Abstract: In one example, a method includes receiving, at a cloud storage site, chunks that each take the form of a hash of a combination that includes two or more salts and a file object, and one of the salts is a retention salt shared by the chunks, monitoring a time period associated with the retention salt, when the time period has expired, removing the chunks that include the retention salt, and depositing the removed chunks in a deleted items cloud store.

Abstract: The system and methods described herein provide content recommendations to user equipment timed to reduce interruption of content. A content recommendation application detects output of first content and determines viewing metrics for the first content. Using the determined viewing metrics, the content recommendation application determines whether output of a content recommendation should be blocked. In response to determining that the viewing metrics indicate output of the content recommendation should be blocked, the content recommendation application blocks the content recommendation. Upon receiving an input changing output of the first content to output of a second content, the content recommendation application unblocks and outputs the content recommendation.

Abstract: A computing system generates, for each of a plurality of sessions, a session representation indicating the order through which a user navigated through a plurality of webpages during the session, and generates for each pair of session representations, a score indicating how similar the session representations in each pair are to each other. The computing system further generates a plurality of clusters by clustering the session representations based on the score for each pair of session representations, determines an optimal number of clusters based on key performance indicators corresponding to each cluster of the plurality of clusters, and generates a natural language description for each cluster of the optimal number of clusters based on the key performance indicators associated with each cluster.

Abstract: An information provision method includes accumulating, in a first database, a first identifier identifying each of one or more service providers, and first device information indicating an electrical device to be designated by each of the one or more service providers in association with each other; accumulating, in a second database, a second identifier identifying each of one or more users, and second device information indicating an electrical device to be used by the one or more users in association with each other; extracting a service provider associated with the first device information when the second device information is updated by addition of a new electrical device to be used by one of the one or more users, and when the new electrical device is included in the electrical devices indicated by the first device information.

Abstract: In an embodiment, a computer-implemented method comprises deploying a dual-active database on a first active database site and a second active database site. The first active database site comprises a first group of disks including a first sub-group of disks and a second sub-group of disks respectively corresponding to a third sub-group of disks and a fourth sub-group of disks included in a second group of disks in the second active database site. The method further comprises storing a first set of database logs on the first sub-group of disks while a second set of database logs is being written on the second sub-group of disks. Contents of the second set of database logs are consistent with contents of the first set of database logs and function as a duplication of the first set of database logs.

Abstract: A highly available database system includes a first instance of a database server on a first cluster of a virtual computing system, a second instance of the database server on a second cluster of the virtual computing system, a first instance of an administration database on the first cluster, and a second instance of the administration database on the second cluster. The first instance of the database server and the second instance of the database server form a highly available database server, the first instance of the administration database and the second instance of the administration database form a highly available administration database, and the first instance of the database server, the second instance of the database server, the first instance of the administration database, and the second instance of the administration database are configured to manage at least one customer database.

Abstract: A shared-nothing database system is provided in which parallelism and workload balancing are increased by assigning the rows of each table to “slices”, and storing multiple copies (“duplicas”) of each slice across the persistent storage of multiple nodes of the shared-nothing database system. When the data for a table is distributed among the nodes of a shared-nothing system in this manner, requests to read data from a particular row of the table may be handled by any node that stores a duplica of the slice to which the row is assigned. For each slice, a single duplica of the slice is designated as the “primary duplica”. All DML operations (e.g. inserts, deletes, updates, etc.) that target a particular row of the table are performed by the node that has the primary duplica of the slice to which the particular row is assigned. The changes made by the DML operations are then propagated from the primary duplica to the other duplicas (“secondary duplicas”) of the same slice.

Abstract: Embodiments of the present disclosure may provide a data clean room architecture that restricts data included in the clean room. The data clean room architecture can implement a policy to enable data restrictions for data shared between multiple parties via a distributed database. Multiple database accounts can implement validation instances to validate queries when received from other database accounts. One or more of the database accounts can provide a query template that is congruent with the validation instance for use by the other database accounts to generate queries against the data shared in the data clean room.

Abstract: Examples of systems described herein include a file server virtual machine of a virtualized file server configured to manage storage of a plurality of storage items. The file server virtual machine including a file system configured to receive an access request directed to a storage item of the plurality of storage items and associated with a user. The file system is further configured to retrieve an access control list having permissions information associated with the storage item, and to cache a permissions profile for the user including all permissions pertaining to the user for the storage item. The file system is further configured to determine whether the access request is permissible based on the cached permissions profile.

Abstract: A point-in-time clone may be created for a database. A request to create the point-in-time clone may be received. The clone may be provided with access to a storage for the database that stores a history of modifications to the database applicable to return data of the database according to a state of the data at the specified point in time. The clone may then be updated so that the updates made to the clone are stored for subsequent access by the clone.

Abstract: A data processing server may receive a set of data objects for frequent pattern (FP) analysis. The set of data objects may be analyzed using an attribute diversity technique. For the set of data attributes of the set of data objects, the server may arrange the attributes in one or more dimensions. The server may initialize a set of centroids on data points and identify mean values of nearby data points. Based on an iteration of the mean value calculation, the server may identify a set of attributes corresponding to final mean values as being groups of similarly frequent attributes. These groups of similarly frequent attributes may be analyzed using an FP analysis procedure to identify frequent patterns of data attributes.

