COMPRESSING A SLICE NAME LISTING IN A DISPERSED STORAGE NETWORK
A method begins by receiving a list range request for a plurality of slice names within a slice name range. The method continues with identifying slice names of the plurality of slice names within the slice name range. The method continues with determining a representation structure for a list range response. The method continues with generating, in accordance with the representation structure, a first portion of a list range response for a first slice name, where the first portion includes a first representation of the first slice name. The method continues with generating, in accordance with the representation structure, one or more subsequent portions of the list range response for remaining slice names of the slice names, where the one or more subsequent portions includes one or more representations of the remaining slices names. The method continues with sending the list range response to a requesting device.
The present U.S. Utility Patent Application claims priority pursuant to 35 U. S.C. § 120 as a continuation-in-part of U.S. Utility application Ser. No. 15/721,093, entitled “DISTRIBUTING REGISTRY INFORMATION IN A DISPERSED STORAGE NETWORK”, filed Sep. 27, 2017, which is a continuation of U.S. Utility application Ser. No. 14/610,220, entitled “DISTRIBUTING REGISTRY INFORMATION IN A DISPERSED STORAGE NETWORK”, filed Jan. 30, 2015, which claims priority pursuant to 35 U.S.C. § 119(e) to U.S. Provisional Application No. 61/974,142, entitled “SCHEDULING REBUILDING OF STORED DATA IN A DISPERSED STORAGE NETWORK”, filed Apr. 02, 2014, expired, all of which are hereby incorporated herein by reference in their entirety and made part of the present U.S. Utility Patent Application for all purposes.
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENTNot Applicable.
INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISCNot Applicable.
BACKGROUND OF THE INVENTION TECHNICAL FIELD OF THE INVENTIONThis invention relates generally to computer networks and more particularly to identifying dispersed error encoded data.
DESCRIPTION OF RELATED ARTComputing devices are known to communicate data, process data, and/or store data. Such computing devices range from wireless smart phones, laptops, tablets, personal computers (PC), work stations, and video game devices, to data centers that support millions of web searches, stock trades, or on-line purchases every day. In general, a computing device includes a central processing unit (CPU), a memory system, user input/output interfaces, peripheral device interfaces, and an interconnecting bus structure.
As is further known, a computer may effectively extend its CPU by using “cloud computing” to perform one or more computing functions (e.g., a service, an application, an algorithm, an arithmetic logic function, etc.) on behalf of the computer. Further, for large services, applications, and/or functions, cloud computing may be performed by multiple cloud computing resources in a distributed manner to improve the response time for completion of the service, application, and/or function. For example, Hadoop is an open source software framework that supports distributed applications enabling application execution by thousands of computers.
In addition to cloud computing, a computer may use “cloud storage” as part of its memory system. As is known, cloud storage enables a user, via its computer, to store files, applications, etc. on an Internet storage system. The Internet storage system may include a RAID (redundant array of independent disks) system and/or a dispersed storage system that uses an error correction scheme to encode data for storage.
The DSN memory 22 includes a plurality of storage units 36 that may be located at geographically different sites (e.g., one in Chicago, one in Milwaukee, etc.), at a common site, or a combination thereof. For example, if the DSN memory 22 includes eight storage units 36, each storage unit is located at a different site. As another example, if the DSN memory 22 includes eight storage units 36, all eight storage units are located at the same site. As yet another example, if the DSN memory 22 includes eight storage units 36, a first pair of storage units are at a first common site, a second pair of storage units are at a second common site, a third pair of storage units are at a third common site, and a fourth pair of storage units are at a fourth common site. Note that a DSN memory 22 may include more or less than eight storage units 36. Further note that each storage unit 36 includes a computing core (as shown in
Each of the computing devices 12-16, the managing unit 18, and the integrity processing unit 20 include a computing core 26, which includes network interfaces 30-33. Computing devices 12-16 may each be a portable computing device and/or a fixed computing device. A portable computing device may be a social networking device, a gaming device, a cell phone, a smart phone, a digital assistant, a digital music player, a digital video player, a laptop computer, a handheld computer, a tablet, a video game controller, and/or any other portable device that includes a computing core. A fixed computing device may be a computer (PC), a computer server, a cable set-top box, a satellite receiver, a television set, a printer, a fax machine, home entertainment equipment, a video game console, and/or any type of home or office computing equipment. Note that each of the managing unit 18 and the integrity processing unit 20 may be separate computing devices, may be a common computing device, and/or may be integrated into one or more of the computing devices 12-16 and/or into one or more of the storage units 36.
