Data files (e.g., word processing documents, presentation documents, spreadsheet documents, pictures or other images, sound files, software applications, executable code, etc.) may be stored in persistent storage locations on storage devices in particular file formats. Accessing one of these data files typically includes retrieval of the entire data file from the persistent storage location.
When the data files are stored in the persistent storage location, the storage device may perform a number of pre-storage processes before writing the data files to the storage location. For example, the storage device may perform security checks on the data files, such as searching for viruses and/or corrupted files. The storage device also may perform property discovery on the data files. The aggregation of one or more of these pre-storage processes may be referred to as a save pipeline. Implementing the save pipeline may be relatively expensive in terms of time and/or resources.
Multiple users may wish to edit a document stored in persistent storage. For example, users may wish to collaboratively author the document. Such multi-user authoring may cause problems in scalability and/or performance. For example, storing changes from multiple users may require a potentially unbounded amount of computation by the save pipeline (e.g., the save pipeline may be implemented for each set of changes for each user). Such a drain on resources may cripple the storage device's ability to handle very frequent file update requests.
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended as an aid in determining the scope of the claimed subject matter.
File updates for a data file may be stored temporarily in a blob storage before being committed to persistent storage. According to aspects, expensive pre-storage processing is performed after coalescing the file updates with the data file to form an updated data file to be committed to the persistent storage. According to other aspects, the file updates are accessible individually or as part of the data file before being committed. In one embodiment, the file updates include incremental updates received from one or more applications. According to other aspects, portions of the data file may be incrementally accessible after being committed to persistent storage.
These and other features and advantages will be apparent from a reading of the following detailed description and a review of the associated drawings. It is to be understood that both the foregoing general description and the following detailed description are explanatory only and are not restrictive of aspects as claimed.
In the following detailed description, references are made to the accompanying drawings that form a part hereof, and in which are shown by way of illustrations specific embodiments or examples. While the disclosure will be described in the general context of program modules that execute in conjunction with an application program that runs on an operating system on a computer system, those skilled in the art will recognize that the disclosure also may be implemented in combination with other program modules. The embodiments described herein may be combined and other embodiments may be utilized without departing from the spirit or scope of the present disclosure. The following detailed description is therefore not to be taken in a limiting sense, and the scope of the invention is defined by the appended claims and their equivalents.
Embodiments of the present disclosure provide an environment in which a storage device, such as a server computing device, may provide efficient processing and storage of data files. Data storage consistent with the principles of the present disclosure is generally provided in a two-stage process. Firstly, data is stored temporarily in a “hot box” or blob storage location. Secondly, some or all of the data within the blob storage location may be transferred to a “cold” or persistent storage location.
As the term is used herein, the hot box or blob storage location refers to a location (e.g., a sandbox) in which data and/or metadata associated with a data file may be stored temporarily as a blob data (e.g., an arbitrary length binary string of data). While stored in the blob storage location, the blob data may be referred to as “hot” data. In one embodiment, the hot data being stored in the blob storage location may include an entire data file or one or more portions (e.g., content and/or metadata) of the data file. In another embodiment, the hot data may include temporary data not intended for persistent storage (e.g., thumbnail previews of the data file).
As the term is used herein, the cold storage location refers to a persistent (i.e., as opposed to temporary) data storage location. Typically, any expensive (e.g., in time, in resources, etc.) data processing is performed only when the hot data is being committed to the cold storage location. Transferring the hot data to the cold storage location may include arranging or integrating the hot data into a data file format recognizable to the storage device.
According to aspects of the disclosure, the blob storage location provides an abstract data model that may be built onto existing infrastructure of the storage device to increase data storage efficiency. For example, appropriate software, such as a handler application program interface (API) disclosed in greater detail herein, may be added to an existing storage device, such as a server computer, to intercept data to be stored persistently, to gather the data in the blob storage location until a predetermined condition is satisfied, and subsequently to transfer the data from the blob storage location to a preexisting cold storage location (e.g., using a preexisting save pipeline).
According to other aspects of the disclosure, the blob storage location may enable incremental storage of and access to data files stored on the storage device. The blob storage location can store data as unformatted blob data. Accordingly, the data being stored in the blob storage location need not conform to an underlying file format of the cold storage location until committed to the cold storage location. Because the blob storage location is agnostic of the underlying file format of the data being stored, portions of or changes to a data file may be stored in and accessed from the blob storage location instead of storing and accessing the entire data file. For example, in one embodiment, one or more data units (e.g., paragraphs, pictures, text blocks, objects, etc.) of a data file may be stored in the blob storage location. In another embodiment, metadata indicating differences between two versions of a file may be stored in the blob storage location.
The data stored in the blob storage location may be coalesced into a proper file format if and when appropriate (e.g., when being committed to the cold storage location). For example, the data may be processed by a file format specific algorithm to arrange the data into an appropriate file format. In one embodiment, after being coalesced, the data may be accessed as a single data file. In another embodiment, additional software may be provided to enable incremental access to the data files stored in the cold storage location as disclosed in greater detail herein.
Referring now to the drawings,
A transfer determination module 106 determines whether some or all of the data contained in the blob storage location should be transferred to a more persistent storage location or arranged in a more persistent storage format. For example, the transfer determination module 106 may determine whether the data stored in the temporary blob storage location includes data intended to replace or supplement data stored in a cold storage location.
If the transfer determination module 106 determines none of the data should be transferred, then the storage process 100 proceeds to an empty operation 110, which removes data from the temporary blob storage location without first committing the data to a cold storage location. For example, the empty operation 110 may delete metadata (e.g., a thumbnail image) associated temporarily with the file. The storage process 100 completes and ends at a stop module 112.
If the transfer determination module 106 determines at least some of the data should be stored in a more persistent manner, however, then a commit operation 108 transfers at least some of the data from the blob storage location to a cold storage location. For example, the commit operation 108 may store the data from the blob storage location in a cold storage database. In one embodiment, the commit operation 108 performs data processing (e.g., anti-virus checking, property discovery, or any other expensive data processing operation) on the data before storing the data at the cold storage location.
