Abstract: A system, method and data structure for processing basic client application data types to add thereto extension types and priority levels adapted for use by each of a plurality of set top box classes.

Abstract: Identifying table joins includes obtaining respective casting similarities between pairs of columns of a first table and a second table. Each pair of columns includes a first column of the first table and a second column of the second table. Ones of the pairs of columns not satisfying a casting similarity condition are discarded to obtain first join candidates. Respective string similarities for the first join candidates are obtained. Ones of the first join candidates not satisfying a string similarity condition are discarded to obtain second join candidates. Final join candidates are obtained using the respective casting similarities and the respective string similarities of the second join candidates. A selected join candidate of the final join candidates is received from a user.

Abstract: A method for consolidating backup status data associated with backup operations performed at a specialty backup service platform into a centralized backup service platform may be provided. The method may include receiving data feeds associated with each backup operation, each data feed comprising backup status data associated with a backup operation performed at the specialty backup service platform. The method may also include extracting the backup status data from each data feed and following the extracting, conforming the backup status data at the centralized backup service platform to be consistent with the standardized format. The method may also include for each data feed received from the specialty backup service platform, running a performance-scan on the backup status data within the data feed for determining whether the backup operation was a success or a failure.

Abstract: Embodiments relate to processing a request from a user device for access rights for a resource. An access management system can send a request to query a (e.g., cached or authoritative) data store for available access rights. The query may include an exact-match or fuzzy query. A set of access-right results responsive to the query can be identified. The system may transmit a communication to the user device that identifies the set, or a subset thereof. Upon receiving a selection of a result, the system can facilitate assigning access rights corresponding to the identified result to the user. In some instances, a level of precision at which a characteristic of an access-right result is identified and/or whether or how access rights are held depends on a request load.

Abstract: A first set and a second set are identified as operands for a set operation of a similarity analysis task iteration. Using respective minimum hash information arrays and contributor count arrays of the two sets, a minimum hash information array and contributor count array of a derived set resulting from the set operation is generated. An entry in the contributor count array of the derived set indicates the number of child sets of the derived set that meet a criterion with respect to a corresponding entry in the minimum hash information array of the derived set. The generated minimum hash information array and the contributor count array are stored as part of input for a subsequent iteration. After a termination criterion of the task is met, output of the task is stored.

Abstract: A computer system hosting a column-store database engine is responsive to database requests for the update and retrieval of data from within a stable data table and providing for the storage of database tuples within a column-store organized database structure. A positional delta tree data structure is implemented in the memory space of the database engine and is operatively coupled in an update data transfer path between a database engine interface and the stable data table. The positional delta tree data structure includes a differential data storage layer operative to store differential update data values in positionally defined relative reference to database tuples stored by the stable data table.

Abstract: Computer-readable media, methods, and systems are disclosed for database table partition pruning based on statistical information associated with non-partition columns. A tree partition specification is received defining partitions for a plurality of computed column statistics. Respective partitions are created for the plurality of computed column statistics based on the tree partition specification. A request is received to compute statistics for a plurality of columns of the plurality of computed column statistics to result in a plurality of computed column statistics. In response to determining that one or more modifications have been made to the partitioned database, the plurality of computed column statistics is marked as invalid. The computed column statistics are refreshed in response to modifications of the partitioned table. Thereafter, the statistics are marked as valid. Unnecessary table partitions are pruned based on the statistics, and the associated query is executed.

Abstract: A dynamic code generation process with configurable connections and variables for extraction, transformation, and load (ETL) processing and validation is disclosed. A code generator loads an input requirement document and a configuration file, and generates workflows, database objects, and parameters. Database code is deployed in a database, ETL code is deployed in an ETL repository, and server code is deployed in an ETL server. A code validator reads the ETL code from the ETL repository and the database code from the database, and performs in-built stage unit testing. The code validator performs a quality check, metadata validation, definition comparisons, and outputs validation results.

Abstract: Technologies described herein can be used for the bulk lazy loading of structured data from a database. A request can be received to initialize an application data structure (such as a structured data object, a hierarchical data structure, an object graph, etc.). The data structure can be analyzed to identify a plurality of child objects of the data structure. Database records associated with the plurality of child objects can then be identified. A loaded child record table can be inspected to determine which of the identified database records are not stored in a cache. A request can be generated, comprising one or more queries to retrieve the uncached subset of database records from the database. Once the uncached subset of records are received from the database, these records can be used, along with the cached subset of the identified database records, to initialize the plurality of child objects of the application data structure.

Abstract: A method includes determining that an amount of available space in a first memory used by a set of relational queries is insufficient for a query, wherein the query comprises a join operation. A first partition of a set of partitions is identified, wherein the first partition possesses a smallest available probe memory size of the set of partitions and a build memory size greater than or equal to a threshold memory size, wherein the threshold memory size is a percentage of a maximum build memory size, and the largest partition of the set of partitions has the maximum build memory size. The first partition is copied from the first memory to a second memory.

