Emc IP Holding Company LLC

Hytrust, Inc.

Datagravity, Inc.

Istvan Gonczi

Sorin Faibish

Ivan Bassov

Philippe Armangau

Vamsi K Vankamamidi

Ivan Basov

Philip N Shilane

Anton Kucherov

Bryan Keith Panner

Paula Long

Misha Zelikov

Janice Ann Lacy

Kumar Kanteti

Gregory James McHale

Dmitry Bochkov

Andrew Ferris

Eric K Mccall

Gregory James Mchale

A technique for performing data deduplication operates at sub-block granularity by searching a deduplication database for a match between a candidate sub-block of a candidate block and a target sub-block of a previously-stored target block. When a match is found, the technique identifies a duplicate range shared between the candidate block and the target block and effects persistent storage of the duplicate range by configuring mapping metadata of the candidate block so that it points to the duplicate range in the target block.

Deduplicating data at sub-block granularity

A method, computer program product, and computer system for identifying duplicate sectors in a block of a plurality of blocks. The duplicate sectors in the block may be zeroed out. A data reduction operation may be performed on the block after the duplicate sectors are zeroed out.

System and method for sub-block deduplication with search for identical sectors inside a candidate block

A method performed by a block-storage server, of storing data is described. The method includes (1) receiving, from a remote file server, data blocks to be written to persistent block storage managed by the block-storage server; (2) receiving, from the remote file server, metadata describing files to which the data blocks belong in a set of filesystems managed by the remote file server; and (3) selectively applying data reduction when storing the data blocks in the persistent block storage based, at least in part, on the received metadata. An apparatus, system, and computer program product for performing a similar method are also provided.

File layer to block layer communication for selective data reduction

A method performed by a block-storage server, of storing data is described. The method includes (1) receiving, from a remote file server, data blocks to be written to persistent block storage managed by the block-storage server; (2) receiving, from the remote file server, metadata describing a placement of the data blocks in a filesystem managed by the remote file server; and (3) organizing the data blocks within the persistent block storage based, at least in part, on the received metadata. An apparatus, system, and computer program product for performing a similar method are also provided.

File layer to block layer communication for block organization in storage

A technique for managing data storage includes generating entropy of blocks on a per-block basis and selectively performing inline compression on blocks based at least in part on their entropy. Entropy of a block provides a rough measure of the block's compressibility. Thus, using per-block entropy enables a storage system to steer compression decisions, e.g., whether to compress and/or how much to compress, flexibly and with high granularity, striking a balance between throughput and storage efficiency.

Adaptive inline compression

A technique for performing data reduction applies deduplication principles when performing data compression, providing a form of enhanced compression. The technique obtains a chunk of data that contains multiple extents and applies deduplication actions to identify duplicate extents within the chunk. The technique marks duplicate extents in metadata. Such duplicate extents need not be compressed using conventional data compression, saving computational resources and considerable time.

Compressing data using deduplication-like methods

Techniques for generating data sets may include: receiving an initial buffer that achieves a compression ratio responsive to compression processing using a compression algorithm, the initial buffer including first content located at a first position in the initial buffer and including second content located at a second position in the initial buffer; and generating a data set of buffers using the initial buffer. The data set may be expected to achieve a specified deduplication ratio responsive to deduplication processing and to achieve the compression ratio responsive to compression processing using the compression algorithm. Generating the data set may include generating a first plurality of buffers where each buffer of the first plurality is not a duplicate of another buffer in the first plurality, and generating a second plurality of duplicate buffers. Each duplicate buffer may be a duplicate of a buffer in the first plurality of buffers.

Techniques for generating data sets with specified compression and deduplication ratios

A method, computer program product, and computing system for receiving a candidate data portion; calculating a distance-preserving hash for the candidate data portion; and performing an entropy analysis on the distance-preserving hash to generate a hash entropy for the candidate data portion.