In one embodiment, the commit operation 108 stores only data obtained from the blob storage location into the cold storage location. In another embodiment, the commit operation 108 merges newly received data with data previously stored in the blob storage location (e.g., by one or more executions of the batch operation 104) before storing the merged data in the cold storage location. In another embodiment, the commit operation 108 merges data stored at the blob storage location with data already stored in the cold storage location.
The empty operation 110 removes data from the temporary blob storage location. In one embodiment, the empty operation 110 removes all data contained in the temporary blob storage location. In another embodiment, the empty operation 110 may remove a set or range of data. For example, the empty operation 110 may remove any data saved in the cold storage location. The storage process 100 completes and ends at a stop module 112 as described above.
The storage device 210 is communicatively coupled to at least a first cold storage 219 and at least a first blob storage 217 associated with the first cold storage 219. In one embodiment, the aggregation of data stored in the first blob storage 217 and the first cold storage 219 represents the current state of a document stored on the storage device 210. In an embodiment, additional blob storages may be associated with the first cold storage 219. In another embodiment, the first blob storage 217 may be associated with additional cold storages.
In general, the first blob storage 217 and the first cold storage 219 each may be maintained on the storage device 210 or at any desired location that is communicatively coupled to the storage device 210. For example, the blob storage 217 may be maintained locally on the storage device 210 and the cold storage 219 may be maintained at a remote location communicatively coupled to the storage device 210. In one embodiment, one or more characteristics of the blob storage 217 may be optimized for speed (e.g., length of time to store and/or access the data). In one embodiment, one or more characteristics of the cold storage 219 may be optimized for long term storage (e.g., to emphasize reliability over speed).
The storage device 210 (e.g., a server computing device) is configured to interact with at least a first user device 220 (e.g., a client computing device). For example, the storage device 210 may be configured to receive an access request from a first user device 220 to store data from the first user device 220 on the storage device 210. In one embodiment, the first user device 220 also may retrieve data from the storage device 210. As shown in
The first user device 220 of
In general, the storage device 210 includes a handler 215 that is configured to communicate with applications executing on the storage device 210, applications executing on the user device 220, or with any other applications communicatively coupled to the storage device 210. In one embodiment, the handler 215 does not determine a file format of the data received from or sent to the applications. In such an embodiment, the handler 215 implements processes that execute independently of an underlying file format of the data.
The handler 215 of the storage device 210 may receive data from the application 222 of the first user device 220 and store the data in the first blob storage 217. For example, the handler 215 periodically may receive updates to the data file DOC 225 (e.g., incremental changes, new versions of the document, etc.) being authored by the application 222 and may store these updates in the first blob storage 217.
In some embodiments, the handler 215 may receive updates for the same data file from multiple user devices. For example, multiple users may edit a data file simultaneously and attempt to share changes. If two or more of the received updates are associated with the same data file, then the handler 215 may store these received updates in the same blob storage location (e.g., the first blob storage 217). Updates relating to different data files, however, are typically stored in different blob storages (e.g., different database tables within one or more blob storage locations).
Subsequently, the handler 215 may transfer the updates from the first blob storage 217 to the first cold storage 219. Embodiments of the handler 215 may coalesce the data stored in the first blob storage 217 with cold data already stored in first cold storage 219. In one embodiment, coalescing the data may include arranging the data according to a particular file format. In such an embodiment, the handler 215 implements processes that execute in accordance with an underlying file format of the data being processed. Embodiments of the handler 215 may refrain from executing the pre-storage processes of the save pipeline on the data being stored into the first blob storage 217. Rather, the pre-storage processes may be performed on the coalesced data when the coalesced data is saved in the first cold storage 219.
The handler 215 also may receive access requests for data from applications communicatively coupled to the storage device 210 (e.g., application 222 on the first user device 220). Such applications may be agnostic of the architecture and storage environment of the storage device 210. Accordingly, the requesting application need not know how the requested data is stored on the storage device (e.g., in the first blob storage 217 or in the first cold storage 219). Rather, the handler 215 of the storage device 210 determines where the requested data is stored, retrieves the requested data from the appropriate storage 217, 219, and sends the requested data to the requesting application. Accordingly, in one embodiment, a second application (not shown) may request and receive access to data provided by the application 222 and stored in the first blob storage 217.
An add operation 306 accesses a blob storage, such as the first blob storage 217 of
In some embodiments, the add operation 306 may read data from the blob storage or a cold storage before adding data to the blob storage. For example, in one embodiment, the add operation 306 may validate the data being added to the blob store is consistent with data stored in the cold store. In another embodiment, the add operation 306 also may be able to use some data from the cold storage to optimize the storage of the new data in the blob storage (e.g., such that subsequent reads are faster).
A determination module 308 determines whether to commit the data stored at the blob storage to a cold storage. In some embodiments, the determination module 308 checks whether instructions to commit the changes have been provided (e.g., by the application 222 of the first user device 220, by the handler 215, etc.). For example, a user of the user device 222 may trigger a transfer of data from the blob storage to the cold storage by selecting a “save” option when editing a data file. In other embodiments, however, the determination module 308 may check other conditions to determine whether to commit the data. For example, the determination module 308 may elect to commit the blob storage data when the blob storage reaches a predetermined size or when a predetermined time limit elapses.
If the determination module 308 determines the data in the blob storage should not yet be committed to the cold storage, then the handling process 300 may complete and end at a stop module 312. If the determination module 308 determines the data in blob storage should be committed, however, then the handling process 300 may proceed to a commit operation 310. The commit operation 310 transfers the data previously stored in the blob storage into the cold storage.
In one embodiment, the commit operation 310 stores all data contained in the blob storage to the cold storage. In another embodiment, the commit operation 310 only commits to the cold storage a portion of the data contained in the blob storage (e.g., all data added before or after a given date and time, all data provided by a particular user application, etc.). The handling process 300 completes and ends at the stop module 312 as described above.
Coalesce operation 404 integrates the data that has been stored in the blob storage. In one embodiment, the coalesce operation 404 may integrate the data stored in the blob storage with any data stored in the cold storage. In one embodiment, the coalesce operation 404 retrieves the entire data file stored in the cold storage. In another embodiment, however, the coalesce operation 404 retrieves one or more relevant portions of the data file to be coalesced with the data from the blob storage. For example, the coalesce operation 404 may accesses the data file in the cold storage incrementally using file format metadata as will be discussed in greater detail herein.
