I had some doubts regarding an Inode vs a Vnode. As far as my understanding goes, inode is the representation of a file that is used by the Virtual File System. Whereas vnodes are file system specific. Is this correct?
Also, I am confused whether inode is a kernel data structure i.e whether it is an in-memory data structure or a data structure that exists on blocks in an actual disk?
To add something to this: The best explanation I could find for a vnode is here on the FreeBSD docs. For the more academically minded there is also the original paper that introduced the concept, [Vnodes: An Architecture for Multiple File System Types in Sun UNIX], which provides a much more in depth resource.
That said vnodes were originally created for FreeBSD because of the proliferation of different types of filesystems that needed to be used like UFS, NFS, etc. Vnodes are meant to provide an abstraction across all possible filesystems so that the OS can interface with them and so that kernel functions don't have to specifically support every filesystem under the sun; they only have to have knowledge of how to interact with the file's vnode.
Back to your original question vnodes, as #Allen Luce mentioned, are in memory abstractions and are not filesystem specific. They can be used interchangeably in UFS, ext4, and whatever else. In contrast, inodes are stored on disk and are specific to the exact filesystem being used. inodes contain metadata about the file like size, owner, pointers to the block addresses among other things. Vnodes contain some data about the file but only attributes that do not change over the file's lifetime so an inode would be the location to reference if you wanted the most information possible about a file. If you're more interested in inodes I would suggest you check out wikipedia which has a good article on them.
Typically (like for Linux and BSD mainstream filesystems), an inode is first an on-disk structure that describes the storage of a file in terms of that disk (usually in blocks). A vnode is an in-memory structure that abstracts much of what an inode is (an inode can be one of its data fields) but also captures things like operations on files, locks, etc. This lets it support non-inode based filesystems, in particular networked filesystems.
It depends on your OS. On a Linux system for instance there is no v-node, only a generic i-node struct inode which although is conceptually similar to a v-node is implemented differently.
For BSD-derived and UNIX kernels, the v-node points to an i-node structure specific to the filesystem, along with some additional information including pointers to functions that operate on the file and metadata not included in the inode. A major difference is the inode is files system while the vnode is not. (In Linux as mentioned above there is both a system-independent inode and a file system-dependent inode)
An inode is not a kernel data structure, the vnode/generic inode is however, being an in-kernel representation of the inode.
The concept of vnode differs to a degree depending on what system you're under, everyone just kind of took the name and ran with it.
Under Linux and Unix, you can consider the abstraction as follow.
Suppose there exists
f.tmp
You want f to stick around while your program is running, because you're accessing it, but if your program ends or crashes, you want to be sure it goes away.
You can do this by opening f, and then unlink() it. You will still retain a reference to f, even though its inode now has 0 directory entries, and so has been marked free. The operating system is still retaining where the file started and its allocation state, until your program ends. This "virtualization" of the inode that no longer exists is a vnode.
Another common situation for this is when you're reading a resource that disappears out from under you. Suppose you're watching a movie, while it is streaming to a temporary location. When the movie is completely downloaded, it will be relocated to another volume for storage. Somehow you can continue watching and scrubbing through the movie so long as it remains open. In this case even though there are again no links, since there is a vnode, this inode can't be cleaned up yet.
This depends on the operating system and the file system you are using or working on. For instance VXFS and ADVFS inode's are nothing but on-disk data structure called vnode's. In general both refer to file metadata.
Simply put, the in-memory data structure vnode is just an inode cache that stores information about
the file(typically inode stores in the disk) so that it can be accessed more quickly.
Related
I am building two operating systems for IoT. The Libertas OS and Hornet OS.
The data APIs are designed to be append-only time series. fsync() is required after each append of byte block to ensure data safety.
The storage could be emmc, SSD, or sdcard. The question is, which filesystem is a better fit for different storage types?
I understand f2fs is designed as append-only. But what about EXT4? Couldn't easily find information about it.
Theoretically, at least for file content, the append shall continue writing on the current underlying block to minimize wearing. Since the file size is changed after append, the file meta-data shall be updated, ideally through append-log.
I also don't know the details of the internal controller of sdcard and emmc, will the controller honor such block level append?
Any insight will be greatly appreciated!
