Today CSCI Coda. Naming: Volumes. Coda GFS PAST. Instructor: Abhishek Chandra. Main Goals: Volume is a subtree in the naming space

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Today CSCI 5105 Coda GFS PAST Instructor: Abhishek Chandra 2 Coda Main Goals: Availability: Work in the presence of disconnection Scalability: Support large number of users Successor of Andrew File System Developed at CMU Uses similar basic architecture Client-server architecture Naming: Volumes Volume is a subtree in the naming space Like a disk partition, but finer granularity Mounting and replication takes place at volume granularity Whole volume must be mounted from its root Crossing mount points allowed 3 4 1

Naming: Shared Name Space All clients see same shared name space All coda volumes are mounted under /coda Each mounted volume inherits name from server namespace coda coda RPC2 Coda runs on top of RPC2 Enhanced version of RPC RPC2 supports Reliable RPC over UDP Side-effects: Application-specific modules called by client and server stubs MultiRPC: Using parallel one-to-one RPCs or IP multicast 5 6 Caching and Replication Client Caching Each file is completely transferred to the client on access Combination of session and transactional semantics Each session is considered to be a transaction Effect of each session applied sequentially Consistency Server makes a callback promise Will notify when file is updated Callback break On file modification, server sends invalidation Session-transaction semantics Current session unaffected Client needs to download updated file before the next session 7 8 2

Server Replication Network Partitions Volume Storage Group (VSG): Group of servers holding a volume replica Available Volume Storage (AVSG): Members of VSG connected to a client Update policy: Read-One, Write-All Performed on members of AVSG Optimistic strategy: Commit changes to local AVSGs Conflict detection: Use version vectors Conflict resolution: Application-dependent or manual 9 10 Disconnected Operations Disconnected clients can operate on their local copies Update propagation and conflict resolution done on reconnection How does a user get a file if it is disconnected? Hoarding Files are pre-cached on the client Files to be hoarded determined using priority Hoard database: Important files specified by user File recently referenced Files are fetched to ensure that: Higher priority files always cached first Get non-zero priority files if cache has space Hoard walk: Reorganizing the cache periodically to meet above requirements 11 12 3

Hoarding: Transitions Google File System (GFS) Main Goals: Scalability: Large amount of data Performance: High rate of distributed processing Fault-tolerance: Server failures common 13 14 Google File Characteristics File sizes very large Generally a collection of crawled documents Several MB-GBs Processing: Dumping crawled content Parsing files, building indices Google File System Requirements Built from commodity hardware Modest no. of very large files File reads: Large sequential reads Small random reads File writes: Large, sequential appends Many concurrent appends High bandwidth rather than low latency 15 16 4

Google Server Cluster Each cluster maintains some files Each file divided into chunks Chunk has a global handle One master and multiple chunk servers Google Server Cluster Multiple chunk servers Each maintains one chunk of the file Chunk maintained on local FS Master Responsible for naming Maintains metadata Location of <filename, chunk index> 17 18 Client File Access Client maps file offset into chunk index Master sends chunk handle and chunk server locations to client Client reads chunk directly from chunk server Reliability and Consistency: Chunk Data Each chunk is replicated Updates performed using a primary-backup scheme Server grants lease to a chunkserver to become primary replica Data disseminated separately from update control flow Caching: No caching on client or chunk server 19 20 5

Replication and Consistency: MetaData Master keeps information in main memory Naming index of chunks Updated by polling chunk servers from time-to-time Could have stale information Critical metadata changes Logged to an operational log Reconstructed by log replay Checkpointing from time-to-time PAST Storage System Goals: Scalability: Large-scale system (WAN) Persistence: Archival High availability 21 22 PAST Architecture Based on a peer-to-peer system Pastry routing system No server-client model Provides probabilistic guarantees on file availability, lookup time, load distribution File System File System PAST PAST PAST Pastry Pastry Pastry TCP/IP TCP/IP TCP/IP FileIDs and NodeIDs Each file has a fileid: 160-bit ID Hash of: file name, owner s key, random salt Replication factor k Determines where a file is placed Each node has a nodeid: 128-bit ID Hash chosen from a uniform ID space 23 24 6

File Placement and Lookup Placement: File is placed on k closest nodes Closeness in terms of fileid and nodeids Lookup: Search is routed through Pastry network O(log N) search time PAST File operations File insertion File placed on k closest nodeids Nodes return receipt File lookup Route request through Pastry network Each file is immutable FileIDs cannot be same across files No deletion File reclamation Similar to insertion Storing nodes remove the file 25 26 Load Balancing and Caching Replica Diversion: Allow file to be stored at a not-closest nodeid If the closest nodeids are saturated New node in leaf set of a closest node Caching: Popular files are cached closer to queries Routing nodes may cache files in unused space Can effectively have > k replicas Summary of DFSs NFS Simple file system interface to distributed data Coda Caching, Hoarding and disconnected operations GFS Server clusters and chunk servers PAST P2P File System, Replication and caching 27 28 7