Each interface 30, 32, and 33 includes software and hardware to support one or more communication links via the network 24 indirectly and/or directly. For example, interface 30 supports a communication link (e.g., wired, wireless, direct, via a LAN, via the network 24, etc.) between computing devices 14 and 16. As another example, interface 32 supports communication links (e.g., a wired connection, a wireless connection, a LAN connection, and/or any other type of connection to/from the network 24) between computing devices 12 & 16 and the DSN memory 22. As yet another example, interface 33 supports a communication link for each of the managing unit 18 and the integrity processing unit 20 to the network 24.
Computing devices 12 and 16 include a dispersed storage (DS) client module 34, which enables the computing device to dispersed storage error encode and decode data 40 as subsequently described with reference to one or more of
In operation, the managing unit 18 performs DS management services. For example, the managing unit 18 establishes distributed data storage parameters (e.g., vault creation, distributed storage parameters, security parameters, billing information, user profile information, etc.) for computing devices 12-14 individually or as part of a group of user devices. As a specific example, the managing unit 18 coordinates creation of a vault (e.g., a virtual memory block associated with a portion of an overall namespace of the DSN) within the DSTN memory 22 for a user device, a group of devices, or for public access and establishes per vault dispersed storage (DS) error encoding parameters for a vault. The managing unit 18 facilitates storage of DS error encoding parameters for each vault by updating registry information of the DSN 10, where the registry information may be stored in the DSN memory 22, a computing device 12-16, the managing unit 18, and/or the integrity processing unit 20.
The DSN managing unit 18 creates and stores user profile information (e.g., an access control list (ACL)) in local memory and/or within memory of the DSN memory 22. The user profile information includes authentication information, permissions, and/or the security parameters. The security parameters may include encryption/decryption scheme, one or more encryption keys, key generation scheme, and/or data encoding/decoding scheme.
The DSN managing unit 18 creates billing information for a particular user, a user group, a vault access, public vault access, etc. For instance, the DSTN managing unit 18 tracks the number of times a user accesses a non-public vault and/or public vaults, which can be used to generate a per-access billing information. In another instance, the DSTN managing unit 18 tracks the amount of data stored and/or retrieved by a user device and/or a user group, which can be used to generate a per-data-amount billing information.
As another example, the managing unit 18 performs network operations, network administration, and/or network maintenance. Network operations includes authenticating user data allocation requests (e.g., read and/or write requests), managing creation of vaults, establishing authentication credentials for user devices, adding/deleting components (e.g., user devices, storage units, and/or computing devices with a DS client module 34) to/from the DSN 10, and/or establishing authentication credentials for the storage units 36. Network administration includes monitoring devices and/or units for failures, maintaining vault information, determining device and/or unit activation status, determining device and/or unit loading, and/or determining any other system level operation that affects the performance level of the DSN 10. Network maintenance includes facilitating replacing, upgrading, repairing, and/or expanding a device and/or unit of the DSN 10.
The integrity processing unit 20 performs rebuilding of ‘bad’ or missing encoded data slices. At a high level, the integrity processing unit 20 performs rebuilding by periodically attempting to retrieve/list encoded data slices, and/or slice names of the encoded data slices, from the DSN memory 22. For retrieved encoded slices, they are checked for errors due to data corruption, outdated version, etc. If a slice includes an error, it is flagged as a ‘bad’ slice. For encoded data slices that were not received and/or not listed, they are flagged as missing slices. Bad and/or missing slices are subsequently rebuilt using other retrieved encoded data slices that are deemed to be good slices to produce rebuilt slices. The rebuilt slices are stored in the DSTN memory 22.
