Distributed File Systems

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1 Distributed File Systems Today l Basic distributed file systems l Two classical examples Next time l Naming things xkdc

2 Distributed File Systems " A DFS supports network-wide sharing of files and devices " DFS typically presents clients with a traditional file system view A single file system namespace that all clients see Files can be shared One client can observe the side-effects of other clients file system activities In many ways, an ideal DFS provides clients with the illusion of a shared, local FS " But with a distributed implementation Read blocks / files from remote machines across a network, instead of from a local disk 2

3 A basic DFS " Client applications issue system calls to the client-side FS (e.g., open, read, close) Nothing changes for them (other than perhaps performance) " Client-side FS execute the actions to service those calls E.g., To server a read request, talk to FS server to read block File server may read it from disk or cache Client-side FS Networking layer File server Networking layer 3

4 DFS issues " What is the basic abstraction A remote file system? Open, close, read, write, A remote disk? Read block, write block " Naming How are files named? Are those names location transparent? is the file location visible to the user? do the names change if the file moves? do the names change if the user moves? 4

5 DFS issues " Caching Caching exists for performance reasons Where are file blocks cached? On the file server? On the client machine? Both? " Sharing and coherency What are the semantics of sharing? What happens when a cached block/file is modified? How does a node know when its cached blocks are stale? If we cache on the client side, we re presumably caching on multiple client machines if a file is being shared 5

6 DFS issues " Replication Replication can exist for performance and/or availability Can there be multiple copies of a file in the network? If multiple copies, how are updates handled? What if there s a network partition? Can clients work on separate copies? If so, how does reconciliation take place? " Performance What is the performance of remote operations? What is the additional cost of file sharing? How does the system scale as the number of clients grows? What are the performance bottlenecks: network, CPU, disks, protocols, data copying? 6

7 Sun s Network File System (NFS) " Developed by SUN as an open-protocol system Now, a common standard for distributed UNIX file access " NFS runs over LANs (even over WANs slowly) " Basic idea Allow a remote directory to be mounted (spliced) onto a local directory Gives access to that remote directory and all its descendants as if they were part of the local hierarchy Ensure simple and fast server crash recovery With multiple clients and a single server, while the server is down everybody is blocked " Pretty similar (except for implementation and performance) to a local mount or link on UNIX 7 7

8 Key to fast crash recovery - statelessness " A stateless protocol server does not keep track of anything that is happening on the client side If client is caching and what, which files are open, where is the file pointer for a file, " Stateful think of open Server open file locally, sends fd back to client Client uses fd on subsequent operations File descriptor is a piece of shared state What if server crashes? char buffer[max]; int fd = open( foo, O_RDONLY); read(fd, buffer, MAX); read(fd, buffer, MAX); read(fd, buffer, MAX); close(fd); " Stateless each client operation carries all info needed to complete the request 8

9 NFS protocol " Key to the protocol file handle File handle is opaque to clients derived from the i-node adding a generation number and file system identifier Unit of file grouping is the mountable file system Generation is needed since file i-node numbers are reused after file is removed " Some operations Lookup Read Write Expects directory file handle, name of file/directory to lookup Returns: file handle Expects: file handle, offset, count Returns: data, attributes Expects file handle, offset, count, data Returns: attributes 9

10 Reading a file App Client Server fd = open( /foo, ); Send Lookup (rootdir FH, foo ) Receive lookup reply Allocate file desc in open file table Store foo s FH intable Store current file position (O) Return file descriptor to app Receive Lookup request Look for foo in root dir Return foo s FH + attributes read(fd, buffer, MAX); Index into open file table with fd Get NFS file handle (FH) Use current file position as offset Send Read(FH, offset, count) Receive read reply Update file position (+bytes read) Set current file position = MAX Return data/error code to app Receive Read request Use FH to get vol/i-node num Read i-node from disk Compute block location (using offset) Read data from disk Return data to client Note that every request has all the information needed to complete it 10

11 Idempotent operations and server failures " When a client sends a message, it may not get a reply Did the network drop it? Did the server crash (before, after)? What to do?! " NSF answer simply retry Set a timer when sending request If reply doesn t arrive on time, retry Key: operations must be idempotent Doing them once or 20 times should be the same E.g., read a value, store data in a given location Counterexample increment a variable Hard to do with everything - mkdir 11

12 NFS architecture Client Server Application program Application program Virtual File System UNIX FS Other FS NFS client NFS protocol RPC Virtual File System NFS client UNIX FS 12

