Retrying failed write operations in a distributed storage network

In various examples, a computing device of a dispersed storage network (DSN) receives a store data request including a data object. The computing device identifies a storage unit pool associated with the store data request. The storage unit pool includes a plurality of storage sets, each of the storage sets associated with a plurality of address ranges that are associated with a respective set of memories of the storage set. The computing device identifies a first set of memories of a first storage set of the storage unit pool, and issues a set of write slice requests to the first set of memories to initiate storage of encoded data slices produced from the data object. When an unfavorable storage condition is detected, the computing device identifies a second set of memories of the first storage set and facilitates storage of the data object in the second set of memories.

BACKGROUND

This invention relates generally to computer networks, and more specifically, to selection of storage resources in a dispersed storage network.

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 a remote storage system. The remote 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.

In a RAID system, a RAID controller adds parity data to the original data before storing it across an array of disks. The parity data is calculated from the original data such that the failure of a single disk typically will not result in the loss of the original data. While RAID systems can address certain memory device failures, these systems may suffer from effectiveness, efficiency and security issues. For instance, as more disks are added to the array, the probability of a disk failure rises, which may increase maintenance costs. When a disk fails, for example, it needs to be manually replaced before another disk(s) fails and the data stored in the RAID system is lost. To reduce the risk of data loss, data on a RAID device is often copied to one or more other RAID devices. While this may reduce the possibility of data loss, it also raises security issues since multiple copies of data may be available, thereby increasing the chances of unauthorized access. In addition, co-location of some RAID devices may result in a risk of a complete data loss in the event of a natural disaster, fire, power surge/outage, etc.

SUMMARY

According to embodiments of the present disclosure, novel methods are presented for use in a dispersed storage network (DSN) to select storage resources for retrying failed write operations. In various examples, a store data request is received, the store data request including a data object. A storage unit pool associated with the store data request is identified, the storage unit pool including a plurality of storage sets. Each of the storage sets is associated, for example, with a plurality of address ranges that are associated with a respective set of memories of the storage set. A first set of memories of a first storage set of the storage unit pool is identified, and a set of write slice requests is issued to the first set of memories to initiate storage of encoded data slices produced from the data object. When an unfavorable storage condition is detected, a second set of memories of the first storage set is identified. The first set of memories and the second set of memories can be located, at least in part, in common storage units of the first storage set. The data object is then stored in the second set of memories.

DETAILED DESCRIPTION

FIG.1is a schematic block diagram of an embodiment of a dispersed, or distributed, storage network (DSN)10that includes a plurality of computing devices12-16, a managing unit18, an integrity processing unit20, and a DSN memory22. The components of the DSN10are coupled to a network24, 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).

Each of the storage units36is operable to store DS error encoded data and/or to execute (e.g., in a distributed manner) maintenance tasks and/or data-related tasks. The tasks may be a simple function (e.g., a mathematical function, a logic function, an identify function, a find function, a search engine function, a replace function, etc.), a complex function (e.g., compression, human and/or computer language translation, text-to-voice conversion, voice-to-text conversion, etc.), multiple simple and/or complex functions, one or more algorithms, one or more applications, maintenance tasks (e.g., rebuilding of data slices, updating hardware, rebooting software, restarting a particular software process, performing an upgrade, installing a software patch, loading a new software revision, performing an off-line test, prioritizing tasks associated with an online test, etc.), etc.

Each of the computing devices12-16, the managing unit18, integrity processing unit20and (in various embodiments) the storage units36include a computing core26, which includes network interfaces30-33. Computing devices12-16may 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 unit18and the integrity processing unit20may be separate computing devices, may be a common computing device, and/or may be integrated into one or more of the computing devices12-16and/or into one or more of the storage units36.

Each interface30,32, and33includes software and hardware to support one or more communication links via the network24indirectly and/or directly. For example, interface30supports a communication link (e.g., wired, wireless, direct, via a LAN, via the network24, etc.) between computing devices14and16. As another example, interface32supports communication links (e.g., a wired connection, a wireless connection, a LAN connection, and/or any other type of connection to/from the network24) between computing devices12and16and the DSN memory22. As yet another example, interface33supports a communication link for each of the managing unit18and the integrity processing unit20to the network24.

As another example, the managing unit18performs network operations, network administration, and/or network maintenance. Network operations includes authenticating user data allocation/access 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 module34) to/from the DSN10, and/or establishing authentication credentials for the storage units36. 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 DSN10. Network maintenance includes facilitating replacing, upgrading, repairing, and/or expanding a device and/or unit of the DSN10. Examples of dynamic resource selection for data access operations are discussed in greater detail with reference toFIGS.9-11.

