A method includes obtaining feature generation code from, which is configured to determine features relating to input data. The method further includes obtaining data grouping code, which is configured to generate training data by determining a plurality of data groupings for the features relating to the input data. The method further includes obtaining modeling code, which is derived at least in part by applying one or more machine learning algorithms to the training data. The method further includes applying a model wrapper code to the feature generation code, the data grouping code, and the modeling code to generate a model wrapper and deploying the model wrapper such that the model wrapper may receive a first application programming interface (API) call including an input data value, determine a score relating to the input data value, and send a second API call including the score in response to the first API call.

Disclosed herein are methods, systems, and processes to distribute and disperse search loads to optimize security event processing in cybersecurity computing environments. A search request that includes a domain specific language (DSL) query directed to a centralized search cluster by an event processing application is intercepted. The event processing application is inhibited from issuing the search request to the centralized search cluster if a structured or semi-structured document matches the DSL query.

A method includes identifying an independent data object of a plurality of independent data objects for retrieval from dispersed storage network (DSN) memory. The method further includes determining a mapping of the plurality of independent data objects into a data matrix, wherein the mapping is in accordance with the dispersed storage error encoding function. The method further includes identifying, based on the mapping, an encoded data slice of the set of encoded data slices corresponding to the independent data object. The method further includes sending a retrieval request to a storage unit of the DSN memory regarding the encoded data slice. When the encoded data slice is received, the method further includes decoding the encoding data slice in accordance with the dispersed storage error encoding function and the mapping to reproduce the independent data object.

In an embodiment of the present invention, a checkpoint is received, the checkpoint indicating at least one source position of unprocessed object(s) of a plurality of objects on at least one source shard in a database system. In response to detecting a shard change related to the checkpoint to the at least one source shard, the shard change resulting in that the at least one source shard is updated to at least one destination shard, a mapping view is generated for representing position change of the unprocessed object(s) related to the shard change. An updated checkpoint is determined for indicating the at least one destination position of the unprocessed object(s) of the plurality of objects on at least one destination shard in the database system based on the mapping view. With these embodiments, the checkpoint may be managed in a more effective way.

A computer-implemented system or process is programmed or configured to use a configuration file to specify one or more tasks to apply to raw ingested data. A task may be a sequence of instructions programmed or configured to format raw ingested data into a dataset in a CSV format. Examples of tasks may include: a parser to parse Cobol data into a CSV, a parser to parse XML into a CSV, a parser to parse text using fixed-width fields to a CSV, a parser to parse files in a zip archive into a CSV, a regular expression search/replace function, or formatting logic to remove lines or blank lines from raw ingested data. In one embodiment, the configuration file may specify a schema definition for a task to use for generating a dataset. In one embodiment, the configuration file may also include one or more access control list (ACL) definitions for the generated dataset. In one embodiment, the building of datasets using the configuration file is automated, for example, on a nightly basis.

Systems and methods for facilitating self-service device integration for a NAC server is provided. According to one embodiment, a database is maintained by a NAC server. The database includes mappings of system object identifiers to corresponding implementation details of associated devices. A system object identifier of a device that is to be modeled within the NAC server based on implementation details of another device is received. A list of candidate devices is retrieved from the database based on the system object identifier. A user of the NAC server is prompted to select a candidate device from the list. Responsive to receipt of the selected candidate device, implementation details of the selected candidate device are mapped against the system object identifier and access to the network device is facilitated based on the implementation details of the selected candidate device by storing the mapping as an entry in the device database.

Various embodiments provide for associating a collection of media items with a graphical element. For instance, a system can: generate corpus data from a set of features of a collection of media content items; determine a set of candidate graphical elements for the collection of media content items based on the corpus data and further based on a set of first mappings associating at least one graphical element and at least one n-gram; determine a set of prediction scores corresponding to the set of candidate graphical elements based on the set of features; determine a ranking for the set of candidate graphical elements based on the set of prediction stores; select a set of predicted graphical elements, from the set of candidate graphical elements, based on the ranking; and provide the set of predicted graphical elements in association with the collection of media content items.

A computer-implemented system or process is programmed or configured to use a configuration file to specify one or more tasks to apply to raw ingested data. A task may be a sequence of instructions programmed or configured to format raw ingested data into a dataset in a CSV format. Examples of tasks may include: a parser to parse Cobol data into a CSV, a parser to parse XML into a CSV, a parser to parse text using fixed-width fields to a CSV, a parser to parse files in a zip archive into a CSV, a regular expression search/replace function, or formatting logic to remove lines or blank lines from raw ingested data. In one embodiment, the configuration file may specify a schema definition for a task to use for generating a dataset. In one embodiment, the configuration file may also include one or more access control list (ACL) definitions for the generated dataset. In one embodiment, the building of datasets using the configuration file is automated, for example, on a nightly basis.

Systems and methods for very fast grouping of “similar” SQL queries according to user-supplied similarity criteria. The user-supplied similarity criteria include a threshold quantifying the degree of similarity between SQL queries and common artifacts included in the queries. A similarity-characterizing data structure allows for the very fast grouping of “similar” SQL queries. Because the computation is distributed among multiple compute nodes, a small cluster of compute nodes takes a short time to compute the similarity-characterizing data on a workload of tens of millions of queries. The user can supply the similarity criteria through a UI or a command line tool. Furthermore, the user can adjust the degree of similarity by supplying new similarity criteria. Accordingly, the system can display in real time or near real time, updated SQL groupings corresponding to the newly supplied similarity criteria using the originally computed similarity-characterizing data structure.

A computer-implemented system or process is programmed or configured to use a configuration file to specify one or more tasks to apply to raw ingested data. A task may be a sequence of instructions programmed or configured to format raw ingested data into a dataset in a CSV format. Examples of tasks may include: a parser to parse Cobol data into a CSV, a parser to parse XML into a CSV, a parser to parse text using fixed-width fields to a CSV, a parser to parse files in a zip archive into a CSV, a regular expression search/replace function, or formatting logic to remove lines or blank lines from raw ingested data. In one embodiment, the configuration file may specify a schema definition for a task to use for generating a dataset. In one embodiment, the configuration file may also include one or more access control list (ACL) definitions for the generated dataset. In one embodiment, the building of datasets using the configuration file is automated, for example, on a nightly basis.