The present disclosure is generally related to deduplication, and more particularly, to selecting a deduplication process based on a difference between performance metrics.
Data deduplication is a process to eliminate or remove redundant data to improve the utilization of storage resources. For example, during the deduplication process, blocks of data may be processed and stored. When a subsequent block of data is received, the subsequent block of data may be compared with the previously stored block of data. If the subsequent block of data matches with the previously stored block of data, then the subsequent block of data may not be stored in the storage resource. Instead, a pointer to the previously stored block of data may replace the contents of the subsequent block of data.
The present disclosure is illustrated by way of example, and not by way of limitation, and can be more fully understood with reference to the following detailed description when considered in connection with the figures as described below.
Aspects of the present disclosure relate to selecting a deduplication process based on a difference between performance metrics. For example, data blocks may be analyzed by a deduplication process to determine whether a duplicate or copy of the data block is currently stored at a storage system. The deduplication process may use a hash function that generates a hash value based on the data block. The generated hash value may be compared with hash values of a deduplication map that identifies currently stored data blocks at the storage system. If the generated hash value matches with any of the hash values in the deduplication map, then the data block may be considered to be a copy or duplicate of another data block that is currently stored at the storage system. Alternatively, the deduplication process may directly compare the received data block with another data block that is currently stored at the storage system. Thus, the deduplication process may be based on comparing a generated hash value with a hash value retrieved from a deduplication map or based on comparing a received data block with a retrieved data block that has been previously stored at the storage system.
The storage system may use either deduplication process to determine whether copies of received data blocks are currently stored at the storage system. For example, a series (i.e., stream) of data blocks may be received to be stored at the storage system. A first hash value may be generated for one of the data blocks of the series of data blocks and the generated hash value may be compared with hash values in a deduplication map. If the first hash value matches with another hash value in the deduplication map, then the corresponding received data block of the series of data blocks may be considered a duplicate of another data block that is currently stored at the storage system.
Subsequently, a deduplication process may be used to determine whether the other data blocks of the series of data blocks are also duplicates of currently stored data blocks at the storage system. For example, the first deduplication process may be used to generate hash values for the other data blocks of the series and retrieve stored hash values associated with the other data blocks and currently stored in the deduplication map. The generated hash values may be compared with the retrieved hash values to determine whether the other data blocks of the series are duplicates of currently stored data blocks. Alternatively, the second deduplication process may be used to retrieve other stored data blocks that are associated with the stored data block and then compare the other received data blocks of the series with the other stored data blocks that have been retrieved to determine whether the other data blocks of the series are duplicates of the currently stored data blocks.
The first deduplication process and the second deduplication process may retrieve, respectively, the stored hash values and the other stored data blocks by retrieving the stored hash values and the stored data blocks from cache memory (i.e., a local memory) and a storage resource (i.e., a backing storage) at the storage system. For example, a subset of the hash values or data blocks may be retrieved from the cache memory and another subset may be retrieved from the storage resource. The retrieving of the hash values or data blocks from the cache memory may take less time than the retrieving of the hash values or data blocks from the storage resource. Thus, depending on the number of hash values to be retrieved that are that are stored at the cache memory as opposed to the storage resource and the number of data blocks to be retrieved that are stored at the cache memory as opposed to the storage resource, the performance of the first deduplication process and the second deduplication process may vary. For example, at certain times, the first deduplication process may be more efficient and take less time than the second deduplication process, and vice versa at other times. Thus, if a particular deduplication process is selected to be used by the storage system, a less efficient and time consuming deduplication process may be selected while a more efficient and less time consuming deduplication process may be available to the storage system.
Aspects of the present disclosure address the above and other deficiencies by determining or calculating performance metrics for the deduplication processes. For example, a first performance metric may be determined for the first deduplication process and a second performance metric may be determined for the second deduplication process. As described in further detail below, the performance metrics may be based on whether the respective data blocks or hash values are stored in cache memory, the storage resource, size of the data blocks that are to be retrieved, the number of data blocks that are to be retrieved, performance characteristics of the storage system, etc. If the first performance metric of the first deduplication process does not exceed the second performance metric of the second deduplication process (e.g., the first and second performance metrics predict less time for performing the first deduplication process as opposed to the second deduplication process) then the first deduplication process may be used to determine whether other data blocks of the series of data blocks received at the storage system are duplicates of currently stored data blocks at the storage system. Otherwise, if the second performance metric predicts that the second deduplication process may take less time to perform than the first performance metric, then the second deduplication process may be used to determine whether the other data blocks of the series of data blocks are duplicates of currently stored data blocks.
Thus, the present disclosure may improve the performance of a storage system by determining performance metrics for performing operations of deduplication processes. For example, the deduplication process that may perform a deduplication operation for data blocks faster than another deduplication process may be selected for use by the storage system when appropriate as based on the performance metrics.