To support data storage integrity verification within the DSN10, the integrity processing unit20(and/or other devices in the DSN10) may perform rebuilding of ‘bad’ or missing encoded data slices. At a high level, the integrity processing unit20performs rebuilding by periodically attempting to retrieve/list encoded data slices, and/or slice names of the encoded data slices, from the DSN memory22. Retrieved encoded slices are checked for errors due to data corruption, outdated versioning, etc. If a slice includes an error, it is flagged as a ‘bad’ or ‘corrupt’ slice. Encoded data slices that are not received and/or not listed may be flagged as missing slices. Bad and/or missing slices may be subsequently rebuilt using other retrieved encoded data slices that are deemed to be good slices in order to produce rebuilt slices. A multi-stage decoding process may be employed in certain circumstances to recover data even when the number of valid encoded data slices of a set of encoded data slices is less than a relevant decode threshold number. The rebuilt slices may then be written to DSN memory22. Note that the integrity processing unit20may be a separate unit as shown, included in DSN memory22, included in the computing device16, and/or distributed among the storage units36.

In the present example, Cauchy Reed-Solomon has been selected as the encoding function (a generic example is shown inFIG.4and a specific example is shown inFIG.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 five, a decode threshold of three, a read threshold of four, and a write threshold of four. In accordance with the data segmenting protocol, the computing device12or16divides 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.,1through 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.

FIG.5illustrates 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 (EDS1_1), the second row of X21-X24 corresponds to a second encoded data slice (EDS2_1), the third row of X31-X34 corresponds to a third encoded data slice (EDS3_1), the fourth row of X41-X44 corresponds to a fourth encoded data slice (EDS4_1), and the fifth row of X51-X54 corresponds to a fifth encoded data slice (EDS5_1). Note that the second number of the EDS designation corresponds to the data segment number. In the illustrated example, the value X11=aD1+bD5+cD9, X12=aD2+bD6+cD10, . . . X53=mD3+nD7+oD11, and X54=mD4+nD8+oD12.

As a result of encoding, the computing device12or16produces 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 EDS1_1through EDS5_1and the first set of slice names includes SN1_1through SN5_1and the last set of encoded data slices includes EDS1_Y through EDS5_Y and the last set of slice names includes SN1_Y through SN5_Y.

In order to recover a data segment from a decode threshold number of encoded data slices, the computing device uses a decoding function as shown inFIG.8. As shown, the decoding function is essentially an inverse of the encoding function ofFIG.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.

In a dispersed storage network, storage units and memory devices may occasionally be unavailable for processing data storage requests (e.g., write slice requests). Such unavailability may affect only a certain part of a DSN address range or sub-address range. In the novel methodologies and devices described more fully below in conjunction withFIGS.9and10, a failed storage request due to such unavailability is resolved by generating a new DSN address (e.g., an address associated with differing or known healthy storage units/memory devices supporting a write threshold number), and retrying the storage request using the new DSN address.

Briefly, in an example of operation, a storage unit pool includes a storage set having 48 storage units, and pillar width of 12. In this example, the first one-quarter of an address range associated with the storage unit pool covers a set of storage units0-11, the second quarter of the address range covers a set of storage units12-23, the next quarter of the address range covers a set of storage units24-35, and the final quarter of the address range covers a set of storage units36-47. If a write slice request(s) is received having a DSN address processed by the set of storage units24-35, and fewer than a write threshold number of storage units of the set are available, a second DSN address is determined for use in retrying the write slice request(s). The second DSN address may specifically avoid the set of storage units24-35(e.g., the second DSN address may cover storage units36-47). In other examples, the second DSN address may cover differing memory devices of the set of storage units24-35.

Referring now toFIG.9, a schematic block diagram of a dispersed storage network (DSN) performing data storage in accordance with an embodiment of the present disclosure is illustrated. The DSN of this example includes the computing device16ofFIG.1, the network24ofFIG.1, and the distributed storage network (DSN) memory22ofFIG.1. The computing device16includes the DS client module34ofFIG.1. The DSN memory22includes a plurality of storage unit pools1-P. Each storage unit pool includes one or more storage sets1-S. Each storage set includes a set of storage units1-n, and each storage unit includes a plurality of memories1-M. Each storage unit may be implemented utilizing the storage unit36ofFIG.1, and further include a DS client module34and a processing module (not separately illustrated). Each memory of each storage set is associated with a DSN address range1-M (e.g., range of slice names). The storage units of a storage set/storage unit pool may be located at a same physical location (site) or located at multiple physical locations without departing from the technology as described herein.

In general, DSN memory22stores a plurality of dispersed storage (DS) error encoded data. The DS error encoded data may be encoded in accordance with one or more examples described with reference toFIGS.3-6, and organized (for example) in slice groupings or pillar groups. The data that is encoded into the DS error encoded data may be of any size and/or of any content. For example, the data may be one or more digital books, a copy of a company's emails, a large-scale Internet search, a video security file, one or more entertainment video files (e.g., television programs, movies, etc.), data files, and/or indexing and key information for use in dispersed storage operations.

In an example of operation of storing data in DSN memory22, the computing device16receives a store data request90. The store data request90includes one or more of a data object, a data object name, and a requester identity. Having received the store data request90, the DS client module34identifies a storage unit pool associated with the store data request. In an example, identifying a storage unit pool includes at least one of performing a vault lookup based on the requester identity, performing a random selection, selecting based on available storage set storage capacity, and selecting based on storage set performance levels.

