The Effectiveness of Deduplication on Virtual Machine Disk Images
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Venti Analysis and Memventi Implementation
Master’s thesis Venti analysis and memventi implementation Designing a trace-based simulator and implementing a venti with in-memory index Mechiel Lukkien [email protected] August 8, 2007 Committee: Faculty of EEMCS prof. dr. Sape J. Mullender DIES, Distributed and Embedded Systems ir. J. Scholten University of Twente ir. P.G. Jansen Enschede, The Netherlands 2 Abstract [The next page has a Dutch summary] Venti is a write-once content-addressed archival storage system, storing its data on magnetic disks: each data block is addressed by its 20-byte SHA-1 hash (called score). This project initially aimed to design and implement a trace-based simula- tor matching Venti behaviour closely enough to be able to use it to determine good configuration parameters (such as cache sizes), and for testing new opti- misations. A simplistic simulator has been implemented, but it does not model Venti behaviour accurately enough for its intended goal, nor is it polished enough for use. Modelled behaviour is inaccurate because the advanced optimisations of Venti have not been implemented in the simulator. However, implementation suggestions for these optimisations are presented. In the process of designing the simulator, the Venti source code has been investigated, the optimisations have been documented, and disk and Venti per- formance have been measured. This allowed for recommendations about per- formance, even without a simulator. Beside magnetic disks, also flash memory and the upcoming mems-based storage devices have been investigated for use with Venti; they may be usable in the near future, but require explicit support. The focus of this project has shifted towards designing and implementing memventi, an alternative implementation of the venti protocol. -
Achieving Superior Manageability, Efficiency, and Data Protection With
An Oracle White Paper December 2010 Achieving Superior Manageability, Efficiency, and Data Protection with Oracle’s Sun ZFS Storage Software Achieving Superior Manageability, Efficiency, and Data Protection with Oracle’s Sun ZFS Storage Software Introduction ......................................................................................... 2 Oracle’s Sun ZFS Storage Software ................................................... 3 Simplifying Storage Deployment and Management ............................ 3 Browser User Interface (BUI) ......................................................... 3 Built-in Networking and Security ..................................................... 4 Transparent Optimization with Hybrid Storage Pools ...................... 4 Shadow Data Migration ................................................................... 5 Third-party Confirmation of Management Efficiency ....................... 6 Improving Performance with Real-time Storage Profiling .................... 7 Increasing Storage Efficiency .............................................................. 8 Data Compression .......................................................................... 8 Data Deduplication .......................................................................... 9 Thin Provisioning ............................................................................ 9 Space-efficient Snapshots and Clones ......................................... 10 Reducing Risk with Industry-leading Data Protection ........................ 10 Self-Healing -
HTTP-FUSE Xenoppix
HTTP-FUSE Xenoppix Kuniyasu Suzaki† Toshiki Yagi† Kengo Iijima† Kenji Kitagawa†† Shuichi Tashiro††† National Institute of Advanced Industrial Science and Technology† Alpha Systems Inc.†† Information-Technology Promotion Agency, Japan††† {k.suzaki,yagi-toshiki,k-iijima}@aist.go.jp [email protected], [email protected] Abstract a CD-ROM. Furthermore it requires remaking the entire CD-ROM when a bit of data is up- dated. The other solution is a Virtual Machine We developed “HTTP-FUSE Xenoppix” which which enables us to install many OSes and ap- boots Linux, Plan9, and NetBSD on Virtual plications easily. However, that requires in- Machine Monitor “Xen” with a small bootable stalling virtual machine software. (6.5MB) CD-ROM. The bootable CD-ROM in- cludes boot loader, kernel, and miniroot only We have developed “Xenoppix” [1], which and most part of files are obtained via Internet is a combination of CD/DVD bootable Linux with network loopback device HTTP-FUSE “KNOPPIX” [2] and Virtual Machine Monitor CLOOP. It is made from cloop (Compressed “Xen” [3, 4]. Xenoppix boots Linux (KNOP- Loopback block device) and FUSE (Filesys- PIX) as Host OS and NetBSD or Plan9 as Guest tem USErspace). HTTP-FUSE CLOOP can re- OS with a bootable DVD only. KNOPPIX construct a block device from many small block is advanced in automatic device detection and files of HTTP servers. In this paper we describe driver integration. It prepares the Xen environ- the detail of the implementation and its perfor- ment and Guest OSes don’t need to worry about mance. lack of device drivers. -
Netbackup ™ Enterprise Server and Server 8.0 - 8.X.X OS Software Compatibility List Created on September 08, 2021