Optionally, the coalesce operation 404 may determine properties of the blob storage data, such as the type of data, the file format of the data, or the relationship between the data stored in the blob storage and the data stored in the cold storage. The data may be integrated differently depending on the determined relationship. For example, in one embodiment, the coalesce operation 404 may determine data obtained from the blob storage includes a new data file to replace the data file stored in the cold storage. In another embodiment, the coalesce operation 404 may determine the data obtained from the blob storage includes a series of incremental updates to be instantiated into the data file stored in the cold storage as will be discussed in greater details herein. In another embodiment, the coalesce operation 404 may determine the data obtained from the blob storage includes metadata to be associated with the data file stored in the cold storage (e.g., via a metadata table auxiliary to the file).
A process operation 406 analyzes the coalesced data and performs any desired type of data processing before the coalesced data in transferred to the cold storage. For example, in one embodiment, the process operation 406 may perform security checks (e.g., may check the coalesced data from viruses, spy-ware, ad-ware, and/or other issues). In another embodiment, the process operation 406 performs property discovery on the coalesced data. In other embodiments, the process operation 406 may perform hyperlink fix-up, firing events, triggering of workflow, and other such processes.
A store operation 408 saves the coalesced and processed data into a cold storage, such as cold storage 219 (see
The data processing and storage system 500 includes a communication module 530, an access handler 540, a blob storage 560, and a cold storage 570. In general, the communication module 530 manages communication (see arrows 525 and 535) between the access handler 540 and one or more applications or processes (e.g., an application 522 on a computing device 520) providing data to be stored or requesting stored data. The access handler 540 stores data to and retrieves data from the blob storage 560 and the cold storage 570.
In one embodiment, the applications providing and requesting data are implemented on one or more remote computing devices coupled to the server 510. In another embodiment, however, the communication module 530 is configured to communicate with an application executing on the server 510 to send and receive data updates. For ease in understanding, the remainder of this document will assume any application providing data to be stored or requesting stored data is executing on a separate computing device from the storage device.
In general, the communication module 530 communicates with the applications providing or requesting data using one or more communication protocols. In one embodiment, the communication module 530 may include one or more communication APIs 532. The applications may be agnostic to the architecture and processes of the server 510 as long as the applications are familiar with the communication protocol used by the communication module 530. Similarly, the server 510 may be agnostic to the architecture of any computing devices communicatively coupled to the server 510 (e.g., the computing device 520) and the processes of any applications executing thereon.
In the example shown in
The communication module 530 also may receive requests from the application 522 to access documents (not shown) stored on the server 510. In such embodiments, the communication module 530 forwards the requests to the access handler 540, obtains the requested data from the access handler 540, and transmits the requested data back to the client computing device 520. In one embodiment, the communication module 530 provides the requested data to the application 522 client computing device 520 without determining an underlying file format of the data.
In general, the access handler 540 includes an access module 542 that manages access to the blob storage 560 and the cold storage 570. In one embodiment, the access module 542 may include one or more access APIs (not shown). In one embodiment, the access module 542 may abstract how data is stored and accessed on the server 510 by accessing the blob storage 560 and cold storage 570 using preexisting storage APIs 550 provided on the server 510 (see arrow 545). The storage APIs 550 each may be tailored to the architecture of the server 510 to provide efficient read and/or write access to server memory implementing the blob and cold storages 560, 570, respectively.
In one embodiment, different storage APIs 550 may be provided for performing the same basic function (e.g., reading from the blob storage 560, writing to the blob storage 560, or reading from the cold storage 570) with different types of data (e.g., data having different file formats). The access module 542 may select which preexisting storage APIs 550 to utilize based on the type of data being stored or accessed. In one embodiment, the access module 542 determines the type of data being stored based on information provided by the providing and/or requesting application via the communication module 530.
The access handler 540 also includes a commit module 544 that transitions that data from the blob storage 560 to the cold storage 570. In general, the commit module 544 retrieves data currently stored in the blob storage 560, commits at least some of the data to the cold storage 570 through a save pipeline, and clears the committed data from the blob storage 560. In one embodiment, the commit module 544 may include one or more commit APIs (not shown) for committing different types and/or formats of data to the cold storage 570.
In one embodiment, the client computing device 520 may trigger the commit module 544 to begin the commit process. For example, in
In other embodiments, however, the commit module 544 may trigger the commit process without interaction with a user application. For example, in one embodiment, the commit module 544 may provide instructions to commit when the commit module 544 determines the blob storage 560 has reached a predetermined size or has filled a predetermined percent of its capacity. In another embodiment, the commit module 544 may provide instructions to commit when the commit module 544 determines a predetermined length of time has elapsed since a previous implementation of the commit process. In other embodiments, the commit module 544 may trigger the commit process based on other such triggering criteria.
In some embodiments, the data processing and storage system 500 also may include file format metadata (FFM) storage 580 in which file format metadata associated with a particular file may be stored. In general, file format metadata enables the access handler 540 or other applications on the storage device 510 to access a data file stored in the cold storage 570 incrementally based on the underlying file format of the stored data file. For example, the file format metadata may include an index representing a general file structure indicating where data can be found within the stored data file. Accordingly, the file format metadata may enable the access handler 540 to retrieve one or more requested data units (e.g., a paragraph) of a data file (e.g., a word processing document) instead of retrieving the entire data file.
Incremental access may enhance the efficiency with which data is retrieved from the cold store 570 and may minimize the resources utilized in the retrieval. For example, in one embodiment, the file format metadata may be stored on the storage device 510 and the cold storage 570 may be maintained at a remote location (not shown). In such an embodiment, accessing the file format metadata locally, determining a relevant section of the data file, and requesting the relevant section from the remote location may be cheaper (e.g., in terms of processing time and/or resources) than retrieving the entire data file from the remote location. In other embodiments, however, the file format metadata may be stored as a data file in the cold storage 570 or as data in the blob storage 560. Updates to the file format metadata also may be stored as data in the blob storage 560.
File format metadata may be generated or updated by the access handler 540 or other module capable of identifying the structure and format of data when data from the blob storage 560 is committed to the cold storage 570. In one embodiment, the file format metadata includes indices and offsets which allow the access handler 540 to perform the incremental access of the data file in the cold storage 570. For example, the access handler 540 may parse the data file to identify relevant data units within the data file and to determine the offset location of the data units for storage as metadata offsets. In one embodiment, the file format metadata is stored as a database.
