Also, some of the features and options are only available in the professional version. Windows 10 is the most popular desktop OS in the world right now and Microsoft is continuing to improve it. However, there is a growing perception among users that Windows is not on par with other operating systems and the performance deteriorates over time. In this article, I will discuss the problem of fragmentation and share some easy steps to defrag Windows To understand defragmentation, we need to begin with fragmentation first.
In simple terms, fragmentation is a process of spreading data across different sectors of the hard disk. It usually happens when there is no contiguous block of memory available to store a file. In such situations, the file is split into several data chunks and spread across different blocks of the hard drive. And defragmentation is, you guessed it right, a process to bring the scattered pieces of data at one place.
Fragmentation is not much of a problem if you have an ample amount of free storage on your PC. However, when there is a space constraint, it becomes harder for the hard drive to allocate data in contiguous blocks.
The problem becomes worse when files are moved, deleted or modified from the hard drive over a long period of time. In such cases, the data is spread across different sectors of the hard drive. So we should defrag Windows 10 periodically so that chunks of files are kept closer to each other. And as a result, it will speed up your Windows PC. Of course, you should. However, Windows 10 automatically defragments the hard disk every week. Whenever Windows finds your PC is sitting idle, it runs a scheduled task in the background which defragments Windows If you want to check when was the last time your hard disk was defragmented, press Windows and R key at once and type dfrgui.
Now, hit enter. It will open the Defragmentation window. To find out the type of memory storage, open the Run window again by pressing Windows and R key. After that, type dfrgui and hit enter. Having said that, if you are not happy with the scheduled defragmentation or want to manually defrag Windows 10 then move to the next section to learn about the steps in detail.
If you want to manually defrag Windows 10 then here are the three different ways to do it. You can choose any of them based on what you find convenient. So without wasting any time, here we go. As we already know there is an inbuilt tool to defragment Windows Here, we will learn how to manually analyze the hard disk and then defragment it.
You can also configure various settings related to defragmentation. Here are the steps to do it. Open the Run window by pressing Windows and R key simultaneously. Here, type dfrgui and hit enter. The green row indicates the suggested density ratio for the table. As you can see, analysis is fast; we analyzed tables in about 10 minutes. One table has been found as a candidate for defragmentation with a suggested density ratio of 0.
Prior to Db2 If you use this new functionality, I would be very interested in hearing your feedback. Depending on the customer feedback that we get, we might want to adapt this heuristic in future versions of the program.
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Technical Articles Dirk Nakott. Currently, the most common storage type, namely a hard drive, is susceptible to fragmentation. Drive head movement requires considerable amount of time. On the other hand the "electronic" type storage devices e.
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Therefore, in a real implementation it would also be desirable to examine metadata of indirect blocks for VVBN mismatches in this way. Note that the container buffer tree for any online volume is frequently available in memory, and can be used this way to locate any moved block, even when the user buffer tree for that block is not in memory.
If the container map is in memory, it is not necessary to update the user buffer tree immediately when a block is moved during defragmentation. In fact, when that is the case, there is no need to update a user buffer tree at all to reflect a block move, for the same reason.
However, it may be desirable nonetheless to do so, at a convenient time, since having an up-to-date user buffer tree will improve read performance because it avoids the relatively time-consuming process of block location being described here. Before further discussing this technique, it is useful to discuss certain background information and to define certain terminology. In some conventional storage servers, data is stored in logical containers called volumes and aggregates.
A volume includes one or more file systems, such as an active file system and, optionally, one or more persistent point-in-time images of the active file system captured at various instances in time.
Although a volume or file system as those terms are used herein may store data in the form of files, that is not necessarily the case. That is, a volume or file system may store data in the form of other units of data, such as blocks or LUNs.
It is assumed here, to facilitate description only and not by way of limitation, that a storage system which implements the technique introduced here is capable of creating and maintaining two different types of volumes: flexible volumes and traditional volumes.
In other words, the boundaries between aggregates and flexible volumes are flexible, such that there does not have to be a one-to-one relationship between a flexible volume and an aggregate.
An aggregate can contain one or more flexible volumes. For example, the technique can be adapted for use in other types of storage systems, such as storage servers which provide clients with block-level access to stored data or processing systems other than storage servers.
Each of the clients 1 may be, for example, a conventional personal computer PC , server-class computer, workstation, or the like. The storage subsystem 4 is managed by the storage server 2. The storage server 2 receives and responds to various read and write requests from the clients 1 , directed to data stored in or to be stored in the storage subsystem 4.
The mass storage devices in the storage subsystem 4 may be, for example, conventional magnetic disks, optical disks such as CD-ROM or DVD based storage, magneto-optical MO storage, or any other type of non-volatile storage devices suitable for storing large quantities of data. In such an embodiment, the N-blade is used to communicate with clients 1 , while the D-blade includes the file system functionality and is used to communicate with the storage subsystem 4.
The N-blade and D-blade communicate with each other using an internal protocol. Alternatively, the storage server 2 may have an integrated architecture, where the network and data components are all contained in a single box.