The DSN interface module 76 functions to mimic a conventional operating system (OS) file system interface (e.g., network file system (NFS), flash file system (FFS), disk file system (DFS), file transfer protocol (FTP), web-based distributed authoring and versioning (WebDAV), etc.) and/or a block memory interface (e.g., small computer system interface (SCSI), internet small computer system interface (iSCSI), etc.). The DSN interface module 76 and/or the network interface module 70 may function as one or more of the interface 30-33 of
In the present example, Cauchy Reed-Solomon has been selected as the encoding function (a generic example is shown in
The computing device 12 or 16 then disperse storage error encodes a data segment using the selected encoding function (e.g., Cauchy Reed-Solomon) to produce a set of encoded data slices.
Returning to the discussion of
As a result of encoding, the computing device 12 or 16 produces a plurality of sets of encoded data slices, which are provided with their respective slice names to the storage units for storage. As shown, the first set of encoded data slices includes EDS 1_1 through EDS 5_1 and the first set of slice names includes SN 1_1 through SN 5_1 and the last set of encoded data slices includes EDS 1_Y through EDS 5_Y and the last set of slice names includes SN 1_Y through SN 5_Y.
To recover a data segment from a decode threshold number of encoded data slices, the computing device uses a decoding function as shown in
In an example of operation of the identifying of the encoded data slices stored in the memory 88, the rebuilding module 90 issues, via the network 24, a list range request 1 that identifies a start slice name range and an end slice name range. The encoded data slices stored in the memory 88 are associated with slice names. The storage unit 36 is associated with a stored slice name range, where the stored slice name range includes slice names of the stored encoded data slices. The stored slice name range includes a range of the list range request. For example, the start slice name range and the end slice name range fall within the stored slice name range.
The storage unit 36 receives the list range request 1. Having received the list range request 1, the storage unit 36 identifies slice names 80 associated with stored encoded data slices corresponding to the list range request 1. For example, the storage unit 36 identifies slices A-1-1, A-1-2, through A-1-M as the slice names that fall within the slice name range of the request.
Having identified the slice names of the stored encoded data slices associated with the request, the storage unit 36, for a first slice name 80 of the slice name range, generates a first portion of a list range response 1 that includes the first slice name (e.g., A-1-1) in a slice name field 89, an entry of a slice revision count field 92 corresponding to the first slice name, and, for each identified revision, the slice revision entry of a slice revision field 94 and a slice length entry of a slice length field 96. In one example, the slice revision entry includes 00h when there are no visible slice revisions. The slice length entry includes a slice length (e.g., number of bytes of the slice) of a slice revision.
Having generated the first portion of the list range response 1, the storage unit 36, for each remaining slice name of the slice name range, generates further portions of the list range response 1 that includes a representation of the remaining slice name in a slice name offset field 81, an entry of another slice revision count field 92 for the remaining slice name, and, for each identified revision of the remaining slice name, a slice revision entry of another slice revision field 94 and a slice length entry of another slice length field 96.
The representation of the remaining slice name includes at least one of an offset from the first slice name based on the remaining slice name, and a result of applying a deterministic function to the first slice name and the remaining slice name. For example, the storage unit 36 generates the representation of the remaining slice name as 10 when the remaining slice name (e.g., A-1-11) is offset by 10 from the first slice name. As such, a size efficiency is provided as successive slice name offset fields are smaller in size (e.g., 4-24 bytes) than the slice name field (e.g., 48 bytes).
The method continues at step 104 where, for a first slice name of the slice name range, the processing module generates a first portion of a list range response that includes the first slice name and one or more other parameters of one or more revisions of stored slices associated with the first slice name. The other parameters include one or more of a slice revision count of the number of the one or more revisions, a slice revision number for each slice revision, and a slice length of the stored slice of each slice revision.
The method continues at step 106 where, for each remaining slice name of the slice name range, the processing module generates another portion of the list range response that includes a representation of the remaining slice name and one or more other parameters of one or more revisions of stored slices associated with the remaining slice name. For example, the processing module generates the other portion of the list range response to include an offset from the first slice name as the representation of the remaining slice name. The method continues at step 108 where the processing module sends the list range response to the requesting entity.
