Abstract: An example method of displaying a data visualization includes displaying a graphical user interface that includes three distinct regions, and receiving user actions to associate two different fields with two different shelves. The method also includes generating, in accordance with the received user actions, data marks to be displayed in a data visualization, each data mark corresponding to a respective retrieved tuple of data from a multidimensional database, where (i) each data mark has an x-position defined according to data for a first field in the respective tuple and (ii) each data mark has a y-position defined according to data for a second field in the respective tuple. The method also includes displaying a data visualization that includes the generated data marks.

Abstract: A system and method are presented that identify new, modified, unchanged, and deleted files in an incremental backup through a file list maintained on the backup destination. The FileList is a flat file in which file information about each file on a source node is stored sequentially into the file. During a subsequent incremental backup, the FileList is read sequentially from the backup destination and is used to generate a search tree. A hash value based on the file path is the key to the search tree, with the file's modified time and size being hashed together to form the value of the tree's key-value pair. Files are examined on the source and compared to the key-value pairs in the search tree. Status information in the search tree is modified to indicate discovered files. Unmodified status information identifies files that have been deleted since the previous backup.

Abstract: A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.

Abstract: A code generator platform may receive source metadata and a target data model. The code generator platform may determine a parameter, of the target data model, that is associated with the attribute. The code generator platform may map, based on the attribute and the source metadata, the data to the parameter of the target data model. The code generator platform may generate, based on mapping the data to the parameter, data transformation code associated with the data and the target data model, wherein the data transformation code, when executed, generates target data that corresponds to the data according to the target data model. The code generator platform may perform an action associated with the data transformation code to permit the data transformation code to be executed in order to update a target database with the target data.

Abstract: An improved data intake and query system that can perform and display ingest-time and search-time field extraction, redaction, copy, and/or categorization is described herein. As described herein, ingest-time field extraction, redaction, copy, and/or categorization may refer to field or field value extraction, redaction, copy, and/or categorization that is performed by a log observer system of the data intake and query system on raw machine data as the raw machine data is ingested or received from a publisher. As described herein, search-time field extraction, redaction, copy, and/or categorization may refer to field or field value extraction, redaction, copy, and/or categorization that is performed by the log observer system and/or other components of the improved data intake and query system on historical raw machine data that has already been ingested and indexed by the improved data intake and query system.

Abstract: The system and method for the development and use of an architecture for a Mission Data File Generator (MDFG) for Electronic Warfare (EW) and other systems, which applies state-of-the art software architecture, workflow design, and Graphical User Interface (GUI) design methods. The resulting MDFG tools are user-friendly to the EW Analyst, and allow development of Mission Data Files (MDFs) more quickly. The method and system are substantially more extensible and maintainable than current MDFG tools.

Abstract: The systems and methods provide for migrating database management system (DBMS) applications to cloud storage by automating a continuous replication of changes made to the DBMS from the DBMS to an associated cloud instance. For example, the systems and methods facilitate the migration of the DBMS via multiple processes performing in parallel—a process to create and provision a new machine instance (e.g., an EC2 instance), a process to clone and transfer parameters of the operating system/software of the DBMS, and a process that backs up and/or captures the application data of the DBMS. In some embodiments, the systems and methods, utilizing parallel processes, and combining outputs of the processes to a synchronization process, efficiently and quickly migrate DBMS applications to cloud storage, among other benefits.

Abstract: A method, article of manufacture, and apparatus for managing data. In some embodiments, this includes determining a usage level of a file, wherein the file is stored in a first storage system, moving the file to a second storage system based on the determined usage level of the file updating location information in a catalog based on the movement of the file, and performing at least a portion of a query on the file after updating location information in the catalog.

Abstract: Described herein are various technologies pertaining to identifying boundaries of a substring in a log file, wherein the substring is to be extracted from the log file and used to construct a table. An indication is received that a user has selected a beginning boundary of the substring, and the ending boundary of the substring is automatically identified.

Abstract: Personalized network searching, in which a search query is received from a user, and a request is received to personalize a search result. Responsive to the search query and the request to personalize the search result, a personalized search result is generated by searching a personalized search object. Responsive to the search query, a general search result is generated by searching the general search object. The personalized search result and the general search result are provided to a client device, an advertisement is selected based at least in part upon the personalized search object, and the advertisement, the personalized search result, and the general search result are displayed.

Abstract: A data analytics system stores a plurality of sequential data blocks in a block cache. Each data block contains one or more data records. Each data record of a data record contains one or more values and a record marker marking the end of the data record. The data analytics system allocates a data block in the block cache to a worker thread. The worker thread parses the data block to identify the one or more data records contained within the data block. The data analytics system determines whether the data block was correctly parsed. Responsive to determining that the data block was correctly parsed, the data analytics system provides the one or more data records contained within the data block to a data analytics workflow.

