Transcript Distribute File System

Satish Puri
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File and File System concept
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File Mounting
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Stateful/Stateless server concept
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Current work and Future work
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Files are named data objects. Files hold structured
data that are used by programs but that are not
part of the programs themselves.
File system is responsible for the naming, creation,
deletion, retrieval, modification, and protection of
a file in the system.
Logical components of a file for users.
File Name
File
Attributes
Data units
 UNIX
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Files are streams of characters for application
programs and sequences of logical fixed size
blocks for file system.
Both sequential and direct access methods are
supported. Other access methods can be built on
top of the flat file structures.
Directory service
Name resolution, add and deletion of files
Authorization service
Capability and /or access control list
File
service
Transaction
Concurrency and replication management
Basic
Read/write files and get/set attributes
System Service
Device, cache, and block management
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Directories are files that contain names and
addresses of other files and subdirectories.
Mapping and locating
Search for a file
Create a file
Delete a file
List a directory
Rename a file
Traverse the file system
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File access must be regulated to ensure
security
Types of access
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Read
Write
Execute
Append
Delete
List
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Create
◦ Allocate space
◦ Make an entry in the directory
Write
◦ Search the directory
◦ Write is to take place at the
location of the write pointer
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Read
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Reposition within file – file
seek
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Delete
◦ Search the directory
◦ Release all file space
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Truncate
◦ Reset the file to length zero
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Open(Fi)
◦ Search the directory
structure
◦ Move the content of the
directory entry to memory
◦ Search the directory
◦ Read is to take place at the
location of the read pointer
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Close(Fi)
◦ move the content in memory
to directory structure on
disk
◦ Set the current file pointer to a
given value
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Get/set file attributes
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System services are a FS’s interface to the
hardware and are transparent to users of FS
◦ Mapping of logical to physical block addresses
◦ Interfacing to services at the device level for file space
allocation/de-allocation
◦ Actual read/write file operations
◦ Caching for performance enhancement
◦ Replicating for reliability improvement
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Attach a remote named file system to the client’s
file system hierarchy at the position pointed to by a
path name
◦ A mounting point is usually a leaf of the directory tree that
contains only an empty subdirectory
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Once files are mounted, they are accessed by using
the concatenated logical path names without
referencing either the remote hosts or local devices
◦ Location transparency
◦ The linked information (mount table) is kept until they are
unmounted
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Different clients may perceive a different FS view
◦ To achieve a global FS view – SA enforces mounting rules
Export: a file server restricts/allows the mounting
of all or parts of its file system to a predefined
set of hosts
◦ The information is kept in the server’s export file
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File system mounting:
◦ Explicit mounting: clients make explicit mounting
system calls whenever one is desired
◦ Boot mounting: a set of file servers is prescribed and all
mountings are performed the client’s boot time
◦ Auto-mounting: mounting of the servers is implicitly
done on demand when a file is first opened by a client
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The mounting protocol is not transparent – the
initial mounting requires knowledge of the
location of file servers
Server registration
◦ File servers register their services, and clients consult with
the registration server before mounting
◦ Clients broadcast mounting requests, and file servers
respond to client’s requests
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State information
Opened files and their clients
File descriptors and file handles
Current file position pointers
Mounting information
Lock status
Session keys
Cache or buffer
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Sateful : a file server maintains internally some of the state
information
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Stateless : a file server maintains none at all.
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Stateful file Server : file servers maintain state information
about clients between requests
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Stateless file Server : when a client sends a request to a server,
the server carries out the request, sends the reply, and then
remove from its internal tables all information about the
request
◦ Between requests, no client-specific information is kept on
the server
◦ Each request must be self-contained: full file name and
offset…
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Overlapping access: multiple copies of the same file
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Interleaving access: multiple granularities of data
access operations
◦ Space multiplexing of the file
◦ Cache or replication
◦ Coherency control: managing accesses to the replicas, to
provide a coherent view of the shared file
◦ Desirable to guarantee the atomicity of updates (to all
copies)
◦ Time multiplexing of the file
◦ Simple read/write, Transaction, Session
◦ Concurrency control: how to prevent one execution
sequence from interfering with the others when they are
interleaved and how to avoid inconsistent or erroneous
results
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Remote access: no file data is kept in the client
machine. Each access request is transmitted directly
to the remote file server through the underlying
network.
Cache access: a small part of the file data is
maintained in a local cache. A write operation or
cache miss results a remote access and update of
the cache
Download/upload access: the entire file is
downloaded for local accesses. A remote access or
upload is performed when updating the remote file
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Lakshman, A. and Malik, P., Cassandra: a
decentralized structured storage system, ACM
SIGOPS Operating Systems Review, volume 44,
number 2, pages 35-40, 2010
-> Facebook and Twitter uses Cassandra (distributed
filesytem)
-> Used for inbox search for about 800 million active
users.
-> The cluster of computers uses regular commodity
hardware prone to failure.
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Shvachko, K., Kuang, H., Radia, S. and Chansler, R., The
hadoop distributed file system, Symposium on Mass
Storage Systems and Technologies, pages 1-10, 2010
Borthakur, D., The hadoop distributed file system:
Architecture and design, Hadoop Project Website, 2007
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HDFS is a filesytem for Hadoop
Designed to run on low cost hardware
Highly fault-tolerant and suitable for large data sets
Hardware failure a norm rather than the exception
Moving computation is cheaper than moving data
Emphasis on high throughput of data
Ungureanu, C., Atkin, B., Aranya, A., Gokhale, S.,
Rago, S., Cakowski, G., Dubnicki, C. and Bohra, A.,
HydraFS: a high-throughput file system for the
HYDRAstor content-addressable storage system,
Proceedings of the 8th USENIX conference on File
and storage technologies, 2010
-> Content addressable storage
-> Stores information that can be retrieved based
on its content, not its storage location.
-> HydraFS isbuilt on top of CAS
DFS at Exascale
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Today (2011): Petascale Computing
O(10K) nodes and O(100K) cores
Near future (~2018): Exascale Computing
– ~1M nodes (100X)
– ~1B processor-cores/threads (10000X)
Ioan Raicu, Pete Beckman, Ian Foster, Making a Case for
Distributed File Systems at Exascale, ACM Workshop on Largescale System and Application Performance (LSAP), 2011