The dispersed storage error encoding parameters include an encoding function (e.g., information dispersal algorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding, non-systematic encoding, on-line codes, etc.), a data segmenting protocol (e.g., data segment size, fixed, variable, etc.), and per data segment encoding values (e.g., pillar width, decode threshold, etc). In this example, a requesting device sends a list request for a range of encoded data slices A-1-1 through A-1-M. The request can include a representation structure for the list response. Alternatively, or in addition to, the representation structure is based on the DSN protocol (e.g., data segmenting protocol, data storage protocol, slice naming protocol, etc). For example, a requesting device determines the DSN protocol is to store the first pillar number of encoded data slices in the first storage unit. In this example, the requesting device determines the representation structure is to exclude (e.g., truncate) the pillar number in a list response. For example, the first slice name representation is A-2 for slice name A-1-2 and a first subsequent portion representation is A-3 for a slice name A-1-3.
As a specific example, a storage device stores encoded data slices A-1-1 through A-1-M that are associated with a range of slice names. The storage device receives a list range request for the range of slice names that are associated with the encoded data slices A-1-1 through A-1-13. The storage device identifies encoded data slices A-1-2 through A-1-5 and A-1-7 through A-1-13 as being stored in memory of the storage device. The storage device generates the first SNR to include “A-2”, the 1st contiguous range SNR to include “3” (to represent A-1-3, A-1-4, and A-1-5), the additional first SNR to include “A-7” and the second contiguous range SNR to include “6” (to represent A-1-8, A-1-9, A-1-10, A-1-11, A-1-12 and A-1-13.
As a specific example, the storage device receives a list range request for the range of slice names that are associated with the encoded data slices A-1-1 through A-1-13. The storage device identifies encoded data slices A-1-2 through A-1-5 and A-1-7 through A-1-13 as being stored in memory of the storage device. The storage device then generates, according to the representation structure, the first SNR to include “A-2”, the 1st missing slice SNR to include A-1-1, the 2nd missing slice SNR to include A-1-6 and the last SNR 113 to include A-1-13.
Note that any of the examples in the preceding figures may be combined. For example, a list range response may include a first SNR and a 1st missing contiguous range SNR. Further note, the offset may also indicate a difference between a first list range response and a second list range response. The offset may also be based on a data object identification, a pillar number, a segment number and other information within the slice name.
The method continues with step 122, where the storage unit identifies slice names of the plurality of slice names within the slice name range. For example, the storage unit identifies the slice names associated with encoded data slices stored in the storage unit within the slice name range.
The method continues with step 124, where the storage unit determines a representation structure for a list range response. The representation structure includes one or more of an offset representation, a first slice name representation, a last slice name representation, a deterministic function representation, a missing encoded data slice representation, a contiguous grouping of encoded data slices representation, a revision representation (e.g., all slice lengths or revisions are the same across two or more slice names, an offset in the revision field, etc.) and any other information regarding the structure of a list name response.
The method continues with step 126, where the storage unit generates, in accordance with the representation structure, a first portion of a list range response for a first slice name of the slice names. The first portion includes a first representation of the first slice name. As an example, the first representation includes one of the first slice name, a result based on performing a deterministic function on the first slice name and a truncated (e.g., shortened) version of the first slice name. Note the first portion and the one or more subsequent portions may each further include a slice revision count field. The slice revision count field includes one or more slice revision fields and one or more corresponding slice length fields.
The method continues with step 128, where the storage unit generates, in accordance with the representation structure, one or more subsequent portions of the list range response for remaining slice names of the slice names. The one or more subsequent portions includes one or more representations of the remaining slices names. For example, a representation of the one or more representations includes one or more of an offset from the first slice name, a result based on a deterministic function applied to the first slice name and a remaining slice name of the remaining slice names, a result based on a number of slice names within a contiguous range of slice names of the remaining slice names, and a last slice name of the slice names.
The method continues with step 130, where the storage unit sends the list range response to the requesting device. In an example, list range response further includes one or more of a request number, a payload length (e.g., a number of bytes after a header), a first slice name, and a last slice name.
It is noted that terminologies as may be used herein such as bit stream, stream, signal sequence, etc. (or their equivalents) have been used interchangeably to describe digital information whose content corresponds to any of a number of desired types (e.g., data, video, speech, audio, etc. any of which may generally be referred to as ‘data’).
