End-To-End Data Integrity for File Systems: a ZFS Case Study
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Copy on Write Based File Systems Performance Analysis and Implementation
Copy On Write Based File Systems Performance Analysis And Implementation Sakis Kasampalis Kongens Lyngby 2010 IMM-MSC-2010-63 Technical University of Denmark Department Of Informatics Building 321, DK-2800 Kongens Lyngby, Denmark Phone +45 45253351, Fax +45 45882673 [email protected] www.imm.dtu.dk Abstract In this work I am focusing on Copy On Write based file systems. Copy On Write is used on modern file systems for providing (1) metadata and data consistency using transactional semantics, (2) cheap and instant backups using snapshots and clones. This thesis is divided into two main parts. The first part focuses on the design and performance of Copy On Write based file systems. Recent efforts aiming at creating a Copy On Write based file system are ZFS, Btrfs, ext3cow, Hammer, and LLFS. My work focuses only on ZFS and Btrfs, since they support the most advanced features. The main goals of ZFS and Btrfs are to offer a scalable, fault tolerant, and easy to administrate file system. I evaluate the performance and scalability of ZFS and Btrfs. The evaluation includes studying their design and testing their performance and scalability against a set of recommended file system benchmarks. Most computers are already based on multi-core and multiple processor architec- tures. Because of that, the need for using concurrent programming models has increased. Transactions can be very helpful for supporting concurrent program- ming models, which ensure that system updates are consistent. Unfortunately, the majority of operating systems and file systems either do not support trans- actions at all, or they simply do not expose them to the users. -
The Page Cache Today’S Lecture RCU File System Networking(Kernel Level Syncmem
2/21/20 COMP 790: OS Implementation COMP 790: OS Implementation Logical Diagram Binary Memory Threads Formats Allocators User System Calls Kernel The Page Cache Today’s Lecture RCU File System Networking(kernel level Syncmem. Don Porter management) Memory Device CPU Management Drivers Scheduler Hardware Interrupts Disk Net Consistency 1 2 1 2 COMP 790: OS Implementation COMP 790: OS Implementation Recap of previous lectures Background • Page tables: translate virtual addresses to physical • Lab2: Track physical pages with an array of PageInfo addresses structs • VM Areas (Linux): track what should be mapped at in – Contains reference counts the virtual address space of a process – Free list layered over this array • Hoard/Linux slab: Efficient allocation of objects from • Just like JOS, Linux represents physical memory with a superblock/slab of pages an array of page structs – Obviously, not the exact same contents, but same idea • Pages can be allocated to processes, or to cache file data in memory 3 4 3 4 COMP 790: OS Implementation COMP 790: OS Implementation Today’s Problem The address space abstraction • Given a VMA or a file’s inode, how do I figure out • Unifying abstraction: which physical pages are storing its data? – Each file inode has an address space (0—file size) • Next lecture: We will go the other way, from a – So do block devices that cache data in RAM (0---dev size) physical page back to the VMA or file inode – The (anonymous) virtual memory of a process has an address space (0—4GB on x86) • In other words, all page -
ZFS (On Linux) Use Your Disks in Best Possible Ways Dobrica Pavlinušić CUC Sys.Track 2013-10-21 What Are We Going to Talk About?