Veritas NetBackup ™ Enterprise Server and Server 8.0 - 8.x.x OS Software Compatibility List Created on September 08, 2021 Click here for the HTML version of this document. <https://download.veritas.com/resources/content/live/OSVC/100046000/100046611/en_US/nbu_80_scl.html> Copyright © 2021 Veritas Technologies LLC. All rights reserved. Veritas, the Veritas Logo, and NetBackup are trademarks or registered trademarks of Veritas Technologies LLC in the U.S. and other countries. Other names may be trademarks of their respective owners. Veritas NetBackup ™ Enterprise Server and Server 8.0 - 8.x.x OS Software Compatibility List 2021-09-08 Introduction This Software Compatibility List (SCL) document contains information for Veritas NetBackup 8.0 through 8.x.x. It covers NetBackup Server (which includes Enterprise Server and Server), Client, Bare Metal Restore (BMR), Clustered Master Server Compatibility and Storage Stacks, Deduplication, File System Compatibility, NetBackup OpsCenter, NetBackup Access Control (NBAC), SAN Media Server/SAN Client/FT Media Server, Virtual System Compatibility and NetBackup Self Service Support. It is divided into bookmarks on the left that can be expanded. IPV6 and Dual Stack environments are supported from NetBackup 8.1.1 onwards with few limitations, refer technote for additional information <http://www.veritas.com/docs/100041420> For information about certain NetBackup features, functionality, 3rd-party product integration, Veritas product integration, applications, databases, and OS platforms that Veritas intends to replace with newer and improved functionality, or in some cases, discontinue without replacement, please see the widget titled "NetBackup Future Platform and Feature Plans" at <https://sort.veritas.com/netbackup> Reference Article <https://www.veritas.com/docs/100040093> for links to all other NetBackup compatibility lists. -
Latency-Aware, Inline Data Deduplication for Primary Storage
iDedup: Latency-aware, inline data deduplication for primary storage Kiran Srinivasan, Tim Bisson, Garth Goodson, Kaladhar Voruganti NetApp, Inc. fskiran, tbisson, goodson, [email protected] Abstract systems exist that deduplicate inline with client requests for latency sensitive primary workloads. All prior dedu- Deduplication technologies are increasingly being de- plication work focuses on either: i) throughput sensitive ployed to reduce cost and increase space-efficiency in archival and backup systems [8, 9, 15, 21, 26, 39, 41]; corporate data centers. However, prior research has not or ii) latency sensitive primary systems that deduplicate applied deduplication techniques inline to the request data offline during idle time [1, 11, 16]; or iii) file sys- path for latency sensitive, primary workloads. This is tems with inline deduplication, but agnostic to perfor- primarily due to the extra latency these techniques intro- mance [3, 36]. This paper introduces two novel insights duce. Inherently, deduplicating data on disk causes frag- that enable latency-aware, inline, primary deduplication. mentation that increases seeks for subsequent sequential Many primary storage workloads (e.g., email, user di- reads of the same data, thus, increasing latency. In addi- rectories, databases) are currently unable to leverage the tion, deduplicating data requires extra disk IOs to access benefits of deduplication, due to the associated latency on-disk deduplication metadata. In this paper, we pro- costs. Since offline deduplication systems impact la- -
Redefine Blockchain Storage
Redefine Blockchain Storage Redefine Blockchain Storage YottaChain Foundation October 2018 V0.95 www.yottachain.io1/109 Redefine Blockchain Storage CONTENTS ABSTRACT........................................................................................... 7 1. BACKGROUND..............................................................................10 1.1. Storage is the best application scenario for blockchain....... 10 1.1.1 What is blockchain storage?....................................... 10 1.1.2. Storage itself has decentralized requirements........... 10 1.1.3 Amplification effect of data deduplication.................11 1.1.4 Storage can be directly TOKENIZE on the chain......11 1.1.5 chemical reactions of blockchain + storage................12 1.1.6 User value of blockchain storage................................12 1.2 IPFS........................................................................................14 1.2.1 What IPFS Resolved...................................................14 1.2.2 Deficiency of IPFS......................................................15 1.3Data Encryption and Data De-duplication..............................18 1.3.1Data Encryption........................................................... 18 1.3.2Data Deduplication...................................................... 19 1.3.3 Data Encryption OR Data Deduplication, which one to sacrifice?.......................................................................... 20 www.yottachain.io2/109 Redefine Blockchain Storage 2. INTRODUCTION TO YOTTACHAIN..........................................22 -
Plan 9 from Bell Labs