As may be used herein, the terms “substantially” and “approximately” provides an industry-accepted tolerance for its corresponding term and/or relativity between items. Such an industry-accepted tolerance ranges from less than one percent to fifty percent and corresponds to, but is not limited to, component values, integrated circuit process variations, temperature variations, rise and fall times, and/or thermal noise. Such relativity between items ranges from a difference of a few percent to magnitude differences. As may also be used herein, the term(s) “configured to”, “operably coupled to”, “coupled to”, and/or “coupling” includes direct coupling between items and/or indirect coupling between items via an intervening item (e.g., an item includes, but is not limited to, a component, an element, a circuit, and/or a module) where, for an example of indirect coupling, the intervening item does not modify the information of a signal but may adjust its current level, voltage level, and/or power level. As may further be used herein, inferred coupling (i.e., where one element is coupled to another element by inference) includes direct and indirect coupling between two items in the same manner as “coupled to”. As may even further be used herein, the term “configured to”, “operable to”, “coupled to”, or “operably coupled to” indicates that an item includes one or more of power connections, input(s), output(s), etc., to perform, when activated, one or more its corresponding functions and may further include inferred coupling to one or more other items. As may still further be used herein, the term “associated with”, includes direct and/or indirect coupling of separate items and/or one item being embedded within another item.
As may be used herein, the term “compares favorably”, indicates that a comparison between two or more items, signals, etc., provides a desired relationship. For example, when the desired relationship is that signal 1 has a greater magnitude than signal 2, a favorable comparison may be achieved when the magnitude of signal 1 is greater than that of signal 2 or when the magnitude of signal 2 is less than that of signal 1. As may be used herein, the term “compares unfavorably”, indicates that a comparison between two or more items, signals, etc., fails to provide the desired relationship.
As may also be used herein, the terms “processing module”, “processing circuit”, “processor”, and/or “processing unit” may be a single processing device or a plurality of processing devices. Such a processing device may be a microprocessor, micro-controller, digital signal processor, microcomputer, central processing unit, field programmable gate array, programmable logic device, state machine, logic circuitry, analog circuitry, digital circuitry, and/or any device that manipulates signals (analog and/or digital) based on hard coding of the circuitry and/or operational instructions. The processing module, module, processing circuit, and/or processing unit may be, or further include, memory and/or an integrated memory element, which may be a single memory device, a plurality of memory devices, and/or embedded circuitry of another processing module, module, processing circuit, and/or processing unit. Such a memory device may be a read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, cache memory, and/or any device that stores digital information. Note that if the processing module, module, processing circuit, and/or processing unit includes more than one processing device, the processing devices may be centrally located (e.g., directly coupled together via a wired and/or wireless bus structure) or may be distributedly located (e.g., cloud computing via indirect coupling via a local area network and/or a wide area network). Further note that if the processing module, module, processing circuit, and/or processing unit implements one or more of its functions via a state machine, analog circuitry, digital circuitry, and/or logic circuitry, the memory and/or memory element storing the corresponding operational instructions may be embedded within, or external to, the circuitry comprising the state machine, analog circuitry, digital circuitry, and/or logic circuitry. Still further note that, the memory element may store, and the processing module, module, processing circuit, and/or processing unit executes, hard coded and/or operational instructions corresponding to at least some of the steps and/or functions illustrated in one or more of the Figures. Such a memory device or memory element can be included in an article of manufacture.
One or more embodiments have been described above with the aid of method steps illustrating the performance of specified functions and relationships thereof. The boundaries and sequence of these functional building blocks and method steps have been arbitrarily defined herein for convenience of description. Alternate boundaries and sequences can be defined so long as the specified functions and relationships are appropriately performed. Any such alternate boundaries or sequences are thus within the scope and spirit of the claims. Further, the boundaries of these functional building blocks have been arbitrarily defined for convenience of description. Alternate boundaries could be defined as long as the certain significant functions are appropriately performed. Similarly, flow diagram blocks may also have been arbitrarily defined herein to illustrate certain significant functionality.
