The present disclosure relates to database technology and in particular to dynamically updating and customizing database partitions. A computer-implemented engine is disclosed for identifying and retrieving a number of data records applicable to generate a response to a request, the engine having access to at least two partitions. Partition statistics are generated indicating correlations between the data records and, based on that partition statistics, the data records having the strongest correlation with each other are relocated to partitions so that the number of partitions which have to be queried in order to generate a response to a data request is minimized. Furthermore, the computational load caused when generating responses is more equally distributed across the partitions.

A computer-implemented method of mapping attribute names of a source data model to a destination data model includes obtaining multiple source attribute names from the source data model, and obtaining multiple destination attribute names from the destination data model. The destination data model includes multiple attributes that correspond to attributes in the source data model having different attribute names. The method includes processing the obtained source attribute names and the obtained destination attribute names to standardize the attribute names according to specified character formatting, supplying the standardized attribute names to a machine learning network model to predict a mapping of each source attribute name to a corresponding one of the destination attribute names, and outputting, according to mapping results of the machine learning network model, an attribute mapping table indicating the predicted destination attribute name corresponding to each source attribute name.

Various implementations of the present application set forth a method comprising generating three-dimensional data and two-dimensional data representing a physical space that includes a real-world asset, generating an extended-reality (XR) stream representing a remote collaboration session between a host device and a set of remote devices, where the XR stream includes a combination of the three-dimensional data and the two-dimensional data, a set of augmented-reality (AR) elements associated with the real-world asset, and a set of performed actions associated with a portion of the digital representation or at least one AR element, serializing the XR stream into a set of serialized chunks, transmitting the serialized chunks to the remote devices, where the remote devices recreate the XR stream in a set of remote XR environments, and transmitting the serialized chunks to a remote storage device, where a device subsequently retrieves the serialized chunks to replay the remote collaboration session.

Techniques for improving system performance based on data characteristics are disclosed. A system may receive updates to a first data set at a first frequency. The system selects a first storage configuration, from a plurality of storage configurations, for storing the first data set based on the first frequency, and stores the first data set in accordance with the first storage configuration. The system may further receive updates to a second data set at a second frequency. The system selects a second storage configuration, from the plurality of storage configurations, for storing the second data set based on the second frequency, and stores the second data set in accordance with the second storage configuration. The second storage configuration is different than the first storage configuration.

Machine data of an operating environment is conveyed by a network to a data intake and query system (DIQS) which reflects the machine data as timestamped entries of a field-searchable datastore. Monitoring functionality may search the machine data to identify notable event instances. A notable event processing system correlates the notable event instance to one or more triaging models which are executed against the notable event to produce a modeled result. Information of the received notable event and the modeled results are combined into an enhanced representation of a notable event instance. The enhanced representation conditions downstream processing to automatically perform or assist triaging of notable event instances to optimize application of computing resources to highest priority conditions in the operating environment.

A system is configured for automatic recognition of data store architecture and tracking dynamic changes and evolution in data store architecture. The system ef is a complementary system, which can be added onto an existing data store system using the existing interfaces or can be integrated with a data store system. The system comprises three main components that are configured to compose an approximation of the data store architecture. The first of these components is adapted to execute an analysis of the architecture of the data store; the second of the components is adapted to collect and compile statistics from said data store; and the third of the components is adapted to compose an approximation of the architecture of said data store.

A method of processing a database can include comparing, using a processor, a delta file with a risk assessment criterion, wherein the delta file is generated from a first schema and a second and different schema, assigning a risk level to a change specified within the delta file according to the comparing, and applying the change of the delta file to a test database conforming to the first schema according to the assigned risk level.

The subject technology receives a statement to perform an operation to add a new column into a table. The subject technology generates a schema hash value for a new schema version associated with a new schema version value. The subject technology stores a mapping of the schema hash value to the new schema version value for the table in a metadata database. The subject technology stores a new schema entry based on the schema hash value, the new schema version value, and the new column for the table in the metadata database. The subject technology performs an operation to add the new column to the table.

Enterprises express the concepts of their electronic business-to-business (B2B) communication in differently structured ontology-like schemas. Collaborations benefit from merging the common concepts into semantically unique Business Entities (BEs) in a merged schema. Methods and systems for labeling the merged schema with descriptive, yet short and unique names, are described. A heuristically ranked list of descriptive candidate phrases for each BE is derived locally from the names and descriptions of the underlying concepts. A semantically unique candidate phrase is assigned to each BE that discriminates it from the other BEs by employing a constraint satisfaction problem solver.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for storing semi-structured data. One of the methods includes maintaining a plurality of schemas; receiving a first semi-structured data item; determining that the first semi-structured data item does not match any of the schemas in the plurality of schemas; and in response to determining that the first semi-structured data item does not match any of the schemas in the plurality of schemas: generating a new schema, encoding the first semi-structured data item in the first data format to generate the first new encoded data item in accordance with the new schema, storing the first new encoded data item in the data item repository, and associating the first new encoded data item with the new schema.