Plan 9 from Bell Labs “UNIX++ Anyone?” Anant Narayanan Malaviya National Institute of Technology FOSS.IN 2007 What is it? Advanced technology transferred via mind-control from aliens in outer space Humans are not expected to understand it (Due apologies to lisperati.com) Yeah Right • More realistically, a distributed operating system • Designed by the creators of C, UNIX, AWK, UTF-8, TROFF etc. etc. • Widely acknowledged as UNIX’s true successor • Distributed under terms of the Lucent Public License, which appears on the OSI’s list of approved licenses, also considered free software by the FSF What For? “Not only is UNIX dead, it’s starting to smell really bad.” -- Rob Pike (circa 1991) • UNIX was a fantastic idea... • ...in it’s time - 1970’s • Designed primarily as a “time-sharing” system, before the PC era A closer look at Unix TODAY It Works! But that doesn’t mean we don’t develop superior alternates GNU/Linux • GNU’s not UNIX, but it is! • Linux was inspired by Minix, which was in turn inspired by UNIX • GNU/Linux (mostly) conforms to ANSI and POSIX requirements • GNU/Linux, on the desktop, is playing “catch-up” with Windows or Mac OS X, offering little in terms of technological innovation Ok, and... • Most of the “modern ideas” we use today were “bolted” on an ancient underlying system • Don’t believe me? A “modern” UNIX Terminal Where did it go wrong? • Early UNIX, “everything is a file” • Brilliant! • Only until people started adding “features” to the system... Why you shouldn’t be working with GNU/Linux • The Socket API • POSIX • X11 • The Bindings “rat-race” • 300 system calls and counting.. -
Primary Data Deduplication – Large Scale Study and System Design
Primary Data Deduplication – Large Scale Study and System Design Ahmed El-Shimi Ran Kalach Ankit Kumar Adi Oltean Jin Li Sudipta Sengupta Microsoft Corporation, Redmond, WA, USA Abstract platform where a variety of workloads and services compete for system resources and no assumptions of We present a large scale study of primary data dedupli- dedicated hardware can be made. cation and use the findings to drive the design of a new primary data deduplication system implemented in the Our Contributions. We present a large and diverse Windows Server 2012 operating system. File data was study of primary data duplication in file-based server analyzed from 15 globally distributed file servers hosting data. Our findings are as follows: (i) Sub-file deduplica- data for over 2000 users in a large multinational corpora- tion is significantly more effective than whole-file dedu- tion. plication, (ii) High deduplication savings previously ob- The findings are used to arrive at a chunking and com- tained using small ∼4KB variable length chunking are pression approach which maximizes deduplication sav- achievable with 16-20x larger chunks, after chunk com- ings while minimizing the generated metadata and pro- pression is included, (iii) Chunk compressibility distri- ducing a uniform chunk size distribution. Scaling of bution is skewed with the majority of the benefit of com- deduplication processing with data size is achieved us- pression coming from a minority of the data chunks, and ing a RAM frugal chunk hash index and data partitioning (iv) Primary datasets are amenable to partitioned dedu- – so that memory, CPU, and disk seek resources remain plication with comparable space savings and the par- available to fulfill the primary workload of serving IO. -
(Brief) 2. an Extensible Compiler for Systems Programming
Show and Tell 1. Plan 9 Things (brief) 2. An Extensible Compiler for Systems Programming Russ Cox rsc@plan9 1127 Show and Tell April 19, 2005 who am i ................................................................................................................. ‘‘Neighborhood kid’’ 1995 summer hacking Excel (jlb) 1995-1997 cable modems (nls, tom) 1997-1999 annoying Plan 9 user 1999 summer doing Plan 9 graphics (rob, jmk) 1999-present assorted Plan 9 hacking Plan 9 Things ........................................................................................................ VBE ߝ use BIOS to set up VGA modes ߝ requires switching into real mode and back Venti ߝ reworked significantly ߝ aggressive caching, prefetching, batching, delayed writes ߝ Bloom filter to avoid index misses Plan 9 from User Space (plan9port) ߝ port bulk of Plan 9 software to Unix systems ߝ Linux, FreeBSD, NetBSD, SunOS, Mac OS X .................................................................................................................................... An Extensible Compiler for Systems Programming Russ Cox Frans Kaashoek Eddie Kohler [email protected] Outline ..................................................................................................................... Why bother? What could it do? How could it work? Ground rules: ߝ interrupt with questions ߝ work in progress ߝ show and tell, not a job talk Man vs. Machine ߝ Linguistic Tensions ................................................... The most important readers of a program are people. -
Data Deduplication Techniques