To the extent used, the flow diagram block boundaries and sequence could have been defined otherwise and still perform the certain significant functionality. Such alternate definitions of both functional building blocks and flow diagram blocks and sequences are thus within the scope and spirit of the claims. One of average skill in the art will also recognize that the functional building blocks, and other illustrative blocks, modules and components herein, can be implemented as illustrated or by discrete components, application specific integrated circuits, processors executing appropriate software and the like or any combination thereof.
In addition, a flow diagram may include a “start” and/or “continue” indication. The “start” and “continue” indications reflect that the steps presented can optionally be incorporated in or otherwise used in conjunction with other routines. In this context, “start” indicates the beginning of the first step presented and may be preceded by other activities not specifically shown. Further, the “continue” indication reflects that the steps presented may be performed multiple times and/or may be succeeded by other activities not specifically shown. Further, while a flow diagram indicates a particular ordering of steps, other orderings are likewise possible provided that the principles of causality are maintained.
The one or more embodiments are used herein to illustrate one or more aspects, one or more features, one or more concepts, and/or one or more examples. A physical embodiment of an apparatus, an article of manufacture, a machine, and/or of a process may include one or more of the aspects, features, concepts, examples, etc. described with reference to one or more of the embodiments discussed herein. Further, from figure to figure, the embodiments may incorporate the same or similarly named functions, steps, modules, etc. that may use the same or different reference numbers and, as such, the functions, steps, modules, etc. may be the same or similar functions, steps, modules, etc. or different ones.
Unless specifically stated to the contra, signals to, from, and/or between elements in a figure of any of the figures presented herein may be analog or digital, continuous time or discrete time, and single-ended or differential. For instance, if a signal path is shown as a single-ended path, it also represents a differential signal path. Similarly, if a signal path is shown as a differential path, it also represents a single-ended signal path. While one or more particular architectures are described herein, other architectures can likewise be implemented that use one or more data buses not expressly shown, direct connectivity between elements, and/or indirect coupling between other elements as recognized by one of average skill in the art.
The term “module” is used in the description of one or more of the embodiments. A module implements one or more functions via a device such as a processor or other processing device or other hardware that may include or operate in association with a memory that stores operational instructions. A module may operate independently and/or in conjunction with software and/or firmware. As also used herein, a module may contain one or more sub-modules, each of which may be one or more modules.
As may further be used herein, a computer readable memory includes one or more memory elements. A memory element may be a separate memory device, multiple memory devices, or a set of memory locations within a memory device. Such a memory device may be a read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, cache memory, and/or any device that stores digital information. The memory device may be in a form a solid state memory, a hard drive memory, cloud memory, thumb drive, server memory, computing device memory, and/or other physical medium for storing digital information.
While particular combinations of various functions and features of the one or more embodiments have been expressly described herein, other combinations of these features and functions are likewise possible. The present disclosure is not limited by the particular examples disclosed herein and expressly incorporates these other combinations.
Claims
1. A method for execution by a storage unit of a dispersed storage network (DSN) comprises:
- receiving, from a requesting device, a list range request for a plurality of slice names within a slice name range, wherein the plurality of slice names are associated with a plurality of encoded data slices stored in the storage unit, wherein data is dispersed storage error encoded into pluralities of sets of encoded data slices and stored in storage units of the DSN, wherein the dispersed storage error encoding is in accordance with dispersed data storage parameters, wherein the pluralities of sets of encoded data slices include the plurality of encoded data slices;
- identifying slice names of the plurality of slice names within the slice name range;
- determining a representation structure for a list range response;
- generating, in accordance with the representation structure, a first portion of a list range response for a first slice name of the slice names, wherein the first portion includes a first representation of the first slice name;
- generating, in accordance with the representation structure, one or more subsequent portions of the list range response for remaining slice names of the slice names, wherein the one or more subsequent portions includes one or more representations of the remaining slices names; and
- sending the list range response to the requesting device.
2. The method of claim 1, wherein the first representation includes one of:
- the first slice name;
- a result based on performing a deterministic function on the first slice name; and
- a truncated version of the first slice name.
3. The method of claim 1, wherein a representation of the one or more representations includes one of:
- an offset from the first slice name;
- a result based on a deterministic function applied to the first slice name and a remaining slice name of the remaining slice names;
- a result based on a number of slice names within a contiguous range of slice names of the remaining slice names; and
- a last slice name of the slice names.
