Abstract: An online system uses a task async engine to coordinate task execution, such as for phased content creation, where the system enables content providers to efficiently create and publish sponsored content in multiple phases. Each phase of the content creation is represented by a draft of the content. Multiple drafts of the content are stored in a repository of the online system for optimizing content delivery and publication, such as quick identification of conflicts in a draft based on analysis of draft fragments of the draft. Objects associated with the sponsored content are stored in an object model. The connections amongst the various draft segments of a draft are stored in a hierarchy structure. Each user associated with a draft has a role, where all of the roles can contribute to the draft. The online system efficiently publishes the drafts and presents the sponsored content to its target users.

Abstract: A system that provides recommendations of documents to a user, the system including a server arrangement, and a database arrangement that stores documents, wherein the server arrangement: receives identification details of the user, obtains prior work associated with the user, determines a user classification of the user based on: the identification details of the user, the prior work associated with the user, and an activity data of the user, determines a document classification for the documents based on a metainformation pertaining to the documents, determines a relevance factor for the documents with respect to the user based on the document classification of the documents, the user classification of the user, and activity data relating to the documents of a plurality of users with similar user classification as the user, and provides recommendations of documents to the user based on relevance factors of the documents.

Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer storage medium for data item recommendation, and relate to the field of information processing. According to this method, a request for a data item is received from a terminal device, the request includes an identifier for identifying the data item and an application type; the application type indicates a type of use of the data item; a recommendation criterion type matching the request is determined based on the application type, the recommendation criterion type indicates a type of a criterion based on which the data item is recommended, a plurality of data items associated with the identifier are determined the plurality of data items are located in a plurality of storage devices and based on the recommendation criterion type, a recommended data item is determined from the plurality of data items as a response.

Abstract: Techniques are disclosed for classifying a user search query for a database system. In disclosed techniques, a computing system receives a user search query for the database system and determines, based on the user search query, a database query that is compatible with an interface of the database system to implement the user search query. In some embodiments, the computing system causes a query remediation interface to be presented to a user that entered the user search query. In some embodiments, the interface includes: a classification of the user search query that specifies attributes of the database query, and one or more elements selectable to alter the database query. The computing system receives, from the user via the query remediation interface, input for altering the database query and determines an updated database query based on the input. The computing system may access the database system using the updated database query.

Abstract: A method, system and computer-usable medium for optimizing of search rules modifying search results. A rules service is initiated prior to executing a given search query from a shopper. A search rule evaluation is performed for the given search query and implementing a search rule that causes actions defined by the search rule to be applied to the given search request query. A list of search rules implemented or fired for each given search query is stored. A tracking record is built based on search rule evaluation that includes the list of implemented or fired rules and rule impact tracking (RIT) records.

Abstract: An apparatus includes processing circuitry and a memory storing instructions that, when executed by the processing circuitry, cause the apparatus to identify a plurality of components and a data flow that interconnects the plurality of components. The instructions cause the apparatus to determine a lineage of a record generated by the plurality of components based on the data flow. The lineage indicates the data flow from a first component to a second component of the plurality of components to generate the record. The instructions cause the apparatus to present, to a user, a visual depiction of the lineage of the record. The visual depiction indicates the data flow of a query through at least the first component and the second component of the plurality of the components to generate the record.

Abstract: A method includes receiving a query expression indicating an expression evaluation for performance upon output of a filtering operator. An operator execution flow indicating performance of the filtering operator serially after the expression evaluation is generated, and execution of this operator execution flow is facilitated by generating an exception column indicating an exception value generated for each of a set of rows based on performing the expression evaluation. The filtering operator of the operator execution flow can be applied by identifying a subset of the set of rows that meet filtering parameters of the filtering operator. When the exception value of at least one row in the subset indicates an error condition, execution of the operator execution flow is aborted. When the exception value of every row in the subset indicates no error, the subset of the set of rows is outputted and execution of the operator execution flow continues.

Abstract: Systems and methods are described to associate data from different nodes of a distributed ledger system. The nodes can generate transaction notifications, log data, and/or metrics data. At least some of the data generated by the nodes can be obtained by a data intake and query system via a distributed ledger system monitor. The data from the distributed ledger system can be stored in the data intake and query system and correlated. Based on an association between at least some of the data of the first node and at least some of the data of the second node, the data intake and query system can determine at least a partial history of a transaction in the distributed ledger system, relationships between components of the distributed ledger system, and/or an architecture of the distributed ledger system.

Abstract: The disclosure provides a database operation method and apparatus. The method comprises: sequentially acquiring, during a process of executing a target transaction by an application server, database operation commands executed by the application server for the target transaction; executing a prediction algorithm on the database operation commands, returning predicted execution results to the application server so that the application server determines a next to-be-executed database operation command, and locally recording the database operation commands and predicted execution data generated from the executing of the prediction; and when acquiring a transaction commit command regarding the target transaction, controlling a database corresponding to the application server to actually execute the target transaction according to the locally recorded database operation commands and the predicted execution data. The disclosed embodiments improve transaction execution efficiency and increase transaction throughput.