ZFS (on Linux) use your disks in best possible ways Dobrica Pavlinušić http://blog.rot13.org CUC sys.track 2013-10-21 What are we going to talk about? ● ZFS history ● Disks or SSD and for what? ● Installation ● Create pool, filesystem and/or block device ● ARC, L2ARC, ZIL ● snapshots, send/receive ● scrub, disk reliability (smart) ● tuning zfs ● downsides ZFS history 2001 – Development of ZFS started with two engineers at Sun Microsystems. 2005 – Source code was released as part of OpenSolaris. 2006 – Development of FUSE port for Linux started. 2007 – Apple started porting ZFS to Mac OS X. 2008 – A port to FreeBSD was released as part of FreeBSD 7.0. 2008 – Development of a native Linux port started. 2009 – Apple's ZFS project closed. The MacZFS project continued to develop the code. 2010 – OpenSolaris was discontinued, the last release was forked. Further development of ZFS on Solaris was no longer open source. 2010 – illumos was founded as the truly open source successor to OpenSolaris. Development of ZFS continued in the open. Ports of ZFS to other platforms continued porting upstream changes from illumos. 2012 – Feature flags were introduced to replace legacy on-disk version numbers, enabling easier distributed evolution of the ZFS on-disk format to support new features. 2013 – Alongside the stable version of MacZFS, ZFS-OSX used ZFS on Linux as a basis for the next generation of MacZFS. 2013 – The first stable release of ZFS on Linux. 2013 – Official announcement of the OpenZFS project. Terminology ● COW - copy on write ○ doesn’t -
Hybrid Drowsy SRAM and STT-RAM Buffer Designs for Dark-Silicon
This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS 1 Hybrid Drowsy SRAM and STT-RAM Buffer Designs for Dark-Silicon-Aware NoC Jia Zhan, Student Member, IEEE, Jin Ouyang, Member, IEEE,FenGe,Member, IEEE, Jishen Zhao, Member, IEEE, and Yuan Xie, Fellow, IEEE Abstract— The breakdown of Dennard scaling prevents us MCMC MC from powering all transistors simultaneously, leaving a large fraction of dark silicon. This crisis has led to innovative work on Tile link power-efficient core and memory architecture designs. However, link link RouterRouter the research for addressing dark silicon challenges with network- To router on-chip (NoC), which is a major contributor to the total chip NI power consumption, is largely unexplored. In this paper, we Core link comprehensively examine the network power consumers and L1-I$ L2 L1-D$ the drawbacks of the conventional power-gating techniques. To overcome the dark silicon issue from the NoC’s perspective, we MCMC MC propose DimNoC, a dim silicon scheme, which leverages recent drowsy SRAM design and spin-transfer torque RAM (STT-RAM) Fig. 1. 4 × 4 NoC-based multicore architecture. In each node, the local technology to replace pure SRAM-based NoC buffers. processing elements (core, L1, L2 caches, and so on) are attached to a router In particular, we propose two novel hybrid buffer architectures: through an NI. Routers are interconnected through links to form an NoC. 1) a hierarchical buffer architecture, which divides the input Four memory controllers are attached at the four corners, which will be used buffers into a set of levels with different power states and 2) a for off-chip memory access. -
Z/OS ICSF Overview How to Send Your Comments to IBM
z/OS Version 2 Release 3 Cryptographic Services Integrated Cryptographic Service Facility Overview IBM SC14-7505-08 Note Before using this information and the product it supports, read the information in “Notices” on page 81. This edition applies to ICSF FMID HCR77D0 and Version 2 Release 3 of z/OS (5650-ZOS) and to all subsequent releases and modifications until otherwise indicated in new editions. Last updated: 2020-05-25 © Copyright International Business Machines Corporation 1996, 2020. US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents Figures................................................................................................................ vii Tables.................................................................................................................. ix About this information.......................................................................................... xi ICSF features...............................................................................................................................................xi Who should use this information................................................................................................................ xi How to use this information........................................................................................................................ xi Where to find more information.................................................................................................................xii -
An Analysis of Data Corruption in the Storage Stack
An Analysis of Data Corruption in the Storage Stack Lakshmi N. Bairavasundaram∗, Garth R. Goodson†, Bianca Schroeder‡ Andrea C. Arpaci-Dusseau∗, Remzi H. Arpaci-Dusseau∗ ∗University of Wisconsin-Madison †Network Appliance, Inc. ‡University of Toronto {laksh, dusseau, remzi}@cs.wisc.edu, [email protected], [email protected] Abstract latent sector errors, within disk drives [18]. Latent sector errors are detected by a drive’s internal error-correcting An important threat to reliable storage of data is silent codes (ECC) and are reported to the storage system. data corruption. In order to develop suitable protection Less well-known, however, is that current hard drives mechanisms against data corruption, it is essential to un- and controllers consist of hundreds-of-thousandsof lines derstand its characteristics. In this paper, we present the of low-level firmware code. This firmware code, along first large-scale study of data corruption. We analyze cor- with higher-level system software, has the potential for ruption instances recorded in production storage systems harboring bugs that can cause a more insidious type of containing a total of 1.53 million disk drives, over a pe- disk error – silent data corruption, where the data is riod of 41 months. We study three classes of corruption: silently corrupted with no indication from the drive that checksum mismatches, identity discrepancies, and par- an error has occurred. ity inconsistencies. We focus on checksum mismatches since they occur the most. Silent data corruptionscould lead to data loss more of- We find more than 400,000 instances of checksum ten than latent sector errors, since, unlike latent sector er- mismatches over the 41-month period. -
