Fair sampling in a hierarchical filesystem

Information

  • Patent Grant
  • 11461286
  • Patent Number
    11,461,286
  • Date Filed
    Tuesday, January 13, 2015
    9 years ago
  • Date Issued
    Tuesday, October 4, 2022
    2 years ago
  • CPC
  • Field of Search
    • US
    • 707 751000
    • CPC
    • G06F17/30221
    • G06F17/30368
    • G06F9/467
    • G06F17/30
    • G06F16/2358
    • G06F16/185
  • International Classifications
    • G06F16/185
    • G06F16/23
    • G06F9/46
    • Term Extension
      4
Abstract
A software and hardware facility persistently maintains metrics on directories at different levels within a tree of a filesystem. The facility hierarchically aggregates attributes of files contained by directories and stores them as metric values in inode date of each directory within a tree. The stored metric values represent summed or otherwise aggregated data from the descendant directories and files. The metric values are utilized to provide representative compositional samplings of data in the filesystem tree structure. Based on the metric value in its inode data, each directory is weighted in a manner that determines the likelihood that each file sample is taken from that directory.
Description
TECHNICAL FIELD

The described technology is directed to the field of filesystems.


BACKGROUND

The demand for scalable storage resources and the ability to provide rapid access to content stored thereby is a key concern to end-users. Enterprises, businesses, and individuals alike now use large scale filesystems to store data that is remotely accessible via a network. Such filesystems are often accessible via closed (e.g., enterprise) and open (e.g., Internet) networks and allow concurrent access via multiple client devices. Various implementations of large scale filesystems relying on network access have been developed. The primary differences between such filesystems are (1) that they use different protocols for the client devices and servers to communicate to read and write data and (2) that the data and corresponding metadata are stored in different ways.


For some filesystems, the protocol provides access to end-users by implementing APIs through a network, while others are specific to operating systems. Some such operating systems include default programs which may be called to synchronously determine and display filesystem information to an end-user. For example, Unix includes a .du program which return file space usage of a directory.


Users benefit from knowing the amount of storage resources as well as the allocation of those resources to various portions of the filesystem, such as directories, sub-directories, and files in a filesystem hierarchy, in order to facilitate management of the filesystem. For example, administrators can allocate system resources to frequently accessed nodes and can determine if additional storage capacity is required.


Systems administrators find useful various kinds of filesystem queries. For example, on system administrator may wish to generate a list of all files created in the past hour.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 shows an environment in which the facility operates.



FIG. 2 is a block diagram illustrating a cluster of storage devices operated by the facility.



FIG. 3 is an abstraction level diagram of the facility.



FIG. 4 shows a sample filesystem tree of filesystem objects.



FIG. 5 shows a representative view of the contents of a filesystem object.



FIG. 6 shows a tree structure indicating a size attribute for a filesystem object and an aggregate size metric value for the filesystem object and descendent filesystem objects in a subtree of the filesystem object.



FIG. 7A shows a tree structure indicating rank attributes, capacity usage (cap_usage) attributes and corresponding reconciled and unreconciled to parent metric values for each directory in that tree.



FIGS. 7B-7E shows the tree structure of FIG. 7A and a dirty list for updating the reconciled and unreconciled to parent metric values in each directory of the tree.



FIG. 8 shows a tree structure indicating weighted metadata for sampling.



FIG. 9 is a display diagram showing an interactive GUI provided by the facility that indicate metric values for directories of a filesystem hierarchy.



FIGS. 10A-10C are display diagrams showing different directory levels selectable through an interactive GUI provided by the facility that indicate metric values for directories of a filesystem hierarchy.





DETAILED DESCRIPTION

The inventors have recognized that conventional filesystems incur significant latency in aggregating metadata attributes of files to obtain hierarchical aggregate metric values (“metric values”) that provide a user with visibility into the filesystem. Traditionally, in tree-structured filesystems, in order to satisfy a request for metrics for a subtree of the filesystem, it has been necessary to systemically and recursively traverse an entire subtree in response to the request. The tree-structured filesystems discussed herein comprise a hierarchical tree of filesystem objects—directories and files—that include a root directory. Each filesystem object contains inode data that includes filesystem administration information. The filesystem object may be directly accessed by the filesystem via filesystem path or address, and the data contained in the inode data may be used by the filesystem to manage the hierarchy.


For example, if a user wants to know how much storage capacity is available in a particular user space, such as in a subtree of the filesystem hierarchy contained by a directory, a conventional filesystem must synchronously aggregate a file size metadata attribute value for each file in each filesystem object in the subtree to return the aggregated value to the user. In another example, if the user wants to know how much storage is dedicated to .crw files in the filesystem, conventional filesystems must synchronously check each file's type and aggregate the size of each that is a .crw file. Not only is does this create an imbalance in system performance, but it imposes a high cost in terms of number of I/O operations. More importantly, it may take hours to return the requested value to the user, depending on the size of the filesystem and its hardware components.


In addition, for conventional filesystems in which numerous users concurrently access the files, the returned values may fail to reflect any modifications to data that occur during the slow scan. Using the prior example, a second user may access the system and delete 2 TB (terabytes) of .crw files in a particular directory. However, if the scan accesses the directory containing those files prior to the deletion and returns the result subsequent to the deletion, that result is inaccurate and will fail to reflect the modified data.


To avoid latency, performance fluctuations, increased I/O costs, and other issues, the inventors have determined that it is desirable to maintain for each directory in a filesystem tree, persistent hierarchical aggregates “metric values” for file attributes of the filesystem objects contained by the subtree defined by that directory. Accordingly, a request for such metrics for a particular subtree can be satisfied without exhaustively traversing each level of the subtree of the filesystem tree structure in response.


A software and hardware facility described herein (“the facility”) addresses these issues by persistently maintaining metrics on directories at different levels within a filesystem tree. The facility may operate with respect to a distributed or monolithic filesystem, such as one maintained by a number of networked nodes in a cluster. In particular, in some embodiments, the facility aggregates attributes of filesystem objects and stores them as metric values in each directory within a tree. In some embodiments, the values stored in a directory represent data summed or otherwise aggregated from filesystem objects contained by an entire subtree of filesystem objects—directories and files—defined by that directory. In some embodiments, the metric values may represent such measures as total space consumed by a filesystem object and all the descendant objects, total number of files within an filesystem object, total data blocks used by a filesystem object and its descendant filesystem objects (if any), etc.


In some embodiments, the metrics stored in a directory containing no other directories is determined by performing an aggregation or other logical operation on attributes of the files contained by the directory. In some embodiments, the metrics stored in other directories are each determined by performing an aggregation or other logical operation on the attributes of the files contained by the directory itself, further aggregated with the corresponding metrics of the child directories. For example, metric values may provide: a most recently accessed filesystem object including all its descendant objects, a most frequently accessed filesystem object in a tree or subtree, a largest filesystem object in set of objects in a tree or subtree, and the like.


By performing in some or all of the ways described above, the facility enables rapid access to metric values based on file attributes and aggregates stored at various levels in the filesystem. Because the metric values for those attributes are maintained in each directory and are updated frequently, the facility typically does not need to traverse significant portions of the filesystem tree in order to determine corresponding metric value.



FIG. 1 illustrates an environment 100 in which the facility may operate. For example, a filesystem may communicate over a network 106, such as the Internet, with computing systems, e.g., clients 102, through a secondary network. In particular, the user executes a browser program on a client in order to display the contents of a user interface which may be used to generate and execute requests to access the facility, e.g., filesystem 110. In some embodiments, a secondary network may include an enterprise network, wireless network, or home network on which the client is operating. Any number of proxy servers or gateway devices may be additionally included in the communication path between the facility 110 and the client 102, though not specifically shown in the illustrated environment. In various embodiments, a variety of computing systems or other devices may be used as a client computer systems, such as mobile phones, personal digital assistants, tablet computers, etc.


In various embodiments, the facility includes computer systems and devices including zero or more of each of the following: a central processing unit (“CPU”) for executing computer programs; a computer memory for storing programs and data while they are being used, including the facility and associated data, an operating system including a kernel, and device drivers; a persistent storage device, such as a hard drive or flash drive for persistently storing programs and data; a computer-readable media drive, such as a floppy, CD-ROM, or DVD drive, for reading programs and data stored on a computer-readable medium; and a network connection for connecting the computer system to other computer systems to send and/or receive data, such as via the Internet or another network and its networking hardware, such as switches, routers, repeaters, electrical cables and optical fibers, light emitters and receivers, radio transmitters and receivers, and the like.


While computer systems configured as described above are typically used to support the operation of the facility, those skilled in the art will appreciate that the facility may be implemented using devices of various types and configurations, and having various components. Furthermore, while various embodiments are described in terms of the environment described above, those skilled in the art will appreciate that the facility may be implemented in a variety of other environments including a single, monolithic computer system, as well as various other combinations of computer systems or similar devices connected in various ways.



FIG. 2 is a block diagram of cluster 200 in a distributed filesystem in which numerous storage devices may be networked together for use in connection with the facility. One or more storage devices additionally may be coupled together in groups, forming nodes (e.g., Node 1202, Node 2206, Node 3212, Node 4220) within the facility. Each node within the cluster 300 has a particular address, or path name accessible via the network filesystem protocol, an instance of which is included on each node. Accordingly, each node in the cluster 200 typically includes one or more computer processors or controllers and data storage devices such as hard disks, solid state disk drives, or similar computer readable storage or memory devices. For example, a node may include one or more server computers themselves, contained by such components. Each of the data storage devices (e.g., disc1204, disc2208, etc.) within a node may store data in blocks, the stored data corresponding to files contained by filesystem object data of the hierarchical tree structures implemented by the facility.



FIG. 3 illustrates abstraction layers provided by the facility in some embodiments. For example, the layers can include an application layer, an operating system layer (OS) that includes a host (local) filesystem, an address abstraction layer that includes a protection/volume 310 (e.g., a protected storage unit) referenced by the local filesystem 308 and a kernel layer that translates requests from the OS layer and an address provided by the address layer.


The application layer of the facility exposes an instance of a web application programming interface (API) 302 (e.g., REST), a network filesystem protocol 304 (NFS), and an application layer network protocol 306 (e.g., SMB). The NFS protocol 304 is an application level protocol used to access the facility over a network, such as the Internet. The application layer network protocol 306 may be used to communicate with other nodes in the facility, accessible by the NFS 304. In some embodiments, the application layer includes protocols such as http, ftp, scp, rsync, afp, afs, or any other application layer protocol capable of providing network-level access to the facility. Any of the aforementioned protocols are considered reasonable variations to the illustrated protocols and may be used in addition to or in place of those protocols.


An OS layer implements a core filesystem 308. To access stored data, the core filesystem 308 references a location (e.g., in a protected storage unit) which is used by the address abstraction layer to retrieve the requested data. Accordingly, the address abstraction layer can include a data storage map 312 that links the referenced location to a particular node and associated disc (e.g., see FIG. 2) on which the requested data is stored.


The facility also includes the kernel layer that translates the filesystem call (for the requested data) into instructions for hardware components. The hardware components may be located in a hardware layer and may include a plurality of storage devices 315 (e.g., disc1, disc2, disc3) that can be distributed across multiple storage nodes.


In some embodiments, the facility manages metric requests for filesystem objects through the web API 302. These requests are stateless in order to account for various platforms on which filesystem may be implemented. Accordingly, calls made from a client device, such as devices 102 in FIG. 1, can request a metric value to be retrieved for one or more filesystem objects stored by the facility. Exemplary metric value requests in some embodiments are provided in the following table:















capacity_usage
total blocks used for file data (not metadata)


moving_capacity_usage
moving sum of capacity_usage



(exponentially decayed, 60 minute lifetime)


num_directories
total directory count under the filesystem



object


num_files
total file count under the filesystem object


num_input_operations
total number of write operations on files


moving_input_operations
moving sum of num_input_operations



(exponentially decayed, 60 minute lifetime)









Each of the metric requests within the table typically returns a value indicating an aggregate value of attributes for a collection of files contained by a directory within the facility. In some embodiments, the metric requests return integer values for aggregated attributes of a file in the facility. The capacity usage and the moving capacity usage may be in units of bytes and, in some embodiments, include 4096-byte data blocks. Some of the metrics maintained by the facility are aggregations on filesystem object attributes of types other than integer. For example, in some embodiments, the facility maintains a recent access (“raccess”) time metric based on applying a latest( )aggregation function to an access time (“atime”) attribute maintained for each descendant filesystem object. In some embodiments, the metrics are checksums.


