Abstract: An application development and deployment system allows an application developer to develop applications for a distributed data intake and query system. The application may include information that associates portions of the application with particular server groups of the distributed data intake and query system. The application may be partitioned to generate target application packages for each of the server groups of the data intake and query system.

Abstract: A system and method for destroying data stored on an immutable distributed ledger utilizes technology from the following fields: encryption, digital signatures, data structures, distributed storage, distributed ledger technology, and smart contracts. Immutable distributed ledgers provide benefits for sensitive data, including availability, integrity, and data processing visibility. The system and method places sensitive data on an immutable distributed ledger and maintains these advantages of immutable distributed ledgers. The system and method also supports the efficient deletion of this sensitive data without compromising the integrity of the ledger.

Abstract: The present technology pertains to a details pane that is displayed in coordination with a file explorer interface. The details pane can display details including activities, comments, and previews for content items displayed in the details pane. In some embodiments, the content items displayed in the file explorer interface can be stored in and accessed from different services, and the details in the details pane can also be populated from diverse sources. In some embodiments, edits or navigations can be performed within a preview of the content item. In some embodiments, comments can be shown along with previews that show the comment located within the content item.

Abstract: Disclosed are systems and methods that automatically classify, filter, and reduce large volumes of feedback data as a function of time using artificial intelligence technology. The aggregated feedback data is reduced by representing the feedback data as sets of descriptors corresponding to one or more time periods that are displayed on a graphical user interface. Feedback data packets are parsed by labeling the feedback data packets with a time period identifier. The feedback data packets are processed utilizing neural network technology to classify the feedback data according to one or more subject identifiers that are each associated with a subject vector. A descriptor analysis is used to process the subject vectors and the feedback data packets to generate descriptor sets comprising one or more descriptors as well as weighting data for each descriptor.

Abstract: A method of providing user access history for a collaborative document includes receiving, by a server, a first request for the collaborative document from a client device of a user of a plurality of users that have permission to access the collaborative document; providing the collaborative document to the client device for presentation to the user in a user interface on the client device; determining whether a collaborator type of the user matches a predefined collaborator type; responsive to determining that the collaborator type of the user matches the predefined collaborator type: creating a first user access history for the collaborative document based on accesses of the collaborative document by one or more of the plurality of users, and providing the first user access history for the collaborative document to the client device for display within a consolidated view of the user interface presenting the collaborative document.

Abstract: In an embodiment, a computer stores source files and source clone files in a source filesystem. The source clone files are shallow copies of the source files, which initially share the same data blocks as the source files. A source file or a source clone file may eventually be modified, where some of the shared blocks are replaced by modified blocks. In a first phase, all data blocks of all source files that are not clones are replicated to a standby filesystem. A second phase compares each clone file on the source filesystem with its base file to detect a set of differed blocks. The second phase copies the differed blocks into the standby filesystem and, in the standby filesystem, applies the differed blocks to a corresponding clone file. Efficiency of keeping the standby filesystem synchronized with the source filesystem is improved by transferring, from the source filesystem to the standby filesystem, only one copy of only data blocks that are modified.

Abstract: An embodiment of the present invention is directed to implementing machine learning to define business logic and lineage. The system analyzes data patterns of SORs as well as consumption attributes to define the business logic. An embodiment of the present invention may achieve over 95% match rate for complex attributes. When provided with thousands of SOR attributes, the innovative system may identify a handful of relevant SOR attributes required as well as the business logic to derive the consumption attribute.

Abstract: A computer-implemented method may comprise receiving proposals to mutate a data stored in a distributed and replicated file system coupled to a network, the distributed and replicated data system comprising a plurality of nodes, each comprising a server. A metadata service maintains and updates a replica of a namespace of the distributed and replicated file system and coordinates updates to the data by generating an ordered set of agreements corresponding to the received proposals, the ordered set of agreements specifying an order in which the nodes are to mutate data stored in data nodes and cause corresponding changes to the state of the namespace. For each agreement in the generated ordered set of agreements, a corresponding writers list may be provided that comprises an ordered list of nodes to execute the agreement and make corresponding changes to the namespace.