Abstract: Systems, methods, and devices for feature release and workload capture in database systems are disclosed. The method includes determining a workload based on one or more client queries to be rerun to test a feature that is unreleased to one or more database clients. The method includes repeatedly executing a test run of the workload to determine a stability factor of the test run. The method includes re-executing, in response to determining the stability factor of the test run, the test run using resources with a different concurrency to confirm the stability factor of the test run. The method includes releasing the feature to the one or more database clients in response to confirming the stability factor of the test run.

Abstract: A processing element is implemented in a stage of a pipeline and configured to execute an instruction. A first array of multiplexers is to provide information associated with the instruction to the processing element in response to the instruction being in a first set of instructions. A second array of multiplexers is to provide information associated with the instruction to the first processing element in response to the instruction being in a second set of instructions. A control unit is to gate at least one of power or a clock signal provided to the first array of multiplexers in response to the instruction being in the second set.

Abstract: Detecting fake news involves analyzing a distribution of publishers who publish many news articles, analyzing a distribution of various topics relating to the published news articles, analyzing a social media context relating to the published news articles, and detecting fake news articles among the news articles based on the analysis of the distribution of publishers, the analysis of the distribution of the various topics, and the analysis of the social media context.

Abstract: Techniques convert a first bitmap into a second bitmap. Such techniques involve determining a first plurality of bits in the first bitmap corresponding to a particular bit in the second bitmap; determining whether the first plurality of bits include a dirty bit as a unit of a processor line width; in response to determining that the first plurality of bits include a dirty bit, setting the particular bit as a dirty bit; and in response to determining that the first plurality of bits do not include a dirty bit, setting the particular bit as a non-dirty bit.

Abstract: A computer-implemented method, system and computer program product for visualizing sparse multi-dimensional data. A multi-dimensional dataset (“dataset”) is converted into a three-dimensional architecture and the remaining dimensions, if any, are arranged into one or more planes. The sparse numeric data of the dataset is converted into multiple planes based on partitioning the three-dimensional architecture by the most sparse dimension and aligning the remaining two-dimensions as two-dimensional planes. Colors or shades of colors are assigned to these planes based on the density quantum of the data present in the planes. Furthermore, planes of the dataset are constructed using the assigned colors or shades of color and the defined opacity values of the planes. The constructed planes are mapped to the dataset in the form of a cube(s) and possibly two-dimensional planes, where the darkest color and the least translucent section(s) of the dataset are positioned in the center of the cube(s).

Abstract: The described technology is generally directed towards validating content selection graphs for use in an in-memory content selection graph data store. When a content selection graph data is generated, the graph nodes can correspond to prebuilt response data. The response data for any of the nodes can be verified against rules based on the type of a node, for example, as well as based on client-specific information for types of clients. The overall validation process can validate the content selection graph for subsequent use, can result in errors or warnings being logged (which may or may not render the graph unusable, e.g., depending on severity), or can fail the content selection graph. If validated, the content selection graph can be used to rapidly return response data when content from the graph is requested.

Abstract: The described technology is generally directed towards coordinating the generation, validation and enabling of content selection graphs in an in-memory content selection graph data store. When a set of content selection graphs is requested, a coordinator starts the generation of the relevant graphs. Upon successful generation, the coordinator starts a validation of the generated graphs against rules for the nodes/response data in the graphs. If the generated graphs pass validation, the coordinator enables the graph set for use in an in-memory cache, whereby when a request to return content selection data is received, an active graph that corresponds to the request and the current time is accessed to obtain and return the response data as the requested content selection data.

Abstract: Systems and methods are described herein for generating enhanced search results utilizing third-party website content within a search engine provided by an electronic catalog of a service provider. This content may be collected in advance of query processing and analyzed to identify a category indicating some attribute of the content (e.g., terms mentioned, topics discussed, object depicted in images/videos/3D data of the content, etc.). Items may be matched to the website through analyzing the textual and/or visual representation data of the website to textual and/or visual representation data associated with an item offered within the electronic catalog. A query may be subsequently received and a third-party website may be identified as being relevant to the search query. In response to the query, the third-party website may be included in a search result list along with images and/or text identifying items pertaining to that website.

Abstract: Recommending analytic tasks based on similarity of datasets is disclosed. One example is a system including a data processor, a matching module, and a recommendation module. The data processor receives an incoming dataset via a processing system, and generates a feature vector for the incoming dataset. The matching module determines similarity measures between the generated feature vector and representative feature vectors for a plurality of datasets in a data repository, and selects at least one dataset of the plurality of datasets based on the similarity measures. The recommendation module identifies at least one analytic task associated with the selected dataset, and recommends, to a computing device via the processing system, the at least one analytic task to be performed on the incoming dataset.

Abstract: Embodiments of the present disclosure may provide a dynamic query execution model. This query execution model may provide acceleration by scaling out parallel parts of a query (also referred to as a fragment) to additional computing resources, for example computing resources leased from a pool of computing resources. Execution of the parts of the query may be coordinated by a parent query coordinator, where the query originated, and a fragment query coordinator.

Abstract: In one embodiment, a branch processing method comprising receiving information from at least two branch execution units; writing two updates per clock cycle to respective first and second write queues based on the information; and writing from the first write queue up to two updates per clock cycle into plural tables of a first predictor and a single update for the single clock cycle when there is an expected write collision, the first predictor comprising a single write or read/write port.