Having identified the storage unit pool, the DS client module34generates a DSN address, where the DSN address falls within an address range (or a sub-address range of an address range) associated with a plurality of storage sets, where each storage set is associated with a plurality of address ranges, and where each address range is associated with a set of memories. For example, the DS client module34generates the DSN address based on a random number to produce an available DSN address within a plurality of address ranges of the identified storage unit pool. As another example, the DS client module34generates the DSN address based on memory attributes such as performance and available capacity.

Having generated the DSN address, the DS client module34initiates storage of the data object at the DSN address. For example, the DS client module34dispersed storage error encodes the data object (or a segment thereof) to produce a plurality of sets of encoded data slices (each set of which may include an information dispersal algorithm (IDA) width number of encoded data slices) and issues, via the network24, one or more sets of write slice requests as write requests92that includes the plurality of sets of encoded data slices to be stored in the storage units associated with the DSN address. Having issued the write requests92, the DS client module34receives write responses94from at least some of the storage units.

When an unfavorable condition is detected with regards to storage of the data object at the DSN address (e.g., less than a write threshold number of favorable write responses have been received), the DS client module34generates another DSN address, where the other DSN address is associated with another set of memories (e.g., of the same set of storage units or from another set of storage units).

Having generated the other DSN address, the DS client module34facilitates storage of the data object at the other DSN address. For example, the DS client module34resends the one or more sets of write slice requests92to a set of storage units associated with the other set of memories. Having resent the one or more sets of write slice requests92, the DS client module34may also update a DSN directory/hierarchical index96(e.g., maintained by the computing device16and/or other DSN devices) or equivalent to associate the data object name and the other DSN address.

In further examples, after another unfavorable condition is detected, the DS client module34may generate a third (or more) DSN address for use in storage of the data object. In addition, when a write slice request fails due to an unavailable or impaired memory device, the associated storage unit(s) may return an error response that includes a list of address ranges of the storage unit associated with available/unavailable memory devices. The DS client module34may then utilize this information to generate a DSN address that falls within an address range including available memory devices. This embodiment may be useful, for example, where only a single set of storage units is available (e.g., a storage set of 12 storage units and an IDA width of 12).

FIG.10is a flowchart100illustrating an example of storing data. The method begins or continues at step102where a processing module (e.g., of a distributed storage (DS) client module34) receives a store data request that includes a data object. Receiving the store data request may further include receiving a requester identity and a data object name. The method continues at step104where the processing module identifies a storage unit pool associated with the store data request. Identifying a storage unit pool may include one or more of interpreting system registry information, interpreting a vault entry associated with the requester identifier, performing a random selection, selecting based on performance, and selecting based on available storage capacity.

The method continues at step106where the processing module generates a dispersed storage network (DSN) address, where the DSN address falls within an address range (or a sub-address range of an address range) associated with the identified storage unit pool. Generating a DSN address may include at least one of generating a random address within the address range of the identified storage unit pool (e.g., to include a vault identifier and a random object number), selecting a next available DSN address, and selecting a DSN address associated with a set of memories associated with favorable performance and storage capacity.

The method continues at step108where the processing module initiates storage of the data object using the DSN address. In various examples, the processing module dispersed storage error encodes the data object to produce a plurality of sets of encoded data slices, generates a plurality of sets of slice names that includes the DSN address (e.g., includes a slice index, a segment number, the vault identifier, and the random object number), generates one or more sets of write slice requests that includes the plurality of sets of encoded data slices and the plurality of sets of slice names, and sends the one or more sets of write slice requests to a storage set associated with the DSN address.

When an unfavorable storage condition is detected, the method continues at step110where the processing module generates a second DSN address. For example, the processing module detects the unfavorable storage condition (e.g., a time frame expires without receiving a write threshold number of favorable write slice responses), identifies a set of memories associated with the DSN address, selects a different set of memories associated with favorable performance and available capacity, and generates a DSN address associated with the other set of memories as the second DSN address.

The method continues at step112where the processing module facilitates storage of the data object using the second DSN address. For example, the processing module issues write slice requests to storage units associated with the other set of memories, where the write slice requests include the plurality of sets of encoded data slices. When receiving favorable write slice responses, the processing module associates the data object name and the second DSN address. For example, the processing module updates a DSN directory. As another example, the processing module updates a dispersed hierarchical index.

The methods described above in conjunction with the computing device16and storage units36can alternatively be performed by other modules (e.g., DS client modules34) of a dispersed storage network or by other devices (e.g., managing unit18or integrity processing unit20). Any combination of a first module, a second module, a third module, a fourth module, etc. of the computing devices and the storage units may perform the method described above. In addition, at least one memory section (e.g., a first memory section, a second memory section, a third memory section, a fourth memory section, a fifth memory section, a sixth memory section, etc. of a non-transitory computer readable storage medium) that stores operational instructions/program instructions can, when executed by one or more processing modules of one or more computing devices and/or by the storage units of the dispersed storage network (DSN), cause the one or more computing devices and/or the storage units to perform any or all of the method steps described above.

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. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flow diagrams, and combinations of blocks in the block diagrams and/or flow diagrams, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.