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Lecture 9: Data Storage and IO Models Lecture 9
Lecture 9 Lecture 9: Data Storage and IO Models Lecture 9 Announcements • Submission Project Part 1 tonight • Instructions on Piazza! • PS2 due on Friday at 11:59 pm • Questions? Easier than PS1. • Badgers Rule! Lecture 9 Today’s Lecture 1. Data Storage 2. Disk and Files 3. Buffer Manager - Prelims 3 Lecture 9 > Section 1 1. Data Storage 4 Lecture 9 > Section 1 What you will learn about in this section 1. Life cycle of a query 2. Architecture of a DBMS 3. Memory Hierarchy 5 Lecture 9 > Section 1 Life cycle of a query Query Result Query Database Server Query Execute Parser Optimizer Select R.text from |…|……|………..|………..| Report R, Weather W |…|……|………..|………..| where W.image.rain() Scheduler Operators |…|……|………..|………..| and W.city = R.city |…|……|………..|………..| and W.date = R.date |…|……|………..|………..| and |…|……|………..|………..| R.text. |…|……|………..|………..| matches(“insurance claims”) |…|……|………..|………..| |…|……|………..|………..| |…|……|………..|………..| |…|……|………..|………..| Query Query Syntax Tree Query Plan Result Segments 6 Lecture 9 > Section 1 > Architecture of a DBMS Internal Architecture of a DBMS query Query Execution data access Storage Manager I/O access 7 Lecture 9 > Section 1 > Storage Manager Architecture of a Storage Manager Access Methods Sorted File Hash Index B+-tree Heap File Index Manager Buffer Manager Recovery Manager Concurrency Control I/O Manager IO Accesses In Systems, IO cost matters a ton! 8 Lecture 9 > Section 1 > Data Storage Data Storage • How does a DBMS store and access data? • main memory (fast, temporary) • disk (slow, permanent) • How -
Rootless Containers with Podman and Fuse-Overlayfs
CernVM Workshop 2019 (4th June 2019) Rootless containers with Podman and fuse-overlayfs Giuseppe Scrivano @gscrivano Introduction 2 Rootless Containers • “Rootless containers refers to the ability for an unprivileged user (i.e. non-root user) to create, run and otherwise manage containers.” (https://rootlesscontaine.rs/ ) • Not just about running the container payload as an unprivileged user • Container runtime runs also as an unprivileged user 3 Don’t confuse with... • sudo podman run --user foo – Executes the process in the container as non-root – Podman and the OCI runtime still running as root • USER instruction in Dockerfile – same as above – Notably you can’t RUN dnf install ... 4 Don’t confuse with... • podman run --uidmap – Execute containers as a non-root user, using user namespaces – Most similar to rootless containers, but still requires podman and runc to run as root 5 Motivation of Rootless Containers • To mitigate potential vulnerability of container runtimes • To allow users of shared machines (e.g. HPC) to run containers without the risk of breaking other users environments • To isolate nested containers 6 Caveat: Not a panacea • Although rootless containers could mitigate these vulnerabilities, it is not a panacea , especially it is powerless against kernel (and hardware) vulnerabilities – CVE 2013-1858, CVE-2015-1328, CVE-2018-18955 • Castle approach : it should be used in conjunction with other security layers such as seccomp and SELinux 7 Podman 8 Rootless Podman Podman is a daemon-less alternative to Docker • $ alias -
System Calls System Calls
System calls We will investigate several issues related to system calls. Read chapter 12 of the book Linux system call categories file management process management error handling note that these categories are loosely defined and much is behind included, e.g. communication. Why? 1 System calls File management system call hierarchy you may not see some topics as part of “file management”, e.g., sockets 2 System calls Process management system call hierarchy 3 System calls Error handling hierarchy 4 Error Handling Anything can fail! System calls are no exception Try to read a file that does not exist! Error number: errno every process contains a global variable errno errno is set to 0 when process is created when error occurs errno is set to a specific code associated with the error cause trying to open file that does not exist sets errno to 2 5 Error Handling error constants are defined in errno.h here are the first few of errno.h on OS X 10.6.4 #define EPERM 1 /* Operation not permitted */ #define ENOENT 2 /* No such file or directory */ #define ESRCH 3 /* No such process */ #define EINTR 4 /* Interrupted system call */ #define EIO 5 /* Input/output error */ #define ENXIO 6 /* Device not configured */ #define E2BIG 7 /* Argument list too long */ #define ENOEXEC 8 /* Exec format error */ #define EBADF 9 /* Bad file descriptor */ #define ECHILD 10 /* No child processes */ #define EDEADLK 11 /* Resource deadlock avoided */ 6 Error Handling common mistake for displaying errno from Linux errno man page: 7 Error Handling Description of the perror () system call. -
Ext4 File System and Crash Consistency