System and method for hash-based entropy calculation

A method, computer program product, and computer system for identifying a plurality of blocks. At least one heuristic associated with at least a portion of the plurality of blocks may be determined. It may be determined whether at least the portion of the plurality of blocks is a candidate for deduplication based upon, at least in part, the at least one heuristic. At least the portion of the plurality of blocks may be deduplicated based upon, at least in part, the at least one heuristic.

System and method for detecting deduplication opportunities

Techniques for processing data may include: receiving a plurality of data chunks for a data set; performing data deduplication processing for the plurality of data chunks; determining, in accordance with one or more criteria, whether a frequency distribution of a frequency histogram of digest byte frequencies is sufficiently uniform; and responsive to determining that the frequency distribution of the frequency histogram is not sufficiently uniform, performing processing to update data deduplication settings for the data set. Updating the data deduplication settings may include using a stronger hash algorithm and/or a larger size digest when generating subsequent digests. The data deduplication processing may include: determining, using a current hash algorithm, a plurality of digests for the plurality of data chunks of the data set; and updating the frequency histogram of digest byte frequencies for the data set in accordance the plurality of digests.

Selection of digest hash function for different data sets

Techniques for data processing may include: receiving a data chunk of the data set; determining, in accordance with criteria including a compressibility ratio for the data set and a cost ratio of compression computation cost and entropy computation cost, whether to activate or deactivate entropy computation for the data set, wherein the compressibility ratio is ratio of a number of compressible data chunks of the data set and a number of uncompressible data chunks of the data set; and responsive to determining to activate entropy computation for the data set, performing first processing comprising: determining an entropy value for the data chunk; and determining, in accordance with the entropy value for the data chunk, whether to compress the data chunk.

Techniques for selectively activating and deactivating entropy computation

A method of accepting writes in a multilayered storage system is provided. The method includes (a) monitoring a rate of flushing of data from a first data storage component to a second data storage component; (b) setting an intake rate for the first data storage component based on the monitored flushing rate; and (c) throttling writes to the first data storage component based on the set intake rate. An apparatus, system, and computer program product for performing a similar method are also provided.

Adaptive ingest throttling in layered storage systems

Techniques for processing data may include: receiving a candidate data block; computing a distance using a distance function, wherein the distance is an entropy-based distance and denotes a measurement of similarity between the candidate data block and a target data block; and determining, using the distance, whether to perform data deduplication of the candidate data block with respect to the target data block to identify at least one sub-block of the candidate data block that is a duplicate of at least one sub-block of the target data block. If the distance is less than a threshold, it may be expected to have a matching sub-block between the candidate and target data blocks. The distance may be a difference between entropy values for the candidate and target data blocks. The first entropy value may be used to determine whether to compress or perform partial deduplication for the candidate data block.

Detecting data deduplication opportunities using entropy-based distance

A method, computer program product, and computing system for performing an entropy analysis on each of a plurality of candidate data chunks associated with a potential candidate to generate a plurality of candidate data chunk entropies; performing an entropy analysis on each of a plurality of target data chunks associated with a potential target to generate a plurality of target data chunk entropies; identifying a candidate data chunk entropy limit, chosen from the plurality of candidate data chunk entropies, and a target data chunk entropy limit, chosen from the plurality of candidate data chunk entropies; and comparing a specific candidate data chunk associated with the candidate data chunk entropy limit to a specific target data chunk associated with the target data chunk entropy limit to determine if the specific candidate data chunk and the specific target data chunk are identical.

System and method for offset-based deduplication

Techniques for processing data may include: receiving a candidate data block; computing a distance using a distance function, wherein the distance denotes a measurement of similarity between the candidate data block and a target data block; and determining, using the distance, whether to perform data deduplication of the candidate data block with respect to the target data block to identify at least one sub-block of the candidate data block that is a duplicate of at least one sub-block of the target data block. The distance may be computed using a bit-wise logical exclusive-or operation of the contents of the candidate data block and the target data block. The distance may be computed using a bit-wise logical exclusive-or operation of digests computed for the candidate and target data blocks using a distance preserving hash function. The target and candidate block may be similar if the distance is less than a threshold.

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Berkley, MA, United States of America

Istvan Gonczi