US20190087599A1

US20190087599A1 - Compressing a slice name listing in a dispersed storage network

Info

Publication number: US20190087599A1
Application number: US16/197,235
Authority: US
Inventors: Jason K. Resch; Andrew D. Baptist; Ilya Volvovski; Wesley B. Leggette
Original assignee: International Business Machines Corp
Current assignee: Pure Storage Inc
Priority date: 2014-04-02
Filing date: 2018-11-20
Publication date: 2019-03-21
Also published as: US11586755B1; US11928230B2; US20230177199A1; US10891390B1

Abstract

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.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

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 DEVELOPMENT

Not Applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not Applicable.

BACKGROUND OF THE INVENTION

TECHNICAL FIELD OF THE INVENTION

This invention relates generally to computer networks and more particularly to identifying dispersed error encoded data.

DESCRIPTION OF RELATED ART

Computing 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.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed or distributed storage network (DSN) in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing core in accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storage error encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an error encoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an error encoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of an encoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storage error decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an error decoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of an example of identifying stored encoded data slices in accordance with the present invention;

FIG. 10 is a logic diagram of an example of a method of identifying stored encoded data slices in accordance with the present invention;

FIGS. 11A-11D are schematic block diagrams of examples of list range responses in accordance with the present invention; and