Study of File System Evolution
Study of File System Evolution Swaminathan Sundararaman, Sriram Subramanian Department of Computer Science University of Wisconsin {swami, srirams} @cs.wisc.edu Abstract File systems have traditionally been a major area of file systems are typically developed and maintained by research and development. This is evident from the several programmer across the globe. At any point in existence of over 50 file systems of varying popularity time, for a file system, there are three to six active in the current version of the Linux kernel. They developers, ten to fifteen patch contributors but a single represent a complex subsystem of the kernel, with each maintainer. These people communicate through file system employing different strategies for tackling individual file system mailing lists [14, 16, 18] various issues. Although there are many file systems in submitting proposals for new features, enhancements, Linux, there has been no prior work (to the best of our reporting bugs, submitting and reviewing patches for knowledge) on understanding how file systems evolve. known bugs. The problems with the open source We believe that such information would be useful to the development approach is that all communication is file system community allowing developers to learn buried in the mailing list archives and aren’t easily from previous experiences. accessible to others. As a result when new file systems are developed they do not leverage past experience and This paper looks at six file systems (Ext2, Ext3, Ext4, could end up re-inventing the wheel. To make things JFS, ReiserFS, and XFS) from a historical perspective worse, people could typically end up doing the same (between kernel versions 1.0 to 2.6) to get an insight on mistakes as done in other file systems. -
Detection Method of Data Integrity in Network Storage Based on Symmetrical Difference
S S symmetry Article Detection Method of Data Integrity in Network Storage Based on Symmetrical Difference Xiaona Ding School of Electronics and Information Engineering, Sias University of Zhengzhou, Xinzheng 451150, China; [email protected] Received: 15 November 2019; Accepted: 26 December 2019; Published: 3 February 2020 Abstract: In order to enhance the recall and the precision performance of data integrity detection, a method to detect the network storage data integrity based on symmetric difference was proposed. Through the complete automatic image annotation system, the crawler technology was used to capture the image and related text information. According to the automatic word segmentation, pos tagging and Chinese word segmentation, the feature analysis of text data was achieved. Based on the symmetrical difference algorithm and the background subtraction, the feature extraction of image data was realized. On the basis of data collection and feature extraction, the sentry data segment was introduced, and then the sentry data segment was randomly selected to detect the data integrity. Combined with the accountability scheme of data security of the trusted third party, the trusted third party was taken as the core. The online state judgment was made for each user operation. Meanwhile, credentials that cannot be denied by both parties were generated, and thus to prevent the verifier from providing false validation results. Experimental results prove that the proposed method has high precision rate, high recall rate, and strong reliability. Keywords: symmetric difference; network; data integrity; detection 1. Introduction In recent years, the cloud computing becomes a new shared infrastructure based on the network. Based on Internet, virtualization, and other technologies, a large number of system pools and other resources are combined to provide users with a series of convenient services [1]. -
Linux Data Integrity Extensions
Linux Data Integrity Extensions Martin K. Petersen Oracle [email protected] Abstract The software stack, however, is rapidly growing in com- plexity. This implies an increasing failure potential: Many databases and filesystems feature checksums on Harddrive firmware, RAID controller firmware, host their logical blocks, enabling detection of corrupted adapter firmware, operating system code, system li- data. The scenario most people are familiar with in- braries, and application errors. There are many things volves bad sectors which develop while data is stored that can go wrong from the time data is generated in on disk. However, many corruptions are actually a re- host memory until it is stored physically on disk. sult of errors that occurred when the data was originally written. While a database or filesystem can detect the Most storage devices feature extensive checking to pre- corruption when data is eventually read back, the good vent errors. However, these protective measures are al- data may have been lost forever. most exclusively being deployed internally to the de- vice in a proprietary fashion. So far, there have been A recent addition to SCSI allows extra protection infor- no means for collaboration between the layers in the I/O mation to be exchanged between controller and disk. We stack to ensure data integrity. have extended this capability up into Linux, allowing filesystems (and eventually applications) to be able to at- An extension to the SCSI family of protocols tries to tach integrity metadata to I/O requests. Controllers and remedy this by defining a way to check the integrity of disks can then verify the integrity of an I/O before com- an request as it traverses the I/O stack. -
