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6.4 Data and File Replication

Explore the challenges in data and file replication, including transparency, concurrent control, failure recovery, and serialization atomicity. Learn about different replication architectures and their impact on read and write operations. Understand the concepts of one-copy serializability and loss of conflicts in replicated objects, and discover various replication protocols and techniques used in distributed systems.

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6.4 Data and File Replication

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  1. 6.4 Data and File Replication Gang Shen

  2. Why replicate • Performance • Reliability • Resource sharing • Network resource saving

  3. Challenge • Transparency • Replication • Concurrent control • Failure recovery • Serialization

  4. Atomicity • In database systems, atomicity is one of the ACID transaction properties. An atomic transaction is a series of database operations which either all occur, or all do not occur[1]. • All or nothing

  5. Atomicity • In DFS (Distributed File System), replicated objects (data or file) should follow atomicity rules, i.e., all copies should be updated (synchronously or asynchronously) or none.

  6. Goal • One-copy serializability: The effect of transactions performed by clients on replicated objects should be the same as if they had been performed one at a time on a single set of objects.[2]

  7. Architecture • FSA , File service agent, client interface • RM, replica manager, provide replication functions [3]

  8. Architecture[3]

  9. Read operations [3] • Read-one-primary, FSA only read from a primary RM, consistency • Read-one, FSA may read from any RM, concurrency • Read-quorum, FSA must read from a quorum of RMs to decide the currency of data

  10. Write Operations[3] • Write-one-primary, only write to primary RM, primary RM update all other RMs • Write-all, update to all RMs • Write-all- available, write to all functioning RMs. Faulty RM need to be synched before bring online.

  11. Write Operations • Write-quorum, update to a predefined quorum of RMs • Write-gossip, update to any RM and lazily propagated to other RMs

  12. Read one primary, write one primary • Other RMs are backups of primary RM • No concurrency • Easy serialized • Simple to implement • Achieve one-copy serializability • Primary RM is performance bottleneck

  13. Read one, Write all • Provides concurrency • Concurrency control protocol needed to ensure consistency (serialization) • Achieve one-copy serializability • Difficult to implement (there will be failed TM to block any updates)

  14. Read one, Write all available • Variation of Read one, Write all • May not guarantee one-copy serializability • Issue of loss conflict in transactions

  15. Loss of Conflicts • Assume to RMs, (a,b), object X,Y replicated to both. • Two transactions • T1:R(X),W(Y),commit • T2:R(Y),W(X),commit

  16. Loss of Conflict • If Xa,Yb failed, transaction as follows • T1:R(Xa),(Yb failed),W(Ya),commit • T2:R(Yb),(Xa failed),W(Xb),commit • There is no conflict since no object is shared. Thus loss conflict. This can introduce error.

  17. Read quorum,Write quorum • Version number attached to replicated object • Highest version numbered object is the latest object in read. • Write operation advances version by 1 • Write quorum > half of all object copies • Write quorum+read quorum > all object copies

  18. Gossip Update • Applicable for frequent read, less update situations • Increased performance • Typical read one, write gossip • Use timestamp

  19. Basic Gossip Update • Used for overwrite • Three operations, read, update, gossip arrive • Read, if TSfsa<=TSrm, RM has recent data, return it, otherwise wait for gossip, or try other RM • Update, if Tsfsa>TSrm, update. Update TSrm send gossip. Otherwise, process based on application, perform update or reject • Gossip arrive, update RM if gossip carries new updates.

  20. Causal Order Gossip Protocol[3] • Used for read-modify • In a fixed RM configuration • Using vector timestamps • Using buffer to keep the order

  21. Windows Server 2003[4] • Support DFS • “State based, multi master” scheduled replication • Use namespace for transparent file sharing • Use Remote Differential Compression to propagate change only to save bandwidth

  22. Continued[5] If replication detects a conflict, last update wins. No merge files, but copies are kept for reference.

  23. Reference [1] Wikipedia; http://en.wikipedia.org/wiki/Atomicity [2] M. T. Harandi;J. Hou (modified: I. Gupta);"Transactions with Replication";http://www.crhc.uiuc.edu/~nhv/428/slides/repl-trans.ppt [3] Randy Chow,Theodore Johnson, “Distributed Operating Systems & Algorithms”, 1998 [4] "Overview of the Distributed File System Solution in Microsoft Windows Server 2003 R2";http://technet2.microsoft.com/WindowsServer/en/library/d3afe6ee-3083-4950-a093-8ab748651b761033.mspx?mfr=true [5] "Distributed File System Replication: Frequently Asked Questions";http://technet2.microsoft.com/WindowsServer/en/library/f9b98a0f-c1ae-4a9f-9724-80c679596e6b1033.mspx?mfr=true

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