One example method includes chunking a respective disk of each of a plurality of virtual machines (VM) to create a respective plurality of chunks associated with each of the VMs, creating, based on the chunking process, a cluster comprising one or more of the VMs, creating a VM template whose data and disk structure match respective data and disk structures of each of the VMs in the cluster, and in response to a file operation involving a first one of the VM disks, defragmenting the first VM disk so that a disk structure of the first VM disk is the same as a disk structure of the VM template.

The present disclosure provides a clustering method and apparatus for spatial points, and an electronic device, relates to the field of artificial intelligence, and in particular, to intelligent transportation. The specific implementation solution includes: clustering multiple spatial points to-be-processed according to distances between the multiple spatial points to-be-processed to obtain multiple first clustering groups; for each first clustering group, determining a first external graph enclosing all the spatial points to-be-processed in this first clustering group; and merging the multiple first clustering groups according to distances between first external graphs of the multiple first clustering groups to obtain at least one second clustering group. Therefore, clustering efficiency can be enhanced.

Methods, systems, and computer-readable media for query language interoperability in a graph database are disclosed. Data elements are inserted into a graph database using one or more of a plurality of graph database query languages. The graph database query languages comprise a first graph database query language associated with a first data model and a second graph database query language associated with a second data model. The data elements are stored in the graph database using an internal data model that differs from the first and second data models. One or more of the data elements are retrieved from the graph database based at least in part on a query. The query is expressed using a different graph database query language than the graph database query language used to insert the one or more retrieved data elements.

A sample rack includes a placement table having an upper surface for placing at least one sample plate thereon, a handle portion holding a proximal end portion of the placement table, the handle portion having a lower end portion positioned lower than a lower surface of the placement table when the upper surface is leveled, and a leg portion attached to the placement table to take a protruding posture in which the leg portion is protruded downward from the lower surface and a storage posture in which the leg portion is not protruded downward from the lower surface. The leg portion is configured to support the sample rack to maintain the upper surface substantially horizontally in cooperation with the lower end portion of the handle portion when the sample rack is placed on a substantially horizontal surface with the leg portion taking the protruding posture.

Provided is a database system and method in which storage is partitioned in an unbalanced format for faster access. In one example, the method may include one or more of receiving a request to store a data record, identifying a partition from among a plurality of partitions of a database based on a shard identifier in the request, automatically determining a unique range of data identifiers designated to the partition from the plurality of partitions, respectively, based on an unbalanced partitioning, determining whether the data identifier is available within the unique range of data identifiers of the identified partition, and storing the data record at the identified partition in response to determining the data identifier is available. The unbalanced partitioning according to various embodiments reduces the partitions that need to be checked during a data insert/access operation of the database.

Dynamically normalizing intervals in a table including receiving, from a client computing system, a request to normalize intervals for a data set on a cloud-based data warehouse, wherein the request comprises a reference to the data set and a data range; generating, on the cloud-based data warehouse, an interval table using the data range; joining, into a joined table on the cloud-based data warehouse, the interval table and the data set; receiving the joined table from the cloud-based data warehouse; and presenting, via a graphical user interface on the client computing system, the joined table as a worksheet.

A method and system for accessing updated data from a database in response to a user query has been developed. First, multiple transaction logs are generated for a database. Each transaction log contains a record of actions executed by a database management system and referenced according to the specified date of the actions. Data updates are received and stored with the database. An incremental database partition is created for each data update. Each incremental database partition is stored with reference to a corresponding transaction log for the date of the data update. The updated data is accessed through the incremental database partition in response to an outdated user query. The outdated user query contains a data access request for a date earlier than the receipt of data updates.

A system and methods for generating and applying learning agents in simulated environments, in which an agent simulation is selected, one or more agent goals are received, and agents are created which are individual instances of the agent simulation with each agent having at least one of the agent goals, wherein the agents are used in the execution of an environment simulation which dynamically changes based on the collective behavior of the agents.

A system for generating product label changes is described. The system includes a product labeling platform executable on a network enabled computing device and a database of at least one selectable master label and at least one selectable jurisdiction label associated with a labeled product. The platform associates at least one selected descriptor from a first pre-defined descriptor set to each change made to a selected master label, and further associates at least one selected descriptor from a second pre-defined descriptor set to each change made to a selected jurisdiction label. The platform further associates a report including the selected descriptors from the first and second pre-defined descriptor sets with the changed label. A system for generating and managing product labels for a product across multiple jurisdictions is also disclosed. Methods including a computer-implemented method of updating a product label and a computer-implemented method of generating and managing product labels for a product across a plurality of jurisdictions are also disclosed.

A system for generating product label changes is described. The system includes a product labeling platform executable on a network enabled computing device and a database of at least one selectable master label and at least one selectable jurisdiction label associated with a labeled product. The platform associates at least one selected descriptor from a first pre-defined descriptor set to each change made to a selected master label, and further associates at least one selected descriptor from a second pre-defined descriptor set to each change made to a selected jurisdiction label. The platform further associates a report including the selected descriptors from the first and second pre-defined descriptor sets with the changed label. A system for generating and managing product labels for a product across multiple jurisdictions is also disclosed. Methods including a computer-implemented method of updating a product label and a computer-implemented method of generating and managing product labels for a product across a plurality of jurisdictions are also disclosed.