According to code segments below, PostgreSQL (the version is REL_13_STABLE) seems to use inversion to describe large object, but I don't understand the meaning of "inversion", or why they are using "inversion" to describe large object.
/*
* Read/write mode flags for inversion (large object) calls
*/
#define INV_WRITE 0x00020000
#define INV_READ 0x00040000
Inversion stems from the inversion file system, an academic idea from the PostgreSQL ecosystem at the University of Berkeley. Read the original paper fir illustration:
Conventional file systems handle naming and
layout of chunks of user data. Users may move
around in the file system’s namespace, and may typically examine a small set of attributes of any given
chunk of data. Most file systems guarantee some
degree of consistency of user data. These observations make it possible to categorize conventional file
systems as rudimentary database systems.
Conventional database systems, on the other
hand, allow users to define objects with new attributes, and to query these attributes easily. Consistency guarantees are typically much stronger than
in file systems. Database systems frequently use an
underlying file system to store user data. Virtually
no commercially-available database system exports a
file system interface.
This paper describes the design and implementation of a file system built on top of a database system. This file system, called “Inversion” because
the conventional roles of the file system and database system are inverted, runs on top of POSTGRES
[MOSH92] version 4.0.1. It supports file storage on
any device managed by POSTGRES, and provides useful services not found in many conventional file systems.
(The emphasis is mine.)
It seems that (inversion) large objects were originally intended as the basis for a file system implementation.
I havea question regarding mmap functionality. when mmap is used in asynchronous mode where the kernel takes care of persisting the data to the mapped file on the disk , is it possible to have the former updates overwrite the later updates ?
Lets say at time T, we modify a location in memory that is memory mapped to a file on disk and again at time T+1 we modify the same location in memory. As the writes to the file are not synchronous, is it possible that kernel first picks up the modifications at time T+1 and then picks up the modifications at time T resulting in inconsistency in the memory mapped file ?
It's not exactly possible. The file is allowed to be inconsistent till msync(2) or munmap(2) - when that happens, dirty (modified) pages are written to disk page by page (sometimes more, depends on filesystem in newer kernels). msync() allows you to specify synchronous operation and invalidation of caches after finished write, which allows you to ensure that the data in cache is the same as data in file. Without that, it's possible that your program will see newer data but file contains older - exact specifics of the rather hairy situation depend on CPU architecture and specific OS implementation of those routines.
Many file storage systems use hashes to avoid duplication of the same file content data (among other reasons), e.g., Git and Dropbox both use SHA256. The file names and dates can be different, but as long as the content gets the same hash generated, it never gets stored more than once.
It seems this would be a sensible thing to do in a OS file system in order to save space. Are there any file systems for Windows or *nix that do this, or is there a good reason why none of them do?
This would, for the most part, eliminate the need for duplicate file finder utilities, because at that point the only space you would be saving would be for the file entry in the file system, which for most users is not enough to matter.
Edit: Arguably this could go on serverfault, but I feel developers are more likely to understand the issues and trade-offs involved.
ZFS supports deduplication since last month: http://blogs.oracle.com/bonwick/en_US/entry/zfs_dedup
Though I wouldn't call this a "common" filesystem (afaik, it is currently only supported by *BSD), it is definitely one worth looking at.
It would save space, but the time cost is prohibitive. The products you mention are already io bound, so the computational cost of hashing is not a bottleneck. If you hashed at the filesystem level, all io operations which are already slow will get worse.
NTFS has single instance storage.
NetApp has supported deduplication (that's what its called in the storage industry) in the WAFL filesystem (yeah, not your common filesystem) for a few years now. This is one of the most important features found in the enterprise filesystems today (and NetApp stands out because they support this on their primary storage also as compared to other similar products which support it only on their backup or secondary storage; they are too slow for primary storage).
The amount of data which is duplicate in a large enterprise with thousands of users is staggering. A lot of those users store the same documents, source code, etc. across their home directories. Reports of 50-70% data deduplicated have been seen often, saving lots of space and tons of money for large enterprises.
All of this means that if you create any common filesystem on a LUN exported by a NetApp filer, then you get deduplication for free, no matter what the filesystem created in that LUN. Cheers. Find out how it works here and here.
btrfs supports online de-duplication of data at the block level. I'd recommend duperemove as an external tool is needed.