When a metric request from a client is received for data stored by the facility, the request is eventually received at a node within the cluster. For example, the request may be received through a REST_API 302 on a REST server (not shown), which is interfaced with the local filesystem 308. The facility retrieves the requested data, such as a metric value, from a particular disc 315 on a node, provided at the address (312) reference by the filesystem 308, and then returns the requested data to the client. In some embodiments, individual metric values for a single filesystem object may be returned. When a request is received for a directory having child directories, all metric values for the entire subtree defined by the directory are returned in response to a single request from a client in some embodiments. The client can parse the values in the response message in order to identify and display a specific metric value for a particular filesystem object to the user. In various embodiments, the response message is formatted in JavaScript Object Notation (JSON), extensible markup language (XML), or other data exchange language.


In some embodiments, the initial request call (e.g., GET, PUT, POST, DELETE) from a client may include a plurality of parameters for the value of the metrics in the response. For example, in one parameter the client is able to indicate a maximum number of “directory entries” to return for a filesystem object. The directory entries may include metric values for the directory and any descendant directories or files, such as those within aa subtree defined by the directory. The returned values may include an aggregate values for the directory as well as any descendant directories. In another parameter, the client is able to provide an order to sort the returned directory entries for the directory. The order may be based on a retrieved metric value determined by aggregating an attribute of one or more files contained by the directory and any descendant directories. For example, the client may select to sort the returned directory entries based on the storage capacity used (e.g. the number of blocks in the facility) by that filesystem object and descendent objects. This parameter mainly pertains to sorting the directory entries corresponding to descendant directories of the requested directory since the requested directory includes the aggregate value of blocks used by each returned directory entry. Additional parameters may include.



FIG. 4 is a hierarchical tree-structure 400 representative of hierarchical data storage in the facility. The tree 400 includes filesystem objects 402, 404, 406, 408, 410, 412, and 414, including a root directory 402. As previously mentioned, a filesystem object can be a directory or a file. Each filesystem object 402, 404, 406, 408, 410, 412, and 414, in a tree typically stores and maintains a relatively current version of attributes and metadata for that filesystem object.


In particular, each filesystem object that is a directory 402, 404, 406, 408, 410, and 412 contains metadata and other data unique to the directory which characterizes files in that directory. The other unique data includes metric values of aggregated attributes for each file in, or “contained” by, the directory, along with information viable to access the contents of each of those files.


Each filesystem object that is a file 414 in the filesystem tree also contains metadata and one or more attributes characterizing that file, which may be aggregated and stored as a metric value in the directory under which that file is located in the filesystem tree. The metadata, aggregated values and other attributes may be stored in an inode portion of the filesystem object, which is later discussed with reference to FIG. 5. In some embodiments, the aggregated values for an individual file are stored in the directory entry pointing to that file. In some cases this is useful, for example, to accelerate operations that parse aggregate values for each entry in a directory.



FIG. 5 illustrates an example linear view of the contents stored in a filesystem object 500. The filesystem object 500 can be stored in a data structure and can be of variable size. Each filesystem object 500 in the facility includes inode data 510 stored in one or more blocks at a particular filesystem location and file or directory data 512 stored at a corresponding filesystem location. Though the inode data is described as being stored both adjacent to and separate from the corresponding file or directory data 512, this inode data can be stored in association with any directory or file in any on-disc format and in any type of filesystem. In some embodiments, for filesystem objects that are directories, the directory data 512 contains a directory map data structure identifying each filesystem object contained by the directory by its name and inode number. For filesystem objects that are files, the file data 512 contains an extent list data structure identifying the disc blocks containing the file contents by the filesystem addresses usable to locate those blocks. In some embodiments, the facility also maintains a global data structure for mapping inode numbers from each inode in the filesystem tree to the filesystem location at which the corresponding inode data is stored. In some embodiments, the facility may store a copy of this global data structure on each node (e.g., in FIG. 2).


For filesystem objects which are directories, the inode data 510 includes both the attributes of the associated directory and current metric values of aggregated attributes for each filesystem object contained by that directory. For example, the inode portion of a directory corresponding to the directory's attributes includes data such as an owner, permissions, number of links to the directory, the size of the directory in bytes or blocks (my_cap_usage), file count in the associated directory (my_num_files), most recent access time (atime), minimum access time, number of times accessed, creation time, modification time, and change (edit) time. The inode portion of the directory corresponding to the aggregate metric values includes data such as, for example, total number of files in and contained by the directory (num_files), total block usage by the directory and files contained by that directory (capacity_usage), total number of directories contained by the directory (num_directories), and various other metrics within the scope of the art. In some embodiments, the inode data also includes metric values corresponding to the Input/Output (I/O) operations performed on the associated directory (or any filesystem object contained therein) and the resource consumption to perform those operations. In some embodiments, the operations include a number of accesses, number of disk actions for accesses, number of memory accesses for accesses, and number of blocks consumed.


For filesystem objects which are files, the inode data 510 may indicate file attributes such as a last access date (file_access), a name (file_name), a type (file_type), and a size (file_size). The file access time may include a date and/or timestamp indicating the last time the file was accessed by a client. The file type may indicate the format in which the file is stored. The file size may indicate the number of bytes, kilobytes or data blocks used to store the file.


The aggregate metrics stored in the inode data for each filesystem object reflect a current state of the files or file contained by that filesystem object, including the corresponding attributes of those files. The aggregate metrics stored in the inode data for each directory also include aggregated values for file attributes of each file contained by that directory. Accordingly, each time that a file contained by a directory or descendant directory of that directory changes, the aggregate metrics in the inode data of the directory are also timely updated to reflect those changes. For example, to reflect the current state of attributes for files contained in a directory of a filesystem tree, the metric values stored in the inode data may be updated (i.e., reconciled) each time that an change is made to a file in that filesystem tree. Accordingly, there are times when updates to one directory or file may not be immediately reflected in all of that directory or file's ancestors. If the updates have not been applied to a particular ancestor directory, the unreconciled data for that directory is reflected in a descendant filesystem object from where the change originated. If the updates have been applied to that directory, an unreconciled value and reconciled value in the descendant filesystem object from where the change originated can reflect it. For example, in some embodiments, if the unreconciled value and reconciled value are equal, this indicates that the metric values in the parent directory's inode data fully reflect the filesystem object's metrics. Maintaining knowledge of whether the attributes for a filesystem object are current or not can provide additional visibility into that filesystem tree. Accordingly, a reconciled value and an unreconciled value corresponding to each attribute in a directory may be stored in the inode data. In some embodiments, the metric values for any given directory are not returned to a client if a descendant directory indicates that there is unreconciled data requiring an update in that directory.


Each change or update to an individual file in a filesystem tree is reflected in the changes to the attributes stored in the inode data of that filesystem object and in any ancestor directories with which that filesystem object may be associated. This updating may be performed up the filesystem tree until the metric values corresponding the changed attribute stored in the root directory's inode data are updated. In some embodiments, the facility asynchronously updates each filesystem object with respect to a received change or alteration to a file stored in the filesystem tree. In some embodiments, the facility systematically traverses the filesystem tree to update each filesystem object. In some such embodiments, the facility continuously updates filesystem objects in a filesystem tree to reflect changes to any file or directory contained in that filesystem tree. As previously mentioned, in some embodiments, the filesystem objects in the filesystem tree are synchronously updated with respect to received changes or alterations to files stored in those filesystem trees. So, updates to filesystem objects in the facility may only be performed each time a change to a filesystem object is received for that respective tree. Various other methods for determining when to update filesystem objects and corresponding inode data stored in those filesystem objects are further discussed with reference to FIGS. 6-7D.


In some embodiments, the inode data 510 includes a value of a metric unreconciled to a parent directory, such as an unreconciled to parent block count and reconciled to parent block count which, when equal, indicate that all updates to the parent directory containing that filesystem object are current.


For example, if an attribute of a file (e.g., file_size) is updated in response to changes made to that file, then the updated file_size attribute will also need to be reflected in the metric corresponding to that file_size attribute in the parent directory and in any ancestor directory of that file. To indicate when the updated attribute is not yet reflected in the corresponding metric of the parent directory, a value of the metric unreconciled in the parent directory indicates a different value than the metric reconciled to parent directory. Each attribute of the file for which a metric value is stored in a parent directory can maintain these unreconciled to parent and reconciled to parent values. When these values differ, it indicates to the facility that the parent directory of that file needs to be updated by the difference between the values during a subsequent I/O operation.


In some embodiments, the facility maintains a separate “list” of filesystem objects having unreconciled data in a filesystem tree instead of, or in addition to, indicating the value of the unreconciled to parent data in the inode data of each filesystem object. In some embodiments, the facility maintains this separate list in volatile memory. Maintaining this list and performing a reconciliation process due to block count, or other attribute changes in a filesystem object, are further discussed with reference to FIGS. 7A-7E.


Referring back to FIG. 5, in some embodiments, the inode data and the second portion of the filesystem object data can be stored at specific location in a block storage unit used to store the filesystem object. For example, in some embodiments, the facility can store a pointer to that specified storage location to obtain the requested data. The filesystem object data includes data such as the payload or actual file data for that filesystem object. For example, in a directory, the data may include information pertaining to the files contained by that directory, such as the file paths and paths to any child directories. Accordingly, the directory data includes information for each file accessible via that directory and the location of the file. Each file contained by a directory may be included in various other directories in the facility as well. For example, as shown in FIG. 4, directory /A 404 defines a subtree made up of directories /A 404, /B 408, /E 410, each of which may contain various data files. The filesystem object for directory /A 404 therefore may store inode data having aggregated values for each of the files contained by /A, /B, and /E, and directory data including paths for each of those files. Any additional file-related or directory-related data within the scope of the present disclosure may also be stored in the second portion of the filesystem object.



FIG. 6 illustrates an example subtree 600 of filesystem objects including at least one attribute and associated metric value for each filesystem object in that subtree. The subtree is defined by a directory /A 602. The subtree 600 may be located in a larger filesystem tree structure, such as the filesystem tree 400 shown in FIG. 4, which is defined by the root directory “I” 402. In the illustrated embodiments of FIG. 6, each filesystem object includes three values. The my_num_files 604 value of “1” in directory /A 602, is an attribute indicating a number of files contained by that particular directory (local file count). The second two values, represented in an ordered pair 616, indicate a reconciled and an unreconciled metric value [reconciled, unreconciled] for that attribute (num_files) in a parent directory (e.g., “/” in FIG. 4) of directory /A 602. In the ordered pair 616, the right value is a value of that metric that is unreconciled in the parent directory [1,000,009, 1,000,009] and the left value is a value of the metric that is reconciled in the parent directory [1,000,009, 1,000,009]. This ordered pair indicates whether the metric value in the parent of the filesystem object (e.g., directory /A 602) fully reflects any updates to that attribute (num_files) in any descendant filesystem object. In FIG. 6, since both metric values 616 in the ordered pair are equal, the corresponding metric in the parent directory (e.g., “/” in FIG. 4) fully reflects the updated metric value.


In FIG. 6, the num_file metric value is a hierarchical aggregate of the number of files (num_files) contained by each descendant directory (e.g., /B 608, /C 610) of that directory (/A 602) and any files directly contained by the directory itself (aggregate file count). For example, in the illustrated embodiment, a metric value (not shown) for the num_files attribute in directory /A 602 is “1,000,009”. This metric value includes the aggregate values of my_num_files in each descendant directory (e.g.,“1,000,003” for /B 608, “5” for /C 610), which include the aggregate values of any descendant files (e.g., FILE1, FILE2, etc.) in those descendant directories. The metric value in directory /A 602 also includes any local files, e.g., “1” 604, contained by the directory /A 602 itself for which that metric value is calculated. Accordingly, when a client requests a metric value for an attribute of a directory in a filesystem tree, which defines a subtree, that value reflects an aggregation of the attributes in any descendant directory plus the attributes of the directory on which the aggregation is performed.