1 Ext4 file system and crash consistency Changwoo Min 2 Summary of last lectures • Tools: building, exploring, and debugging Linux kernel • Core kernel infrastructure • Process management & scheduling • Interrupt & interrupt handler • Kernel synchronization • Memory management • Virtual file system • Page cache and page fault 3 Today: ext4 file system and crash consistency • File system in Linux kernel • Design considerations of a file system • History of file system • On-disk structure of Ext4 • File operations • Crash consistency 4 File system in Linux kernel User space application (ex: cp) User-space Syscalls: open, read, write, etc. Kernel-space VFS: Virtual File System Filesystems ext4 FAT32 JFFS2 Block layer Hardware Embedded Hard disk USB drive flash 5 What is a file system fundamentally? int main(int argc, char *argv[]) { int fd; char buffer[4096]; struct stat_buf; DIR *dir; struct dirent *entry; /* 1. Path name -> inode mapping */ fd = open("/home/lkp/hello.c" , O_RDONLY); /* 2. File offset -> disk block address mapping */ pread(fd, buffer, sizeof(buffer), 0); /* 3. File meta data operation */ fstat(fd, &stat_buf); printf("file size = %d\n", stat_buf.st_size); /* 4. Directory operation */ dir = opendir("/home"); entry = readdir(dir); printf("dir = %s\n", entry->d_name); return 0; } 6 Why do we care EXT4 file system? • Most widely-deployed file system • Default file system of major Linux distributions • File system used in Google data center • Default file system of Android kernel • Follows the traditional file system design 7 History of file system design 8 UFS (Unix File System) • The original UNIX file system • Design by Dennis Ritche and Ken Thompson (1974) • The first Linux file system (ext) and Minix FS has a similar layout 9 UFS (Unix File System) • Performance problem of UFS (and the first Linux file system) • Especially, long seek time between an inode and data block 10 FFS (Fast File System) • The file system of BSD UNIX • Designed by Marshall Kirk McKusick, et al. -
How to Create a Custom Live CD for Secure Remote Incident Handling in the Enterprise
How to Create a Custom Live CD for Secure Remote Incident Handling in the Enterprise Abstract This paper will document a process to create a custom Live CD for secure remote incident handling on Windows and Linux systems. The process will include how to configure SSH for remote access to the Live CD even when running behind a NAT device. The combination of customization and secure remote access will make this process valuable to incident handlers working in enterprise environments with limited remote IT support. Bert Hayes, [email protected] How to Create a Custom Live CD for Remote Incident Handling 2 Table of Contents Abstract ...........................................................................................................................................1 1. Introduction ............................................................................................................................5 2. Making Your Own Customized Debian GNU/Linux Based System........................................7 2.1. The Development Environment ......................................................................................7 2.2. Making Your Dream Incident Handling System...............................................................9 2.3. Hardening the Base Install.............................................................................................11 2.3.1. Managing Root Access with Sudo..........................................................................11 2.4. Randomizing the Handler Password at Boot Time ........................................................12 -
File Handling in Python
hapter C File Handling in 2 Python There are many ways of trying to understand programs. People often rely too much on one way, which is called "debugging" and consists of running a partly- understood program to see if it does what you expected. Another way, which ML advocates, is to install some means of understanding in the very programs themselves. — Robin Milner In this Chapter » Introduction to Files » Types of Files » Opening and Closing a 2.1 INTRODUCTION TO FILES Text File We have so far created programs in Python that » Writing to a Text File accept the input, manipulate it and display the » Reading from a Text File output. But that output is available only during » Setting Offsets in a File execution of the program and input is to be entered through the keyboard. This is because the » Creating and Traversing a variables used in a program have a lifetime that Text File lasts till the time the program is under execution. » The Pickle Module What if we want to store the data that were input as well as the generated output permanently so that we can reuse it later? Usually, organisations would want to permanently store information about employees, inventory, sales, etc. to avoid repetitive tasks of entering the same data. Hence, data are stored permanently on secondary storage devices for reusability. We store Python programs written in script mode with a .py extension. Each program is stored on the secondary device as a file. Likewise, the data entered, and the output can be stored permanently into a file. -
In Search of the Ideal Storage Configuration for Docker Containers