As noted above, a data processing and storage environment having features that are examples of inventive aspects in accordance with the principles of the disclosure can be implemented on a computing device (e.g., a server computer, a personal computer, a notebook computer, a PDA, a Smartphone, or any other such storage device). A non-limiting embodiment of a storage system 600 configured to implement the data processing and storage environment 500 of
In
In a basic configuration, the computing device 610 typically includes at least one processing unit 615 for executing applications and processing data stored in system memory 620. Depending on the exact configuration and type of computing device 610, the system memory 620 may include, but is not limited to, RAM, ROM, EEPROM, flash memory, CD-ROM, digital versatile disks (DVD) or other optical storage devices, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or other memory technology.
System memory 620 typically stores an operating system 622, such as the WINDOWS® operating systems from MICROSOFT CORPORATION of Redmond, Wash., suitable for controlling the operation of the computing device 610. System memory 620 also may include a handler application 624, a blob storage 626, and a cold storage 628. The handler application 624 may include a communication application program interface (“COMMUN API”) 621, an access API 623, and a commit API 625. The system memory 620 also may store one or more software applications 627, such as document management applications for storing and providing access to documents or document authoring applications for generating and editing documents.
Server computing device 610 also may include one or more input device(s) 630, such as a keyboard, mouse, pen, keypad, D-pad, scroll-wheel, jog-wheel, voice input device, touch input device, etc., for entering and manipulating data. Output device(s) 635, such as a display screen, speakers, printer, etc., also may be included with server computing device 610. These input devices 630 and output devices 635 are well known in the art and need not be discussed at length herein.
The server computing device 610 also may include communication device media 640 that allow the device 610 to communicate with other computing devices, for example, the user computing device 220 of
Referring to
In one embodiment, the unique data key is generated on a storage device implementing the blob storage 700. In an embodiment, the unique data key is generated by a handler, such as handler 540 of
As noted above, a handler (e.g., access handler 540 of
The blob database 810 also includes a third data field 816 for storing a data tag. In general, a data tag may include any information to be associated with the data blob in the second data field 814. For example, a data tag may include metadata about the data blob to be stored (e.g., a timestamp), any data provided by the application requesting storage of the data blob, metadata regarding the blob database 810, or any other data that may be useful to associate with the data blob in the second data field 814. In one embodiment, data tags enable an application (e.g., application 522 of
The add process 900 initializes and begins at a start module 902 and proceeds to a receive operation 904. The receive operation 904 receives (e.g., from an application on a remote computing device) a request to add data to the blob data base 710, 810. Typically, the request includes the data to be stored.
A generate operation 906 creates a unique data key and adds the unique data key to a first data field (e.g., data field 712 of
A first put operation 908 adds the data to be stored to a second data field (e.g., data field 714 of
An optional second put operation 910 may add a tag to a third data field (e.g., data field 816 of
A return operation 912 returns the data key associated with the data. For example, in one embodiment, the return operation 912 sends the data key to an access module (e.g., access module 542 of
In one embodiment, the access module enables requesting applications to remain agnostic of the blob storage database format. In another embodiment, the access module forwards the data key to a communication module (e.g., communication module 530 of
The receive operation 1004 receives a request from an application to retrieve data from the blob storage. In one embodiment, the receive operation 1004 also receives one or more data keys (e.g., a range of data keys) associated with the data to be retrieved. In another embodiment, the receive operation 1004 receives one or more tags (e.g., a range of tags) associated with the data to be retrieved. In other embodiments, the receive operation 1004 receives search conditions or other information by which the data to be retrieved may be identified.
A query operation 1006 searches the blob storage (e.g., blob database 710) using the received data key(s), the received tag(s), and/or other received information to obtain the associated data. For example, embodiments of the query operation 1006 may search the data entries in the blob storage for a particular data key, a range of data keys, or all data entries associated with a particular tag. In another embodiment, the query operation 1006 may search the blob storage for data entries meeting certain conditions, such as the most recent entry (e.g., highest data key in sequence), the oldest entry (e.g., lowest data key in sequence), the biggest entry (e.g., occupying most memory resources), or other such conditions.
A return operation 1008 sends the retrieved data to the requesting application. In some embodiments, the return operation 1008 passes the retrieved data to an access module. In one embodiment, the access module forwards the data to a communication module, which forwards the data to the requesting application. In another embodiment, the access module processes the data to satisfy an underlying file format and forwards the processed data to the requesting application. The retrieve process 1000 completes and ends at a stop module 1010.
The delete process 1100 initializes and begins at a start module 1102 and proceeds to a receive operation 1104. The receive operation 1104 receives a request to delete data from the blob storage (e.g., blob storage 700, 800 of
A find operation 1106 accesses the blob storage database using the received data key(s), the received tag(s), the received data, and/or other received information to locate the data entries to be deleted. A remove operation 1108 removes the data associated with the data entries from the blob storage database. The delete process 1100 completes and ends at a stop module 1110.
The principles of the present disclosure can be better understood by walking through an example application.
The handler 1220 enables the applications 1212, 1214, 1216 to access files stored on the data storage system 1200. For example, the handler 1220 may enable the applications 1212, 1214, 1216 to access (e.g., retrieve, save, modify, etc.) File A and/or File B stored in the cold storage 1250 of the data storage system 1200. The handler 1220 also manages when modifications made to files, such as File A and File B, are stored in blob storage (e.g., blob storages 1230, 1240) and when the modifications are coalesced and transferred to the cold storage 1250.
In general, each blob storage 1230, 1240 is associated with at least one data file stored in the cold storage 1250. In one embodiment, each blob storage 1230, 1240 may be associated with multiple cold data files. By associating a single blob storage with multiple cold data files, data updates common to the cold data files may be stored and committed efficiently (e.g., by tail merging the data). In other embodiments, however, each cold data file (e.g., File A and File B) may be associated with one or more unique blob storages (e.g., each of which may have a unique identifier). For example, each user editing a cold data file may have a unique blob storage (or section of a blob storage) for storing changes to the cold data file made by the user.