2010 International Conference on Future Information Technology and Management Engineering Data Deduplication Techniques Qinlu He, Zhanhuai Li, Xiao Zhang Department of Computer Science Northwestern Poly technical University Xi'an, P.R. China [email protected] Abstract-With the information and network technology, rapid • Within a single file (complete agreement with data development, rapid increase in the size of the data center, energy compression) consumption in the proportion of IT spending rising. In the great green environment many companies are eyeing the green store, • Cross-document hoping thereby to reduce the energy storage system. Data de • Cross-Application duplication technology to optimize the storage system can greatly reduce the amount of data, thereby reducing energy consumption • Cross-client and reduce heat emission. Data compression can reduce the number of disks used in the operation to reduce disk energy • Across time consumption costs. By studying the data de-duplication strategy, processes, and implementations for the following further lay the Data foundation of the work. Center I Keywords-cloud storage; green storage ; data deduplication V I. INTRODUCTION Now, green-saving business more seriously by people, especially in the international fmancial crisis has not yet cleared when, how cost always attached great importance to the Figure 1. Where deduplication can happend issue of major companies. It is against this background, the green store data de-duplication technology to become a hot Duplication is a data reduction technique, commonly used topic. in disk-based backup systems, storage systems designed to reduce the use of storage capacity. It works in a different time In the large-scale storage system environment, by setting period to fmd duplicate files in different locations of variable the storage pool and share the resources, avoid the different size data blocks. -
Microsoft SMB File Sharing Best Practices Guide
Technical White Paper Microsoft SMB File Sharing Best Practices Guide Tintri VMstore, Microsoft SMB 3.0 Protocol, and VMware 6.x Author: Neil Glick Version 1.0 06/15/2016 @tintri www.tintri.com Contents Executive Summary ...............................................................................1 Consolidated List of Practices...................................................................1 Benefits of Native Microsoft Windows 2012R2 File Sharing . 1 SMB 3.0 . 2 Data Deduplication......................................................................................2 DFS Namespaces and DFS Replication (DFS-R) ..............................................................2 File Classification Infrastructure (FCI) and File Server Resource Management Tools (FSRM) ..........................2 NTFS and Folder Security ................................................................................2 Shadow Copy of Shared Folders ...........................................................................3 Disk Quotas ...........................................................................................3 Deployment Architecture for a Windows File Server ........................................3 Microsoft Windows 2012R2 File Share Virtual Hardware Configurations................4 Network Best Practices for SMB and the Tintri VMstore ..................................5 Subnets ..............................................................................................6 Jumbo Frames .........................................................................................6 -
Avoiding the Disk Bottleneck in the Data Domain Deduplication File System
Avoiding the Disk Bottleneck in the Data Domain Deduplication File System Benjamin Zhu Data Domain, Inc. Kai Li Data Domain, Inc. and Princeton University Hugo Patterson Data Domain, Inc. Abstract Disk-based deduplication storage has emerged as the new-generation storage system for enterprise data protection to replace tape libraries. Deduplication removes redundant data segments to compress data into a highly compact form and makes it economical to store backups on disk instead of tape. A crucial requirement for enterprise data protection is high throughput, typically over 100 MB/sec, which enables backups to complete quickly. A significant challenge is to identify and eliminate duplicate data segments at this rate on a low-cost system that cannot afford enough RAM to store an index of the stored segments and may be forced to access an on-disk index for every input segment. This paper describes three techniques employed in the production Data Domain deduplication file system to relieve the disk bottleneck. These techniques include: (1) the Summary Vector, a compact in-memory data structure for identifying new segments; (2) Stream-Informed Segment Layout, a data layout method to improve on-disk locality for sequentially accessed segments; and (3) Locality Preserved Caching, which maintains the locality of the fingerprints of duplicate segments to achieve high cache hit ratios. Together, they can remove 99% of the disk accesses for deduplication of real world workloads. These techniques enable a modern two-socket dual-core system to run at 90% CPU utilization with only one shelf of 15 disks and achieve 100 MB/sec for single-stream throughput and 210 MB/sec for multi-stream throughput.