For a large filesystem tree structure including many directories, performing an aggregation operation on all filesystem objects in that filesystem tree can consume considerable processing resources and elapsed time to determine a metric value for a given directory. However, as previously discussed, these additional metrics that include aggregate values of file attributes, are stored in the inode data for each directory. The inode data may be updated each time a filesystem object is updated. This inode data maintains a relatively accurate indication of the attributes for a given directory, even if recent changes to one or more files in that directory are not yet reflected. Accordingly, this allows for rapid and easy access to current filesystem attributes, which may facilitate performance and allocation of resources in both large and scalable filesystems



FIGS. 7A-7E illustrate at least one method for updating attributes and associated metric values in filesystem objects of a filesystem tree. The method tracks each filesystem object to which a change is applied in a file path from the updated file to the root directory. To implement such tracking, each modified filesystem object may be added to a set of unreconciled filesystem objects, one or more of which is iteratively updated in the tree during a subsequent operation. For example, the set 722 may be a list of unreconciled filesystem objects maintained in a filesystem tree. Accordingly, the set 722 of filesystem objects may include both files and directories whose attributes have been changed, but not yet updated to reflect the change, and which may require an update in an ancestor filesystem object.



FIG. 7A is example of a tree structure for data stored in a filesystem, such as for directory /A shown in FIG. 6. The filesystem tree 700 includes a directory /A 702 and various descendant directories /B 708, /C 710, and /D 716, and a file FILE2724 of the directory /A 702. The directories and file also indicate two attributes that the facility maintains in the inode data stored in each filesystem object, which is either a directory or a file. For example, in directory /A 702, the two attributes include a rank 704 and a capacity usage (cap_usage) 706. The rank indicates a level of the filesystem tree in which the filesystem object is located. For example, the directory /A 704 indicates “rank=1” since it is at the top of the tree hierarchy (and, a first descendant of the root directory “/” in FIG. 6). The filesystem object's capacity usage 706 identifies a number of blocks used by a particular filesystem object as discussed with reference to FIG. 3. In FIG. 7A, directory /A 702 has a cap_usage of “1”, though the aggregate cap_usage of the sub-tree defined by directory /A 702 has a cap_usage of “99” (i.e., 5 (FILE2)+45 (/D)+18 (/C)+30 (/B)+1(/A)=99). Though the rank and cap_usage are attributes used in the updating process of the following description, it is understood that various additional attributes are considered and either or both the rank and cap_usage are not required attributes within the facility.


The filesystem tree in each of FIGS. 7A-7E also indicate an ordered pair [reconciled, unreconciled] 712 providing the value of the cap_usage metric for the reconciled to parent block count and the unreconciled to parent block count in each filesystem object in that tree 700. These values 712 indicate whether changes to the block count value in each filesystem object have been updated (e.g., are current) in the parent directory of that respective filesystem object. Accordingly, in some embodiments, if all updates have been reconciled to a parent directory of a given filesystem object, the reconciled cap_usage and unreconciled cap_usage ordered pair 712 are equal. FIG. 7A illustrates such an embodiment since the aggregate block count in the ordered pair 712 is equal [99, 99].



FIG. 7B illustrates the filesystem tree 700 after changes are made to FILE2724 in directory /D 716. When the changes are made to a file, in some embodiments, the changes are immediately reflected in the attribute values stored among the inode data for that filesystem object. Accordingly, FILE2724 reflects an updated cap_usage of “15”. However, FILE2724 is still considered “unreconciled” since the changes to that file still need to be reflected in the directory data and the attributes stored in the inode data of the directory /D 716 which contains FILE2724. As a result, FILE2724 is then added to a separate file for a set 722 of “dirty” filesystem objects. The set 722 tracks the filesystem objects requiring an update to reflect changed attributes of a changed file (e.g., FILE2) in that directory (e.g., /D). A “dirty” filesystem object is also indicated in reconciled and unreconciled values (e.g., FILE2724) that provide differing numbers (e.g., [5, 15]) for reconciled and unreconciled block counts in its parent directory /D 716.


Once the corresponding metrics in the inode data for FILE2724 have been updated in directory /D 716, the next associated ancestor filesystem object in the file path from FILE2724 to the root directory (not shown), is added to the set 722 of dirty filesystem objects being tracked for updating. So, after reconciliation is performed in FIG. 7B, the next filesystem object added to the set 722 is directory /D 712 (shown in FIG. 7C). This is because the new value of the cap_usage attribute may alter at least one metric value of the aggregated attributes stored in the inode data of the parent directory /C 710, which contains directory /D 716 (and FILE2722). Additionally, the reconciled and unreconciled block counts in FILE2724 are then updated [15, 15] to reflect the reconciled updates to the aggregate metrics in directory /D 716. The reconciled and unreconciled counts in directory /D 716 are also updated to reflect the unreconciled blocks [50, 60] in its parent directory (/C 710) as illustrated in FIG. 7C.


In various embodiments, the facility stores the set 722 of dirty filesystem objects either as persistent data (on-disk) or volatile data (in-memory), each of which has its advantages and disadvantages. For example, where the set 722 stored in persistent storage, no initial inode scan is necessary at startup, but updates to each filesystem object are slower than when the set 722 is maintained in volatile storage. Where the set 722 is stored in volatile storage, normal operations are performed faster, but an initial inode scan is required at startup.


In some embodiments, if more than one filesystem object is located in the set 722, the filesystem object having the lowest rank (e.g., farthest file path length from the root directory) in the filesystem tree may be updated first such that its attributes indicate the updated cap_usage value. This ensures that all updates to filesystem objects in the filesystem tree are not repeated, which improves the efficiency of the facility. The filesystem objects within the set 722 of filesystem objects to be updated may be reconciled in an iterative process. Additionally, the filesystem objects in the set 722 may be sorted in order to remove duplicates and to update entries having the lowest rank first. This is done in order to avoid unnecessary and repeated updates to a filesystem object whose descendent also is included in the set 722.


As discussed previously, any updates to a filesystem object may be reflected in hierarchical aggregates indicated by the metric values stored in the inode data for each filesystem object. Once a filesystem object is updated, the filesystem object's entry in the set 722 is removed and the filesystem object's parent directory is added to the set 722. Additionally, the reconciled and unreconciled values for that attribute are updated to reflect the unreconciled data in that filesystem object's parent directory. The metric values indicated in each filesystem object may be updated in a direct path of the directories from the updated file to the root directory. Thus, only the filesystem objects in the path of the file to the root directory need be updated. Unaffected filesystem objects and subtrees are therefore not traversed or updated. So, system resource consumption may be reduced, relative to the time required for iterative scans of the full filesystem tree, and metric values of filesystem object attributes may be updated more quickly since system resources are not allocated to perform unnecessary tasks.


In some embodiments, where the facility receives a request for metric values in a “dirty” filesystem object (i.e., in set 722, or a descendant thereof in set 722), the facility updates only the filesystem object (and any descendants) in the set 722 prior to servicing the request. In some embodiments, the facility updates all filesystem objects in the set 722 prior to servicing a request by a user. In such embodiments, the facility can ensure the most up-to-date metrics for the request. To alternatively determine whether a filesystem object (or descendant thereof) is not completely current, the facility can also check the reconciled and unreconciled count for each descendant of that filesystem object. If any counts differ, the facility can then either update each of the descendants to the requested filesystem object prior to servicing the request, or update the entire tree to the root directory, as previously mentioned,



FIG. 7C illustrates the filesystem tree structure 700 in which the change to FILE2716 is subsequently updated in the inode data associated with directory /C 710. This is indicated by the differing reconciled and unreconciled values [50, 60] of the ordered pair in directory /D 716, which signify that only fifty blocks are currently reconciled in directory /C and sixty blocks need to be reconciled to make the metric values stored in directory /C current. The reconciled value “68” in the ordered pair of its parent directory /C illustrates where the update is to be applied. Accordingly, the set 722 of filesystem objects reflects an entry of directory /D 710. The set 722 of filesystem objects also includes a newly added filesystem object, FILE3726, for which the cap_usage of “10” needs to be updated in the cap_usage metric of its parent directory /B 708. Accordingly, FILE3 indicates reconciled and unreconciled ordered pair values of [0, 10] since 10 blocks need to be added to the reconciled block count (i.e., “30”) in directory /B 708 to make that directory's aggregate attributes current.


As shown in FIG. 7C, directory /D 716 and FILE3726 may concurrently be processed during the next iteration since both have a rank of “3”. In some embodiments, each iteration, or processing of filesystem objects in the set 722 of filesystem objects, removes filesystem objects on corresponding levels (e.g., “rank” in FIG. 7C) of the filesystem tree structure. In other embodiments, each filesystem object in the set 722 may be processed and updated sequentially, based on the order in which that filesystem object is placed in the set 722. In the aforementioned embodiment, one or more entries in the set is processed during each iteration.



FIG. 7D illustrates a tree structure 700 in which directory /D 716 and FILE3726 reflect the updates processed during the iteration performed in FIG. 7C. Accordingly, the cap_usage aggregate attribute in the inode data for directory /B 708 now reflects an updated unreconciled to parent metric value of “40” in the ordered pair values [30, 40] in that directory. Similarly, directory /C 710 now reflects an unreconciled value of “78” in the ordered pair [68, 78]. These unreconciled values both reflect unreconciled cap_usage metrics in the common parent directory /A 702 as well as indicate those directories as being “dirty”. So, these parent directories (IC and /B) in the direct path of the processed filesystem objects (/D and FILE3) are added to the set 722 of filesystem objects to be updated. The set 722 then includes directories /B 708 and /C 710, which are concurrently processed during the next iteration because both are rank “2” in the filesystem tree 700. The reconciled and unreconciled values in FILE3726 and directory /D 716 are also updated to indicate updates applied to their respective parent directories and those filesystem objects are then removed from the set 722 of filesystem objects.


Once directories /B 708 and /C 710 are processed, as illustrated in FIG. 7E, directory /A is then added to the set 722 of dirty filesystem objects. Since that directory is the parent directory for both /B 708 and /C 710, the duplicate entry is removed in order to prevent unnecessary processing of directory /A on the next iteration. The reconciled to parent and unreconciled parent values 712 for directory /A 702 are also updated to reflect an unreconciled cap-usage value (99, 119) in its parent directory (not shown). The reconciled and unreconciled values in directories /B 708 [40, 40] and /C 710 [78, 78] can also be updated to indicate an updated aggregate metric value in the parent directory (/A). Once directory /A 702 has been processed in a similar manner during the next iteration, directory /A 702 will be removed from the set 722 and the value for that filesystem object attribute will also be updated to “119”. Accordingly, the ordered pair will be [119, 119].


An alternative approach to update the aggregate metric value in, for example, directory /A 702 (in FIG. 7D), is to take the difference between the reconciled and unreconciled values for cap_usage in both directories /B 708 and /C 710, sum (e.g., sum ( )) those differences, and add that sum to the cap_usage metric value stored in directory /A 702. For example, in directory /B 708 the difference [30, 40] is “10” and in directory /C 710 the difference [68, 78] is “10”. So, “20” is the sum of those differences, which is then added to a prior stored, or reconciled value (“99”) for cap_usage in directory /A 702. If during this update a change occurred to a lower ranking filesystem object in the filesystem tree (e.g., /D 716), prior to processing the update on directory /A 702, then directory /A 702 would remain in the set of filesystem objects 722 until directory /D 716 is processed. Each lower ranking filesystem object (e.g., from /D up) will then be processed in a similar manner described above, prior to directory /A 702. This prevents additional processing on directory /A 702, such that all updates on that directory may be processed in the same iteration and reflect the most current update to cap_usage (or other attribute) in the inode data of that directory.


