Abstract: Embodiments relate to computing systems, methods, and non-transitory computer-readable storage media. Identifier collisions are determined in historical event data based on short identifiers associated with a first event location and short identifiers associated with a second event location geographically dispersed from the first event location. Behavior analytics are performed on short identifiers in the historical event data to generate behavioral models associated with the short identifiers. Adjusted behavioral models are generated based on the determined identifier collisions. A short identifier is obtained from a client device, and based on the short identifier, an adjusted behavioral model of the adjusted behavioral models is determined. An expected event frequency is determined based on the adjusted behavioral model and an actual event frequency is determined.

Abstract: Change notify responses can be utilized to inform a remote computer that a file or directory that is being monitored has changed. A change notify response can include a path name to the file or directory being referenced. In some examples, a cache of path names can be maintained in a user space of a server implementing change notify responses. When a module that generates a change notify response does generate such a response, the module can first access the cache to determine if the relevant path name is located in the cache. Where the relevant path name is not located in the cache, the module can obtain the path name from kernel space and store it in the cache.

Abstract: Stream retention in a data storage system is described herein. A method as described herein can include receiving, by a device operatively coupled to a processor, a hold for a portion of a data stream, wherein the data stream comprises respective events indexed by time, and wherein the portion of the data stream is bounded by a first event of the data stream that is associated with a first time and a second event of the data stream that is associated with a second time; generating, by the device, a synthetic stream comprising the portion of the data stream; and preventing, by the device, events of the data stream that are included in the synthetic stream from alteration.

Abstract: A method of generating matching metadata vectors for identifying content items in a store searchable by input vectors, the method comprising: receiving multiple training inputs, each training input comprising a content identifier indicative of a content item, and at least one natural language description of the content item; for each training input: converting the natural language description into at least one text component; generating at least one vector, each vector corresponding to one text component; generating a set of component parts for each vector, each component part corresponding to a coordinate initialized with a random value; adjusting each random coordinate based on the relationship of each component part to other vectors; determining a weighting for each vector with respect to the item; and defining a metadata vector for each item comprising the vectors containing the adjusted coordinates for that item and the weighting for each vector.

Abstract: A data storage system includes non-volatile data storage including a container partition and a browsable partition and control circuitry configured to backup a file in the non-volatile data storage at least in part by receiving the file from a host, the file including a plurality of chunks of data, storing the plurality of chunks of data in the browsable partition of the non-volatile data storage, determining that one or more of the plurality of chunks has been modified, storing the one or more modified chunks in a container partition of the non-volatile data storage, determining a new chunk associated with each of the one or more modified chunks, and storing the one or more new chunks in the browsable partition of the non-volatile data storage.

Abstract: In some examples, a system performs data deduplication using a deduplication fingerprint index in a hash data structure comprising a plurality of blocks, wherein a block of the plurality of blocks comprises fingerprints computed based on content of respective data values. The system merges, in a merge operation, updates for the deduplication fingerprint index to the hash data structure stored in a persistent storage. As part of the merge operation, the system mirrors the updates to a cached copy of the hash data structure in a cache memory, and updates, in an indirect block, information regarding locations of blocks in the cached copy of the hash data structure.

Abstract: Described are systems and methods for storing a variable number of instances of data objects (e.g., 1, 2, 3, or up to N?1 instances, where N is the number of instances of the data object included in primary data) in secondary storage across a data storage network. In some examples, a system for storing a variable number of instances of data objects includes, one or more computing devices storing a set of data objects and multiple storage devices distinct from the one or more computing devices. Each of the multiple storage devices is configured to store at least a single instance of a data object. The system also includes a database configured to store information associated with the data objects. This information includes substantially unique identifiers for the data objects and, for each of the data objects, a number of instances of the data object stored on the multiple storage devices.

Abstract: A method of storing a data object includes dividing data of a data object into a first part of data and a second part of data, in response to receiving a writing request for a data object, the first part of data including a data field of the data object, the second part of data including a meta data of the data object; writing the first part of data into a first data file stored in a first external storage device; and writing, into a second data file stored in a second external storage device, first location information, and the second part of data, the first location information including location information of the first part of data within the first external storage device.

Abstract: A data writing and reading method and apparatus, and a cloud storage system. The data writing method includes an access node receiving a data write request, identifying domain identification information contained in the data write request when failing to obtain an available management node, and querying a pre-saved index according to the domain identification information, wherein the index includes a correspondence between a resource pool and domain identification information, identifying a target resource pool that matches the domain identification information, each resource pool including at least one storage server, determining, from at least one storage server included in the target resource pool, one of the storage servers as a target storage server, and writing data to be written into the target storage server, to ensure that the cloud storage system operates normally without additional cost when all management nodes are at fault or the management node cluster network is abnormal.

Abstract: Methods and systems for cross cluster replication are provided. Exemplary methods include: periodically requesting by a follower cluster history from a leader cluster, the history including at least one operation and sequence number pair, the operation having changed data in a primary shard of the leader cluster; receiving history and a first global checkpoint from the leader cluster; when a difference between the first global checkpoint and a second global checkpoint exceeds a user-defined value, concurrently making multiple additional requests for history from the leader cluster; and when a difference between the first global checkpoint and the second global checkpoint is less than a user-defined value, executing the at least one operation, the at least one operation changing data in a primary shard of the follower cluster, such that an index of the follower cluster replicates an index of the leader cluster.

