Abstract: A method includes executing a program that specifies operations and accessing a translation file that includes instructions for translating the language of the program into a language of a database. The translation file specifies operations in the language of the program that are supported by the database and the semantic meaning of the supported operations in the language of the database. Operations of the program that are unsupported by the database are processed by the program. Operations of the program that are supported by the database are determined from the translation file, and a portion of the program representing the supported operations is translated, using the translation file, into the language of the database and transmitted to the database. Data resulting from execution, within the database, of the translated portion of the program representing the operations that are supported by the database is received by the program.

Abstract: Aspects of the present disclosure relate to providing, based on a partial query string, a plurality of autosuggestions that are diverse in nature such that the user is more likely to see the preferred complete query terms and therefore more likely to select one of the preferred suggestions which will increase search efficiency. As described herein, such functionality relates to generating cluster groups of candidate suggestions, each cluster including sub-topics, then performing the search based on a selected cluster or sub-topic. To generate the cluster groups, systems and methods, as described herein, analyze the similarity between candidate suggestions as well as the popularity of generated sub-topics. The cluster groups and sub-topics may be displayed visually, and in certain embodiments the cluster groups are ordered vertically from top to bottom and aligned to the left side of the display, while sub-topics are ordered horizontally from left to right following the cluster label.

Abstract: Described herein are, among other things, techniques, devices, and systems for generating one or more trained machine-learning models used for generating content-item recommendations. Also described herein are techniques, devices, and systems for applying a consumption history of a particular user to the trained model(s) to generate score data indicating a correlation between each content-item title and the consumption history, as well as modifying this score data using one or more biasing factors for generating result data. In addition, the techniques, devices, and systems may use this result data, along with received user input, for determining an order in which to present one or more content items to the user. For example, this may include determining which content items to recommend to a user and in which order to do so.

Abstract: Despite the increase of memory capacity and CPU computing power, memory performance remains the bottleneck of in-memory database management systems due to ever-increasing data volumes and application demands. Because the scale of data workloads has out-paced traditional CPU caches and memory bandwidth, one can improve data movement from memory to computing units to improve performance in in-memory database scenarios. A near-memory database accelerator framework offloads data-intensive database operations via or to a near-memory computation engine. The database accelerator's system architecture can include a database accelerator software module/driver and a memory module with a database accelerator engine. An application programming interface (API) can be provided to support database accelerator functionality. Memory of the database accelerator can be directly accessible by the CPU.

Abstract: Described herein are, among other things, techniques, devices, and systems for generating one or more trained machine-learning models. Also described herein are techniques, devices, and systems for applying a consumption history of a particular user to the trained model(s) to generate score data indicating a correlation between each content-item title and the consumption history. The techniques then determine a ranked list of content items having a highest correlation to the consumption history, which may be used to retrieve videos associated with the most-correlated content items for generating a compilation video composed of these retrieved videos.

Abstract: A database system and a computer implemented method for managing functions in the database system is provided. The method, implemented using instructions that may be stored in the database system, involves obtaining first data representing a set of one or more operations to be performed on data in the database system. Second data, representing a function definition, is derived from the first data and the function definition includes the set of one or more operations and a set of state variables. A function is generated according to the second data. Generating the function includes storing a set of one or more values for respective ones of the state variables. The set of values are stored in an isolated computing environment in the database system and the function is configured to operate on the values in the isolated computing environment.

Abstract: A method for rapid data analysis includes receiving and interpreting a first query operating on a first dataset partitioned into shards by a first field; collecting a first data sample from a first set of data shards; calculating a first result to the first query based on analysis of the first data sample; and partitioning a second dataset into shards by a second field based on the first result.

Abstract: A method for stratified-sampling-based query execution includes: receiving a query; collecting a first data sample from the first dataset using a non-stratified sampling technique; performing statistical analysis on the first data sample; identifying a stratum classifier from the statistical analysis; generating a stratum classification by calculating strata boundaries for the stratum classifier; and calculating a result to the query based on analysis of the second data sample.

Abstract: A method comprises: storing, by a computing system, a relational data in a data lake; spinning-up, by an orchestration system of the computing system, an ephemeral computing node on a computing device of the computing system; importing, by the ephemeral computing node, a copy of the relational data from the data lake into a relational database management system (RDBMS) installed on the ephemeral computing node; after importing the copy of the relational data into the RDBMS, performing, by the ephemeral computing node, a computing process that runs within the RDBMS and that uses the copy of the relational data; and after completion of the computing process on the ephemeral computing node, spinning-down, by the orchestration system, the ephemeral computing node.

Abstract: A control device determines, every control cycle, whether or not process values stored in a time-series manner satisfy a predetermined event condition. When the event condition is satisfied, the control device causes a chapter associated with the satisfied event condition to be stored in correspondence with time information that specifies the control cycle. The control device determines a target section with the time information in correspondence with a chapter that satisfies an extraction condition being defined as the reference, and extracts time-series data of the stored process values included in the determined target section.