For ease in understanding in the example shown in
The following description will walk through some of the operational flows disclosed above to trace through a first example editing session in which the first and second applications 1212, 1214 edit File A and a second example editing session in which the third application 1216 edits File B.
In
With respect to the first editing session of File A, the handling process 300 (
An add operation 306 accesses the first blob storage 1230 and stores the received data (e.g., a delta file Δ1) in the first blob storage 1230 (see
A generate operation 906 creates a new data key (e.g., data key “K1”) and adds the new data key K1 to a first data field 1232 in a new data entry 1231 (see
A return operation 912 returns the data key K1 associated with the data Δ1 to the handler 1220. In one embodiment, the return operation 912 also returns a blob storage identifier (not shown). Subsequently, the handler 1220 may use the returned data key K1 and optionally the blob storage identifier to access the data Δ1 while the data Δ1 is stored in the blob storage 1230. The add process 900 completes and ends at a stop module 914. The results of the add process 900 with respect to the blob storage 1230 are shown in
Referring again back to handling process 300, a determination module 308 determines whether to commit the data (e.g., delta Δ1) stored in the blob storage 1230 to the cold storage 1250. In this example walkthrough, the determination module 308 determines the first application 1212 has not provided instructions to commit and no other commit criteria (e.g., time elapsed, size of blob storage, etc.) has been satisfied. Accordingly, the handling process 300 completes and ends at a stop module 312.
The handling process 300 repeats each time new storage instructions and data for File A are received from one of the applications 1212, 1214, 1216 during the first editing session. For example, when additional incremental changes Δ2 are received from the second application 1214, the handling process 300 initializes and begins again at the start module 302 and proceeds to the receive operation 304. The receive operation 304 obtains from the second application 1214 the data Δ2 to be stored and instructions to store the data Δ2 at the storage system 1200.
The add operation 306 accesses the first blob storage 1230 and stores the received data Δ2 in the first blob storage 1230 (see
The determination module 308 of handling process 300 determines whether to commit the data Δ1, Δ2 stored in the blob storage 1230 to the cold storage 1250. In this iteration of the walkthrough, the determination module 308 determines the instructions to commit the modifications to persistent storage have been received (e.g., from the second application 1214 of
The commit operation 310 stores the data previously stored in the blob storage 1230 into the cold storage 1250. In the example shown, the blob storage 1230 is a global blob storage (e.g., is common to all accessing applications 1212, 1214). Accordingly, the commit instructions provided by the second application 1214 result in the transfer of data provided by both the first and second applications 1212, 1214 to the cold storage 1250. In other embodiments, however, each application may be associated with its own blob storage or partitioned section of the blob storage for a particular data file and, accordingly, may commit only its own instructions. The handling process 300 completes and ends at the stop module 312.
One example process for implementing the commit operation 310 of
In some embodiments, the coalesce operation 404 determines how the data stored in the blob storage 1230 relates to the data stored in the cold storage 1250. For example, the coalesce operation 404 may determine the data Δ1, Δ2 stored in the blob storage 1230 (see
An optional process operation 406 analyzes the data (e.g., modified File A) and determines whether any action should be taken before storing the data in the cold storage 1250. For example, security checks or property discovery may be performed. A store operation 408 saves the data (e.g., modified File A) into the cold storage 1250. In one embodiment, the store operation 408 replaces File A with modified File A. An empty operation 410 removes the transferred data from the blob storage 1230 (see
One example process for implementing the empty operation 410 of the commit process 400 is the delete process 1100 disclosed above with reference to
A find operation 1106 accesses the blob storage 1230 and a delete operation 1108 removes the data Δ1 , Δ2 associated with the data entries 1231, 1233 of the blob storage 1230. In this example walkthrough, the find operation 1106 does not need to search the blob storage 1230 for specific data entries, but rather identifies all data entries 1231, 1233 containing data sets, such as Δ1, Δ2. The delete process 1100 completes and ends at a stop module 1110. The results of the commit process 400 with respect to the blob storage 1230 are shown in
The disclosure will now walk through the second example editing session with respect to File B. The third application 1216 requests and receives content and metadata of File B from the handler 1220, which obtains File B from the cold storage 1250. The third application 1216 modifies the content and/or the metadata of File B to create a revised File B1.
The third application 1216 then sends File B1 as a complete data file to the handler 1220 for storage on the storage system 1200. When the handler 1220 receives the File B1 and the instructions to store the File B1, the handling process 300 (
The add operation 306 accesses the second blob storage 1240 associated with the File B and stores the received data File B1 in the second blob storage 1240. For example, the add operation 306 may generate a new data key Y1 and add the new data key Y1 and the received data File B1 to a first data entry 1241 of the second blob storage 1240 using the add process 900 as described above (see
The determination module 308 of handling process 300 determines whether to commit the data (e.g., File B1) stored in the blob storage 1240 to the cold storage 1250. In this iteration of the example walkthrough, the determination module 308 determines no instructions to commit data to persistent storage have been received (e.g., from any of the applications 1212, 1214, 1216 of
The handling process 300 repeats each time new storage instructions and data for File B are received from one of the applications 1212, 1214, 1216. For example, when another revised copy File B2 of the document File B is sent from the third application 1216, the handling process 300 initializes and begins again at the start module 302 and proceeds to the receive operation 304. The receive operation 304 obtains from the third application 1216 the data File B2 to be stored and instructions to store the data File B2 on the storage system 1200.
The add operation 306 accesses the second blob storage 1240 and stores the received data File B2 in the first blob storage 1240. For example, the add operation 306 may generate a new data key Y2 and add the new data key Y2 and the received data File B2 to a second data entry 1243 of the second blob storage 1240 using the add process 900 as described above. The new data key Y2 may be returned to the handler 1220 for use in subsequent access requests for File B2. The results of the add operation 306 with respect to the blob storage 1250 are shown in
The determination module 308 of handling process 300 determines whether to commit the data File B1, File B2 stored in the blob storage 1240 to the cold storage 1250. In this iteration of the example walkthrough, the determination module 308 determines instructions to commit the modifications represented by data File B1 and File B2 to persistent storage have been received. Accordingly, the handling process 300 completes and ends at a stop module 312.