Accordingly, in some embodiments, the facility updates a directory's aggregated metric value for a specific attribute by summing a difference between the reconciled and unreconciled values in a child directory with the metric value previously stored in that directory. In another example, referring back to FIG. 7B, each directory and file maintains a count of [reconciled, unreconciled] data to facilitate aggregation of filesystem object attributes. The difference between the unreconciled data in directory /D is equal to “10” (reconciled=50, unreconciled=60). So, to determine the metric value for that attribute of cap_usage in directory /A/C, the filesystem simply sums “68” plus the difference “10” to perform the aggregation. This value can be verified, or alternatively determined, by recalculating values of all entries in directory /C to generate a new aggregate value.


Though the aforementioned embodiments maintain a separate list (e.g., the set of filesystem objects 722) to update metrics in the facility, the metrics can be updated by other methods which do not include such a list or associated filesystem object ranks. For example, in some embodiments, the facility ensures the currency of all of the metrics in the entire filesystem tree each time a filesystem object is updated. In effect, each time a filesystem object is updated, the system traverses the filesystem tree in which that filesystem object is stored to the root directory and updates the metrics in each directory of the direct path from the filesystem object location in the filesystem tree until the root directory is updated to also reflect the update. In some embodiments, an asynchronous, or background process continually traverses trees accumulating and updating metric values for file attributes in the filesystem objects.


To handle filesystem object updates such as deletion of a file or directory from a filesystem tree, the reconciled and unreconciled data for each ancestor directory can be updated in a similar manner as previously described with reference to FIGS. 7A-7E. However, instead of adding the difference between the reconciled and unreconciled values in the filesystem object, the value of the deleted filesystem object is considered a negative unreconciled value in the parent directory associated with that filesystem object. Accordingly, the difference between the reconciled value in the deleted filesystem object and the unreconciled value in the parent is subtracted from the parent's reconciled value during a subsequent operation. Based on this adjustment, each directory in a path from the parent of the deleted filesystem object to the root is ultimately updated normally, such as through the process described in FIGS. 7A-7E (i.e., placing each filesystem object on a separate list 722). Furthermore, any unreconciled value in the deleted filesystem object is ignored since that filesystem object is being removed from the filesystem tree. To handle updates such as renaming a filesystem object, e.g., moving the filesystem object to another directory, the facility performs the aforementioned deletion process under the current name, and creates a new filesystem object under the new name, such as described in FIG. 7C with reference to FILE3. If the filesystem object had any unreconciled data, e.g. differing values in the ordered pair, the unreconciled value remains consistent throughout the deletion and creation process. The updating process for the unreconciled data then occurs normally (e.g., via the process in FIGS. 7A-7E) during a subsequent iteration on the renamed filesystem object.


For filesystem object attributes not having integer values, metric values can be updated by aggregation functions (e.g., latest( )) which compare a prior value of that respective value in each filesystem object being updated. For example, the attribute can include an raccess attribute identifying a most recent access date/time (“atime”) of the filesystem object. The facility can compare the previous raccess date in a directory with an updated raccess date received from a descendant filesystem object, as opposed to looking at the raccess dates of all of the descendants in a subtree defined by that directory. For certain metrics and/or aggregation functions, a new aggregation can be performed across all filesystem objects in a tree or subtree in order to update metric values.


In some embodiments, the facility retrieves information about characteristics of a node, a cluster, or the entire filesystem from statistical sampling of a filesystem tree. The facility chooses the fraction of samples taken from files in each directory of the filesystem tree in such a way as to achieve a sample population that is appropriately distributed across the filesystem tree. In some embodiments, the facility determines the overall number of samples taken to satisfy a desired confidence level in the results.



FIG. 8 illustrates an unbalanced filesystem subtree 800 defined by a directory /USR 802, which has two child directories, directory /USER1808 and directory /USER2812. The shown subtree includes two file types, music 818 and other (non-music) data 822, specific to each of the child directories. In an example, the facility performs sampling using block count attribute (i.e., cap_usage) to answer the question, “what percentage of files stored in the subtree are music files?” Where the directory /USER1808 includes only four data files 810, while the directory /USER2812 includes one thousand music files 814. A simplistic even sampling performed on the root directory /USR 802 would result in a sample from each of the descendant directories 50% of the time. Accordingly, the sampling would result in a 50/50 split of music and data files in the root directory /USR 802. Since the file count attribute for each directory, /USER 1808 and /USER 2812, indicates that the root directory /USR 802 is not made up of 50% music files and 50% data files, these sampling results are clearly skewed and inaccurate. Thus, this approach to sampling may result in the erroneous conclusion regarding the makeup of a particular directory.


To avoid the aforementioned errors, the facility uses a fair sampling approach in which it uses the metric values stored in the inode data of the directories to weight these directories in a manner that determines the likelihood that each file sample gets taken from each directory. By weighting the directories in this way, the facility achieves an improved representative sampling of the composition of the data in the filesystem tree structure. Additionally, since any attribute of a filesystem object can be utilized to weight the directories, the representative sampling is improved for each individual filesystem attribute.


To perform fair sampling on the filesystem subtree 800, the facility uses, for example, a NUM_FILES attribute associated with each directory to establish sampling frequency weights for each directory of the filesystem tree. The NUM_FILES value is the total number of files associated with a directory summed with the files in all descendant directories. Using this NUM_FILES attribute therefore answers the question, “what percentage of files are music files?” So, the total number of files to be sampled between the two directories /USER1808 and /USER2812 for the root directory /USR 802 is 1004 since the NUM_FILES attribute 806 for the root directory indicates “1005” and the my_num_files attribute for the root directory indicates “1”. By storing the aggregate file count in the inode data (e.g., 816, 820) of each directory, the system can quickly query those directories and determine that the files under directory /USER1808 should be sampled “4” times out of every “1004” samples, or approximately 0.4% of the time, and the files under directory /USER2812 should be sampled “1000” times out of every “1004” samples, or 99.6% of the time. If one hundred samples are taken in this manner, the sample results would indicate ˜99% of the files are music files in the root directory /USR 802. This result is more accurate than the 50% music files calculated without using the metric values corresponding the aggregated attributes of the files contained by the root directory /USR 802. This type of weighted sampling may be applied to any attribute of files within a filesystem tree in the facility and may facilitate improved visibility into the files contained by that tree. For example, weighted sampling may be used to determine a file size for two directories including unbalanced average file sizes, e.g., one includes .mp4 files and the other includes .doc files.



FIG. 9 is an example screenshot of graphical user interface displayed on a client device, such a computing device. The user may elect to view various analytics 902 regarding the filesystem, such as a particular filesystem tree structure. For example, the user may select a particular directory, e.g., root directory “/”, for which to view those analytics. In response, the facility returns the one or more metric values along with a graphical representation of those metric values corresponding to a pathname 904 indicating the selected directory. The metric values include storage data for the indicated root directory “/”, such as an overall size (277.5 gigabytes) 906 of the directory 904, including a percentage (99.7%) of available storage capacity used by that directory, and a percentage (5.69%) of overall storage capacity used by that directory in the facility. The metric values includes a recent access (raccess) date 910 on which any file in the directory was last modified and a creation date 908 on which the directory was created. Additionally, the metric values indicate an aggregate number (8288) of directories 912 in the directory 904 and an aggregate number (56877) of files 914 in that directory.


In some embodiments, the graphical user interface indicates metric values for operations performed in a directory. For example, a listing of the top I/Os per second (“IOPS”) activity 916 within the selected directory 904 is displayed. Each of these directory entries includes the path of the file at which the I/O is performed along with the number of I/O operations performed per second with respect to that file. A user can select parameters for returning the IOPS activity as well. For example, in some embodiments, the user can elect to view any IOPS namespace activity 920 related to reads and/or writes to namespaces or directories in the selected directory. In other embodiments, the user may elect to view IOPS file activity 922 related to files contained in the directories of the root directory.


The graphical representation of the metric values can include the directories of first-level (e.g., rank 1) that are children of the root directory “/”, represented by the columns 918 of the graphic. The height (y-axis) 924, 926, 928, and 930, of each directory rectangle reflects the aggregate number of files or storage capacity used by that directory in relation to its parent directory. Accordingly, some of the smaller-size directories may not be visible in the graphical representation of the root directory shown in FIG. 9.



FIGS. 10A-10C are example screenshots of a graphical user interface displaying on a client device metrics for various directories in a filesystem tree. In FIG. 10A, a root directory is shown to be selected at the corresponding path 1000 in the filesystem, which is further indicated by the pathname “I” 1002 proximate to a plurality of analytics relating to that directory. Within the selected directory, there has been no recent activity. Accordingly, though each operation performed on the directory 1006 is selected for display, the IOPS activity 1004 in the cumulative analytics is empty. The size of the selected directory is graphically represented by the height of the column indicating that directory. In particular, column 1008 indicates directory “/” and its height 1018 corresponds to the size of the root directory (1.6 TB). The size of each of the three directories within the root directory (/music, /user, /MORE) is further indicated by the height of each of those child directories in relation to the root directory. So, based on the visual representation, the /music directory in column 1010 is clearly the largest, with the /user directory consuming more than the /MORE directory. To determine the exact size of a directory visible within the graphical representation, such as the “music” directory, the user simply selects that directory in the graphical representation.



FIG. 10B shows an example screenshot of the graphical user interface displaying analytics for the “music” directory after selection of that directory in FIG. 10A. As shown, the directory path 1000 now indicates the path “/music” for the /music directory. Additionally, the pathname 1002 and corresponding analytics are also updated to reflect analytics specific to that selected directory. In the graphical representation, the /music directory column 1010 is the leftmost column and each of the directories in the music directory are further expanded and detailed in the graphical representation. The height 1020 of the /music directory column 1010 now corresponds to 1.3 TB as indicated in the analytics for that directory. To determine the metrics of any child (or descendent) directory contained by the /music directory, the user can then select a displayed directory in the graphical representation. For example, the user can select the /music/zoso directory in column 1012, which shows the child directories for the /music directory.



FIG. 10C shows an example screenshot of the graphical user interface displaying analytics for the /music/zoso directory after selection of that directory in FIG. 10B. After selection of the /music/zoso directory, the path 1000 is updated to show the path for that directory “/music/zoso” and the path name 1002 is updated as well. The graphical representation is also updated to reflect the /music/zoso directory at the leftmost column 1012 and the correspond directories (or files) contained by the /music/zoso directory. As with the preceding FIGS. 10A-10B, the height 1022 of the /music/zoso directory corresponds to the size (167.0 GB) of the directory. Furthermore, the height of each directory in each child or descendant directory in relation to the parent directory corresponds to the size of that directory,


By providing enhanced visibility into the attributes of a data storage filesystem aggregated and stored at different levels in the filesystem hierarchy may facilitate management of the filesystem. It may be desirable to acquire analytics on portions or the entirety of a data storage filesystem tree. Analytics may relate to system capacity such as space usage by subdirectories, file counts, what is the newest/oldest file in a directory/tree, what file is most/least accessed, a histogram of file sizes, a breakdown of characteristics by file type such as space usage, file count, and the like. Other analytics may relate to performance such as transfer rates, I/O operations such as total operations, timing of I/O operations, latency and the like. This information may be used by system administrators for purposes such as: allocation of most frequently accessed data to data storage devices having a fast response time; customized backups based on date of most recent modification or change; resource planning based on total block usage by filesystem; and the like.


Live metrics of aggregate file attributes are therefore stored by the facility in the inode of a directory in the filesystem tree structure. The metric values are live in the sense that they are updated with respect to received updates for any filesystem object within the tree structure. Though each metric value may not reflect the most recent update to a particular directory, those metric values are current, or relatively current. Accordingly, the requested metric values are returned with a very low degree of latency unlike external systems. In some embodiments, the metrics are gathered from a recent system snapshot, where snapshot frequency and resulting latency may be set by a system administrator.