Abstract: Methods for page split detection and affinity in query processing pushdowns are performed by systems and devices. Page servers perform pushdown operations based on specific, and specifically formatted or generated, information, instructions, and data provided thereto from a compute node. Page servers also determine that page splits have occurred during reading of data pages maintained by page servers during pushdown operations, and also during fulfillment of compute node data requests. To detect a data page has split, page servers utilize information from a compute node of an expected next data page which is compared to a next data page in the page server page index. A mismatch in the comparison by page servers indicates data page was split. Compute nodes and page servers store and maintain off-row data generated during data operations via page affinity considerations where the off-row data is stored at the same page server as the data.

Abstract: Columns of a table are stored in either row-major format or column-major format in an in-memory DBMS. For a given table, one set of columns is stored in column-major format; another set of columns for a table are stored in row-major format. This way of storing columns of a table is referred to herein as dual-major format. In addition, a row in a dual-major table is updated “in-place”, that is, updates are made directly to column-major columns without creating an interim row-major form of the column-major columns of the row. Users may submit database definition language (“DDL”) commands that declare the row-major columns and column-major columns of a table.

Abstract: Systems and methods for entering and storing data. User input defining a data set is received. A data collection construct including a data entry user interface for inputting data in the data set is defined using the user input. A data storage construct including queries for retrieving the data is automatically defined based on the user input. Additional user input indicating modifications to the data set is received. The data collection construct, the data storage construct, and the queries are automatically updated based on the additional user input indicating modifications to the data set.

Abstract: Systems, methods, and other embodiments associated with dynamic inclusion of custom columns into a logical model are described. In one embodiment, a method includes: accepting a mapping between a placeholder logical column of a static logical model and a custom physical column; generating an enriched dataset that combines a description of the custom physical column with values of the custom physical column; placing the enriched dataset into the placeholder logical column; and presenting the static logical model with the enriched dataset in the placeholder logical column.

Abstract: A method includes determining a first node set and a second node set that are in a distributed database and that are separately associated with a first data table, where data in the first data table is stored in the first node set, migrating the data from the first node set to the second node set, receiving, in a process of migrating the data, a target service request for the first data table, determining, in response to the target service request, a third node set in the first node set and the second node set that is configured to respond to the target service request, and sending the target service request to a first data node in the third node set.

Abstract: Techniques are provided for reporting space savings due to pattern matching in storage systems. For example, in one embodiment, an exemplary method comprises, when a given allocation unit in a storage system matches one or more predefined patterns, (i) setting a corresponding pattern flag for the given allocation unit, and (ii) incrementing at least one pattern counter; generating at least one snapshot of at least a portion of a file comprising the given allocation unit; and determining a range of data reduction attributed to pattern matching based on said at least one pattern counter, wherein one extreme of said range of data reduction attributed to pattern matching excludes said one or more predefined patterns in said at least one snapshot.

Abstract: Columns of a non-relational data store may be efficiently dropped. A drop column request for a table stored in a non-relational database may be received. In response to the drop column request, schema information for the table may be updated to filter out the column from subsequent read responses to read requests. A backup of the table is created and evaluated to identify those items in the table that include the column. The column is then deleted from the identified items.

Abstract: An object management system (OMS) receives a plurality of objects to be stored. The OMS identifies a subset of objects associated with a same time period and a same namespace from the plurality of objects and generates a batch object comprising the subset of objects. The OMS issues a write request to store the batch object in an object storage system (OSS) and stores, for each object in the subset of objects, a data structure comprising an identifier of the batch object and a position of the object within the batch object. Upon receiving a read request for an object, the OMS determines, based on the data structure, whether the object is stored in the OSS and issues a read request to the OSS based on the identifier of the batch object and the position of the object within the batch, if the objects is stored in the OSS.

Abstract: A system for prioritizing and resolving inconsistencies in digital evidence. The system includes a database containing a first type of data and a second type of data related to an incident record and an electronic computing device including an electronic processor. The electronic processor is configured to receive the first and second types of data from the database, determine an inconsistency between the first and second types of data, and determine an incident type from the incident record. The electronic processor is also configured to determine whether a priority of the determined inconsistency meets a threshold case impact level. When the priority of the inconsistency meets the threshold case impact level, the electronic processor is configured to take a first notification action and when the priority of the inconsistency does not meet the threshold case impact level, the electronic processor is configured to take a second notification action.

