Abstract: In some examples, a cluster comprises peer nodes and a distributed data store implemented across the peer nodes, a method of remote linking of data objects for data transfer between a first node cluster and a second node cluster among the peer nodes, the method comprising: creating a data object group including multiple remote data objects, wherein a plurality of remote data objects in the data object group represent a same first virtual machine and are registrable on at least the first and second node clusters of the peer DMS nodes; creating or identifying remote links to a plurality of the remote data objects in the data object group; designating a member of the data object group as an active member of the group; and assigning a task to the active member to be completed using remote links.

Abstract: A method for multi-stage processing of user queries for enhanced information retrieval. The method includes generating self-complete derived queries from a search query. The method includes extracting query entities from each derived query and mapping the query entities with a plurality of electronic documents to identify a set of relevant electronic documents. The method includes sorting the derived queries based on the number of relevant electronic documents related to each derived query to obtain a sorted sequence of derived queries and searching a result for each derived query sequentially from the set of relevant electronic documents according to the sorted sequence of derived queries, and appending the result retrieved for one derived query with a consequent derived query to obtain a final search result. The method involves breakdown of a search query into derived queries and resolve each derived query separately and sequentially to reduce complexity and computation cost.

Abstract: Methods, systems, and devices for data management are described. A data management system (DMS) may determine to generate a backup instance of an application that includes multiple user accounts. The DMS may identify a time window for generation of the backup instance based on a set of backup parameters associated with the application. The DMS may calculate respective runtime durations for the user accounts based on respective quantities of data objects in the user accounts and respective backup job types associated with the data objects. The DMS may determine respective values of a semaphore parameter based on the respective runtime durations and the time window, where the semaphore parameter defines a threshold quantity of data objects to be processed in parallel. The DMS may generate the backup instance of the application based on processing the user accounts in accordance with the respective values of the semaphore parameter.

Abstract: In some implementations, the techniques described herein relate to a method including: receiving a request from a user to analyze a consumer microservice; retrieving first source code associated with the consumer microservice and second source code associated with a producer microservice; analyzing the first source code to identify issues in the first source code; retrieving log data generated by the consumer microservice; analyzing the first source code, the second source code, and the log data to identify unused fields transmitted by the producer microservice to the consumer microservice; generating a report including the issues and the unused fields; and transmitting the report to the user responsive to the request.

Abstract: Techniques are disclosed relating to index metadata that is usable for accessing multi-level data structures. A computer system may operate a database, including maintaining a set of records having a set of corresponding keys. The computer system may create multi-level data structures that facilitate key range lookups against those records. A given multi-level data structure may store key information indicative of a subset of the corresponding keys. The computer system may create separate index metadata that is usable for accessing the multi-level data structures. The index metadata may specify indications of key information that is stored in the multi-level data structures and locations of the multi-level data structures. The computer system may perform a key range lookup that includes using the index metadata to determine a particular set of the multi-level data structures whose key information corresponds to a key range of the key range lookup.

Abstract: Methods, systems, and devices for data management are described. A system supporting malware detection may obtain event data such as risk scores corresponding to events associated with a set of computing entities. Using the event data, the system may construct a graph that includes nodes that represent the set of computing entities, and edges that represent the events, where the edges are between initiator and affected nodes and are associated with the respective event risk scores. Using the graph, respective node risk scores may be calculated for at least some nodes of the graph, and one or more anomalous nodes may be identified based on the one or more anomalous nodes having respective node risk scores that satisfy a threshold. The system may then output an indication of one or more computing entities corresponding to the one or more anomalous nodes.

Abstract: A data management system (DMS) may use a staggered full snapshot rollout approach to obtain full snapshots of multiple computing objects. The DMS may identify that a quantity of the multiple objects scheduled for full backups by the DMS exceeds a threshold quantity. The DMS may initiate, at a first time, and based on the quantity of objects exceeding the threshold quantity, a first set of full snapshots corresponding to a first subset of objects included in the multiple objects. The DMS may initiate, at a second time subsequent to the first time, a second set of full snapshots corresponding to a second subset of objects included in the multiple objects. The second subset of objects may be different than the first subset of objects. The DMS may continue to obtain full snapshots of respective subsets of the multiple objects until all of the scheduled full snapshots are obtained.