On the third iteration of this example walkthrough for File B, one of the applications 1212, 1214, 1216 subsequently provides metadata M1 (e.g., a thumbnail image, an abstract summary, etc.) associated with File B for storage without providing instructions to commit the updates to persistent storage. The metadata is added to the blob storage 1240 using the processes described above for adding File B1 and File B2 (see
At any point during the editing sessions, one or more of the applications 1212, 1214, 1216 may access the data stored in the blob storages 1230, 1240. For example, if the first and second applications 1212, 1214 are simultaneously editing separate copies (not shown) of the document File A, then the first and second applications 1212, 1214 may synchronize their respective copies by each periodically checking for changes to File A saved to the storage system 1200 by the other application. In one embodiment, each application may send a timestamp (e.g., as a tag 816 of
One example process by which the data entries may be retrieved from the storage system 1200 is the retrieve process 1000 of
A query operation 1006 searches the blob storage 1240 using the received timestamp to determine the data entry associated with the timestamp. The query operation 1006 also may determine which data entries were generated after the data entry associated with the timestamp and obtain the data from these data entries. A return operation 1008 sends the obtained data to the handler 1220, which may present the obtained data to the requesting application. In one embodiment, the handler 1220 organizes the obtained data into a file format known to the requesting application. The retrieve process 1000 completes and ends at a stop module 1010.
Embodiments of the disclosure may be implemented as a computer process (method), a computing system, or as an article of manufacture, such as a computer program product or computer readable media. The processes (programs) can be implemented in any number of ways, including the structures described in this document. One such way is by machine operations, of devices of the type described in this document. Another optional way is for one or more of the individual operations of the methods to be performed on a computing device in conjunction with one or more human operators performing some of the operations. These human operators need not be collocated with each other, but each can be only with a machine that performs a portion of the program.
The computer program product may be a computer storage media readable by a computer system and encoding a computer program of instructions for executing a computer process. The computer program product may also be a propagated signal on a carrier readable by a computing system and encoding a computer program of instructions for executing a computer process. The term computer readable media as used herein includes both storage media and communication media.
Those skilled in the art will appreciate that the disclosure may be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, and the like. The disclosure may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices. Generally, program modules include routines, programs, components, data structures, and other types of structures that perform particular tasks or implement particular abstract data types.
Number | Name | Date | Kind |
---|---|---|---|
4855580 | Van Maanen, Jr. | Aug 1989 | A |
5107443 | Smith et al. | Apr 1992 | A |
5142619 | Webster, III | Aug 1992 | A |
5313394 | Clapp | May 1994 | A |
5339389 | Bates et al. | Aug 1994 | A |
5446842 | Schaeffer et al. | Aug 1995 | A |
5486686 | Zdybel | Jan 1996 | A |
5535332 | Ishida | Jul 1996 | A |
5568640 | Nishiyama | Oct 1996 | A |
5623659 | Shi et al. | Apr 1997 | A |
5630138 | Raman | May 1997 | A |
5664186 | Bennett et al. | Sep 1997 | A |
5671428 | Muranaga et al. | Sep 1997 | A |
5692178 | Shaughnessy | Nov 1997 | A |
5729734 | Parker | Mar 1998 | A |
5751958 | Zweben | May 1998 | A |
5781732 | Adams | Jul 1998 | A |
5781908 | Williams et al. | Jul 1998 | A |
5787262 | Shakib et al. | Jul 1998 | A |
5835950 | Cho | Nov 1998 | A |
5963931 | Fagg | Oct 1999 | A |
6000945 | Sanchez-Lazer | Dec 1999 | A |
6006239 | Bhansali et al. | Dec 1999 | A |
6026461 | Baxter et al. | Feb 2000 | A |
6055546 | Pongracz et al. | Apr 2000 | A |
6065026 | Cornelia | May 2000 | A |
6067551 | Brown et al. | May 2000 | A |
6073161 | DeBoskey et al. | Jun 2000 | A |
6088702 | Plantz | Jul 2000 | A |
6202085 | Benson et al. | Mar 2001 | B1 |
6209010 | Gauthier | Mar 2001 | B1 |
6209128 | Gerard et al. | Mar 2001 | B1 |
6240414 | Beizer et al. | May 2001 | B1 |
6244575 | Vaartstra | Jun 2001 | B1 |
6275935 | Barlow | Aug 2001 | B1 |