Enhancing the Accuracy of Synthetic File System Benchmarks Salam Farhat Nova Southeastern University, [email protected]
Nova Southeastern University NSUWorks CEC Theses and Dissertations College of Engineering and Computing 2017 Enhancing the Accuracy of Synthetic File System Benchmarks Salam Farhat Nova Southeastern University, [email protected] This document is a product of extensive research conducted at the Nova Southeastern University College of Engineering and Computing. For more information on research and degree programs at the NSU College of Engineering and Computing, please click here. Follow this and additional works at: https://nsuworks.nova.edu/gscis_etd Part of the Computer Sciences Commons Share Feedback About This Item NSUWorks Citation Salam Farhat. 2017. Enhancing the Accuracy of Synthetic File System Benchmarks. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, College of Engineering and Computing. (1003) https://nsuworks.nova.edu/gscis_etd/1003. This Dissertation is brought to you by the College of Engineering and Computing at NSUWorks. It has been accepted for inclusion in CEC Theses and Dissertations by an authorized administrator of NSUWorks. For more information, please contact [email protected]. Enhancing the Accuracy of Synthetic File System Benchmarks by Salam Farhat A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor in Philosophy in Computer Science College of Engineering and Computing Nova Southeastern University 2017 We hereby certify that this dissertation, submitted by Salam Farhat, conforms to acceptable standards and is fully adequate in scope and quality to fulfill the dissertation requirements for the degree of Doctor of Philosophy. _____________________________________________ ________________ Gregory E. Simco, Ph.D. Date Chairperson of Dissertation Committee _____________________________________________ ________________ Sumitra Mukherjee, Ph.D. Date Dissertation Committee Member _____________________________________________ ________________ Francisco J. -
Understanding Real World Data Corruptions in Cloud Systems
Understanding Real World Data Corruptions in Cloud Systems Peipei Wang, Daniel J. Dean, Xiaohui Gu Department of Computer Science North Carolina State University Raleigh, North Carolina {pwang7,djdean2}@ncsu.edu, [email protected] Abstract—Big data processing is one of the killer applications enough to require attention, little research has been done to for cloud systems. MapReduce systems such as Hadoop are the understand software-induced data corruption problems. most popular big data processing platforms used in the cloud system. Data corruption is one of the most critical problems in In this paper, we present a comprehensive study on the cloud data processing, which not only has serious impact on characteristics of the real world data corruption problems the integrity of individual application results but also affects the caused by software bugs in cloud systems. We examined 138 performance and availability of the whole data processing system. data corruption incidents reported in the bug repositories of In this paper, we present a comprehensive study on 138 real world four Hadoop projects (i.e., Hadoop-common, HDFS, MapRe- data corruption incidents reported in Hadoop bug repositories. duce, YARN [17]). Although Hadoop provides fault tolerance, We characterize those data corruption problems in four aspects: our study has shown that data corruptions still seriously affect 1) what impact can data corruption have on the application and system? 2) how is data corruption detected? 3) what are the the integrity, performance, and availability -
ECE 598 – Advanced Operating Systems Lecture 19
ECE 598 { Advanced Operating Systems Lecture 19 Vince Weaver http://web.eece.maine.edu/~vweaver [email protected] 7 April 2016 Announcements • Homework #7 was due • Homework #8 will be posted 1 Why use FAT over ext2? • FAT simpler, easy to code • FAT supported on all major OSes • ext2 faster, more robust filename and permissions 2 btrfs • B-tree fs (similar to a binary tree, but with pages full of leaves) • overwrite filesystem (overwite on modify) vs CoW • Copy on write. When write to a file, old data not overwritten. Since old data not over-written, crash recovery better Eventually old data garbage collected • Data in extents 3 • Copy-on-write • Forest of trees: { sub-volumes { extent-allocation { checksum tree { chunk device { reloc • On-line defragmentation • On-line volume growth 4 • Built-in RAID • Transparent compression • Snapshots • Checksums on data and meta-data • De-duplication • Cloning { can make an exact snapshot of file, copy-on- write different than link, different inodles but same blocks 5 Embedded • Designed to be small, simple, read-only? • romfs { 32 byte header (magic, size, checksum,name) { Repeating files (pointer to next [0 if none]), info, size, checksum, file name, file data • cramfs 6 ZFS Advanced OS from Sun/Oracle. Similar in idea to btrfs indirect still, not extent based? 7 ReFS Resilient FS, Microsoft's answer to brtfs and zfs 8 Networked File Systems • Allow a centralized file server to export a filesystem to multiple clients. • Provide file level access, not just raw blocks (NBD) • Clustered filesystems also exist, where multiple servers work in conjunction.