Abstract: Techniques are disclosed relating to index metadata that is usable for accessing multi-level data structures. A computer system may operate a database, including maintaining a set of records having a set of corresponding keys. The computer system may create multi-level data structures that facilitate key range lookups against those records. A given multi-level data structure may store key information indicative of a subset of the corresponding keys. The computer system may create separate index metadata that is usable for accessing the multi-level data structures. The index metadata may specify indications of key information that is stored in the multi-level data structures and locations of the multi-level data structures. The computer system may perform a key range lookup that includes using the index metadata to determine a particular set of the multi-level data structures whose key information corresponds to a key range of the key range lookup.

Abstract: Techniques are disclosed relating to merge operations for multi-level data structures, such as log-structured merge-trees (LSM trees). A computer system may store, in a database, a plurality of files as part of an LSM tree and a plurality of database key structures. A given one of the plurality of database key structures may indicate, for a corresponding one of the plurality of files, a set of key ranges derived from database records that are included in the corresponding file. The computer system may determine, using ones of the plurality of database key structures, a key range overlap that is indicative of an extent of overlap of key ranges from a set of the plurality of files with respect to a particular key range. Based on the determined key range overlap, the computer system may assign a priority level to a merge operation that involves the set of files.

Abstract: A method and system for multi-table question answering is provided herein. The method includes receiving a complex question from a user. The method may further include decomposing the complex question into one or more sub-questions using one or more of but not limited to coreference resolution, dependency parsing, chunking and prompt techniques. The method may further include generating code scripts for each sub-question using a Large Language Model (LLM). The method may further include executing the code scripts to retrieve relevant structured data from a plurality of tables. The method may further include generating an answer to the complex question based on the retrieved structured data.

Abstract: Methods, systems, and devices for data management are described. A data management system (DMS) may determine to generate a backup instance of an application that includes multiple user accounts. The DMS may identify a time window for generation of the backup instance based on a set of backup parameters associated with the application. The DMS may calculate respective runtime durations for the user accounts based on respective quantities of data objects in the user accounts and respective backup job types associated with the data objects. The DMS may determine respective values of a semaphore parameter based on the respective runtime durations and the time window, where the semaphore parameter defines a threshold quantity of data objects to be processed in parallel. The DMS may generate the backup instance of the application based on processing the user accounts in accordance with the respective values of the semaphore parameter.

Abstract: Techniques are disclosed relating to compressing database keys. A computer system may receive a request to write a database record to a storage medium. The database record may include a database key and a corresponding data value. The computer system may compress the database key by replacing a portion of the database key with particular data that identifies a location of a reference database key and an amount of similarity determined between the database key and the reference database key. The computer system may write the database record to the storage medium. The database record may include the compressed database key and the corresponding data value.

Abstract: In some examples, a cluster comprises peer nodes and a distributed data store implemented across the peer nodes, a method of remote linking of data objects for data transfer between a first node cluster and a second node cluster among the peer nodes, the method comprising: creating a data object group including multiple remote data objects, wherein a plurality of remote data objects in the data object group represent a same first virtual machine and are registrable on at least the first and second node clusters of the peer DMS nodes; creating or identifying remote links to a plurality of the remote data objects in the data object group; designating a member of the data object group as an active member of the group; and assigning a task to the active member to be completed using remote links.

Abstract: Techniques are disclosed relating to probabilistic data structures. A database node may maintaining a probabilistic data structure capable of encoding database keys. The probabilistic data structure may include a plurality of levels that are each capable of storing an indication of a transition between successive characters in a database key. The database node may insert a particular database key into the probabilistic data structure and the particular database key may comprise a series of characters. The inserting may include setting, for each transition between successive characters of the series of characters, an indication in a corresponding level of the plurality of levels that is indicative of that transition. The database node may further maintain lineage information specifying one or more lineages that correspond to the transition.

