Methods for facilitating efficient analysis of time-based file system properties using histograms and devices thereof

#This technology generally relates to data storage and, more particularly, to methods and devices for improved file system directory analytics using histograms in hierarchical directory tree data structures.

#Tree data structures are commonly used by computing devices to maintain data having an associated hierarchical arrangement. In one exemplary deployment, information regarding a file system can be maintained in a branched tree structure, such as a network attached storage (NAS) directory tree with interior nodes corresponding to directories and leaf nodes corresponding to files and maintaining a collection of properties or values. In a NAS environment, many storage nodes can store portions of a distributed database that each maintain a portion of a distributed directory tree structure associated with the file system. Analytics software can then utilize the directory tree maintained in the distributed database to report on the file system.

#For example, a directory tree can be used by administrators to determine which directories in the file system have not been accessed in a prior historical time period (e.g., the last year) in order to identify space that can be reclaimed via migration to an archival storage tier. In another example, administrators can use a directory tree to determine the directories of the file system for which there has been a significant amount of modification in a prior historical time period (e.g., the last week). However, access and modification queries, for example, currently take a significant amount of resources (e.g., time and processor cycles) to generate a responsive report.

#FIG. 1 is a block diagram of a network environment with exemplary data storage apparatuses;

#FIG. 2 is a block diagram of an exemplary node computing device of one of the data storage apparatuses of FIG. 1;

#FIG. 3 is a flowchart of an exemplary method for facilitating file system analytics using histograms maintained in a directory tree;

#A clustered, distributed network environment 100 that may implement one or more aspects of the technology described and illustrated herein is shown in FIG. 1. The network environment 100 includes data storage apparatuses 102(1)-102(n) that are coupled over a cluster fabric 104 that includes communication network(s) and facilitates communication between the data storage apparatuses 102(1)-102(n) (and one or more modules, components, etc. therein, such as, node computing devices 106(1)-106(n), for example), although any number of other elements or components can also be included in the clustered network environment 100 in other examples.

#This technology provides a number of advantages including methods, non-transitory computer readable media, and computing devices that improve file system directory analytics using histograms in hierarchical directory tree data structures. This technology utilizes modification and access histograms of varying time period granularity for each directory in a directory tree, which are propagated upward to facilitate quicker analytics reporting. The histograms include buckets with values representing the amount (e.g., total file size) of files within a particular directory associated with the histograms that have been accessed or modified within the calendar time period corresponding to the buckets.

#Leveraging the histograms, this technology does not require re-computing oldest or newest files, and thereby advantageously reduces overhead on the file system. For example, if a file is deleted, this technology only decreases a value in an appropriate bucket without requiring a rescan of the directory tree. Additionally, this technology generates near real-time graphical presentations of an entire file system with respect to historical access and modification. With the interactive graphical interfaces, administrators can efficiently drill down into the directory tree to find aged items of interest (e.g., oldest or newest file).