The claimed system and method describes a root cause analysis system for a radio access network. Some aspects include automatic identification of possible causes for network issues, their ranking, determination of the root (main) cause and execution of related best actions, alerts and reporting in order to automatically identify, mitigate or eliminate the problem.

Methods, information handling systems and computer readable media are disclosed for generation of consistent structured data hash values across platforms and structured data formats. In one embodiment, a method includes identifying, at an information handling system, a set of data segments within a set of structured data and expressing the set of structured data in a standard format. This embodiment of the method further includes, for each of the data segments within the set of data segments, applying a hash algorithm to produce a data segment hash value and obtaining a standardized identifier for the data segment. The method continues with assembling an aggregate hash code comprising the standardized identifier and the data segment hash value for each of the data segments, and confirming an association of the aggregate hash code with the set of structured data.

A computer-generated data entry is received. The computer-generated data entry is segmented into a set of tokens. A plurality of different token permutation groupings are determined. Each of the different token permutation groupings includes a different subset of tokens from the set of tokens of the computer-generated data entry. For the computer-generated data entry, a corresponding token permutation grouping identifier is determined for each grouping of the plurality of different token permutation groupings. It is determined whether the computer-generated data entry belongs to any data entry cluster among a plurality of previously identified data entry clusters based on a search performed using the token permutation grouping identifiers of the computer-generated data entry.

As described herein, a system, method, and computer program are provided for normalizing a JSON structure. In use, input defining at least one entity type of a target data structure is received. A source JSON structure is identified. The source JSON structure is traversed for a particular JSON data type to map values in the source JSON structure to corresponding entities of the target data structure based on the at least one entity type defined for the target data structure, where each entity of the target data structure is defined using a relative path between nodes of the source JSON structure.

A method of rendering a service graph illustrating dependencies between a frontend and a backend of an application comprises generating a plurality of frontend traces from a plurality of frontend spans and generating a plurality of backend traces from a plurality of backend spans ingested from the application. The method also comprises aggregating frontend metrics data using the plurality of frontend traces and backend metrics data using the plurality of backend traces. The method further comprises determining connection information between one or more frontend traces of the plurality of frontend traces and corresponding backend traces of the plurality of backend traces. The method also comprises rendering the service graph using the connection information and the aggregated frontend and backend metrics data.

An attribute information setting section loads information indicating whether or not access to each of a plurality of files is allowed, into a memory. A readout request receiving section receives a readout request including a file path from a program. A hash value deriving section derives a hash value of a file path included in the readout request. A file confirming section confirms whether or not the derived hash value matches with one of hash values of the files included in software. A determining section refers to the information loaded into the memory by the attribute information setting section in a case in which matching of the hash values is confirmed, to thereby determine whether or not a process on the file which has been subjected to the readout request is executable.

Systems and methods for controlling data in a hierarchy receive a data query corresponding to data organized within nodes in a data hierarchy, wherein the data hierarchy is defined by a plurality of dimensions. A data traversal of the data hierarchy is performed including a rollup operation between different nodes at different levels of the plurality of dimensions. The rollup operation aggregates data values of the nodes at the different levels. Aggregated values for different nodes at each level are output based on the rollup operation, and the data query is executed using the aggregated values for the different nodes.

A system and method are presented that analyze evaluation data concerning a subject using attributes that are logically arranged in a geometric structure such as a rectangular array. A plurality of dimension layers is laid on top of the logical arrangement of data. Each dimension layers assigns values to a plurality of dimensions based on the value of neighboring attribute groups. Each dimension layer can be associated with one or more reporting configurations that contain descriptors for the defined dimensions as well as formatting instructions for report-like output.

A system and method for processing of queries including receiving a query including a set operation and a sort operation, wherein the set operation includes a first data structure and a second data structure and the sort operation requests a result set that is sorted based on a column or attribute of the first data structure and a column or attribute of the second data structure; generating a query plan in which a sort operation occurs prior to the set operation; determining a first, partial set of one or more resultant rows responsive to the query; sending the first, partial set of one or more resultant rows responsive to the query to a client; determining a second, partial set of one or more resultant rows responsive to the query; and sending the second, partial set of one or more resultant rows to the client.

A storage structure for data containing relational objects, as well as methods for retrieval and visualized display of data so stored are capable of recording relations among all objects in any scenario, as well as new relational states caused by changes and corresponding events happening in succession. The storage structure uses uniform formats to process information into logical and relational data, thereby contributing to subsequent characteristic analysis, supporting retrieval by objects and designated relational modes, and providing accurate display of information and its variations through versatile, visualized way.