Distributed Transactions March 15, 2001. 2 Transactions What is a Distributed Transaction?  A transaction that involves more than one server  Network.

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Presentation transcript:

Distributed Transactions March 15, 2001

2 Transactions What is a Distributed Transaction?  A transaction that involves more than one server  Network can be unreliable, asynchronous  Need a failure model that is practical  e.g., System R design  Objectives: Consistency, Fault-Tolerance, Performance, Availability

3 Transaction Model  Use nested transactions  One coordinator for each top-level or nested transaction  Failure model  Asynchronous communication (e.g., unreliable network)  Servers may fail unexpectedly  No bugs that cause servers to send the wrong message at the wrong time  Byzantine failures can kill performance Transactions, cont.

4 Example One-Phase Commit Protocol  Coordinator sends commit/abort requests to all participants  Wait until you hear back  Timeout (or a similar mechanism) and try again if you don't hear back  No unilateral decision - commit needs to finish once it starts, even if there is a system failure  One issue: Failures can lead to long wait times Transactions, cont.

5 Two Phase Commit  Any participant can request a transaction commit/abort  Transaction must be aborted if 1 participant aborts  Phase I - Vote  A “commit” vote means that participants can carry out the commit if told to  Save process state in non-volatile storage (enhanced crash recovery)  Phase II - Carry out the decision  To commit, every participant must vote “commit”  Timeouts help get around lost messages Transactions, cont.

6 Two Phase Commit, Nested Transactions  Commit can occur even if all participants do not vote for commit  More sophisticated coordination needed  Hierarchic  Voting is done hierarchically, along the nested transaction tree  Flat  Top-level coordinator gets votes directly from all coordinators who have provisionally committed  Also need an abort list Transactions, cont.

7 Distributed Deadlock  Centralized detection  Performance issues  False positives (e.g., Phantom Deadlocks)  To help prevent deadlocks, use two-phase locking

8 Recovery  Need all or nothing semantics  For each transaction being processed, track:  Object values  Intentions list -  Transaction status (e.g., prepared, committed, aborted) Transactions, cont.

9 Logging For Simple Transactions  Keep one log file that records updates  e.g., Each time transaction code modifies a locked object, log the new value  To prepare to commit, move relevant logged items to recovery manager  e.g., objects in intentions list, intentions list, transaction status  Transaction state change recorded by recovery manager (prepared, aborted, committed)  Transactions not committed to the recovery manager are aborted upon a crash Transactions, cont.

10 Distributed Recovery from two-phase commit  Two new transaction states - done (server state), uncertain (client state)  Phase I - uncertain (client voted Yes)  Phase II - done (transaction complete - optional) Transactions, cont.