6317777 | Skarbo et al. | Nov 2001 | B1 |
6324544 | Alam et al. | Nov 2001 | B1 |
6327584 | Xian et al. | Dec 2001 | B1 |
6327611 | Everingham | Dec 2001 | B1 |
6341291 | Bentley et al. | Jan 2002 | B1 |
6342906 | Kumar et al. | Jan 2002 | B1 |
6363352 | Dailey et al. | Mar 2002 | B1 |
6411965 | Klug | Jun 2002 | B2 |
6430576 | Gates et al. | Aug 2002 | B1 |
6438548 | Grim, III et al. | Aug 2002 | B1 |
6438563 | Kawagoe | Aug 2002 | B1 |
6446093 | Tabuchi | Sep 2002 | B2 |
6526434 | Carlson et al. | Feb 2003 | B1 |
6529905 | Corsberg et al. | Mar 2003 | B1 |
6560614 | Barboy et al. | May 2003 | B1 |
6560620 | Ching | May 2003 | B1 |
6574377 | Cahill et al. | Jun 2003 | B1 |
6610104 | Lin et al. | Aug 2003 | B1 |
6662209 | Potts, Jr. et al. | Dec 2003 | B2 |
6681371 | Devanbu | Jan 2004 | B1 |
6681382 | Kakumani | Jan 2004 | B1 |
6687878 | Eintracht et al. | Feb 2004 | B1 |
6711718 | Pfeil et al. | Mar 2004 | B2 |
6751618 | Germscheid et al. | Jun 2004 | B1 |
6757678 | Myllymaki | Jun 2004 | B2 |
6757696 | Multer et al. | Jun 2004 | B2 |
6757767 | Kelleher | Jun 2004 | B1 |
6757871 | Sato et al. | Jun 2004 | B1 |
6760840 | Shimbo et al. | Jul 2004 | B1 |
6772165 | O'Carroll | Aug 2004 | B2 |
6842768 | Shaffer | Jan 2005 | B1 |
6854087 | Takeo et al. | Feb 2005 | B1 |
6925476 | Multer et al. | Aug 2005 | B1 |
6976213 | Letourneau et al. | Dec 2005 | B1 |
6983416 | Bae | Jan 2006 | B1 |
6993522 | Chen et al. | Jan 2006 | B2 |
7007235 | Hussein et al. | Feb 2006 | B1 |
7024429 | Ngo et al. | Apr 2006 | B2 |
7024430 | Ingraham et al. | Apr 2006 | B1 |
7039679 | Mendez et al. | May 2006 | B2 |
7047407 | Itoh | May 2006 | B2 |
7053839 | Cassel | May 2006 | B2 |
7058663 | Johnston et al. | Jun 2006 | B2 |
7065633 | Yates, Jr. | Jun 2006 | B1 |
7069505 | Tamano | Jun 2006 | B2 |
7089278 | Churchill et al. | Aug 2006 | B1 |
7110936 | Hiew | Sep 2006 | B2 |
7111237 | Chan | Sep 2006 | B2 |
7124151 | Choi | Oct 2006 | B1 |
7124362 | Tischer | Oct 2006 | B2 |
7127501 | Beir et al. | Oct 2006 | B1 |
7149776 | Roy et al. | Dec 2006 | B1 |
7155465 | Lee et al. | Dec 2006 | B2 |
7185277 | Bernstein et al. | Feb 2007 | B1 |
7200668 | Mak | Apr 2007 | B2 |
7203708 | Liu et al. | Apr 2007 | B2 |
7209948 | Srinivasa | Apr 2007 | B2 |
7225189 | McCormack et al. | May 2007 | B1 |
7240091 | Hopmann et al. | Jul 2007 | B1 |
7249314 | Walker | Jul 2007 | B2 |
7293049 | Kadyk et al. | Nov 2007 | B2 |
7310657 | Nakamura | Dec 2007 | B2 |
7315978 | Giles | Jan 2008 | B2 |
7328243 | Yeager | Feb 2008 | B2 |
7346705 | Hullot | Mar 2008 | B2 |
7401291 | Ramaley | Jul 2008 | B2 |
7496577 | Williamson | Feb 2009 | B2 |
7529780 | Braginsky et al. | May 2009 | B1 |
7536641 | Rosenstein et al. | May 2009 | B2 |
7565603 | Jones et al. | Jul 2009 | B1 |
7577906 | Friedrichowitz | Aug 2009 | B2 |
7594163 | Slack-Smith | Sep 2009 | B2 |
7603357 | Gourdol | Oct 2009 | B1 |
7610287 | Dean | Oct 2009 | B1 |
7647292 | Hayashi | Jan 2010 | B2 |
7650336 | Herrmann | Jan 2010 | B1 |
7664750 | Frees | Feb 2010 | B2 |
7694217 | Croft | Apr 2010 | B2 |
7714222 | Taub | May 2010 | B2 |
7761784 | Parks | Jul 2010 | B2 |
7788326 | Buchheit | Aug 2010 | B2 |
7792788 | Melmon | Sep 2010 | B2 |
7839532 | Brawn | Nov 2010 | B2 |
7912811 | Hodel-Widmer | Mar 2011 | B2 |
7941399 | Bailor | May 2011 | B2 |
7962853 | Bedi et al. | Jun 2011 | B2 |
8019780 | Pinkerton et al. | Sep 2011 | B1 |
8028229 | Bailor | Sep 2011 | B2 |
20010018697 | Kunitake et al. | Aug 2001 | A1 |
20020007287 | Straube et al. | Jan 2002 | A1 |
20020022122 | Hirata | Feb 2002 | A1 |
20020065848 | Walker et al. | May 2002 | A1 |
20020069192 | Aegerter | Jun 2002 | A1 |
20020188598 | Myllymaki | Dec 2002 | A1 |
20030028600 | Parker | Feb 2003 | A1 |
20030093760 | Suzuki | May 2003 | A1 |
20030097410 | Atkins et al. | May 2003 | A1 |
20030097638 | Tamano | May 2003 | A1 |
20030115481 | Baird | Jun 2003 | A1 |
20030140067 | Sesek | Jul 2003 | A1 |
20030159105 | Hiebert | Aug 2003 | A1 |
20030167281 | Cohen et al. | Sep 2003 | A1 |
20030172113 | Cameron et al. | Sep 2003 | A1 |
20030172168 | Mak et al. | Sep 2003 | A1 |
20030208534 | Carmichael | Nov 2003 | A1 |
20040039829 | Bucher | Feb 2004 | A1 |
20040068505 | Lee et al. | Apr 2004 | A1 |
20040107224 | Bera | Jun 2004 | A1 |
20040122870 | Park et al. | Jun 2004 | A1 |
20040122898 | Srinivasa | Jun 2004 | A1 |
20040122912 | Kim et al. | Jun 2004 | A1 |
20040133858 | Barnett | Jul 2004 | A1 |
20040143630 | Kaufmann | Jul 2004 | A1 |
20040172395 | Edelstein et al. | Sep 2004 | A1 |
20040177343 | McVoy | Sep 2004 | A1 |
20040199550 | Ito et al. | Oct 2004 | A1 |
20040205539 | Mak | Oct 2004 | A1 |
20040205653 | Hadfield et al. | Oct 2004 | A1 |
20040230903 | Elza et al. | Nov 2004 | A1 |