It would require a fair amount of work to make this work in a file system. First of all, a user might be creating a copy of a file, planning to edit one copy, while the other remains intact -- so when you eliminate the duplication, the hard link you created that way would have to give COW semantics.
Second, the permissions on a file are often based on the directory into which that file's name is placed. You'd have to ensure that when you create your hidden hard link, that the permissions were correctly applied based on the link, not just the location of the actual content.
Third, users are likely to be upset if they make (say) three copies of a file on physically separate media to ensure against data loss from hardware failure, then find out that there was really only one copy of the file, so when that hardware failed, all three copies disappeared.
This strikes me as a bit like a second-system effect -- a solution to a problem long after the problem ceased to exist (or at least matter). With hard drives current running less than $100US/terabyte, I find it hard to believe that this would save most people a whole dollar worth of hard drive space. At that point, it's hard to imagine most people caring much.
There are file systems that do deduplication, which is sort of like this, but still noticeably different. In particular, deduplication is typically done on a basis of relatively small blocks of a file, not on complete files. Under such a system, a "file" basically just becomes a collection of pointers to de-duplicated blocks. Along with the data, each block will typically have some metadata for the block itself, that's separate from the metadata for the file(s) that refer to that block (e.g., it'll typically include at least a reference count). Any block that has a reference count greater than 1 will be treated as copy on write. That is, any attempt at writing to that block will typically create a copy, write to the copy, then store the copy of the block to the pool (so if the result comes out the same as some other block, deduplication will coalesce it with the existing block with the same content).
Many of the same considerations still apply though--most people don't have enough duplication to start with for deduplication to help a lot.
At the same time, especially on servers, deduplication at a block level can serve a real purpose. One really common case is dealing with multiple VM images, each running one of only a few choices of operating systems. If we look at the VM image as a whole, each is usually unique, so file-level deduplication would do no good. But they still frequently have a large chunk of data devoted to storing the operating system for that VM, and it's pretty common to have many VMs running only a few operating systems. With block-level deduplication, we can eliminate most of that redundancy. For a cloud server system like AWS or Azure, this can produce really serious savings.
I know that in Unix (specifically, Mac OS X) the superblock stores information about the layout of data on the disk, including the disk addresses at which the inodes begin and end. I want to scan the list of inodes in my program to look for deleted files. How can I find the disk address at which the inodes begin? I have looked at the statfs command but it does not provide this information.
Since you mention Mac OS X, let's assume you mean to do this for HFS+ only. The Wikipedia page provides some information about possible ways to start, for instance it says this about the on-disk layout:
Sectors 0 and 1 of the volume are HFS boot blocks. These are identical to the boot blocks in an HFS volume. They are part of the HFS wrapper.
Sector 2 contains the Volume Header equivalent to the Master Directory Block in an HFS volume. The Volume Header stores a wide variety of data about the volume itself, for example the size of allocation blocks, a timestamp that indicates when the volume was created or the location of other volume structures such as the Catalog File or Extent Overflow File. The Volume Header is always located in the same place.
The Allocation File which keeps track of which allocation blocks are free and which are in use. It is similar to the Volume Bitmap in HFS, each allocation block is represented by one bit. A zero means the block is free and a one means the block is in use. The main difference with the HFS Volume Bitmap, is that the Allocation File is stored as a regular file, it does not occupy a special reserved space near the beginning of the volume. The Allocation File can also change size and does not have to be stored contiguously within a volume.
It becomes more complicated, after that. Read up on B* trees, for instance.
I'm no Mac OS user, but it would surprise me if there weren't already tools written to scan for deleted files, perhaps some are open source and could provide a more concrete starting point?
You'll have quite some trouble to find deleted files because there's not much left on the disk to find when you delete a file.
If you delete a file on a FAT (or UDF) file system, its directory entry simply gets marked as "deleted", with most of the dir entry still intact.
On HFS volumes, due to their use of B-Trees, deleted edits must be removed from the directory or else searching for items wouldn't work any more efficiently (well, this argument may be a bit weak, but fact is that deleted entries get removed and overwritten).
So, unless the deletion took place by writing over a directory sector by accident, or by re-initializing the volume, you'll not find much.