Abstract: Provided is a method, computer program product, and system for classifying a set of data items based on format organizations. A processor may determine at least one format organization of a set of data items. The format organization of a data item indicates a symbol type of at least one continuous symbol in the data item and a number of the at least one continuous symbol. The processor may determine at least one candidate data class for the set of data items from a plurality of predetermined data classes based on the at least one format organization. The processor may classify the set of data items into at least one target data class selected from the at least one candidate data class. In this way, the set of data items can be efficiently classified.

Abstract: A system and a method for contextual categorization of data comprises a server having a processor and a non-transitory computer-readable storage medium in electronic communication with the processor and comprising program instructions executable by the processor to access an initial inventory of data set and metadata associated with the initial inventory of data set. The system is then configured to classify the initial inventory of data set by using the metadata into (a) reduced set of data comprising high level sensitivity classification and (b) a remainder data set.

Abstract: The present disclosure relates to restricting electronic activities from being linked with record objects. According to at least one aspect of the disclosure, a method can include accessing, by one or more processors, a plurality of electronic activities, accessing a plurality of record objects of one or more systems of record, identifying an electronic activity of the plurality of electronic activities to match to one or more record objects, determining a data source provider associated with providing access to the electronic activity, and identifying a system of record corresponding to the determined data source provider. The system of record can include a plurality of candidate record objects to which to match the electronic activity. The method can include restricting the electronic activity from being linked with the at least one record object.

Abstract: In accordance with various embodiments, described herein is a system (Data Artificial Intelligence system, Data AI system), for use with a data integration or other computing environment, that leverages machine learning (ML, DataFlow Machine Learning, DFML), for use in managing a flow of data (dataflow, DF), and building complex dataflow software applications (dataflow applications, pipelines). In accordance with an embodiment, the system provides a programmatic interface, referred to herein in some embodiments as a foreign function interface, by which a user or third-party can define a service, functional and business types, semantic actions, and patterns or predefined complex data flows based on functional and business types, in a declarative manner, to extend the functionality of the system.

Abstract: A method may include obtaining a first matrix that represents data in a data set and obtaining a number of clusters into which the data is to be grouped. The method may further include constructing a second matrix using the first matrix and the number of clusters. The second matrix may represent a formulation of a first optimization problem in a framework of a second optimization problem. The method may further include solving the second optimization problem using the second matrix to generate a solution of the second optimization problem and mapping the solution of the second optimization problem into a first solution matrix that represents a solution of the first optimization problem. The method may further include grouping the data into multiple data clusters using the first solution matrix. A number of the multiple data clusters may be equal to the number of clusters.

Abstract: Methods and systems are provided for improved access to rows of data in a distributed data system. Each data row is associated with a partition. Data rows are distributed in one or more files and an impure file includes data rows associated multiple partitions. A clustering set is generated from a plurality of impure files by selecting a candidate impure file based on file access activity metrics and one or more neighbor impure files. Data rows of the impure files included in the clustering set are sorted according to their respective associated partitions. A set of disjoint partition range files are generated based on the sorted data rows of the impure files included in the clustering set. Each file of the set of disjoint partition range files is transferred to a respective target partition.

Abstract: The subject technology determines an availability zone skew among multiple zones. The subject technology, based on the availability zone skew, determines a target skew to meet a global balancing of cluster instances. The subject technology, based on the target skew, selects a particular zone among multiple zones. The subject technology deploys a particular type of cluster instance to the particular zone. The subject technology, for each zone from the multiple zones, determining a respective number of cluster instances. The subject technology identifies a first zone that includes a highest number of cluster instances based on the respective number of cluster instances from each zone. The subject technology identifies a second zone that includes a lowest number of cluster instances based on the respective number of cluster instances from each zone.

Abstract: Methods, systems, and devices supporting data storage are described. A database server may store information in a group of files. As more information is stored at the database in the files, the sizes of the files may be increased. Techniques are described for uniformly growing files in the group of files to maintain a similar size for the files as the amount of storage increases. These techniques may prevent one file from becoming disproportionately larger than another file of the file group, supporting efficient read and write operations at the database. The file growth may be based on the file sizes as well as an amount of storage to be added for the group of files. For example, an application managing the file growth may sort the files by size, track uniform growth running totals, and determine file growth commands based on the uniform growth running totals.

Abstract: A computer-implemented method for representing and storing data in an extendable graph data structure using artificial intelligence includes obtaining business requirements data, business workflow data, and dictionary data. A relationship between one or more entities in the obtained business requirement data and the business workflow data is identified using the obtained dictionary data and applying a natural language processing technique and topic based trend identification from existing entities and associated attributes. An extendable graph data structure represented by an enriched adjacency matrix for the identified relationship between the one or more entities is generated and stored. One or more trends are identified using the stored graph data structure.

Abstract: A system for a product navigator is provided. The system receives a search string at a business-type classification interface on an interactive user display. A search type associated with the search string may be determined based on a search type selection from a plurality of search types. A search of a database may be initiated for an entry matching the search string according to the search type, where the entry has corresponding business-type classification data including a brief classification description, an extended classification description, and an associated classification code. The brief classification description and the extended classification description may be output on the interactive user display based on receiving the corresponding business-type classification data from the database.