Abstract: A data labeling method, apparatus and system are provided. The method includes: sampling a data source according to an evaluation task for the data source to obtain sampled data; generating a labeling task from the sampled data; sending the labeling task to a labeling device; and receiving a labeled result of the labeling task from the labeling device. As such, an automatic evaluation of data can be implemented by using the evaluation task, and evaluation efficiency is improved.

Abstract: Techniques are disclosed for tuning external invocations utilizing weight-based parameter resampling. In one example, a computer system determines a plurality of samples, each sample being associated with a parameter value of a plurality of potential parameter values of a particular parameter. The computer system assigns weights to each of the parameter values, and then selects a first sample for processing via a first external invocation based on a weight of the parameter value of the first sample. The computer system then determines feedback data associated with a level of performance of the first external invocation. The computer system adjusts the weights of the parameter values of the particular parameter based on the feedback data. The computer system then selects a second sample of the plurality of samples to be processed via execution of a second external invocation based on the adjustment of weights of the parameter values.

Abstract: In some examples, a system performs data deduplication using a deduplication fingerprint index in a hash data structure comprising a plurality of blocks, wherein a block of the plurality of blocks comprises fingerprints computed based on content of respective data values. The system merges, in a merge operation, updates for the deduplication fingerprint index to the hash data structure stored in a persistent storage. As part of the merge operation, the system mirrors the updates to a cached copy of the hash data structure in a cache memory, and updates, in an indirect block, information regarding locations of blocks in the cached copy of the hash data structure.

Abstract: Implementations include setting a session variable of each of a plurality of tenants to a first timestamp, importing, after the first timestamp, a first set of content to a shared container within a database system, during importing, each tenant in the plurality of tenants accessing pre-import data stored in the shared container based on the session variable being set to the first timestamp, and after importing the first set of content to the shared container, un-setting, at a second timestamp, the session variable of each of the plurality of tenants from the first timestamp, after the second timestamp, each tenant in the plurality of tenants accessing post-import data stored in the shared container.

Abstract: Example embodiments involve a system and methods for identifying valuable view item pages for search engine optimization. According to certain embodiments, the system performs operations that include predicting the probability of future traffic for a given product based on a number of product level factors as input variables, and identifying a selection of view item pages corresponding to the products with the probability of the highest future traffic in order to maximize the driving natural search traffic to a linked site of the corresponding view item page.

Abstract: Disclosed are a data processing method and device, the method including: setting the scale of data; analyzing and computing a correlation between the data according to the scale of the data; and processing the data on the basis of the correlation according to a processing method corresponding to a set processing type. According to different processing types, disclosed are: a data management and storage method; a method for establishing indexes and analyzing management data; a method for managing and storing data on the basis of indexes; a method for displaying data; a method for analyzing and computing data; and a method for progressive transmission of data.

Abstract: A method for managing a log structured merged (LSM) tree of key value (KV) pairs, the LSM tree is stored in a non-volatile memory, the method may include merging runs of the LSM tree to provide merged runs; writing merged runs to the non-volatile memory; adding new runs to the LSM tree, wherein the adding comprises writing runs to the non-volatile memory; and updating at least one management data structure (MDS) to reflect the merging and the adding; wherein an MDS of the at least one MDS stores a mapping between keys of the KV pairs of the LSM tree, fingerprints associated with the KV pairs of the LSM tree, and compressed run identifiers that identify runs of the LSM tree.

Abstract: A first numerical value is obtained based on a first data source. The first numerical value is stored in a tree structure according to a precision by storing an exponent for the first numerical value in an exponential node of the tree structure and storing respective significant figure digits of the first numerical value in respective regular nodes of the tree structure. Information is computed for nodes in the tree structure. The information includes one or more of statistics, metrics, or histogram information. The computed information is employed to respond to a query related to the data source.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to improve spatial-temporal data management. An example apparatus includes a hypervoxel data structure generator to generate a root hexatree data structure having sixteen hypernodes, an octree manager to improve a spatiotemporal data access efficiency by generating a first degree of symmetry in the root hexatree, the octree manager to assign a first portion of the hypernodes to a positive temporal subspace and to assign a second portion of the hypernodes to a negative temporal subspace, and a quadtree manager to improve the spatiotemporal data access efficiency by generating a second degree of symmetry in the root hexatree, the quadtree manager to assign respective hypernodes of the positive temporal subspace and the negative temporal subspace to respective positive and negative spatial subspaces.

