Certain implementations of the disclosed technology may include methods and computing systems for performing high-density data compression, particularly on numerical data that demonstrates various patterns, and patterns of patters. According to an example implementation, a method is provided. The method may include extracting a data sample from a data set, compressing the data sample using a first compression filter configuration, and calculating a compression ratio associated with the first compression filter configuration. The method may also include compressing the data sample using a second compression filter configuration and calculating a compression ratio associated with the second compression filter configuration. A particular compression filter configuration to utilize in compressing the entire data set may be selected based on a comparison of the compression ratio associated with the first compression filter configuration and a compression ratio associated with the second compression filter configuration.

A computer processing system includes a processor to operate in a first computing environment. The processor creates a generic application layer by scrubbing a new application layer within the computer processing system to remove objects associated with the new application layer and specific to the first computing environment. The processor further creates within the computer processing system a single composited layered image by merging the generic application layer with at least one other application layer having objects associated therewith.

A computer processing system includes a processor to operate in a first computing environment. The processor creates a generic application layer by scrubbing a new application layer within the computer processing system to remove objects associated with the new application layer and specific to the first computing environment. The processor further creates within the computer processing system a single composited layered image by merging the generic application layer with at least one other application layer having objects associated therewith.

The disclosed technology relates to a system configured to detect a modification to a node in a tree data structure. The node is associated with a content item managed by a content management service as well as a filename. The system may append the filename and a separator to a filename array, determine a location of the filename in the filename array, and store the location of the filename in the node.

A data storage arrangement includes a memory and a controller, where the controller receives an indication of data to be anonymized. The controller further parses a data element to be stored and generates a copy of one or more data portions to be anonymized. The controller further deletes one or more data portions to be anonymized to generate a modified data element to be stored. The controller further generates a copy of the modified data element to be stored utilizing deduplication. The data storage arrangement thus takes in account data anonymization during deduplication (i.e. an anonymization aware deduplication).

A file storage include: a processor that receives a write request for a file from an application, writes data of the file to a storage unit, then compresses the data of the written file, and writes the compressed data to the storage unit. The processor determines a compression algorithm to be used for the compression according to an amount of data, which is written during a predetermined time, of one or more written files.

Embodiments of small file restore process in deduplication file system wherein restoration requires issuing a read request within an I/O request to the file system. The process places the files in a prefetch queue such that a combined size of the files meets or exceeds a size of the prefetch queue as defined by a prefetch horizon. A file handler disassociates prefetch streams from read streams. The handler prefetches the read operations and stores them in memory. The stream corresponding to a read will only open as the read requests hit the queue processor. As a result, the stream usage is very low, since the I/O, worker threads and the read streams are disassociated from each other.

Automated methods and systems for compressing log messages stored in a log message databased are described herein. The automated methods and systems perform lossy compression of an original set of log messages by identifying log messages that represent each of the various types of events recorded in the original set. The log messages in the original set are overwritten by corresponding representative log messages. Source coding is used to construct a source coding scheme and variable length binary codewords for each of the representative log messages. The representative log messages are replaced by the codewords, which occupies significantly less storage space than the original set. The lossy compressed set of log messages can be decompressed to obtain the representative log messages using the source coding scheme.

The method for uploading a configuration file includes: obtaining, by a network device, a local configuration file, where the local configuration file includes configuration information of the network device; compressing, by the network device, the local configuration file, to obtain a compressed file; and sending, by the network device, a configuration file upload request to a storage apparatus, where the configuration file upload request includes the compressed file, and the configuration file upload request is used for requesting the storage apparatus to store the compressed file.

The present invention discloses a gene sequencing data compression preprocessing, compression and decompression method, a system, and a computer-readable medium. The preprocessing method implementation steps include: obtaining reference genome data; obtaining a mapping relationship between a short string K-mer and a prediction character c to obtain a prediction data model P1 containing any short string K-mer in the positive strand and negative strand of a reference genome and the prediction character c in a corresponding adjacent bit. The compression and decompression methods relate to performing compression/decompression on the basis of the prediction data model P1. The system is a computer system including a program for executing the previous method. The computer-readable medium includes a computer program for executing the previous method. The present invention can be oriented towards lossless gene sequencing data compression, provides fully effective information for a high-performance lossless compression and decompression algorithm for gene sequencing data.