The deduplication process may be an inline data deduplication process where a data block is received and then analyzed before being stored in the storage resource 130. For example, the data deduplication process may determine whether copies of the data blocks 110 that are received are currently stored in the storage resource 130 (e.g., a solid-state non-volatile memory such as flash memory) before storing the received data blocks 110 in the storage resource 130. Thus, the inline data deduplication process may be performed as a stream of data blocks 110 are received to be stored in the storage resource 130.
In general, the deduplication process may receive a data block (e.g., of the series of data blocks) and perform a hash function with the data block to generate a hash value. The hash function may transform the data block of an arbitrary size to data of a fixed size corresponding to the hash value. The deduplication process may store the hash value for comparison with a subsequent data block. For example, when the subsequent data block is received, the hash function may be performed on the subsequent data block to generate a corresponding hash value based on the contents of the subsequent data block. If the corresponding hash value of the subsequent data block matches the previously stored hash value, then the contents of the subsequent data block may be a copy of the contents of the previously received data block. Instead of storing the contents of the subsequent data block, a pointer to the previously received data block with the matching hash value may be used to replace the contents of the subsequent data block.
As shown in
As described in further detail with regard to
The storage resource 130 may correspond to non-disk storage media that is managed by or coupled with the deduplication selector component 125. For example, the storage resource 130 may be one or more solid-state drives (SSDs), flash memory based storage, any type of solid-state non-volatile memory, or any other type of non-mechanical storage device. In some embodiments, the storage resource 130 may be a storage device that includes a flash memory.
As shown in
The processing logic may determine a first performance metric associated with retrieving one or more data blocks associated with the particular data block (block 240). The first performance metric may be based on retrieving data blocks that are proximate (e.g., logically proximate in a logical space or physically proximate at the storage resource) to the particular data block at the location at the storage resource of the storage system that is identified by the generated hash value. For example, the data blocks may be in a particular range of data blocks that includes the particular data block or is around the particular data block. The retrieving of the data blocks may be based on retrieving the data blocks from a cache memory of the storage system and/or from a storage resource of the storage system. For example, the data blocks may be retrieved from the cache memory instead of the storage resource when the respective data blocks are currently stored at the cache memory. Thus, the first performance metric may be based on whether data blocks that are to be retrieved are currently stored at the cache memory or the storage resource. The first performance metric may indicate a better performance (e.g., less time to perform a first deduplication process) when more data blocks to be retrieved are currently stored at the cache memory. Further details with regards to determining a performance metric are described in conjunction with
Furthermore, the processing logic may determine a second performance metric associated with retrieving one or more hash values associated with the series of data blocks (block 250). The second performance metric may be based on retrieving hash values that are stored in a deduplication map and generating hash values for the other data blocks of the series of data blocks. Furthermore, the second performance metric may similarly indicate a better performance (e.g., less time to perform a second deduplication process) when more hash values of the deduplication map that are to be retrieved are currently stored at the cache memory instead of the storage resource.
Referring to
As shown in
In operation, a series of data blocks 305 may be received by the deduplication selector component 125 of the storage system 310 to be stored at the storage resource 330. In response to receiving the data blocks 305, a deduplication process may be selected by the deduplication selector component 125 as described in conjunction with
Although aspects of the present disclosure relate to inline data deduplication, the disclosure herein may be applied to post-processing data deduplication that may be used to analyze data blocks currently stored on the storage resource 330. For example, the post-processing deduplication may analyze each data block that is currently stored on the storage resource 330 to determine whether the corresponding data block is a copy or duplicate of another data block currently stored on the storage resource 330.
Thus, data blocks and hash values may be stored in a local memory and a storage resource. A deduplication process may be selected based on a distribution of the data blocks and hash values in the local memory and the storage resource.
As shown in
Referring to
As shown in
Subsequently, the processing logic may determine the first performance metric for the first deduplication process based on the number of data blocks that are to be retrieved from the storage resource, the size of the data blocks, the number of read accesses, and the hardware cost (block 530). In some embodiments, the first performance metric may indicate a longer amount of time to perform the first deduplication process when the number of data blocks to be retrieved from the storage increases, the size of the data blocks increases, the number of read accesses increases, and when the hardware cost corresponds to an increase in network bandwidth and processing usage.
As shown in
Subsequently, the processing logic may determine the second performance metric for the second deduplication process based on the number of hash values that are to be retrieved from deduplication map at the storage resource, the number of read accesses, the hardware cost, and the amount of time to generate the hash values (block 575). In some embodiments, the second performance metric may indicate a longer amount of time to perform the second deduplication process when the number of hash values to be retrieved from the storage increases, the number of read accesses increases, when the hardware cost corresponds to an increase in network bandwidth and processing usage, and when the amount of time to generate the hash values increases.