In some embodiments, in addition to storing metrics in the inodes of directories that are aggregated from the filesystem objects of the subtree defined by each directory, the facility also stores metrics in the inodes of files that relate solely to each file. The file metrics are copies of the file's attributes. In some embodiments, files can be added to the set of filesystem objects to be updated, as discussed in FIGS. 7A-7D.


In various embodiments, this information may facilitate the understanding of additional filesystem characteristics that may not be embedded in metadata such as: what percent of space within the filesystem is consumed by particular types of file (e.g., music files), how many files are owned or controlled by, or were created by, a particular user, information relative to additional user specified attributes (e.g., client or patient names) which may be embedded into file name structure, tags in file header data and the like.


From the foregoing, it will be appreciated that specific embodiments of the invention have been described herein for purposes of illustration, but that various modifications may be made without deviating from the scope of the invention. Accordingly, the invention is not limited except as by the appended claims.

Claims
  • 1. A method for providing one or metrics for a hierarchical filesystem tree associated with a data store for a plurality of data files, wherein the method is performed by a computer system that executes instructions to perform actions, comprising: instantiating a facility that performs actions including: maintaining a global data structure for mapping inode numbers from each inode in the filesystem tree to a filesystem location at which corresponding inode data is stored, wherein each filesystem object includes directory data and inode data that is stored in one or more blocks at the filesystem location, and wherein a copy of the global data structure is stored at each node in the data store;receiving one or more requests, from a user, for one or more aggregated values for one or more filesystem objects in one or more directories of the tree; andproviding one or more responses to the request for the one or more aggregated values to the user based on previously performed actions, including: determining one or more metrics, for the one or more aggregated values, that are persistently stored in each directory of the tree that corresponds to at least one filesystem object, wherein the one or more metrics reflect an aggregation of one or more attributes of the one or more filesystem objects that correspond to one or more directories of a subtree of the tree, and wherein the one or more metrics includes a total space consumed by a filesystem object and all of its descendant filesystem objects, a total number of files within the filesystem object, and a total number of data blocks used by the filesystem object and all of its descendant filesystem objects;defining the subtree by a directory corresponding to the one or more filesystem objects, and wherein the providing of the aggregated values based on the previously determined one or more metrics persistently stored at the one or more corresponding directories reduces latency and computational resources of the filesystem tree in comparison to a traverse of one or more portions of the filesystem tree to determine the one or more metrics;synchronously updating the one or more metrics for the directory based on one or more changes to the one or more filesystem objects that correspond to the directory;determining a sampling frequency weight for fair sampling of the composition of data stored in the hierarchical filesystem tree to provide improve representative sampling based on the one or more attributes of the one or more filesystem objects for each directory that directly corresponds to the determined one or more metrics stored in the corresponding directory, wherein a value of the sampling frequency weight indicates a likelihood that fair sampling of the composition of data in one or more file system objects is taken from the corresponding directory; andasynchronously updating the one or more metrics for each intermediate directory on a path between a root directory and the directory for the one or more filesystem objects having the one or more changes based on the sampling frequency weight that corresponds to the one or more attributes of the one or more filesystem objects for each intermediate directory.
  • 2. The method of claim 1, further comprising: sampling the one or more filesystem objects in each directory of the tree in accordance with the sampling frequency weight defined for it.
  • 3. The method of claim 2, wherein each act of sampling a filesystem object comprises retrieving at least one piece of metadata describing the file.
  • 4. A non-transitory computer-readable medium having contents capable of causing a computing system to perform a method for providing data in a hierarchical filesystem tree associated with a data store for a plurality of data files, wherein the method is performed by the computer system that executes instructions to perform actions, comprising: instantiating a facility that performs actions including:maintaining a global data structure for mapping inode numbers from each inode in the filesystem tree to a filesystem location at which corresponding inode data is stored, wherein each filesystem object includes directory data and inode data that is stored in one or more blocks at the filesystem location, and wherein a copy of the global data structure is stored at each node in the data store;receiving one or more requests, from a user, for one or more aggregated values for one or more filesystem objects in one or more directories of the tree; andproviding one or more responses to the request for the one or more aggregated values to the user based on previously performed actions, including: determining one or more metrics, for the one or more aggregated values, that are persistently stored in each directory of the tree that corresponds to at least one filesystem object, wherein the one or more metrics reflect an aggregation of one or more attributes of the one or more filesystem objects that correspond to one or more directories of a subtree of the tree, and wherein the one or more metrics includes a total space consumed by a filesystem object and all of its descendant filesystem objects, a total number of files within the filesystem object, and a total number of data blocks used by the filesystem object and all of its descendant filesystem objects;defining the subtree by a directory corresponding to the one or more filesystem objects, and wherein the providing of the aggregated values based on the previously determined one or more metrics persistently stored at the one or more corresponding directories reduces latency and computational resources of the filesystem tree in comparison to a traverse of one or more portions of the filesystem tree to determine the one or more metrics;synchronously updating the one or more metrics for the directory based on one or more changes to the one or more filesystem objects that correspond to the directory;determining a sampling frequency weight for fair sampling of the composition of data stored in the hierarchical filesystem tree to provide improve representative sampling based on the one or more attributes of the one or more filesystem objects for each directory that directly corresponds to the determined one or more metrics stored in the corresponding directory, wherein a value of the sampling frequency weight indicates a likelihood that fair sampling of the composition of data in one or more file system objects is taken from the corresponding directory; andasynchronously updating the one or more metrics for each intermediate directory on a path between a root directory and the directory for the one or more filesystem objects having the one or more changes based on the sampling frequency weight that corresponds to the one or more attributes of the one or more filesystem objects for each intermediate directory.
  • 5. The non-transitory computer-readable medium of claim 4, wherein the method further comprises: sampling the one or more filesystem objects in each directory of the tree in accordance with the sampling frequency weight defined for it.
  • 6. The non-transitory computer-readable medium of claim 5, wherein each act of sampling a filesystem object comprises retrieving at least one piece of metadata describing the file.
  • 7. The method of claim 1, further comprising determining a currency of the one or more metrics based on at least one change that occurred to a descendant directory on the direct path.
  • 8. The method of claim 1, further comprising updating the one or more metrics to reflect each alteration to each attribute of the one or more filesystem objects.
  • 9. The method of claim 1, further comprising employing inode data for each directory to store the corresponding one or more metrics.
  • 10. The method of claim 1, wherein the facility provides the one or more aggregated values to the user based on the one or metric values that correspond to each directory on the path.
  • 11. The non-transitory computer-readable medium of claim 4, further comprising determining a currency of the one or more metrics based on at least one change that occurred to a descendant directory on the direct path.
  • 12. The non-transitory computer-readable medium of claim 4, further comprising updating the one or more metrics to reflect each alteration to each attribute of the one or more filesystem objects.
  • 13. The non-transitory computer-readable medium of claim 4, further comprising employing inode data for each directory to store the corresponding one or more metrics.
  • 14. The non-transitory computer-readable medium of claim 4, wherein the facility provides the one or more aggregated values to the user based on the one or metric values that correspond to each directory on the path.
  • 15. A computer system for providing one or metrics for a hierarchical filesystem tree associated with a data store for a plurality of data files, wherein the computer system executes instructions to perform actions, comprising: instantiating a facility that performs actions including: maintaining a global data structure for mapping inode numbers from each inode in the filesystem tree to a filesystem location at which corresponding inode data is stored, wherein each filesystem object includes directory data and inode data that is stored in one or more blocks at the filesystem location, and wherein a copy of the global data structure is stored at each node in the data store;receiving one or more requests, from a user, for one or more aggregated values for one or more filesystem objects in one or more directories of the tree; andproviding one or more responses to the request for the one or more aggregated values to the user based on previously performed actions, including: determining one or more metrics, for the one or more aggregated values, that are persistently stored in each directory of the tree that corresponds to at least one filesystem object, wherein the one or more metrics reflect an aggregation of one or more attributes of the one or more filesystem objects that correspond to one or more directories of a subtree of the tree, and wherein the one or more metrics includes a total space consumed by a filesystem object and all of its descendant filesystem objects, a total number of files within the filesystem object, and a total number of data blocks used by the filesystem object and all of its descendant filesystem objects;defining the subtree by a directory corresponding to the one or more filesystem objects, and wherein the providing of the aggregated values based on the previously determined one or more metrics persistently stored at the one or more corresponding directories reduces latency and computational resources of the filesystem tree in comparison to a traverse of one or more portions of the filesystem tree to determine the one or more metrics;synchronously updating the one or more metrics for the directory based on one or more changes to the one or more filesystem objects that correspond to the directory;determining a sampling frequency weight for fair sampling of the composition of data stored in the hierarchical filesystem tree to provide improve representative sampling based on the one or more attributes of the one or more filesystem objects for each directory that directly corresponds to the determined one or more metrics stored in the corresponding directory, wherein a value of the sampling frequency weight indicates a likelihood that fair sampling of the composition of data in one or more file system objects is taken from the corresponding directory; andasynchronously updating the one or more metrics for each intermediate directory on a path between a root directory and the directory for the one or more filesystem objects having the one or more changes based on the sampling frequency weight that corresponds to the one or more attributes of the one or more filesystem objects for each intermediate directory.
  • 16. The system of claim 15, further comprising determining a currency of the one or more metrics based on at least one change that occurred to a descendant directory on the direct path.
  • 17. The system of claim 15, further comprising updating the one or more metrics to reflect each alteration to each attribute of the one or more filesystem objects.
  • 18. The system of claim 15, further comprising employing inode data for each directory to store the corresponding one or more metrics.
  • 19. The system of claim 15, wherein the facility provides the one or more aggregated values to the user based on the one or metric values that correspond to each directory on the path.
  • 20. The system of claim 15, further comprising: sampling the one or more filesystem objects in each directory of the tree in accordance with the sampling frequency weight defined for it, wherein each act of sampling a filesystem object comprises retrieving at least one piece of metadata describing the file.
CROSS-REFERENCE TO RELATED APPLICATION(S)

This application claims the benefit of provisional application Nos. 61/982,926 and 61/982,931, both filed on Apr. 23, 2014, each of which is hereby incorporated by reference in its entirety.