Abstract: Techniques to create zone maps automatically and efficiently for database query processing are disclosed. The techniques comprise creating a sample dataset to represent an original dataset, building a query workload modeler to characterize a full workload of queries, constructing a clustering quality evaluator to evaluate query performance on a dataset with a certain clustering on the columns, finding a clustering solution by evaluating different applications of the workload to the sample dataset corresponding to different clusterings, and determining which columns of the clustering solution could benefit from zone maps.

Abstract: A computer-implemented content suggestion engine provides content suggestions to a requesting user based on information about content items that other users may have independently categorized or organized into folders within a content repository. Embodiments of the method comprise a content repository having a plurality of content items, where each content item is associated with one or more user-created folders. Embodiments further comprise receiving, via a network, a suggestion request for suggested content, where the suggestion request identifies a first content item for which suggestions are sought. Other content items in the content repository are then identified as potential suggestions based on the application of a formal relationship between the first content item and the potential suggested content items. One or more of the potential suggested content items may then be provided in response to the suggestion request via the network.

Abstract: Analyzing log data, such as security log data and machine data, is disclosed. A baseline is built for a set of machine data. The baseline is built at least in part by determining a plurality of signature profiles for a plurality of respective time slices. An occurrence of an anomaly associated with the source of the machine data is determined. The occurrence is determined at least in part by determining that received machine data does not conform to the baseline within a threshold.

Abstract: Roughly described, a database accelerator is installed in a network having client systems which makes database queries to a particular IP address and port, and database servers which accept queries received at an IP address and port. The accelerator includes a cache, and is arranged to receive, through a network port, a database query made by a client system and directed to the particular IP address and port, return response data from the cache if available there, and if not, then forward the query through a network port to the database servers. Upon receipt of response data from the servers, the accelerator can retain it in its cache in addition to forwarding it back to the client. By installing the accelerator transparently in the network, no changes are required to either the client or server software in order to add query caching functionality to an existing client/server database arrangement.

Abstract: A URL collecting method includes accessing, by a URL collecting apparatus, a web server of a first URL; receiving, by the URL collecting apparatus, a first web page from the web server; and a URL dynamic collecting step of collecting, by the URL collecting apparatus, one or more URLs invoked while performing some or all of source codes of the first web page.

Abstract: A method and system. Target clusterability is calculated as an average of a respective clusterability of at least one target data item comprised by a target domain. Target-side matchability is calculated as an average of a respective matchability of each target centroid of the target domain to source centroids of a source domain, wherein the source domain comprises at least one source data item. Source-side matchability is calculated as an average of a respective matchability of each source centroid of said source centroids to the target centroids. Source-target pair matchability is calculated as an average of the target-side matchability and the source-side matchability. Cross-domain clusterability between the target domain and the source domain is calculated as a linear combination of the calculated target clusterability and the calculated source-target pair matchability. The cross-domain clusterability is transferred to a device.

Abstract: Systems and methods are disclosed for search query language identification. One method comprises generating a seed dictionary comprising a plurality of labeled dictionary terms and receiving a plurality of unlabeled sample query terms. The plurality of unlabeled sample query terms are compared to the plurality of labeled dictionary terms at a first time, and a first set of labeled sample query terms are generated by labeling at least a subset of the plurality of unlabeled sample query terms based on the first comparison. Remaining unlabeled sample query terms are then compared with the first set of labeled sample query terms at a second time, and a second set of labeled sample query terms are generated by labeling the remaining unlabeled sample query terms based on the second comparison. The first and second sets of labeled sample query terms are provided to a machine learning model configured for query language prediction.

Abstract: An apparatus includes a memory and a hardware processor that receives a query from a device. The query includes first search parameters. The processor also retrieves, from a database and based on the first search parameters, a plurality of previously issued queries and applies a machine learning algorithm on the plurality of previously issued queries to determine second search parameters. The processor further adds the second search parameters to the query to form an enhanced query and communicates the enhanced query to a plurality of response systems. The processor then receives, from the plurality of response systems, a plurality of responses to the enhanced query, constructs, based on the plurality of responses to the enhanced query, an enhanced response to the query, and communicates the enhanced response to the device for selection of a response from the plurality of responses.

Abstract: Mechanisms are provided for training a computer implemented model. The mechanisms perform multiple instances of training of the computer implemented model, where each instance of training of the computer implemented model comprises training the computer implemented model using a different training data set to generate a different instance of a trained computer implemented model. The mechanisms generate computer implemented model results after each instance of training by executing the corresponding instance of the trained computer implemented model. The mechanisms record differences in the instances of training of the computer implemented model in association with corresponding identifiers of the instances of trained computer implemented model and corresponding computer implemented model results.

Abstract: Embodiments disclosed herein generally relate to a method for searching a database. The application receives an input identifying one or more users. The application matches the input to one or more user accounts, each user account corresponding to a user that was identified. The application presents to a requestor public accounts of each identified user account. The application receives a keyword input that filters one or more files in the public accounts. The application receives an input that saves a search comprising the user accounts and the keyword input. The application queries the database using the search. The application presents to the requestor a list of all files found using the search. The application dynamically updates the list to include new files matching a criteria of the search as new files satisfying the search are uploaded to the database.