In Search of the Ideal Storage Configuration for Docker Containers Vasily Tarasov1, Lukas Rupprecht1, Dimitris Skourtis1, Amit Warke1, Dean Hildebrand1 Mohamed Mohamed1, Nagapramod Mandagere1, Wenji Li2, Raju Rangaswami3, Ming Zhao2 1IBM Research—Almaden 2Arizona State University 3Florida International University Abstract—Containers are a widely successful technology today every running container. This would cause a great burden on popularized by Docker. Containers improve system utilization by the I/O subsystem and make container start time unacceptably increasing workload density. Docker containers enable seamless high for many workloads. As a result, copy-on-write (CoW) deployment of workloads across development, test, and produc- tion environments. Docker’s unique approach to data manage- storage and storage snapshots are popularly used and images ment, which involves frequent snapshot creation and removal, are structured in layers. A layer consists of a set of files and presents a new set of exciting challenges for storage systems. At layers with the same content can be shared across images, the same time, storage management for Docker containers has reducing the amount of storage required to run containers. remained largely unexplored with a dizzying array of solution With Docker, one can choose Aufs [6], Overlay2 [7], choices and configuration options. In this paper we unravel the multi-faceted nature of Docker storage and demonstrate its Btrfs [8], or device-mapper (dm) [9] as storage drivers which impact on system and workload performance. As we uncover provide the required snapshotting and CoW capabilities for new properties of the popular Docker storage drivers, this is a images. None of these solutions, however, were designed with sobering reminder that widespread use of new technologies can Docker in mind and their effectiveness for Docker has not been often precede their careful evaluation. -
System Calls and Standard I/O
System Calls and Standard I/O Professor Jennifer Rexford http://www.cs.princeton.edu/~jrex 1 Goals of Today’s Class • System calls o How a user process contacts the Operating System o For advanced services that may require special privilege • Standard I/O library o Generic I/O support for C programs o A smart wrapper around I/O-related system calls o Stream concept, line-by-line input, formatted output, ... 2 1 System Calls 3 Communicating With the OS User Process signals systems calls Operating System • System call o Request to the operating system to perform a task o … that the process does not have permission to perform • Signal o Asynchronous notification sent to a process … to notify the process of an event that has occurred o 4 2 Processor Modes • The OS must restrict what a user process can do o What instructions can execute o What portions of the address space are accessible • Supervisor mode (or kernel mode) o Can execute any instructions in the instruction set – Including halting the processor, changing mode bit, initiating I/O o Can access any memory location in the system – Including code and data in the OS address space • User mode o Restricted capabilities – Cannot execute privileged instructions – Cannot directly reference code or data in OS address space o Any such attempt results in a fatal “protection fault” – Instead, access OS code and data indirectly via system calls 5 Main Categories of System Calls • File system o Low-level file I/O o E.g., creat, open, read, write, lseek, close • Multi-tasking mechanisms o Process -
MINCS - the Container in the Shell (Script)
MINCS - The Container in the Shell (script) - Masami Hiramatsu <[email protected]> Tech Lead, Linaro Ltd. Open Source Summit Japan 2017 LEADING COLLABORATION IN THE ARM ECOSYSTEM Who am I... Masami Hiramatsu - Linux kernel kprobes maintainer - Working for Linaro as a Tech Lead LEADING COLLABORATION IN THE ARM ECOSYSTEM Demo # minc top # minc -r /opt/debian/x86_64 # minc -r /opt/debian/arm64 --arch arm64 LEADING COLLABORATION IN THE ARM ECOSYSTEM What Is MINCS? My Personal Fun Project to learn how linux containers work :-) LEADING COLLABORATION IN THE ARM ECOSYSTEM What Is MINCS? Mini Container Shell Scripts (pronounced ‘minks’) - Container engine implementation using POSIX shell scripts - It is small (~60KB, ~2KLOC) (~20KB in minimum) - It can run on busybox - No architecture dependency (* except for qemu/um mode) - No need for special binaries (* except for libcap, just for capsh --exec) - Main Features - Namespaces (Mount, PID, User, UTS, Net*) - Cgroups (CPU, Memory) - Capabilities - Overlay filesystem - Qemu cross-arch/system emulation - User-mode-linux - Image importing from dockerhub And all are done by CLI commands :-) LEADING COLLABORATION IN THE ARM ECOSYSTEM Why Shell Script? That is my favorite language :-) - Easy to understand for *nix administrators - Just a bunch of commands - Easy to modify - Good for prototyping - Easy to deploy - No architecture dependencies - Very small - Able to run on busybox (+ libcap is perfect) LEADING COLLABORATION IN THE ARM ECOSYSTEM MINCS Use-Cases For Learning - Understand how containers work For Development - Prepare isolated (cross-)build environment For Testing - Test new applications in isolated environment - Test new kernel features on qemu using local tools For products? - Maybe good for embedded devices which has small resources LEADING COLLABORATION IN THE ARM ECOSYSTEM What Is A Linux Container? There are many linux container engines - Docker, LXC, rkt, runc, .. -
Understanding the Performance of Container Execution Environments