Abstract: In some examples, a duster comprises peer nodes and a distributed data store implemented across the peer nodes, a method of remote linking of data objects for data transfer between a first node cluster and a second node cluster among the peer nodes; the method comprising: creating a data object group including multiple remote data objects, wherein a plurality of remote data objects in the data object group represent a same first virtual machine and are registrable on at least the first and second node clusters of the peer DMS nodes; creating or identifying remote links to a plurality of the remote data objects in the data object group; designating a member of the data object group as an active member of the group; and assigning a task to the active member to be completed using remote links.

Abstract: Techniques are disclosed relating to building an in-memory multi-level data structure useable to determine presence or absence of key ranges in files consisting of database records. In various embodiments, a computer system operates a database, including maintaining a set of records having a set of corresponding keys that are accessible in key-sorted order and generates a multi-level data structure that facilitates key range lookups against the set of records. The generating may include accessing ones of the set of keys in key-sorted order and determining, for a particular accessed key that includes a set of characters, an intermediate level within the multi-level data structure and a subset of the characters of the particular accessed key for insertion. The computer system may insert, starting at the intermediate level, information that identifies the subset of characters, with the inserting being performed without traversing any levels before the intermediate level.

Abstract: A method and a system for identifying suitable participants for a proposed transaction is provided. The method includes receiving transaction-specific information that relates to a proposed transaction; determining a search term based on the transaction-specific information; retrieving, from a memory, participant-specific information that relates to at least one prospective participant with respect to the proposed transaction; applying, to the participant-specific information, a search algorithm that uses the determined search term; and using a result of the applying of the search algorithm to determine whether to offer an opportunity to participate in the proposed transaction to each of the at least one prospective participant. The search algorithm is initially applied to a first list of prospective participants, and when a number of prospective participants to which an opportunity is offered is less than a threshold number, then the search algorithm is applied to a broader list of prospective participants.

Abstract: Techniques are disclosed relating to merge operations for multi-level data structures, such as log-structured merge-trees (LSM trees). A computer system may store, in a database, a plurality of files as part of an LSM tree and a plurality of database key structures. A given one of the plurality of database key structures may indicate, for a corresponding one of the plurality of files, a set of key ranges derived from database records that are included in the corresponding file. The computer system may determine, using ones of the plurality of database key structures, a key range overlap that is indicative of an extent of overlap of key ranges from a set of the plurality of files with respect to a particular key range. Based on the determined key range overlap, the computer system may assign a priority level to a merge operation that involves the set of files.

Abstract: Techniques are disclosed relating to merge operations for multi-level data structures, such as log-structured merge-trees (LSM trees). A computer system may store, in a database, a plurality of files as part of an LSM tree and a plurality of database key structures. A given one of the plurality of database key structures may indicate, for a corresponding one of the plurality of files, a set of key ranges derived from database records that are included in the corresponding file. The computer system may determine, using ones of the plurality of database key structures, a key range overlap that is indicative of an extent of overlap of key ranges from a set of the plurality of files with respect to a particular key range. Based on the determined key range overlap, the computer system may assign a priority level to a merge operation that involves the set of files.

Abstract: Techniques are disclosed relating to index metadata that is usable for accessing multi-level data structures. A computer system may operate a database, including maintaining a set of records having a set of corresponding keys. The computer system may create multi-level data structures that facilitate key range lookups against those records. A given multi-level data structure may store key information indicative of a subset of the corresponding keys. The computer system may create separate index metadata that is usable for accessing the multi-level data structures. The index metadata may specify indications of key information that is stored in the multi-level data structures and locations of the multi-level data structures. The computer system may perform a key range lookup that includes using the index metadata to determine a particular set of the multi-level data structures whose key information corresponds to a key range of the key range lookup.