Abstract: Systems, computer program products, and methods are described herein for evaluating, validating, correcting, and loading data feeds based on artificial intelligence input. The present invention may be configured to receive a data feed from a source for loading to a target data structure, analyze, based on historical feed data, metadata of the data feed to determine a likelihood of the data feed failing to load, and determine whether the likelihood of the data feed failing to load satisfies a threshold. The present invention may be configured to load the data feed to the target data structure, determine, after loading the data feed to the target data structure, whether the data feed failed to load, and either correct errors in the data feed or add error-containing portions of the data feed to a failed data log.

Abstract: Provided are systems, methods, and computer-program products for a contextual connection system. In various implementations, the system can receive data corresponding to an interaction between a first node and a second node. The system can use an interaction history to associate the first node with a subset of other nodes. The system can receive input corresponding to a search, where the search is associated with the third node. The search requests a list of nodes, where nodes in the list of nodes are likely to accept a connection request from the third node. The system can determine similarity between the third node and the second node. Determining the similarity can further include using the similarity and a result of searching to identify the context associated with the first node. The system can add the first node to the list of nodes, and respond to the search with the list of nodes.

Abstract: Techniques and systems can receive a query identifying a name linked to performance data of a computer system and a location of the performance data. The name linked to the performance data of the computer system and the location of the performance data can be communicated to a first computer-implemented system. The first computer-implemented system can include identifying data derived from the name and the location of the performance data. Identifying data derived from the name and the location of the performance data can be received from the first computer-implemented system. The identifying data derived from the name and the location of the performance data can be used to retrieve the performance data. The performance data can be hosted by a second computer-implemented system that is different than the first computer-implemented system.

Abstract: According to one general aspect, a system may include a plurality of data nodes. Each data node may include either or both of a first storage medium and a second storage medium that is slower than the first storage medium. Each data node may be configured to store a piece data in either the first storage medium or the second storage medium. The system may be configured to store a plurality of copies of an active piece of data within two or more data nodes. A fast copy of the active piece of data may be stored by a first storage medium of a first data node. One or more slow copies of the active piece of data may be stored by respective second storage mediums of one or more respective other data nodes.

Abstract: Provided are a search result presentation method, a readable medium and a terminal device. The search result presentation method includes steps described below. In response to a search instruction for a target entity object, at least one multimedia resource for presenting the use effect of the target entity object is acquired, where the at least one multimedia resource is obtained based on multimedia content corresponding to the target entity object; and the at least one multimedia resource is presented.

Abstract: Methods and systems are provided for migrating data between systems without downtime. User requests may be handled adaptively during migration of data records from a first record system to a second record system, to maintain access to the data during the migration. The handling may include receiving a user request; determining at least one data record associated with the received user request; determining if a copy of the data record in the first record system is still active; and if the copy of the data record in the first record system is still active, forwarding the user request to the first record system. The user request may be forwarded to the second record system if the copy of the data record in the first record system is not active, and a retry mechanism may be used if the user request is not handled by the second record system.

Abstract: Routines are used to connect bot queries entered via a bot interface and database queries executed on a database. Each routine is associated with routine configurations, including (a) query attributes associated with bot queries that trigger the routine, (2) a database query executed or to be executed for the routine, and/or (3) display settings for displaying information returned from the database query in a bot response. Each routine is configured to generate an output structured data object (SDO) indicating information returned from the database query and the display settings applicable to the information. The output SDOs from the various routines are transmitted to the bot application via a single API endpoint. The routine configurations are entered by a design user through one or more design user interfaces rendered by an integrative configuration application module.

Abstract: A classification apparatus includes a memory and a processor. The memory is configured to store rules corresponding to a corpus of rules in respective rule entries, each rule includes a respective set of unmasked bits having corresponding bit values, and at least some of the rules include masked bits. The rules in the corpus conform to respective Rule Patterns (RPs), each RP defining a respective sequence of masked and unmasked bits. The processor is configured to cluster the RPs, using a clustering criterion, into extended Rule Patterns (eRPs) associated with respective hash tables including buckets for storing rule entries. The clustering criterion aims to minimize an overall number of the eRPs while meeting a collision condition that depends on a specified maximal number of rule entries per bucket.

Abstract: Systems, methods, devices and non-transitory, computer-readable storage media are disclosed for a wearable multimedia device and cloud computing platform with an application ecosystem for processing multimedia data captured by the wearable multimedia device. In some implementations, a first event data structure is obtained, the first event data structure including first content and a first label including a first plurality of nested categories. A second event data structure is obtained, the second event data structure including second content, and a second label including a second plurality of nested categories. The second label is different from the first label. A context of a mobile device is determined. At least one of the first content or the second content to present using the mobile device is determined. Using the mobile device, the at least one of the first content or the second content is presented.

Abstract: Described herein are systems and methods for extracting and combining XML files of an XFA document. The systems include processors and memory for efficient processing and data storage. The systems can identify XFA documents and generate XML files by parsing the XFA documents. The systems can identify XML nodes within XML files, with each node corresponding to a particular node type, and generate web forms including web nodes, with each web node mapped to a corresponding XML node. The systems can receive input corresponding to the respective node type and store an association between the input received for the web node and the node type and an identifier of an XML node to which the web node is mapped. The systems can update the XML files using the association and generate the populated XFA document by combining the updated XML files according to the schema of the XFA document.