Abstract: A seed value assigned to a database table is determined. Numerically ordered invocation numbers are determined. Unordered pseudorandom numbers are generated based on the seed value and the invocation numbers to index temporally ordered data changes to the database table. It is determined whether the total number of yet-to-be-saved pseudorandom numbers reaches a maximum total number threshold. If so, the yet-to-be-saved pseudorandom numbers and a sequence of corresponding invocation numbers are saved in a sync table.

Abstract: Systems and methods for generating tables are provided. The systems and methods perform operations comprising accessing a text document comprising a plurality of strings; processing the text document by a machine learning model to generate a table comprising a plurality of entries that organizes the plurality of strings into rows and columns over a plurality of iterations; and at each of the plurality of iterations, estimating by the machine learning model a first value of a first entry of the plurality of entries based on a second value of a second entry of the plurality of entries that has been determined in a prior iteration.

Abstract: Various embodiments set forth systems and techniques for concurrent log and dump processing. The techniques include selecting, from a datastore, a chunk comprising one or more rows of data; comparing the one or more rows of data in the chunk with a first set of log events in a change log associated with the datastore, wherein each log event included in the first set of log events occurs after a first log event in the change log and prior to a second log event in the change log; selecting, based on the comparison, one or more non-conflicting rows in the chunk; and transmitting, to an output, one or more log events associated with the one or more non-conflicting rows in the chunk prior to processing a second set of log events in the change log, wherein the second set of log events occur after the second log event.

Abstract: Provided herein are systems and methods for a stream object configuration, including configuring and processing streams on views and streams on tables. For example, a method includes parsing, by at least one hardware processor, a received query to determine a plurality of data processing operations associated with a base table. A stream object on the base table is generated. The stream object includes a plurality of query results from executing the plurality of data processing operations and a corresponding plurality of time stamps of times the plurality of query results are obtained. A stream expansion of the stream object is performed. The stream expansion is based on computing changes to the base table from the plurality of data processing operations.

Abstract: Systems and methods for guaranteeing the integrity of created within or transferred using a network of moving things. Different types of data from different data sources may be monitored, and various approaches to validating such data may be employed using expected data characteristics, alternate data sources, and historical information to help maximize the likelihood that data destined for a particular destination is available when needed, and is found to be valid and reliable.

Abstract: The present embodiments may relate to secondary systems that verify potential fraud or the absence thereof. Artificial intelligence and/or chatbots may be employed to verify veracity of statements used in connection with insurance or loan applications, and/or insurance claims. For instance, a veracity analyzer (VA) computing device includes a processor in communication with a memory device, and may be configured to: (1) generate at least one model by analyzing a plurality of historical statements to identify a plurality of reference indicators correlating to inaccuracy of a historical statement; (2) receive a data stream corresponding to a current statement; (3) parse the data stream using the at least one model to identify at least one candidate indicator included in the current statement matching at least one of the plurality of reference indicators; and/or (4) flag, in response to identifying the at least one candidate indicator, the current statement as potentially false.

Abstract: Embodiments of the system in include a memory that stores a metamodel including a plurality of predefined characteristics for data sets. A data repository stores a plurality of heterogeneous data sets, each of the plurality of data sets comprising a plurality of data batches received over time. An interface receives a new data set for storage into the data repository, and data health reasoner to retrieve the stored metamodel from the memory, the stored metamodel including a plurality of predefined characteristics. The data health reasoner determines measured values of a subset of the plurality of predefined characteristics identified based on the stored metamodel, and determines a set of data health metrics for the data set based on the measured values of the subset of the set of the predefined characteristics. The data health reasoner formulates a plurality of data validation assertions for the data set and apply the plurality of data validation assertions to each instance of the data set.

Abstract: Methods and systems for anomaly detection in relational databases. The methods and systems perform operations comprising: accessing a data object including a data set that has been collected over a given time interval; selecting a reference data point from the data set; computing an angle representing a data growth rate of the data set at least within the given time interval relative to the reference data point; determining that the angle representing the data growth rate of the data set within the given time interval exceeds a specified threshold; and in response to determining that the angle representing the data growth rate of the data set within the given time interval exceeds the specified threshold, triggering an anomaly detection operation.

