (MN messages) At most N-M+1 processes will respond to the first request In the worst case only one process abandons its uncertainty and will respond to another initiator: (N-M+1)+(N-M+2)+…+N

27. Formal Models for Distributed Negotiations27 Calculating the Message Complexity of 2PC In the worst case the total number of TP messages will be: NM +  i=1 (N-M+i) = NM + NM – M 2 + M(M+1)/2 = 2NM – M 2 /2 + M/2 messages This quantity is maximum when M=N N(3N+1)/2 messages The 2PC together with worst-case TP amount to 3N + N(3N+1)/2 = N(3N+7)/2 messages M

28. Formal Models for Distributed Negotiations28 Communication Topology The communication topology of a protocol is the specification of who sends messages to whom e.g. in 2PC without TP, the coordinator sends messages to participants and vice versa Participants do not send messages directly to each other The topology is described as a tree of height 1 Coordinator Participant …

29. Formal Models for Distributed Negotiations29 Alternative 2PCs To reduce time and message complexity of centralized 2PC, two variations have been proposed, based on different communication topologies Decentralized 2PC Communication topology is a complete graph Improve time complexity Linear 2PC (aka Nested 2PC) Linearly ordered processes Reduce the number of messages

30. Formal Models for Distributed Negotiations30 Decentralized 2PC Depending on its own vote, the coordinator sends YES or NO to all participants Informs that it is time to vote Tells the coordinator’s vote If the message is NO Each participant decides abort and stops Otherwise, each participant sends back its vote to ALL OTHER PARTICIPANTS After receiving all votes each process can decide autonomously If all are YES and its own vote is YES, decide commit Otherwise it decides abort Timeouts can be employed as in the centralized 2PC

31. Formal Models for Distributed Negotiations31 Evaluation of Decentralized 2PC In the absence of failures, only 2 rounds are necessary Coordinator voting YES / NO Each participant voting YES / NO More messages are needed: N 2 +N messages N messages in the first round N 2 messages in the second round (and this is just in absence of failures)

32. Formal Models for Distributed Negotiations32 Linear 2PC Each participant can communicate only with its left / right neighbors The coordinator is the leftmost process It sends its vote YES / NO to its right neighbor This message has a dual meaning as in decentralized 2PC Each participant p waits for the vote from its left neighbor If it is YES, and p votes YES, then p tells YES to its right neighbor Otherwise, p tells NO to its right neighbor When the rightmost participant receives the vote, it makes the final decision commit / abort The decision is propagated from right to left When the coordinator receives it, the protocol ends Timeout periods are influenced by positions

33. Formal Models for Distributed Negotiations33 Evaluation of Linear 2PC Only 2N messages needed N votes from left to right N decisions from right to left (and this is just in absence of failures) Unfortunately the same amount of rounds is needed: 2N rounds No two messages are sent concurrently

34. Formal Models for Distributed Negotiations34 Comparison of 2PC Variants RoundsMessages Centralized 2PC33N Decentralized 2PC2N 2 +N Linear 2PC2N Hybrid communication topologies are also possible e.g. Linear for voting, complete for conveying decision 2N messages, N+1 rounds The choice of the protocol might be influenced by the available communication topology

35. Formal Models for Distributed Negotiations35 From 2PC to 3PC In 2PC, if all operational participants are uncertain, they are blocked They cannot decide abort even if aware that processes they cannot communicate with have failed, because some of them could have decided commit before failure The 3CP is an ACP designed to rule out this situation It guarantees that if any operational process is uncertain, then no (operational / failed) process can have decided commit Thus, if p realizes that any operational site is uncertain, then p can decide abort Why does 2PC violate this property? A participant p can receive commit while q is still uncertain

36. Formal Models for Distributed Negotiations36 Sketch of 3PC: The Idea After the coordinator has found that all votes were YES, it sends pre-commit messages to all participants When a participant p receives pre-commit, it knows that all participants voted YES p is no longer uncertain, but does not decide commit yet p knows that it will decide commit unless it fails p acknowledges the receipt of pre-commit When the coordinator collects all acks it knows that no participant is uncertain The coordinator sends commit to all participants When a participant receives commit, it decides commit If a participant voted NO, then 3PC behaves as 2PC

37. Formal Models for Distributed Negotiations37 Sketch of 3PC: Some Notes In absence of failures, 3PC involves 5 rounds and up to 5N messages Participants have four possible states Aborted, Uncertain, Committable, Committed For p and q any two participants, only certain combinations of their states are possible Timeouts can occur in five situations 3 are trivially handled 2 require a complex termination protocol Election protocol (for a new coordinator) based on a linear ordering of participants The new coordinator checks the states of all operational participants Timeouts are again necessary

38. Formal Models for Distributed Negotiations38 Recap We have seen Atomic Commitment Problem Several ACP protocols Generic ACP Centralized 2PC (Good middle ground) Non-Blocking ACP Decentralized 2PC (OK if end-to-end delays must be minimized) Linear 2PC (OK if messages are expensive) 3PC (sketched) Learned some criteria to evaluate and compare protocols Usually also dependent on the communication topology

39. Formal Models for Distributed Negotiations39 References Concurrency control and recovery in database systems (Chapter 7, Addison-Wesley 1987) P. Bernstein, N. Goodman, V. Hadzilacos Non-blocking atomic commitment (Chapter 6 of Distributed Systems, Addison-Wesley 1995) O. Babaoglu, S. Toueg