US Referenced Citations (318)
Number Name Date Kind
5165031 Pruul et al. Nov 1992 A
5283875 Gibson et al. Feb 1994 A
5319773 Britton et al. Jun 1994 A
5410684 Ainsworth et al. Apr 1995 A
5410719 Shackleford Apr 1995 A
5442561 Yoshizawa Aug 1995 A
5953719 Kleewein et al. Sep 1999 A
6236996 Bapat et al. May 2001 B1
6385641 Jiang et al. May 2002 B1
6415283 Conklin Jul 2002 B1
6496944 Hsiao et al. Dec 2002 B1
6560615 Zayas et al. May 2003 B1
6772435 Thexton et al. Aug 2004 B1
6772735 Thexton et al. Aug 2004 B2
6874130 Baweja et al. Mar 2005 B1
6892211 Hitz et al. May 2005 B2
6965903 Agarwal et al. Nov 2005 B1
6965936 Wipfel et al. Nov 2005 B1
7165158 Yagawa Jan 2007 B1
7213040 Stokes et al. May 2007 B1
7330948 Deguchi et al. Feb 2008 B2
7467333 Keeton et al. Dec 2008 B2
7594138 Abdulvahid Sep 2009 B2
7636743 Erofeev Dec 2009 B2
7693876 Hackworth et al. Apr 2010 B2
7757056 Fair Jul 2010 B1
7844580 Srivastava et al. Nov 2010 B2
7933870 Webster Apr 2011 B1
7937421 Mikesell et al. May 2011 B2
7962709 Agrawal Jun 2011 B2
7966293 Owara et al. Jun 2011 B1
8027827 Bitar et al. Sep 2011 B2
8046378 Zhuge et al. Oct 2011 B1
8108429 Sim-Tang et al. Jan 2012 B2
8296312 Leung Oct 2012 B1
8341540 Haynes et al. Dec 2012 B1
8355407 Wookey et al. Jan 2013 B2
8364648 Sim-Tang Jan 2013 B1
8423733 Ozdemir Apr 2013 B1
8423821 Keith, Jr. Apr 2013 B1
8448170 Wipfel et al. May 2013 B2
8463825 Harty et al. Jun 2013 B1
8489656 Erofeev Jul 2013 B2
8504733 Iyer et al. Aug 2013 B1
8515911 Zhou et al. Aug 2013 B1
8612404 Bone et al. Dec 2013 B2
8645323 Jackiewicz et al. Feb 2014 B2
8661447 Olliff et al. Feb 2014 B1
8725691 Natanzon May 2014 B1
8776050 Plouffe et al. Jul 2014 B2
8782655 Blanding et al. Jul 2014 B2
8806154 Gupta et al. Aug 2014 B1
8838887 Burke et al. Sep 2014 B1
8838931 Marshak et al. Sep 2014 B1
8849764 Long et al. Sep 2014 B1
8849809 Seshadri Sep 2014 B1
8868797 Kirac et al. Oct 2014 B1
8924364 Zhong et al. Dec 2014 B1
8972694 Dolan et al. Mar 2015 B1
9015214 Nishida et al. Apr 2015 B2
9026765 Marshak et al. May 2015 B1
9031994 Cao et al. May 2015 B1
9032170 Vaghani et al. May 2015 B2
9047017 Dolan et al. Jun 2015 B1
9141633 Li et al. Sep 2015 B1
9143379 Berger et al. Sep 2015 B1
9158653 Gold Oct 2015 B2
9171145 Dash et al. Oct 2015 B2
9244975 Das et al. Jan 2016 B2
9244976 Zhang et al. Jan 2016 B1
9361187 Jarvis Jun 2016 B2
9384252 Akirav et al. Jul 2016 B2
9459804 Natanzon et al. Oct 2016 B1
9501487 Yuan et al. Nov 2016 B1
9547560 Lee Jan 2017 B1
9600193 Ahrens et al. Mar 2017 B2
9727432 Cutforth et al. Aug 2017 B1
9747171 Beeken et al. Aug 2017 B2
9753782 Fang et al. Sep 2017 B2
9753932 Brow et al. Sep 2017 B1
9753987 Dolan et al. Sep 2017 B1
9785377 Shin et al. Oct 2017 B2
10140185 Lopez et al. Nov 2018 B1
10261868 Brown et al. Apr 2019 B2
10275493 Mostak Apr 2019 B1
10303561 Beeken et al. May 2019 B2
10318401 Rothschilds et al. Jun 2019 B2
10339101 Gupta Jul 2019 B1
10423609 Strauss Sep 2019 B1
10437509 Alexeev et al. Oct 2019 B1
10447779 Dieterich et al. Oct 2019 B2
10474635 Unger et al. Nov 2019 B1
10534758 Carpenter et al. Jan 2020 B1
10540662 Barlett et al. Jan 2020 B2
10545986 Tappan et al. Jan 2020 B2
10621147 Liang et al. Apr 2020 B1
10664408 Chatterjee May 2020 B1
10678663 Sharma et al. Jun 2020 B1
10725977 Chmiel et al. Jul 2020 B1
10795796 Bai et al. Oct 2020 B1
10860546 Ye et al. Dec 2020 B2
11023535 Greenwood et al. Jun 2021 B1
11157458 Carter et al. Oct 2021 B1
20010039622 Hitz et al. Nov 2001 A1
20020059439 Arroyo et al. May 2002 A1
20020065835 Fujisaki May 2002 A1
20020083073 Vaidya et al. Jun 2002 A1
20020099691 Lore et al. Jul 2002 A1
20020178271 Graham et al. Nov 2002 A1
20030033308 Patel et al. Feb 2003 A1
20030145009 Forman et al. Jul 2003 A1
20030177379 Hori et al. Sep 2003 A1
20030182313 Federwisch et al. Sep 2003 A1
20040030727 Armangau et al. Feb 2004 A1
20040093474 Lin et al. May 2004 A1
20040098425 Wiss et al. May 2004 A1
20040153479 Mikesell et al. Aug 2004 A1
20040255048 Lev Ran et al. Dec 2004 A1
20050015674 Haugh Jan 2005 A1
20050027748 Kisley Feb 2005 A1
20050065986 Bixby et al. Mar 2005 A1
20050091663 Bagsby Apr 2005 A1
20050114593 Cassell et al. May 2005 A1
20050114726 Ouchi May 2005 A1
20050119996 Ohata et al. Jun 2005 A1
20050154866 Steely, Jr. et al. Jul 2005 A1
20050195660 Kavuri et al. Sep 2005 A1
20050223019 Das et al. Oct 2005 A1
20060004890 Semple et al. Jan 2006 A1
20060053139 Marzinski et al. Mar 2006 A1
20060089982 Abbott et al. Apr 2006 A1
20060090036 Zohar et al. Apr 2006 A1
20060123005 Burnett et al. Jun 2006 A1
20060173842 Horvitz et al. Aug 2006 A1
20060271604 Shoens Nov 2006 A1
20070011302 Groner et al. Jan 2007 A1
20070027985 Ramany et al. Feb 2007 A1
20070100855 T. Kohl May 2007 A1
20070118561 Idicula et al. May 2007 A1
20070143371 Kottomtharayil Jun 2007 A1
20080028006 Liu et al. Jan 2008 A1
20080059399 DeLorme et al. Mar 2008 A1
20080059541 Fachan et al. Mar 2008 A1
20080082593 Komarov Apr 2008 A1
20080162608 Torii et al. Jul 2008 A1
20080172366 Hanne et al. Jul 2008 A1
20080228772 Plamondon Sep 2008 A1
20080250357 Lee et al. Oct 2008 A1
20080256474 Chakra et al. Oct 2008 A1
20080270469 Myerson et al. Oct 2008 A1
20080270928 Chakra et al. Oct 2008 A1
20080282244 Wu et al. Nov 2008 A1
20080288306 MacIntyre et al. Nov 2008 A1
20080301256 McWilliams et al. Dec 2008 A1
20080313217 Dunsmore et al. Dec 2008 A1
20090077087 Urano et al. Mar 2009 A1
20090138500 Yuan et al. May 2009 A1
20090199190 Chen et al. Aug 2009 A1
20090222509 King et al. Sep 2009 A1
20090240539 Slawson et al. Sep 2009 A1
20090274047 Kruys et al. Nov 2009 A1
20090319566 Wald et al. Dec 2009 A1
20090327642 Ogihara et al. Dec 2009 A1
20100030825 Matsuzawa et al. Feb 2010 A1
20100036895 Boyd et al. Feb 2010 A1
20100088317 Bone et al. Apr 2010 A1
20100161557 Anderson et al. Jun 2010 A1
20100179959 Shoens Jul 2010 A1
20100217948 Mason et al. Aug 2010 A1
20100241668 Susanto Aug 2010 A1
20100281214 Jernigan, IV Nov 2010 A1
20100287512 Gan et al. Nov 2010 A1
20110039622 Levenson Feb 2011 A1
20110066668 Guarraci Mar 2011 A1
20110082836 Wang et al. Apr 2011 A1
20110125799 Kandasamy et al. May 2011 A1
20110125973 Lev et al. May 2011 A1
20110161381 Wang et al. Jun 2011 A1
20110161964 Piazza et al. Jun 2011 A1
20110196833 Drobychev et al. Aug 2011 A1
20110196899 Hughes et al. Aug 2011 A1
20110202925 Banerjee et al. Aug 2011 A1
20110246724 Marathe et al. Oct 2011 A1
20120036463 Krakovsky Feb 2012 A1
20120066179 Saika Mar 2012 A1
20120096059 Shimizu et al. Apr 2012 A1
20120136843 Bone et al. May 2012 A1
20120151438 Bach et al. Jun 2012 A1
20120166478 Das et al. Jun 2012 A1
20120179886 Prahlad et al. Jul 2012 A1
20120216005 Naito et al. Aug 2012 A1
20120317079 Shoens et al. Dec 2012 A1
20130019072 Strasser et al. Jan 2013 A1
20130024609 Gorobets et al. Jan 2013 A1
20130073819 Havewala et al. Mar 2013 A1
20130086121 Preslan Apr 2013 A1
20130091168 Bhave et al. Apr 2013 A1
20130110787 Garimella et al. May 2013 A1
20130191355 Bone et al. Jul 2013 A1
20130212579 Ben-Shaul et al. Aug 2013 A1
20130227236 Flynn et al. Aug 2013 A1
20130254163 Savage et al. Sep 2013 A1
20130304903 Mick et al. Nov 2013 A1
20130311454 Ezzat Nov 2013 A1
20130318194 Timbs Nov 2013 A1
20130325806 Bachar et al. Dec 2013 A1
20130325808 Bachar et al. Dec 2013 A1
20130339406 Kanfi Dec 2013 A1
20140006354 Parkinson et al. Jan 2014 A1
20140040199 Golab et al. Feb 2014 A1
20140040693 Kim et al. Feb 2014 A1
20140059158 Chen et al. Feb 2014 A1
20140095249 Tarakad et al. Apr 2014 A1
20140101389 Nellans Apr 2014 A1
20140156956 Ezra Jun 2014 A1
20140181441 Kottomtharayil et al. Jun 2014 A1
20140189267 Qi et al. Jul 2014 A1
20140237193 Shivashankaraiah Aug 2014 A1
20140258609 Cui et al. Sep 2014 A1
20140280485 A Hummaida et al. Sep 2014 A1
20140281307 Peterson Sep 2014 A1
20140281411 Abdallah Sep 2014 A1
20140344222 Morris et al. Nov 2014 A1
20140372384 Long et al. Dec 2014 A1
20140372607 Gladwin Dec 2014 A1
20140373032 Merry et al. Dec 2014 A1
20150006226 Smith et al. Jan 2015 A1
20150012666 Pannese et al. Jan 2015 A1
20150067086 Adriaens et al. Mar 2015 A1
20150067142 Renkema Mar 2015 A1
20150106145 Hamilton et al. Apr 2015 A1
20150135331 Das May 2015 A1
20150143026 Reddy et al. May 2015 A1
20150149736 Kwon et al. May 2015 A1
20150186217 Eslami Sarab Jul 2015 A1
20150186529 Rope et al. Jul 2015 A1
20150193347 Kluesing et al. Jul 2015 A1
20150215405 Baek et al. Jul 2015 A1
20150234716 Brooker et al. Aug 2015 A1
20150234879 Baldwin et al. Aug 2015 A1
20150242263 Klose Aug 2015 A1
20150248253 Kim et al. Sep 2015 A1
20150278282 Sardina et al. Oct 2015 A1
20150347126 Tibble et al. Dec 2015 A1
20160034356 Aron et al. Feb 2016 A1
20160110105 Karamcheti et al. Apr 2016 A1
20160139836 Nallathambi et al. May 2016 A1
20160147654 Zhao et al. May 2016 A1
20160224430 Long et al. Aug 2016 A1
20160239185 Balimidi et al. Aug 2016 A1
20160246816 Abiri et al. Aug 2016 A1
20160269501 Usgaonkar et al. Sep 2016 A1
20160292013 Li et al. Oct 2016 A1
20160292429 Manville et al. Oct 2016 A1
20160306810 Ni et al. Oct 2016 A1
20160314046 Kumarasamy Oct 2016 A1
20160335278 Tabaaloute et al. Nov 2016 A1
20160357677 Hooker et al. Dec 2016 A1
20160359859 Capone Dec 2016 A1
20160371297 Okun Dec 2016 A1