4. The method of claim 1, wherein the first portion further includes a slice revision count field, wherein the slice revision count field includes one or more of:
- one or more slice revision fields; and
- one or more corresponding slice length fields.
5. The method of claim 1, wherein the one or more subsequent portions each further include a slice revision count field, wherein the slice revision count field includes one or more of:
- one or more slice revision fields; and
- one or more corresponding slice length fields.
6. The method of claim 1, wherein the list range response further includes one or more of:
- a request number;
- a payload length;
- a first slice name; and
- a last slice name.
7. The method of claim 1 further comprises:
- generating, in accordance with the representation structure, for a last slice name of the slice names, a last portion of the list range response.
8. The method of claim 1, wherein the representation structure includes one or more of:
- an offset representation;
- a first slice name representation;
- a last slice name representation;
- a deterministic function representation;
- a missing encoded data slice representation;
- a contiguous grouping of encoded data slices representation; and
- a revision representation.
9. The method of claim 1, wherein the list range request includes the representation structure.
10. A storage unit of a dispersed storage network (DSN) comprises:
- memory;
- an interface; and
- a processing module operably coupled to the memory and the interface, wherein the processing module is operable to: receive, via the interface and from a requesting device, a list range request for a plurality of slice names within a slice name range, wherein the plurality of slice names are associated with a plurality of encoded data slices stored in the storage unit, wherein data is dispersed storage error encoded into pluralities of sets of encoded data slices and stored in storage units of the DSN, wherein the dispersed storage error encoding is in accordance with dispersed data storage parameters, wherein the pluralities of sets of encoded data slices include the plurality of encoded data slices; identify slice names of the plurality of slice names within the slice name range; determine a representation structure for a list range response; generate, in accordance with the representation structure, a first portion of a list range response for a first slice name of the slice names, wherein the first portion includes a first representation of the first slice name; generate, in accordance with the representation structure, one or more subsequent portions of the list range response for remaining slice names of the slice names, wherein the one or more subsequent portions includes one or more representations of the remaining slices names; and send, via the interface, the list range response to the requesting device.
11. The storage unit of claim 10, wherein the processing module is operable to generate the first representation to include one of:
- the first slice name;
- a result based on performing a deterministic function on the first slice name; and
- a truncated version of the first slice name.
12. The storage unit of claim 10, wherein processing module is operable to generate a representation of the one or more representations to include one or more of:
- an offset from the first slice name;
- a result based on a deterministic function applied to the first slice name and a remaining slice name of the remaining slice names;
- a result based on a number of slice names within a contiguous range of slice names of the remaining slice names; and
- a last slice name of the slice names.
13. The storage unit of claim 10, wherein the processing module is operable to generate the first portion to further include a slice revision count field, wherein the slice revision count field includes one or more of:
- one or more slice revision fields; and
- one or more corresponding slice length fields.
14. The storage unit of claim 10, wherein the processing module is further operable to generate the one or more subsequent portions to each further include a slice revision count field, wherein the slice revision count field includes one or more of:
- one or more slice revision fields; and
- one or more corresponding slice length fields.
15. The storage unit of claim 10, wherein the processing module is operable to generate the list range response to include one or more of:
- a request number;
- a payload length;
- a first slice name; and
- a last slice name.
16. The storage unit of claim 10, wherein the processing module is further operable to:
- generating, in accordance with the representation structure, for a last slice name of the slice names, a last portion of the list range response.
17. The storage unit of claim 10, wherein the representation structure includes one or more of:
- an offset representation;
- a first slice name representation;
- a last slice name representation;
- a deterministic function representation;
- a missing encoded data slice representation;
- a contiguous grouping of encoded data slices representation; and
- a revision representation.
18. The storage unit of claim 10, wherein the list range request includes the representation structure.
Type: Application
Filed: Nov 20, 2018
Publication Date: Mar 21, 2019
Inventors: Jason K. Resch (Chicago, IL), Andrew D. Baptist (Mt. Pleasant, WI), Ilya Volvovski (Chicago, IL), Wesley B. Leggette (Chicago, IL)
Application Number: 16/197,235