FIG. 12 is a logic diagram of an example of a method of listing stored encoded data slices in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, or distributed, storage network (DSN) 10 that includes a plurality of computing devices 12-16, a managing unit 18, an integrity processing unit 20, and a DSN memory 22. The components of the DSN 10 are coupled to a network 24, which may include one or more wireless and/or wire lined communication systems; one or more non-public intranet systems and/or public internet systems; and/or one or more local area networks (LAN) and/or wide area networks (WAN).
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 FIG. 2, or components thereof) and a plurality of memory devices for storing dispersed error encoded data.
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 FIGS. 3-8. In this example embodiment, computing device 16 functions as a dispersed storage processing agent for computing device 14. In this role, computing device 16 dispersed storage error encodes and decodes data on behalf of computing device 14. With the use of dispersed storage error encoding and decoding, the DSN 10 is tolerant of a significant number of storage unit failures (the number of failures is based on parameters of the dispersed storage error encoding function) without loss of data and without the need for a redundant or backup copies of the data. Further, the DSN 10 stores data for an indefinite period of time without data loss and in a secure manner (e.g., the system is very resistant to unauthorized attempts at accessing the data).
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.
FIG. 2 is a schematic block diagram of an embodiment of a computing core 26 that includes a processing module 50, a memory controller 52, main memory 54, a video graphics processing unit 55, an input/output (IO) controller 56, a peripheral component interconnect (PCI) interface 58, an IO interface module 60, at least one IO device interface module 62, a read only memory (ROM) basic input output system (BIOS) 64, and one or more memory interface modules. The one or more memory interface module(s) includes one or more of a universal serial bus (USB) interface module 66, a host bus adapter (HBA) interface module 68, a network interface module 70, a flash interface module 72, a hard drive interface module 74, and a DSN interface module 76.
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 FIG. 1. Note that the IO device interface module 62 and/or the memory interface modules 66-76 may be collectively or individually referred to as IO ports.
FIG. 3 is a schematic block diagram of an example of dispersed storage error encoding of data. When a computing device 12 or 16 has data to store it disperse storage error encodes the data in accordance with a dispersed storage error encoding process based on dispersed storage error encoding parameters. 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. The per data segment encoding values include a total, or pillar width, number (T) of encoded data slices per encoding of a data segment i.e., in a set of encoded data slices); a decode threshold number (D) of encoded data slices of a set of encoded data slices that are needed to recover the data segment; a read threshold number (R) of encoded data slices to indicate a number of encoded data slices per set to be read from storage for decoding of the data segment; and/or a write threshold number (W) to indicate a number of encoded data slices per set that must be accurately stored before the encoded data segment is deemed to have been properly stored. The dispersed storage error encoding parameters may further include slicing information (e.g., the number of encoded data slices that will be created for each data segment) and/or slice security information (e.g., per encoded data slice encryption, compression, integrity checksum, etc.).
In the present example, Cauchy Reed-Solomon has been selected as the encoding function (a generic example is shown in FIG. 4 and a specific example is shown in FIG. 5); the data segmenting protocol is to divide the data object into fixed sized data segments; and the per data segment encoding values include: a pillar width of 5, a decode threshold of 3, a read threshold of 4, and a write threshold of 4. In accordance with the data segmenting protocol, the computing device 12 or 16 divides the data (e.g., a file (e.g., text, video, audio, etc.), a data object, or other data arrangement) into a plurality of fixed sized data segments (e.g., 1 through Y of a fixed size in range of Kilo-bytes to Tera-bytes or more). The number of data segments created is dependent of the size of the data and the data segmenting protocol.
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. FIG. 4 illustrates a generic Cauchy Reed-Solomon encoding function, which includes an encoding matrix (EM), a data matrix (DM), and a coded matrix (CM). The size of the encoding matrix (EM) is dependent on the pillar width number (T) and the decode threshold number (D) of selected per data segment encoding values. To produce the data matrix (DM), the data segment is divided into a plurality of data blocks and the data blocks are arranged into D number of rows with Z data blocks per row. Note that Z is a function of the number of data blocks created from the data segment and the decode threshold number (D). The coded matrix is produced by matrix multiplying the data matrix by the encoding matrix.
FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encoding with a pillar number (T) of five and decode threshold number of three. In this example, a first data segment is divided into twelve data blocks (D1-D12). The coded matrix includes five rows of coded data blocks, where the first row of X11-X14 corresponds to a first encoded data slice (EDS 1_1), the second row of X21-X24 corresponds to a second encoded data slice (EDS 2_1), the third row of X31-X34 corresponds to a third encoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to a fourth encoded data slice (EDS 4_1), and the fifth row of X51-X54 corresponds to a fifth encoded data slice (EDS 5_1). Note that the second number of the EDS designation corresponds to the data segment number.
Returning to the discussion of FIG. 3, the computing device also creates a slice name (SN) for each encoded data slice (EDS) in the set of encoded data slices. A typical format for a slice name 80 is shown in FIG. 6. As shown, the slice name (SN) 80 includes a pillar number of the encoded data slice (e.g., one of 1-T), a data segment number (e.g., one of 1-Y), a vault identifier (ID), a data object identifier (ID), and may further include revision level information of the encoded data slices. The slice name functions as, at least part of, a DSN address for the encoded data slice for storage and retrieval from the DSN memory 22.
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.
FIG. 7 is a schematic block diagram of an example of dispersed storage error decoding of a data object that was dispersed storage error encoded and stored in the example of FIG. 4. In this example, the computing device 12 or 16 retrieves from the storage units at least the decode threshold number of encoded data slices per data segment. As a specific example, the computing device retrieves a read threshold number of encoded data slices.
To recover a data segment from a decode threshold number of encoded data slices, the computing device uses a decoding function as shown in FIG. 8. As shown, the decoding function is essentially an inverse of the encoding function of FIG. 4. The coded matrix includes a decode threshold number of rows (e.g., three in this example) and the decoding matrix in an inversion of the encoding matrix that includes the corresponding rows of the coded matrix. For example, if the coded matrix includes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2, and 4, and then inverted to produce the decoding matrix.
FIG. 9 is a schematic block diagram of another embodiment of a dispersed storage network (DSN) that includes a rebuilding module 90, the network 24 of FIG. 1, and the storage unit 36 of FIG. 1. The rebuilding module 90 may be implemented by one of a computing device 12 or 16, a managing unit 18, and a integrity processing unit 20 of FIG. 1. The storage unit 36 includes the memory 88. The DSN functions to efficiently identify encoded data slices stored in the memory 88.
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).
FIG. 10 is a flowchart illustrating an example of identifying stored encoded data slices. The method begins or continues at step 100 where a processing module (e.g., of a dispersed storage (DS) client module) receives a list range request from a requesting entity, where the request includes a slice name range. The method continues at step 102 where the processing module identifies slice names of stored slices that correspond to the slice name range. For example, the processing module identifies slice names of stored encoded data slices where the slice names fall within the slice name range.
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.
FIGS. 11A-11D are a schematic block diagrams of examples of list range responses (e.g., a list range response of FIG. 9). The list range responses identify stored encoded data slices within a slice name range. For example, a list range response from a storage unit to a computing device of the DSN includes one or more representations of a range of slice names that identify the encoded data slices stored within the storage unit.
FIG. 11A is an example of a list range response message that includes a first slice name representation (SNR) 110 and a subsequent portion(s) representation 112. The first slice name representation identifies the first slice name. In one example, a representation is able to identify one or more slice names in accordance with one or more of a DSN protocol. In one example, the DSN protocol is based on dispersed storage error encoding parameters. For example, a data object A is dispersed storage error encoded in accordance with dispersed storage error encoding parameters to produce a plurality of sets of encoded data slices that are stored in a set of storage units of the DSN. In one example, a first encoded data slice of each set of the plurality of sets of encoded data slices are grouped into a first group of encoded data slices (e.g., share a common pillar number (e.g., 1 of A-1-1 through A-1-M)) and stored in a first storage unit of the set of storage units in accordance with the DSN protocol.
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.
FIG. 11B is an example of a list range response that includes a first slice name representation 110 and a last slice name representation 113. In one example, the first and last representations are of a similar representation structure. For example, the first slice name representation includes a result based on a deterministic function applied to the first slice name and the last slice name representation includes a second result based on the deterministic function applied to the last slice name. In a second example, the first and last representations are not of a similar representation structure. For example, the first slice name representation is the first slice name and the last slice name representation is an offset value of the last slice name from the first slice name.
FIG. 11C is a schematic block diagram of another example of a list range response that includes a first slice name representation (SNR) 110, a first contiguous range SNR 114, another first SNR and a second contiguous range SNR 116. In one example, a (e.g., the first) contiguous range SNR 114 includes the first SNR 110 (e.g., based on a DSN protocol). In a second example, the first contiguous range SNR 114 does not include the first SNR 110.
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 1^stcontiguous 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.
FIG. 11D is a schematic block diagram of another example of a list range response that includes a first SNR field 110, a 1^stmissing SNR field 115, a 2^ndmissing SNR field 115 and a last SNR field 113. In an example, the storage unit storing encoded data slices A-1-1 through A-1-13 receives a list range request that includes a slice name range and a representation structure that indicates to respond with a first slice name representation of the first slice name within the slice name range, a last slice name representation for the first slice name within the slice name range, and one or more missing SNRs 115.
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 1^stmissing slice SNR to include A-1-1, the 2^ndmissing 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 1^stmissing 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.
FIG. 12 is a logic diagram of an example of a method of listing stored encoded data slices in accordance with the present invention. The method begins with step 120, where a storage unit receives a list range request for a plurality of slice names within a slice name range, wherein the plurality of slice names is associated with a plurality of encoded data slices stored in the storage unit. In an example, data is dispersed storage error encoded into pluralities of sets of encoded data slices and stored in storage units of the DSN. The dispersed storage error encoding is in accordance with dispersed data storage parameters and the pluralities of sets of encoded data slices include the plurality of encoded data slices stored in the storage unit.
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

What is claimed is:

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 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 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:

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.