20160380878 Bugenhagen et al. Dec 2016 A1
20170024152 Bhagi et al. Jan 2017 A1
20170032006 Anglin et al. Feb 2017 A1
20170046143 Kochhar et al. Feb 2017 A1
20170052898 Ash et al. Feb 2017 A1
20170078164 Hildebrand et al. Mar 2017 A1
20170091046 Bangalore et al. Mar 2017 A1
20170118287 Beck Apr 2017 A1
20170123883 Hail May 2017 A1
20170123935 Pandit et al. May 2017 A1
20170163728 Chawla et al. Jun 2017 A1
20170201582 Zhang et al. Jul 2017 A1
20170270180 State Sep 2017 A1
20170286455 Li et al. Oct 2017 A1
20170316321 Whitney et al. Nov 2017 A1
20170336983 Roh et al. Nov 2017 A1
20170344598 Constantinescu et al. Nov 2017 A1
20170344905 Hack et al. Nov 2017 A1
20170366609 Dieterich et al. Dec 2017 A1
20180040029 Zeng et al. Feb 2018 A1
20180059946 Kunii et al. Mar 2018 A1
20180089031 Mitkar et al. Mar 2018 A1
20180101546 Krasnow et al. Apr 2018 A1
20180129443 Karve et al. May 2018 A1
20180203798 Hughes et al. Jul 2018 A1
20180276078 Blea et al. Sep 2018 A1
20180288057 Varadamma et al. Oct 2018 A1
20180314423 Gong et al. Nov 2018 A1
20180365115 Fang et al. Dec 2018 A1
20190087770 Walsh et al. Mar 2019 A1
20190095112 Lingarajappa Mar 2019 A1
20190102700 Babu et al. Apr 2019 A1
20190163589 McBride et al. May 2019 A1
20190163591 Ouyang et al. May 2019 A1
20190196879 Dutta et al. Jun 2019 A1
20190212921 Liang et al. Jul 2019 A1
20190220189 Yang et al. Jul 2019 A1
20190286521 Okpotse et al. Sep 2019 A1
20190286528 Wu et al. Sep 2019 A1
20190384640 Swamy et al. Dec 2019 A1
20200004977 Araujo et al. Jan 2020 A1
20200026438 Peleg et al. Jan 2020 A1
20200034077 Haravu et al. Jan 2020 A1
20200142878 Varadarajan et al. May 2020 A1
20200174692 Dave et al. Jun 2020 A1
20200409583 Kusters et al. Dec 2020 A1
20210004355 Iwase Jan 2021 A1
20210042263 Zdornov et al. Feb 2021 A1
20210042282 Cseri et al. Feb 2021 A1
20210056074 Zhu Feb 2021 A1
20210110150 Kakrana et al. Apr 2021 A1
20210191650 Vansteenkiste et al. Jun 2021 A1
20210240393 Jo et al. Aug 2021 A1
20210240678 Patel et al. Aug 2021 A1
20210311841 McNutt Oct 2021 A1
20210374105 Kodama et al. Dec 2021 A1
20220019361 Kurata et al. Jan 2022 A1
20220091739 Kumar et al. Mar 2022 A1
Foreign Referenced Citations (6)
Number Date Country
1217551 Jun 2002 EP
1498829 Jan 2005 EP
1999044145 Sep 1999 WO
0072201 Nov 2000 WO
2009007250 Jan 2009 WO
2012029259 Mar 2012 WO
Non-Patent Literature Citations (179)
Entry
Office Communication for U.S. Appl. No. 14/859,114 dated Jun. 26, 2019, pp. 1-27.
Office Communication for U.S. Appl. No. 16/434,157 dated Jul. 25, 2019, pp. 1-16.
Office Communication for U.S. Appl. No. 14/595,043 dated Aug. 27, 2019, pp. 1-34.
International Search Report and Written Opinion for application PCT/US2016038242 dated Oct. 11, 2016, pp. 1-11.
Office Communication for U.S. Appl. No. 15/957,809 dated Jan. 24, 2019, pp. 1-28.
Office Communication for U.S. Appl. No. 16/226,587 dated Feb. 25, 2019, pp. 1-65.
Office Communication for U.S. Appl. No. 15/473,051 dated Jun. 30, 2017, pp. 1-22.
Office Communication for U.S. Appl. No. 16/004,182 dated Mar. 5, 2019, pp. 1-46.
Office Communication for U.S. Appl. No. 16/004,182 dated Aug. 23, 2018, pp. 1-46.
Office Communication for U.S. Appl. No. 16/004,208 dated Aug. 27, 2018, pp. 1-11.
European Communication and European Search Report for European Application No. 18155779.4, dated Apr. 17, 2018, pp. 1-15.
Office Communication for U.S. Appl. No. 16/262,756 dated Aug. 5, 2019, pp. 1-48.
Office Communication for U.S. Appl. No. 16/262,756 dated Apr. 2, 2019, pp. 1-40.
Office Communication for U.S. Appl. No. 16/262,756 dated Oct. 25, 2019, pp. 1-6.
Office Communication for U.S. Appl. No. 16/775,041 dated Mar. 11, 2020, pp. 1-8.
Office Communication for U.S. Appl. No. 16/228,716 dated Jun. 24, 2019, pp. 1-28.
Office Communication for U.S. Appl. No. 16/231,354 dated Jul. 10, 2019, pp. 1-19.
Office Communication for U.S. Appl. No. 16/226,587 dated Aug. 5, 2019, pp. 1-55.
Office Communication for U.S. Appl. No. 16/228,716 dated Feb. 28, 2019, pp. 1-27.
Office Communication for U.S. Appl. No. 16/231,354 dated Mar. 25, 2019, pp. 1-19.
Office Communication for U.S. Appl. No. 16/262,790 dated Aug. 23, 2019, pp. 1-20.
Office Communication for U.S. Appl. No. 16/262,790 dated Apr. 18, 2019, pp. 1-24.
Office Communication for U.S. Appl. No. 16/234,395 dated Aug. 8, 2019, pp. 1-28.
Office Communication for U.S. Appl. No. 16/234,334 dated Apr. 5, 2019, pp. 1-24.
Office Communication for U.S. Appl. No. 16/234,395 dated Mar. 28, 2019, pp. 1-36.
Kappes et al. “Virtualization-aware Access Control for Multitenant Filesystems”, University of Ioannina, Greece, Technical Report No. DCS2013-1, 8, 61-64. (Year: 2013), pp. 1-6.
Hitz et al. “Merging NT and UNIX filesystem permissions”, In Proceedings of the 2nd conference on USENIX Windows NT Symposium-vol. 2 (pp. 10-10). USENIX Association. (Year: 1998, August), pp. 1-10.
Office Communication for U.S. Appl. No. 16/234,334 dated Oct. 11, 2019, pp. 1-22.
Official Communication for U.S. Appl. No. 15/473,051 dated Jun. 30, 2017, pp. 1-23.
Official Communication for U.S. Appl. No. 15/694,604 dated Jun. 3, 2019, pp. 1-14.
Official Communication for U.S. Appl. No. 16/004,182 dated Aug. 23, 2018, pp. 1-46.
Official Communication for U.S. Appl. No. 16/004,182 dated Mar. 5, 2019, pp. 1-46.
Official Communication for U.S. Appl. No. 16/004,182 dated Jul. 3, 2019, pp. 1-50.
Official Communication for U.S. Appl. No. 16/004,182 dated May 22, 2019, pp. 1-6.
Official Communication for U.S. Appl. No. 16/004,182 dated Jan. 7, 2020, pp. 1-54.
Official Communication for U.S. Appl. No. 14/595,043 dated Jun. 7, 2019, pp. 1-29.
Official Communication for U.S. Appl. No. 14/859,061 dated Sep. 22, 2017, pp. 1-29.
Official Communication for U.S. Appl. No. 15/831,236 dated Mar. 30, 2018, pp. 1-8.
Official Communication for U.S. Appl. No. 15/831,236 dated Aug. 15, 2018, pp. 1-27.
Office Communication for U.S. Appl. No. 15/694,604 dated Nov. 20, 2019, pp. 1-24.
Office Communication for U.S. Patent Application No. 14/859,114 dated Nov. 19, 2018, pp. 1-41.
Office Communication for U.S. Appl. No. 14/859,114 dated Jan. 31, 2019, pp. 1-5.
Office Communication for U.S. Appl. No. 14/859,114 dated Mar. 7, 2019, pp. 1-39.
Office Communication for U.S. Appl. No. 14/859,114 dated Sep. 13, 2019, pp. 1-8.
Office Communication for U.S. Appl. No. 14/859,114 dated Nov. 26, 2019, pp. 1-43.
Office Communication for U.S. Appl. No. 15/288,853 dated Sep. 19, 2018, pp. 1-27.
Chimera, “Value Bars: An Information Visualization and Navigation Tool for Multi-attribute Listings”, CHI '92, Monterey, CA, May 3-7, 1992, pp. 293-294.
Office Communication for U.S. Appl. No. 15/288,853 dated Mar. 25, 2019, pp. 1-25.
Cudre-Mauroux, et al., “TrajStore: An Adaptive Storage System for Very Large Trajectory Sets”, ICDE 2010, Long Beach, CA, Mar. 1-6, 2010, pp. 109-120.
Office Communication for U.S. Appl. No. 15/474,047 dated Sep. 18, 2017, p. 1-24.
Office Communication for U.S. Appl. No. 15/474,047 dated Mar. 9, 2018, pp. 1-12.
Office Communication for U.S. Appl. No. 15/474,047 dated Jun. 11, 2018, pp. 1-7.
Office Communication for U.S. Appl. No. 15/474,047 dated Aug. 15, 2018, pp. 1-24.
Office Communication for U.S. Appl. No. 15/957,809 dated Jun. 28, 2018, pp. 1-42.
Office Communication for U.S. Appl. No. 16/436,825 dated Jul. 11, 2019.
Office Communication for U.S. Appl. No. 15/854,447 dated May 6, 2019, pp. 1-31.
Office Communication for U.S. Appl. No. 16/505,562 dated Aug. 30, 2019, pp. 1-46.
European Communication and European Search Report for European Application No. 17206518.7 dated Apr. 5, 2018, pp. 1-8.
Karatza et al. Epoch load sharing in a network of workstations, Simulation Symposium, 2001. Proceedings. 34th Annual Apr. 22-26, 2001, Piscataway, NJ, USA, IEEE, Apr. 22, 2001 (Apr. 22, 2001), pp. 36-42, XP010541274, ISBN: 978-0-7695-1092-7.
Office Communication for U.S. Appl. No. 16/125,573 dated Nov. 21, 2019, pp. 1-24.
Office Communication for U.S. Appl. No. 16/226,587 dated Oct. 24, 2019, pp. 1-6.
Office Communication for U.S. Appl. No. 16/234,334 dated Jan. 16, 2020, pp. 1-8.
Office Communication for U.S. Appl. No. 16/262,756 dated Jan. 28, 2020, pp. 1-27.
Office Communication for U.S. Appl. No. 16/434,157 dated Jan. 29, 2020, pp. 1-12.
Office Communication for U.S. Appl. No. 16/262,790 dated Feb. 6, 2020, pp. 1-8.
Office Communication for U.S. Appl. No. 14/859,114 dated Mar. 13, 2020, pp. 1-22.
Office Communication for U.S. Appl. No. 16/752,451 dated Mar. 12, 2020, pp. 1-14.
Office Communication for U.S. Appl. No. 16/779,362 dated Mar. 26, 2020, pp. 1-10.
Wikipedia clustered file system page from date Jul. 9, 2019, retrieved using the WayBackMachine, From https://web.archive.org/web/20190709083400/https://en.wikipedia.org/wiki/Clustered_file_system (Year: 2019), pp. 1-6.
Wikipedia raft page from date Jul. 16, 2019, retrieved using the WayBackMachine, from https://web.archive.org/web/20190716115001/https://en.wikipedia.org/wiki/Raft (computer_science) (Year: 2019), pp. 1-4.
Office Communication for U.S. Appl. No. 16/004,182 dated Mar. 23, 2020, pp. 1-6.
Office Communication for U.S. Appl. No. 16/752,509 dated Apr. 2, 2020, pp. 1-42.
Office Communication for U.S. Appl. No. 16/152,277 dated Apr. 3, 2020, pp. 1-10.