Understanding the performance of container execution environments Guillaume Everarts de Velp, Etienne Rivière and Ramin Sadre [email protected] EPL, ICTEAM, UCLouvain, Belgium Abstract example is an automatic grading platform named INGIn- Many application server backends leverage container tech- ious [2, 3]. This platform is used extensively at UCLouvain nologies to support workloads formed of short-lived, but and other institutions around the world to provide computer potentially I/O-intensive, operations. The latency at which science and engineering students with automated feedback container-supported operations complete impacts both the on programming assignments, through the execution of se- users’ experience and the throughput that the platform can ries of unit tests prepared by instructors. It is necessary that achieve. This latency is a result of both the bootstrap and the student code and the testing runtime run in isolation from execution time of the containers and is impacted greatly by each others. Containers answer this need perfectly: They the performance of the I/O subsystem. Configuring appro- allow students’ code to run in a controlled and reproducible priately the container environment and technology stack environment while reducing risks related to ill-behaved or to obtain good performance is not an easy task, due to the even malicious code. variety of options, and poor visibility on their interactions. Service latency is often the most important criteria for We present in this paper a benchmarking tool for the selecting a container execution environment. Slow response multi-parametric study of container bootstrap time and I/O times can impair the usability of an edge computing infras- performance, allowing us to understand such interactions tructure, or result in students frustration in the case of IN- within a controlled environment. -
High Velocity Kernel File Systems with Bento
High Velocity Kernel File Systems with Bento Samantha Miller, Kaiyuan Zhang, Mengqi Chen, and Ryan Jennings, University of Washington; Ang Chen, Rice University; Danyang Zhuo, Duke University; Thomas Anderson, University of Washington https://www.usenix.org/conference/fast21/presentation/miller This paper is included in the Proceedings of the 19th USENIX Conference on File and Storage Technologies. February 23–25, 2021 978-1-939133-20-5 Open access to the Proceedings of the 19th USENIX Conference on File and Storage Technologies is sponsored by USENIX. High Velocity Kernel File Systems with Bento Samantha Miller Kaiyuan Zhang Mengqi Chen Ryan Jennings Ang Chen‡ Danyang Zhuo† Thomas Anderson University of Washington †Duke University ‡Rice University Abstract kernel-level debuggers and kernel testing frameworks makes this worse. The restricted and different kernel programming High development velocity is critical for modern systems. environment also limits the number of trained developers. This is especially true for Linux file systems which are seeing Finally, upgrading a kernel module requires either rebooting increased pressure from new storage devices and new demands the machine or restarting the relevant module, either way on storage systems. However, high velocity Linux kernel rendering the machine unavailable during the upgrade. In the development is challenging due to the ease of introducing cloud setting, this forces kernel upgrades to be batched to meet bugs, the difficulty of testing and debugging, and the lack of cloud-level availability goals. support for redeployment without service disruption. Existing Slow development cycles are a particular problem for file approaches to high-velocity development of file systems for systems. -
Container-Based Virtualization for Byte-Addressable NVM Data Storage
2016 IEEE International Conference on Big Data (Big Data) Container-Based Virtualization for Byte-Addressable NVM Data Storage Ellis R. Giles Rice University Houston, Texas [email protected] Abstract—Container based virtualization is rapidly growing Storage Class Memory, or SCM, is an exciting new in popularity for cloud deployments and applications as a memory technology with the potential of replacing hard virtualization alternative due to the ease of deployment cou- drives and SSDs as it offers high-speed, byte-addressable pled with high-performance. Emerging byte-addressable, non- volatile memories, commonly called Storage Class Memory or persistence on the main memory bus. Several technologies SCM, technologies are promising both byte-addressability and are currently under research and development, each with dif- persistence near DRAM speeds operating on the main memory ferent performance, durability, and capacity characteristics. bus. These new memory alternatives open up a new realm of These include a ReRAM by Micron and Sony, a slower, but applications that no longer have to rely on slow, block-based very large capacity Phase Change Memory or PCM by Mi- persistence, but can rather operate directly on persistent data using ordinary loads and stores through the cache hierarchy cron and others, and a fast, smaller spin-torque ST-MRAM coupled with transaction techniques. by Everspin. High-speed, byte-addressable persistence will However, SCM presents a new challenge for container-based give rise to new applications that no longer have to rely on applications, which typically access persistent data through slow, block based storage devices and to serialize data for layers of block based file isolation.