20040239700 | Baschy | Dec 2004 | A1 |
20040243644 | Steere et al. | Dec 2004 | A1 |
20050004990 | Durazo | Jan 2005 | A1 |
20050033811 | Bhogal et al. | Feb 2005 | A1 |
20050071386 | Wolfgang | Mar 2005 | A1 |
20050097440 | Lusk et al. | May 2005 | A1 |
20050177617 | Banginwar | Aug 2005 | A1 |
20050198132 | Vellante | Sep 2005 | A1 |
20050203962 | Zhou | Sep 2005 | A1 |
20050210392 | Koide et al. | Sep 2005 | A1 |
20050216524 | Gomes et al. | Sep 2005 | A1 |
20050223066 | Buchheit | Oct 2005 | A1 |
20050234943 | Clarke | Oct 2005 | A1 |
20050240858 | Croft et al. | Oct 2005 | A1 |
20050251738 | Hirano et al. | Nov 2005 | A1 |
20050256907 | Novik et al. | Nov 2005 | A1 |
20050262203 | Buchheit | Nov 2005 | A1 |
20050289512 | Matsusaka | Dec 2005 | A1 |
20060015539 | Wolf | Jan 2006 | A1 |
20060015811 | Tanaka | Jan 2006 | A1 |
20060020360 | Wu | Jan 2006 | A1 |
20060031264 | Bosworth et al. | Feb 2006 | A1 |
20060041596 | Stirbu et al. | Feb 2006 | A1 |
20060047656 | Dehlinger | Mar 2006 | A1 |
20060053194 | Schneider | Mar 2006 | A1 |
20060053195 | Schneider et al. | Mar 2006 | A1 |
20060080432 | Spataro et al. | Apr 2006 | A1 |
20060085402 | Brown et al. | Apr 2006 | A1 |
20060101328 | Albornoz | May 2006 | A1 |
20060106879 | Zondervan et al. | May 2006 | A1 |
20060123033 | Livshits | Jun 2006 | A1 |
20060136511 | Ngo et al. | Jun 2006 | A1 |
20060136809 | Fernstrom | Jun 2006 | A1 |
20060200755 | Melmon et al. | Sep 2006 | A1 |
20060218476 | Gombert | Sep 2006 | A1 |
20060242549 | Schwier | Oct 2006 | A1 |
20060248038 | Kaplan et al. | Nov 2006 | A1 |
20060259524 | Horton | Nov 2006 | A1 |
20070066293 | Peng | Mar 2007 | A1 |
20070118598 | Bedi et al. | May 2007 | A1 |
20070130334 | Carley | Jun 2007 | A1 |
20070186157 | Walker et al. | Aug 2007 | A1 |
20070186171 | Junuzovic et al. | Aug 2007 | A1 |
20070198952 | Pittenger | Aug 2007 | A1 |
20070203917 | Du et al. | Aug 2007 | A1 |
20070226320 | Hager et al. | Sep 2007 | A1 |
20070226604 | Chalasani et al. | Sep 2007 | A1 |
20070271502 | Bedi et al. | Nov 2007 | A1 |
20070283321 | Hegde | Dec 2007 | A1 |
20080028300 | Krieger et al. | Jan 2008 | A1 |
20080059187 | Roitblat et al. | Mar 2008 | A1 |
20080059539 | Chin | Mar 2008 | A1 |
20080072141 | Hodel-Widmer | Mar 2008 | A1 |
20080086718 | Bostic | Apr 2008 | A1 |
20080097993 | Nanba | Apr 2008 | A1 |
20080098294 | Le | Apr 2008 | A1 |
20080114740 | Vergottini | May 2008 | A1 |
20080126953 | Davidson | May 2008 | A1 |
20080147590 | Bechtel | Jun 2008 | A1 |
20080177782 | Poston | Jul 2008 | A1 |
20080180740 | Kimura et al. | Jul 2008 | A1 |
20080195800 | Lee et al. | Aug 2008 | A1 |
20080235579 | Champion et al. | Sep 2008 | A1 |
20080256113 | Rasmussen | Oct 2008 | A1 |
20080256114 | Rasmussen | Oct 2008 | A1 |
20080263032 | Vailaya et al. | Oct 2008 | A1 |
20080270386 | Ohi | Oct 2008 | A1 |
20080294895 | Bodner | Nov 2008 | A1 |
20080320384 | Nagarajan | Dec 2008 | A1 |
20090006936 | Parker | Jan 2009 | A1 |
20090006946 | Hanson et al. | Jan 2009 | A1 |
20090006948 | Parker | Jan 2009 | A1 |
20090063489 | Neumann | Mar 2009 | A1 |
20090094231 | Marvit et al. | Apr 2009 | A1 |
20090094242 | Lo et al. | Apr 2009 | A1 |
20090157811 | Bailor | Jun 2009 | A1 |
20090171987 | Coppinger et al. | Jul 2009 | A1 |
20090193331 | Croft | Jul 2009 | A1 |
20090228473 | Kannan | Sep 2009 | A1 |
20090235158 | Rosenstein et al. | Sep 2009 | A1 |
20090249224 | Davis et al. | Oct 2009 | A1 |
20090271696 | Bailor | Oct 2009 | A1 |
20090282041 | Skaria | Nov 2009 | A1 |
20090282462 | Skaria | Nov 2009 | A1 |
20090327294 | Bailor | Dec 2009 | A1 |
20100023562 | Kreuch et al. | Jan 2010 | A1 |
20100070464 | Aymeloglu et al. | Mar 2010 | A1 |
20100088676 | Yuan | Apr 2010 | A1 |
20100095198 | Bultrowicz et al. | Apr 2010 | A1 |
20100131836 | Dukhon | May 2010 | A1 |
20100281074 | Bailor et al. | Nov 2010 | A1 |
20110055702 | Jakobson | Mar 2011 | A1 |
20110184906 | Bailor | Jul 2011 | A1 |
Number | Date | Country |
---|---|---|
1804836 | Jul 2006 | CN |
101042702 | Sep 2007 | CN |
19844071 | Apr 1999 | DE |
1290575 | Jun 2005 | EP |
1681652 | Jul 2006 | EP |
2005310158 | Nov 2005 | JP |
10-0331685 | Apr 2002 | KR |
1020060047218 | May 2006 | KR |
200424868 | Nov 2004 | TW |
200627259 | Dec 2005 | TW |
0125986 | Apr 2001 | WO |
WO 0133362 | May 2001 | WO |
0188750 | Nov 2001 | WO |
WO 0233575 | Apr 2002 | WO |
WO 2005114467 | Dec 2005 | WO |
WO 2007034858 | Mar 2007 | WO |
WO 2007062949 | Jun 2007 | WO |
WO 2009061638 | May 2009 | WO |
WO 2009076010 | Jun 2009 | WO |
WO 2009079116 | Jun 2009 | WO |
WO 2009134548 | Nov 2009 | WO |
WO 2009154842 | Dec 2009 | WO |
WO 2009158108 | Dec 2009 | WO |
Number | Date | Country | |
---|---|---|---|
20090228473 A1 | Sep 2009 | US |