Abstract: The present disclosure relates to a method in a distributed and non-hierarchical node comprising a set of data items for determining a synchronization state between said node and one or more distributed and non-hierarchical nodes communicatively coupled to form a cluster, wherein the set of data items are locally replicated at each node. The method comprises generating a snapshot comprising information relating to the set of data items at a snapshot time Ts, said information identifying changes to the data items where each change comprises a time stamp, where only changes to the data items with a time stamp<T0, where Ts>T0, are included in the snapshot, although changes to the data items up to the time Ts, have been received and stored in the nodes, receiving corresponding generated snapshots from all other nodes in the cluster, and determining a synchronization state based on a comparison between the generated and received snapshots.

Abstract: Methods and systems for distributed transaction processing include assigning portions of a logical unit of work to one or more transaction participants. Resource usage information relating to the portions of the logical unit of work is tracked from the respective one or more transaction participants. A last participant is determined based on the tracked resource usage information using a processor. The logical unit of work is resolved. Resolving the logical unit of work includes sending a prepare flow to each of the transaction participants except the last participant to optimize resolution efficiency.

Abstract: An example operation includes one or more of obtaining, by a moving vehicle, a first data including one or more of at least one first video and at least one first image of a moving transport, analyzing the first data, by the moving vehicle, to determine an initial issue, querying, by the moving vehicle, a server for a second data based on the analyzing, wherein the second data is one or more of at least one second video and at least one second image of the moving transport at a previous time, verifying, by the moving vehicle, an issue exists based on a delta above a threshold between the first data and the second data, and sending, by the moving vehicle, the verified issue to the server.

Abstract: A method for indexing objects in a computerized system having an index, comprising identifying in the computerized system an at least one indexed object that meets an at least one criterion related to contents of the at least one indexed object, detecting an at least one non-indexed object having a property similar to an at least one property of the at least one indexed object that was identified, and indexing the at least one non-indexed object in the index, wherein the method is performed by the computerized system, and an apparatus for performing the same.

Abstract: Systems and methods are disclosed for generating a distributed execution model with untrusted commands. The system can receive a query, and process the query to identify the untrusted commands. The system can use data associated with the untrusted command to identify one or more files associated with the untrusted command. Based on the files, the system can generate a data structure and include one or more identifiers associated with the data structure in the distributed execution model. The system can distribute the distributed execution model to one or more nodes in a distributed computing environment for execution.

Abstract: Queries are monitored in a database which receives input from a stream computing application to identify data of interest. Parameters defining the data of interest, which are preferably expressed as a logical query, are sent to the stream computing application, which then processes the in-flight streamed data satisfying the parameters in some special manner. In some embodiments, the stream computing application increases the processing priority of in-flight data satisfying the parameters. In some embodiments, the stream computing application applies additional processing steps to the in-flight data satisfying the parameters to provide enhanced data or metadata.

Abstract: A central service provider manages a blockchain network that writes the cryptographic hash of each executed transaction in a block to the blockchain network. For each executed transaction, the central service provider generates and transmits a transaction receipt such that a party can verify that the transaction was appropriately executed. Additionally, a party can check that the party's records are correct by providing transaction data describing details of transactions recorded in the party's records to the central service provider. The central service provider verifies the party's records by comparing the transaction data in the party's records to the blocks of transaction records in the blockchain network. In some scenarios, the central service provider may identify or receive an identification of a discrepancy arising from one or more transactions. The central service provider can reconcile the identified discrepancy.

Abstract: The overall architecture and details of a scalable video fingerprinting and identification system that is robust with respect to many classes of video distortions is described. In this system, a fingerprint for a piece of multimedia content is composed of a number of compact signatures, along with traversal hash signatures and associated metadata. Numerical descriptors are generated for features found in a multimedia clip, signatures are generated from these descriptors, and a reference signature database is constructed from these signatures. Query signatures are also generated for a query multimedia clip. These query signatures are searched against the reference database using a fast similarity search procedure, to produce a candidate list of matching signatures. This candidate list is further analyzed to find the most likely reference matches. Signature correlation is performed between the likely reference matches and the query clip to improve detection accuracy.

Abstract: An approach is provided for providing record-level sensitivity-based data storage in a networked computing environment. For each data record of a plurality of data records (e.g., rows) in a dataset, the record sensitivity is identified based on the data included in the data record, allowing different sensitivities to be identified for different records in the same dataset. A data center that has a data center sensitivity level that matches the record sensitivity is selected for the identified record sensitivity. Each data record is stored to a selected data center, with data records having different record sensitivities being stored in different data centers of different types, locations, etc.