Abstract: A shared-nothing database system is provided in which parallelism and workload balancing are increased by assigning the rows of each table to “slices”, and storing multiple copies (“duplicas”) of each slice across the persistent storage of multiple nodes of the shared-nothing database system. When the data for a table is distributed among the nodes of a shared-nothing system in this manner, requests to read data from a particular row of the table may be handled by any node that stores a duplica of the slice to which the row is assigned. For each slice, a single duplica of the slice is designated as the “primary duplica”. All DML operations (e.g. inserts, deletes, updates, etc.) that target a particular row of the table are performed by the node that has the primary duplica of the slice to which the particular row is assigned. The changes made by the DML operations are then propagated from the primary duplica to the other duplicas (“secondary duplicas”) of the same slice.

Abstract: There is provided a system for dynamically updating data in dataset, comprising: at least one processor executing a code for: receiving, an indication of a trigger for a change of a first cell of a first dataset, accessing a relational graph to identify at least one second cell of at least one second dataset dependent on the triggered change to the first cell, evaluating a set of rules to determine an update to perform for each second cell in response to the triggered change of the first cell, and updating each second cell by differentially applying the update to a previous value of the second cell.

Abstract: Implementations provide a method to consolidate data records of regimens for treating oncology conditions. The method includes: accessing data records each encoding multi-tier data characteristics of a regimen for treating a particular oncology condition; receiving a first data record encoding a first regimen specific to a first healthcare provider institution; parsing the first data record according to a hierarchy of the encoded multi-tier data characteristics; distributing a respective weight to each of the encoded data characteristics to account for the potentially missing data characteristic; comparing data characteristics of the first data record with data characteristics from the data records by applying the respective weight to each data characteristic at a particular tier of the hierarchy such that a respective compound score is generated for each data record; and based on the compound scores for all data records, determining a prevailing data record of regimen as matching the first data record.

Abstract: Certain embodiments of the present disclosure provide techniques for detecting anomalous activity in a computing system. The method generally includes receiving a request to perform an action in a computing system. The request is added to a historical time-series data set. A portion of the historical time-series data set is selected for use in determining whether the received request is an anomalous request, and a set of previously identified outliers are removed from the selected portion of the historical time-series data set. An anomaly score is calculated based on a statistical analysis of the received request and the selected portion of the historical time-series data set, wherein the anomaly score comprises a predicted number of operations executed to isolate the received request from the selected portion of the historical time-series data set. One or more actions are taken to process the received request based on the calculated anomaly score.

Abstract: A big data analysis system may include a big data repository communicatively coupled to a data accumulation server and a predictive graph processing system. The data accumulation server may be configured to receive information from a plurality of data sources, the information corresponding to user interaction with one or more computing devices associated with an organization via a networked computing system, store the information received from the plurality of sources in the big data repository; and monitor the plurality of data sources to update the data stored in the big data repository. The predictive graph processing system is configured to receive information stored in the big data repository, transform the information received from the big data repository into a predictive graph data set based on a predictive model, and store the predictive graph data set to a visualization data repository.

Abstract: A shared-nothing database system is provided in which parallelism and workload balancing are increased by assigning the rows of each table to “slices”, and storing multiple copies (“duplicas”) of each slice across the persistent storage of multiple nodes of the shared-nothing database system. When the data for a table is distributed among the nodes of a shared-nothing system in this manner, requests to read data from a particular row of the table may be handled by any node that stores a duplica of the slice to which the row is assigned. For each slice, a single duplica of the slice is designated as the “primary duplica”. All DML operations (e.g. inserts, deletes, updates, etc.) that target a particular row of the table are performed by the node that has the primary duplica of the slice to which the particular row is assigned. The changes made by the DML operations are then propagated from the primary duplica to the other duplicas (“secondary duplicas”) of the same slice.

Abstract: Systems and methods are provided for synchronizing messages. The systems and methods include operations for: identifying a difference between a current state of a messaging application and a shared synchronization database, wherein the shared synchronization database is updated via a third-party application in response to the third-party application receiving, from a server, a notification related to the messaging application, the messaging application and the third-party application being implemented on a client device; retrieving information from the shared synchronization database to update the current state of the messaging application based on the identified difference; and transmitting, to the server by the messaging application, a request for content based on the update to the current state of the messaging application.

Abstract: The disclosed technology relates to a system configured to identify a first operation in a first set of operations configured to converge a server state and a file system state, wherein the first operation is not in a second set of operations generated in response to an change to at least one of the server state and the file system state. The system is further configured to cancel the first operation, identify a second operation in both the first set of operations and the second set of operations, and initiate execution of the second operation concurrently with the canceling of the first operation.

Abstract: A memory stores therein, with respect to a database containing records each having a first data item and a second data item, an index that includes, in association with each candidate value that is used as the first data item, record specification information specifying two or more records with the candidate value and a statistical value obtained from values of the second data item registered in the two or more records. A processor receives a query including a search condition specifying a requested value of the first data item and a command requesting statistical processing of values of the second data item registered in records satisfying the search condition, retrieves the statistical value associated with a candidate value satisfying the search condition from the index, and outputs a processing result based on the retrieved statistical value for the query.