Abstract: A storage service is configured to receive one or more instructions specifying transformations that are to be applied to data sets stored by the storage service when the data sets are made available outside of particular storage locations within the storage service. In response to triggering events that make the data sets available outside of the particular storage locations, the storage services causes the transformations to be performed on the data sets prior to the data sets being accessible at one or more destination locations outside of the particular storage locations where the data sets are stored. In some embodiments, the transformations are performed on hardware included in the storage service or are performed on external hardware at the direction of the storage service.

Abstract: An example operation includes one or more of receiving a block, extracting information from the block, correlating an identifier to the information as previously stored in a first storage area, replacing the information in the block with the identifier, and submitting the block with the identifier for storage in a second storage area. The identifier links to the information previously stored in the first storage area in order to allow for recovery of the information, and at least the second storage area is in a blockchain.

Abstract: The present disclosure provides systems and methods for an interactive user interface that allows for one or more submissions of update information related to a point of interest to be reviewed. The system may receive the submission from a computing device. The system may analyze the submission to determine the type of content, such as the name, address, website, photo, etc. related to the point of interest. The type of content may be classified using a machine learning model. The model may compare the content of the submission to a model of the type of content to determine whether the submission is approved for publishing or whether additional information is needed. The system may transmit one or more notifications to the computing device. The notifications may include updates on the workflow status of the submission.

Abstract: Systems and methods for decoding distributed ledger transactions by data intake and query systems. An example method includes: receiving a transaction of a distributed ledger, wherein the transaction includes transaction data and an identifier of an account of the distributed ledger; receiving a bytecode module, wherein the bytecode module is associated with the account of the distributed ledger; computing a bytecode digital fingerprint associated with the bytecode module; identifying, among a plurality of stored application binary interface (ABI) definitions, an ABI definition having an ABI digital fingerprint that matches the bytecode digital fingerprint; and producing decoded transaction data by decoding, using the identified ABI definition, the transaction data.

Abstract: A distribution server restructures content and information published to a topic tree for more efficient and meaningful presentation to a subscribing client. To do so, the distribution server receives a request to create a topic view from a client and creates the topic view in response. The topic view includes a set of selected topics and a topic view mapping. The topic view mapping maps the topic paths for the set of selected topics to a set of reference topics at a set of reference paths. In other words, the topic view restructures the content and information by creating new branches in the topic tree. Whenever a selected topic receives an update from a publisher, the distribution server publishes the update as restructured content and information to the reference topics at the reference paths. A client subscribed to the reference path receives the update in a restructured manner.

Abstract: Methods and systems for executing non-blocking transactions at a database are provided. The method includes receiving a write transaction that is directed to a partition of a table stored by a cluster of database nodes. The method includes generating, at a database node of the cluster, a synthetic timestamp based on a first time associated with the database node and a duration, wherein the synthetic timestamp exceeds the first time by the duration. The method includes executing, based on determining the synthetic timestamp, one or more operations of the write transaction at one or more replicas of the partition. The method includes committing, based on a threshold number of acknowledgements, the one or more operations of the write transaction at the one or more replicas. The method includes sending, based on a second time exceeding the synthetic timestamp, an indication of success of the write transaction.

Abstract: A method and apparatus of a device that grows and/or shrinks a table that is shared between a writer and a plurality of readers is described. In an exemplary embodiment, a device receives an entry to be added to the shared table. In response to receiving the entry, the device remaps shared table to add a new storage segment to the shared table. The device further adds the entry to the shared table, where the entry is stored in the new storage segment. In addition, the device updates a shared table characteristic to indicate that the shared table has changed. The device further shrinks the shared table by remapping the table to remove a segment of the table.

Abstract: Systems, computer program products, and methods are described herein for identification and recordation of base components of a resource within a virtual medium. The present invention is configured to electronically receive, from a user input device, a request to generate a non-fungible token (NFT) for a first portion of a resource; in response, retrieve information associated with the first portion of the resource; initiate an NFT engine on the first portion of the resource; generate, using the NFT engine, an NFT for the first portion of the resource, wherein the NFT comprises at least the information associated with the first portion of the resource; record the NFT in a distributed ledger; and transmit control signals configured to cause the user input device to display a notification indicating that the NFT has been generated and recorded in the distributed ledger.