The storage server 2 further may be coupled through a switching fabric to other similar storage servers not shown which have their own local storage subsystems. In this way, all of the storage subsystems can form a single storage pool, to which any client of any of the storage servers has access. The storage server 2 includes an operating system to control its operation, an example of which is shown in FIG.
The operating system 20 and its constituent elements are preferably implemented in the form of software. However, in some embodiments, some or all of the elements of the operating system may be implemented in the form of hardware e.
These layers include a file system manager The file system manager 21 is software that manages the one or more file systems managed by the storage server 2. In particular, the file system manager 21 imposes a hierarchy e. To allow the storage server 2 to communicate over the network 3 e. The network access layer 23 includes one or more drivers which implement one or more lower-level protocols to communicate over the network, such as Ethernet or Fibre Channel. To enable the storage server 2 to communicate with the storage subsystem 4 , the operating system 20 includes a storage driver layer 24 , and a storage access layer 25 operatively coupled between the file system manager 21 and the storage driver layer Also shown in FIG.
The file system manager 21 also includes a read handler 28 , a write allocator 29 and a segment cleaner The read handler 28 is responsible for processing client-initiated read requests.
The write allocator 29 is responsible for determining an appropriate storage destination whenever a block is written.
This may be done in response to, for example, a client-initiated write request, a RAID parity recomputation, or a defragmentation process. The segment cleaner 30 is responsible for determining which segments groups of contiguous disk blocks to move during defragmentation, as described further below. Accordingly, the segment cleaner 30 provides information on its determinations to the write allocator 29 , which decides where to place the relocated blocks.
The operating system 20 also maintains three special types of data structures used by the file system manager 21 to keep track of used and free space in the storage subsystem 4. These data structure types include an active map 31 , a free space map 32 and a summary map A separate instance of each of these three data structures is maintained for each aggregate and for each flexible volume managed by the storage server 2. The active map 31 of a volume indicates which PVBNs are currently used allocated in an active file system.
The free space map 32 indicates which PVBNs in the volume are free not allocated. A Snapshot is NetApp's implementation of a read-only, persistent, point-in-time image PPI of a data set and its associated metadata, such as a volume. An aggregate utilizes a PVBN space that defines the storage space of blocks provided by the disks in the aggregate. A PVBN, therefore, is an address of a physical block in the aggregate.
Each VVBN space is an independent set of numbers that corresponds to locations within the file, which locations are then translated to disk block numbers DBNs on disk. Since a volume is a logical not physical data container, it has its own block allocation structures e. Each file in the aggregate is represented in the form of a user buffer tree.
A buffer tree is a hierarchical structure which used to store metadata about the file, including pointers for use in locating the blocks for the file. An inode is a metadata container which used to store metadata about the file, such as ownership of the file, access permissions for the file, file size, file type, and pointers to the highest level of indirect blocks for the file.
Each file has its own inode, and each inode is stored in a corresponding inode file for the volume. Each inode file is also represented as a buffer tree, where each direct block of the inode file's buffer tree is an inode. The file is assigned an inode , which in the illustrated embodiment directly references Level 1 L1 indirect blocks To simplify description, FIG.
However, the storage server 2 may allow three or more levels of blocks below the inode , i. Each PVBN identifies a physical block in the aggregate itself which may be a direct or indirect block and the corresponding VVBN identifies the logical block number of that block in the volume. Note that the PVBN and VVBN in any given index both refer to the same block, although one is a physical address and the other is a logical address.
The inode and indirect blocks in FIG. A container buffer tree can have a structure similar to the tree structure of a user file, as shown in FIG. Every block in a container file represents one VVBN for the flexible volume that the container file represents. The container buffer tree also has an inode, which is assigned an inode number equal to a virtual volume id VVID.
The container file is typically one large, sparse virtual disk, which contains all blocks owned by the volume it represents. An FBN of a given block identifies the offset of the block within the file that contains it.
Since each volume in the aggregate has its own distinct VVBN space, one container file in the aggregate may have an FBN that is different from FBN in another container file in the aggregate. Referring again to FIG. Thus, a separate inode file is maintained for each file system within each volume in the storage system. Note that each inode file is itself represented as a buffer tree although not shown that way in FIG. Each inode in an inode file is the root of the user buffer tree of a corresponding file.
The FSInfo block contains metadata for the file system rather than for individual files within the file system.
An aggregate is also represented in the storage server as a volume. Consequently, the aggregate is assigned its own superblock, which contains metadata of the aggregate and points to the inode file for the aggregate. The inode file for the aggregate contains the inodes of all of the flexible volumes within the aggregate, or more precisely, the inodes of all of the container files within the aggregate.
Hence, each volume has a structure such as shown in FIG. As such, the storage system implements a nesting of file systems, where the aggregate is one file system and each volume within the aggregate is also a file system. As a result of this structure and functionality, every direct L0 block within a flexible volume is referenced by two separate buffer trees: a user buffer tree the buffer tree of the file which contains the block and a container buffer tree the buffer tree of the container file representing the volume which contains the block.
Note that version 7. The process of FIG. A consistency point is the recurring event at which any new or modified data that has been temporarily cached in the storage server's memory is committed to long-term storage e.
A consistency point typically occurs periodically e. Referring now to FIG.
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