Office Communication for U.S. Appl. No. 16/004,182 dated Apr. 28, 2020, pp. 1-52.
Office Communication for U.S. Appl. No. 16/152,259 dated Apr. 29, 2020, pp. 1-19.
Office Communication for U.S. Appl. No. 14/859,114 dated Jun. 5, 2020, pp. 1-6.
Office Communication for U.S. Appl. No. 16/262,756 dated Jun. 8, 2020, pp. 1-43.
Office Communication for U.S. Appl. No. 16/752,451 dated Jul. 23, 2020, pp. 1-31.
Office Communication for U.S. Appl. No. 14/859,114 dated Jul. 23, 2020, pp. 1-28.
Office Communication for U.S. Appl. No. 16/152,615 dated Aug. 6, 2020, pp. 1-18.
Office Communication for U.S. Appl. No. 16/779,362 dated Aug. 7, 2020, pp. 1-33.
Office Communication for U.S. Appl. No. 16/883,922 dated Aug. 7, 2020, pp. 1-18.
Office Communication for U.S. Appl. No. 16/775,041 dated Aug. 18, 2020, pp. 1-17.
Office Communication for U.S. Appl. No. 16/883,879 dated Sep. 1, 2020, pp. 1-18.
Extended European Search Report for European Patent Application No. 16812585.4 dated Nov. 7, 2018, pp. 1-9.
Comer, Douglas, “The Ubiquitous B-Tree,” Computing Surveys, vol. 11, No. 2, Jun. 1979. Computer Science Department, Purdue University, West Lafayette, Indiana 47907, pp. 121-137.
Office Communication for European Patent Application No. 16812585.4 dated Jan. 2, 2020, pp. 1-6.
Bloom, Burton H. “Space/Time Trade-offs in Hash Coding with Allowable Errors,” Communications of the ACM, vol. 13, No. 7, Jul. 1970. Computer Usage Company, Newton Upper Falls, Massachusetts, pp. 422-426.
Office Communication for U.S. Appl. No. 16/262,756 dated Aug. 24, 2020, pp. 1-21.
Office Communication for European Patent Application No. 18155779.4 dated Oct. 8, 2019, pp. 1-4.
Office Communication for U.S. Appl. No. 16/152,259 dated Aug. 28, 2020, pp. 1-5.
Office Communication for U.S. Appl. No. 16/752,509 dated Aug. 11, 2020, pp. 1-7.
Office Communication for U.S. Appl. No. 16/152,277 dated Oct. 16, 2020, pp. 1-10.
Office Communication for U.S. Appl. No. 16/152,615 dated Oct. 20, 2020, pp. 1-7.
Office Communication for U.S. Appl. No. 16/775,041 dated Nov. 3, 2020, pp. 1-5.
Office Communication for U.S. Appl. No. 17/062,500 dated Nov. 12, 2020, pp. 1-12.
Office Communication for U.S. Appl. No. 16/004,182 dated Nov. 30, 2020, pp. 1-55.
Office Communication for U.S. Appl. No. 14/859,144 dated Dec. 1, 2020, pp. 1-24.
Office Communication for U.S. Appl. No. 16/883,922 dated Dec. 2, 2020, pp. 1-9.
Office Communication for U.S. Appl. No. 16/883,879 dated Dec. 8, 2020, pp. 1-5.
Examination Report, for European Patent Application No. 17206518.7 dated Feb. 23, 2021, pp. 1-6.
Office Communication for U.S. Patent Application No. 14/859,114 dated Mar. 8, 2021, pp. 1-4,
Office Communication for U.S. Appl. No. 16/004,182 dated Mar. 8, 2021, pp. 1-60.
Office Communication for U.S. Appl. No. 17/062,500 dated Mar. 9, 2021, pp. 1-17.
Office Communication for U.S. Appl. No. 16/152,277 dated Mar. 18, 2021, pp. 1-10.
Offfice Communication for U.S. Appl. No. 17/160,698 dated Mar. 18, 2021, pp. 1-11.
Office Communication for U.S. Appl. No. 16/152,277 dated Dec. 28, 2020, pp. 1-5.
Office Communication for U.S. Appl. No. 16/004,182 dated Jan. 28, 2021, pp. 1-4.
Office Communication for U.S. Appl. No. 17/115,529 dated Feb. 8, 2021, pp. 1-15.
Office Communication for U.S. Appl. No. 16/262,756 dated Feb. 10, 2021, pp. 1-19.
Office Communication for U.S. Appl. No. 17/114,384 dated Feb. 17, 2021, pp. 1-12.
Office Communication for U.S. Appl. No. 17/062,500 dated May 18, 2021, pp. 1-4.
Office Communication for U.S. Appl. No. 17/203,371 dated May 20, 2021, pp. 1-10.
Office Communication for U.S. Appl. No. 17/115,529 dated May 25, 2021, pp. 1-18.
Office Communication for U.S. Appl. No. 14/859,114 dated May 26, 2021, pp. 1-11.
Office Communication for U.S. Appl. No. 16/262,756 dated May 27, 2021, pp. 1-7.
Office Communication for U.S. Appl. No. 17/114,384 dated May 27, 2021, pp. 1-13.
Office Communication for U.S. Appl. No. 17/190,653 dated May 27, 2021, pp. 1-11.
Office Communication for U.S. Appl. No. 16/741,567 dated Jun. 8, 2021, pp. 1-5.
Office Communication for U.S. Appl. No. 17/114,384 dated Aug. 3, 2021, pp. 1-4.
Office Communication for U.S. Appl. No. 17/115,529 dated Aug. 12, 2021, pp. 1-4.
Office Communication for U.S. Appl. No. 17/190,653 dated Aug. 27, 2021, pp. 1-11.
Office Communication for U.S. Appl. No. 17/114,384 dated Sep. 2, 2021, pp. 1-5.
Office Communication for U.S. Appl. No. 16/152,277 dated Sep. 3, 2021, pp. 1-4.
Office Communication for U.S. Appl. No. 16/004,182 dated Sep. 10, 2021, pp. 1-4.
Office Communication for U.S. Appl. No. 16/004,182 dated Sep. 29, 2021, pp. 1-11.
Office Communication for U.S. Appl. No. 16/152,277 dated Oct. 18, 2021, pp. 1-5.
International Search Report and Written Opinion for International Patent Application No. PCT/US2021/023525 dated Oct. 12, 2021, pp. 1-7.
Office Communication for U.S. Appl. No. 17/115,529 dated Oct. 22, 2021, pp. 1-20.
Office Communication for U.S. Appl. No. 17/062,500 dated Oct. 27, 2021, pp. 1-17.
Office Communication for U.S. Appl. No. 16/741,567 dated Oct. 28, 2021, pp. 1-11.
Office Communication for U.S. Appl. No. 17/203,452 dated Nov. 2, 2021, pp. 1-13.
Office Communication for U.S. Appl. No. 17/190,653 dated Nov. 10, 2021, pp. 1-6.
Office Communication for U.S. Appl. No. 17/484,167 dated Nov. 18, 2021, pp. 1-15.
Office Communication for U.S. Appl. No. 17/588,120 dated Apr. 11, 2022, pp. 1-36.
Office Communication for U.S. Appl. No. 17/588,895 dated Apr. 27, 2022, pp. 1-6.
Office Communication for U.S. Appl. No. 17/190,653 dated Apr. 28, 2022, pp. 1-13.
Office Communication for U.S. Appl. No. 17/510,043 dated Apr. 29, 2022, pp. 1-10.
Office Communication for U.S. Appl. No. 17/115,529 dated Apr. 29, 2022, pp. 1-4.
Office Communication for U.S. Appl. No. 17/062,500 dated Jan. 7, 2022, pp. 1-4.
Office Communication for U.S. Appl. No. 16/741,567 dated Jan. 11, 2022, pp. 1-6.
Office Communication for U.S. Appl. No. 17/203,452 dated Jan. 14, 2022, pp. 1-4.
Office Communication for U.S. Appl. No. 17/510,043 dated Jan. 21, 2022, pp. 1-13.
Office Communication for U.S. Appl. No. 16/741,567 dated Feb. 7, 2022, pp. 1-8.
Office Communication for U.S. Appl. No. 17/530,420 dated Feb. 10, 2022, pp. 1-24.
Office Communication for U.S. Appl. No. 16/004,182 dated Feb. 10, 2022, pp. 1-24.
Office Communication for U.S. Appl. No. 17/115,529 dated Feb. 18, 2022, pp. 1-20.
Office Communication for U.S. Appl. No. 17/203,452 dated Feb. 24, 2022, pp. 1-14.
Office Communication for U.S. Appl. No. 17/484,167 dated Mar. 11, 2022, pp. 1-11.
Office Communication for U.S. Appl. No. 17/062,500 dated Mar. 22, 2022, pp. 1-19.
Office Communication for U.S. Appl. No. 17/504,289 dated Mar. 28, 2022, pp. 1-9.
Office Communication for U.S. Appl. No. 17/203,452 dated Jun. 23, 2021, pp. 1-11.
Office Communication for U.S. Appl. No. 16/152,277 dated Jun. 25, 2021, pp. 1-10.
Office Communication for U.S. Appl. No. 16/004,182 dated Jul. 1, 2021, pp. 1-58.
Office Communication for U.S. Appl. No. 17/160,698 dated Jul. 2, 2021, pp. 1-12.
International Search Report and Written Opinion for International Patent Application No. PCT/US2021/023531 dated Jul. 6, 2021, pp. 1-7.
Office Communication for U.S. Appl. No. 17/062,500 dated Jul. 12, 2021, pp. 1-18.
Office Communication for U.S. Appl. No. 16/775,041 dated Jul. 21, 2021, pp. 1-11.
Office Communication for U.S. Appl. No. 17/504,289 dated Dec. 7, 2021, pp. 1-15.
Office Communication for U.S. Appl. No. 17/114,384 dated Dec. 14, 2021, pp. 1-7.
Office Communication for U.S. Appl. No. 17/190,653 dated Dec. 21, 2021, pp. 1-12.
Office Communication for U.S. Appl. No. 17/508,869 dated Dec. 22, 2021, pp. 1-9.
Office Communication for U.S. Appl. No. 17/491,017 dated Dec. 23, 2021, pp. 1-41.
Office Communication for U.S. Appl. No. 14/859,114 dated Jul. 24, 2017, pp. 1-49.
Office Communication for U.S. Appl. No. 14/658,015 dated Jan. 4, 2018, pp. 1-28.
Office Communication for U.S. Appl. No. 14/859,114 dated Feb. 21, 2018, pp. 1-25.
Office Communication for U.S. Appl. No. 14/595,043 dated May 4, 2017, pp. 1-30.
Office Communication for U.S. Appl. No. 14/595,043 dated May 25, 2018, pp. 1-5.
Office Communication for U.S. Appl. No. 14/595,043 dated Feb. 23, 2018, pp. 1-16.
Office Communication for U.S. Appl. No. 14/658,015 dated Apr. 27, 2017, pp. 1-7.
Office Communication for U.S. Appl. No. 14/859,114 dated May 11, 2018, pp. 1-5.
Office Communication for U.S. Appl. No. 14/859,114 dated Jun. 27, 2018, pp. 1-39.
Office Communication for U.S. Appl. No. 15/957,809 dated Jun. 28, 2018, pp. 1-33.
Office Communication for U.S. Appl. No. 14/595,043 dated Oct. 5, 2018, pp. 1-17.
Office Communication for U.S. Appl. No. 14/658,015 dated Jul. 13, 2018, pp. 1-14.
Office Communication for U.S. Appl. No. 17/491,017 dated May 12, 2022, pp. 1-50.
Office Communication for U.S. Appl. No. 17/484,167 dated May 17, 2022, pp. 1-3.
Office Communication for U.S. Appl. No. 17/484,167 dated Jun. 10, 2022, pp. 1-5.
Office Communication for U.S. Appl. No. 17/203,452 dated Jun. 22, 2022, pp. 1-22.
Related Publications (1)
Number Date Country
20150310035 A1 Oct 2015 US
Provisional Applications (2)
Number Date Country
61982926 Apr 2014 US
61982931 Apr 2014 US