Abstract: A journal-based database may include items, e.g., organized in a table, associated with a journal. The journal may include a hash-chained set of blocks individually including data representing previous and/or current versions of the individual items. The database may receive a request to redact specific data from the database. The database may search the blocks to determine whether the specific data exists. When the specific data exists in a block of the journal, the database may redate the specific data in the identified block. The database may retain existing metadata of the block such that cryptographic verifiability of the hash-chained blocks may be preserved.

Abstract: Embodiments may facilitate data analytics for a cloud computing environment. A plurality of system tables may store system metadata that associates a first materialized view with a first view and a first table. A transaction compute unit may process an update request relevant to the first view. A query parser may capture the update request from the transaction compute unit and detect which system tables are associated with the update request relevant to the first view. Responsive to the request, the query processor arranges for first table data to be replicated and transmit a materialized view request to a materialized view compute unit. The materialized view compute unit may be created as a Materialized View-as-a-Service (“MVaaS”) independent of the transaction compute unit. The materialized view compute unit may receive the materialized view request, refresh the first materialized view, compute the first materialized view, and store a result of the computation.

Abstract: A computer system extracts contender values as positively associated with a pre-defined value from a compilation of one or more electronically stored semi-structured document(s) and/or one or more electronically stored unstructured document(s). The computer system performs a multi-dimensional analysis to narrow the universe of contender values from all words on a page of the compilation to the contender value(s) with the highest likelihood of being associated with the pre-defined value. The system's platform allows every user of the system to customize the system according to the user's needs. Various aspects can enable users to mine document stores for information that can be charted, graphed, studied, and compared to help make better decisions.

Abstract: A website is navigated automatically in a sequential manner, for example by performing a series of specific network requests in a specified order, without necessarily using a browser, and without necessarily rendering each web page in the sequence. Interactions with a website are automatically recorded, stored, and analyzed. Requests and responses can be associated with particular input/output operations. Based on the analysis, the system can determine what data is expected by web servers, so that it can effectively simulate browser operations in connection with those web servers, and extract useful information from the data received in response to those operations. Thus, data extraction and/or other operations can be performed more efficiently and more quickly, while reducing the computing resources needed.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: bundling multiple registered queries of a dataset using a scheduling technique, wherein the dataset is homogenous in schema; running a single table scan of the dataset to process the multiple registered queries of the dataset in parallel; and generating a respective output responsive to each of the multiple registered queries. Other embodiments are disclosed.

Abstract: Methods, systems, and computer program products for a secure database-as-a-service are provided herein. A computer-implemented method includes obtaining, by a database service, data associated with one or more client devices to be stored in at least one encrypted database; encrypting, without mutation and in accordance with one or more security requirements, at least a portion of the data using an order preserving encryption scheme, wherein the encrypting comprises (i) computing a set of encryption parameters for the portion of the data and (ii) applying a process that converts a fixed-length cipher text corresponding to the portion of the data to a variable-length cipher text; and storing the encrypted data in the at least one encrypted database, wherein the database service enables one or more indexes to be built over the encrypted data to improve performance of query processing.

Abstract: Queries to a consistent view of a data set across different types of query engines are performed. Portions of a query received at a first type of query engine that can be performed at a different type of a query engine can be identified. A consistent view of a data set stored in a common data store can be provided by the first type of query engine to the second query engine. When the different type of query engine performs the portion of the query, the different type of query engine applies the consistent view of the data set. A result for the query can be returned by the first type of query engine based on results from the different type of query engine.

Abstract: An approach is disclosed for optimizing jobs, which involve effective data retrieval across multiple data sources, via an externalized query pattern. The approach receives a query. The approach allocates computing power to one or more computing nodes to process a job for the received query. The approach determines whether the job for the received query corresponds to an identifier indexed in a search engine. The approach retrieves, in response to determining the job for the received query corresponds to the indexed identifier, attribute data corresponding to the indexed identifier from the search engine. The approach provides a response to the received query request, in which the response includes the attribute data corresponding to the indexed identifier.