The exemplary computer system 600 includes a processing device 602, a main memory 604 (e.g., read-only memory (ROM), flash memory, dynamic random access memory (DRAM) such as synchronous DRAM (SDRAM)), a solid-state non-volatile memory 606 (e.g., flash memory, 3D crosspoint (XPoint) memory, magnetoresistive random-access memory (MRAM), or any other such storage media that does not use a physical disk), and a data storage device 616, which communicate with each other via a bus 608.
Processing device 602 represents one or more general-purpose processing devices such as a microprocessor, central processing unit, or the like. More particularly, the processing device 602 may be a complex instruction set computing (CISC) microprocessor, reduced instruction set computing (RISC) microprocessor, very long instruction word (VLIW) microprocessor, or a processor implementing other instruction sets or processors implementing a combination of instruction sets. The processing device 602 may also be one or more special-purpose processing devices such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), network processor, or the like. The processing device 602 is configured to execute the deduplication selector component 125 of
While the computer-readable storage medium 624 is shown in the illustrative examples to be a single medium, the term “computer-readable storage medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term “computer-readable storage medium” shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the present disclosure. The term “computer-readable storage medium” shall accordingly be taken to include, but not be limited to, solid-state memories, optical media, and magnetic media.
Although the operations of the methods herein are shown and described in a particular order, the order of the operations of each method may be altered so that certain operations may be performed in an inverse order or so that certain operation may be performed, at least in part, concurrently with other operations. In certain implementations, instructions or sub-operations of distinct operations may be in an intermittent and/or alternating manner.
It is to be understood that the above description is intended to be illustrative, and not restrictive. Many other implementations will be apparent to those of skill in the art upon reading and understanding the above description. The scope of the disclosure should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.
In the above description, numerous details are set forth. It will be apparent, however, to one skilled in the art, that the present disclosure may be practiced without these specific details. In some instances, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring the present disclosure.
Some portions of the detailed descriptions above are presented in terms of algorithms and symbolic representations of operations on data bits within a computer memory. These algorithmic descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. An algorithm is here, and generally, conceived to be a self-consistent sequence of steps leading to a desired result. The steps are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like.
It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless specifically stated otherwise, as apparent from the following discussion, it is appreciated that throughout the description, discussions utilizing terms such as “receiving,” “determining,” “performing,” “using,” “registering,” “recording,” or the like, refer to the action and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical (electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices.
The present disclosure also relates to an apparatus for performing the operations herein. This apparatus may be specially constructed for the required purposes, or it may comprise a general purpose computer selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a computer readable storage medium, such as, but not limited to, any type of disk including floppy disks, optical disks, CD-ROMs, and magnetic-optical disks, read-only memories (ROMs), random access memories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, or any type of media suitable for storing electronic instructions, each coupled to a computer system bus.
The algorithms and displays presented herein are not inherently related to any particular computer or other apparatus. Various general purpose systems may be used with programs in accordance with the teachings herein, or it may prove convenient to construct more specialized apparatus to perform the required method steps. The required structure for a variety of these systems will appear as set forth in the description below. In addition, the present disclosure is not described with reference to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the disclosure as described herein.
The present disclosure may be provided as a computer program product, or software, that may include a machine-readable medium having stored thereon instructions, which may be used to program a computer system (or other electronic devices) to perform a process according to the present disclosure. A machine-readable medium includes any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer). For example, a machine-readable (e.g., computer-readable) medium includes a machine (e.g., a computer) readable storage medium (e.g., read only memory (“ROM”), random access memory (“RAM”), magnetic disk storage media, optical storage media, flash memory devices, etc.).
The words “example” or “exemplary” are used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as “example” or “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects or designs. Rather, use of the words “example” or “exemplary” is intended to present concepts in a concrete fashion. As used in this application, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or”. That is, unless specified otherwise, or clear from context, “X includes A or B” is intended to mean any of the natural inclusive permutations. That is, if X includes A; X includes B; or X includes both A and B, then “X includes A or B” is satisfied under any of the foregoing instances. In addition, the articles “a” and “an” as used in this application and the appended claims should generally be construed to mean “one or more” unless specified otherwise or clear from context to be directed to a singular form. Moreover, use of the term “an embodiment” or “one embodiment” or “an implementation” or “one implementation” throughout is not intended to mean the same embodiment or implementation unless described as such. Furthermore, the terms “first,” “second,” “third,” “fourth,” etc. as used herein are meant as labels to distinguish among different elements and may not necessarily have an ordinal meaning according to their numerical designation.
This is a continuation application for patent entitled to a filing date and claiming the benefit of earlier-filed U.S. Pat. No. 11,704,036, issued Jul. 18, 2023, which is a continuation of U.S. Pat. No. 10,133,503, filed Nov. 20, 2018, which is a non-provisional application of U.S. Provisional Application No. 62/330,728, filed May 2, 2016 each of which are herein incorporated by reference in their entirety.
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