Scale and Performance in a Distributed File System

Jinyong Yoon, 2010. 10. 18.

Outline

Andrew File System The Prototype Changes for Performance Effect of Changes for Performance Comparison with A Remote-Open File Sys-

tem Conclusion

Andrew File System

Developed at Carnegie Mellon University Distributed file system by considerations of scale

Locality of file references Present a homogeneous, location-transparent file

name space to all the client workstations Use 4.2 BSD

Server▪ A set of trusted servers – Vice

Clients▪ User level processes – Venus▪ File system call hooking▪ Contacts with servers only opens and closes for a whole-file transfer

▪ Caches files from Vice▪ Store modified copies of files back on the servers

Andrew File System - Overview

worksta-tion

Venus

UserPro-gram

Unix Kernel

Disk

Server

Vice

Unix Kernel

Disk

worksta-tion

Venus

UserPro-gram

Unix Kernel

Disk

worksta-tion

Venus

UserPro-gram

Unix Kernel

Disk

Server

Vice

Unix Kernel

Disk

Network

The Prototype - Descrip-tion Venus on the client with a dedicated process Persistent process on the server Each server stored the directory hierarchy

Mirroring the structure of the Vice files .admin directory – Vice file status info Stub directory – location database

Vice-Venus interface by their full pathname There’s no notion of a low-level name such as inode

Before using a cached file, Venus verifies its time-stamp Each open of a file thus resulted in at least one interac-

tion with a server, even if the file were already in the cache and up to date

The Prototype – Qualitative Observations

stat primitive To test for the presence of files To obtain status information before opening

files Each stat call involved a cache validity check Increase total running time and the load on

servers Dedicated Process

Excessive context switching overhead Critical resource limits excess High virtual memory paging demands

The Prototype – Qualitative Observations

Remote Procedure Call (RPC) Simplification of implementation Network related resources in the kernel to be

exceeded Location Database

Difficult to move users’ directories between servers

Etc. Use Vice file without recompilation or relinking

The Prototype - Bench-mark Benchmark

Command scripts that operates on a collection of files 70 files (source code of an application program) 200kb Stand-alone Benchmark and 5 phases

The Prototype - Bench-mark Skewed distribution of Vice calls

TestAuth – Validate cache entries GetFileStat – Obtain status information about files absent

from the cache

The Prototype - Bench-mark Load unit

Load placed on a server by a single client workstation running this benchmark

A load unit – 5 Andrew users

The Prototype - Bench-mark CPU/disk utilization profiling

Performance bottleneck is CPU Frequently context switches The time spent by the servers in traversing full path-

names

Changes for Perfor-mance Cache management

Previous▪ Status(in virtual memory)/Data(in local disk) cache▪ Interception only opening/closing operations▪ Modifications to a cached files are reflected back to

Vice when the file is closed Callback - the server promises to notify it before al-

lowing a modification▪ This reduces cache validation traffic▪ Each should maintain callback state information ▪ There is a potential for inconsistency

Changes for Perfor-mance Name resolution

Previous▪ inode – unique, fixed-length▪ pathname – one or more, variable-length▪ namei routine – maps a pathname to an inode▪ Each Vice pathname involves implicit namei operation▪ CPU overhead on the servers

fid – unique, fixed-length, two-level name▪ Map a component of a pathname to a fid▪ Each 32 bit-Volume number, Vnode number, Uniquifuier▪ Volume number: Identifying a Volume on one server▪ Vnode number: Index into an file storage information array▪ Uniquifuier: Allowing Reuse of Vnode number

Changes for Perfor-mance Communication and server process

structure Using Lightweight Processes (LWPs) instead

of a single process An LWP is bound to a particular client only

for the duration of a single server operation. Low-level storage representation

Access files by their inodes▪ vnode on the servers▪ inode on the clients

Change for Performance – Overall Design

worksta-tion

UserPro-gram

Unix Kernel

Unix File System

Unix file system calls

- If D is in the cache and has a callback on it

- If D is in the cache but has no call-back on it

- If D is not in the cacheNon-local file opera-tions

Local Disk

Change for Performance – Effect Scalability

19% slower than stand-alone workstation Prototype is 70% slower

Change for Performance – Effect Scalability

Comparison with A Remote-Open File System

Remote Open The data in a file are not fetched en masse Instead the remote site potentially participates in each

individual read an write operation File is actually opened on the remote site rather than the

local site NFS

Comparison with A Remote-Open File System

Comparison with A Remote-Open File System

Advantage of remote-open file system Low latency

Conclusion

Scale impacts Andrew in areas be-sides performance and operability