13 NFS implementation " NFS defines new layers in the Unix file system " The virtual file system (VFS) provides a standard interface, using v-nodes as file handles A v-node describes either a local or remote file " Mounting done by a separate mount service On each server a /etc/exports w/ names of local FS available for remote mounting and a ACL for each Clients use a modified version of mount that uses an RPC protocol to mount a remote FS (hard or soft-mounted) 13

14 NFS implementation " NFS defines a set of RPC operations for remote file access Searching a directory Reading directory entries Manipulating links and directories Reading/writing files Getting/setting attributes " Every node may be a client, a server, or both E.g., a given machine might export some directories and import others 14

15 NFS caching / sharing " Client caching for performance (both reads and writes) Update visibility when do updates from a client become visible to others? Stale cache server has the latest copy but client has a cached version " NSF flush-on-close flush updates when closing file (or every 30s in newer versions Clients check (getattr) with server before using cache Bombard server with getattr è cache attr for a shorter time Now, are you getting the latest copy or the cache one? But, once open, different clients can perform concurrent reads and writes to it and get inconsistent data 15

16 CMU s Andrew File System (AFS) " Developed at CMU (1980s) to support all of its student computing (work led by Satyanarayanan, or Satya) " One key design aspect Whole-file caching on the local disk Consists of workstation clients (with disks) and dedicated file server machines (differs from NFS) " First version (called ITC) With open, client sends fetch with entire pathname Serve traversed pathname, find file, ship the entire file back Read/write locally Flush the whole file at closing, if the file has been modified Next time file is accessed, send a TestAuth message to server to see if the file has changed If not, proceed with local copy 16

17 From AFS version 1 to 2 " Sever overloaded; measure to diagnose " Path-traversal cost are high Use file handles " Client issues too many TestAuth to server Use callbacks " Load balancing problem Define volumes; move volumes between servers if necessary " Each client was handle by a single process, w/ context switching costs and other overhead Use threads instead of processes in the server 17

18 Other AFS issues " What happen if two clients are modifying a file at the same time? Last write wins " What about crash recovery? Client crash maybe the server was trying to send an invalidation Server crash callbacks are kept in memory, so when server reboots it has no idea who has what " Other improvements Andrew has a single name space your files have the same names everywhere in the world In NFS you can mount a FS where you pleased User authentication, flexible user-managed access control 18

19 Google s File System (GFS) NFS, etc. GFS Independence Small Scale Variety of workloads Cooperation Large scale Very specific, well-understood workloads 19

20 GFS environment " Why did Google build its own file system? " Google has unique FS requirements Huge volume of data Huge read/write bandwidth Reliability over tens of thousands of nodes with frequent failures (commodity nodes based clusters) Mostly operating on large data blocks Needs efficient distributed operations " Google s unique position it has control over, and customizes, its: Applications, libraries, operating system, networks even its computers! 20

21 GFS files " Files are huge by traditional standards (GB, TB, PB) " Most files are mutated by appending new data rather than overwriting existing data For instance, what did you search for, which link did you follow, " Once written, the files are only read, and often only sequentially Mining for patters " Appending becomes the focus of performance optimization and atomicity guarantees 21

22 GFS architecture GFS Client File name, chunk index Contact address Master Master Master Replicated master Instructions Chunk-server state Chunk ID, range Chunk data Chunk server Linux FS Chunk server Linux FS Chunk server Linux FS Files divided into fixed-size chunks (64 MB) identified by an immutable global uid Each chunk is replicated on multiple chunk servers for reliability Master maintains all FS metadata (e.g., where s a chunk) Master uses heartbeat to check on chunk servers Neither clients nor chunk servers cache file data, no coherence issues Clients do cache metadata, however If master s gone, use Paxos to select new one from among the replicas 22

23 GFS caching and interactions " Master uses heartbeat to check on chunk servers " Neither clients nor chunk servers cache file data, no coherence issues " Clients do cache metadata, however " If master s gone, use Paxos to select a new one from among the replicas 23

24 Summary " There are a number of issues to deal with: What is the basic abstraction?, naming, caching, sharing and coherency, replication, performance, workload " No right answer! Different systems make different tradeoffs " Performance is always an issue always a tradeoff between performance and the semantics of file operations (e.g., for shared files). " Caching of file blocks is crucial in any file system maintaining coherency is a crucial design issue. " Newer systems are dealing with issues such as disconnected operation for mobile computers, and huge workloads (e.g., Google) 24

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