Abstract: The subject technology determines whether a table is sufficiently clustered. The subject technology in response to determining the table is not sufficiently clustered, selects one or more micro-partitions of the table to be reclustered. The subject technology constructs a data structure for the table. The subject technology extracts minimum and maximum endpoints for each micro-partition in the data structure. The subject technology sorts each of one or more peaks in the data structure based on height. The subject technology sorts overlapping micro-partitions based on width. The subject technology selects based on which micro-partitions are within the tallest peaks of the one or more peaks and further based on which of the overlapping micro-partitions have the widest widths.

Abstract: Automatic clustering of a database table is disclosed. A method for automatic clustering of a database table includes receiving an indication that a data modification task has been executed on a table and determining whether the table is sufficiently clustered. The method includes, in response to determining the table is not sufficiently clustered, selecting one or more micro-partitions of the table to be reclustered. The method includes assigning each of the one or more micro-partitions to an execution node to be reclustered.

Abstract: Automatic clustering of a database table is disclosed. A method for automatic clustering of a database table includes receiving an indication that a data modification task has been executed on a table and determining whether the table is sufficiently clustered. The method includes, in response to determining the table is not sufficiently clustered, selecting one or more micro-partitions of the table to be reclustered. The method includes assigning each of the one or more micro-partitions to an execution node to be reclustered.

Abstract: The subject technology determines whether a table is sufficiently clustered. The subject technology in response to determining the table is not sufficiently clustered, selects one or more micro-partitions of the table to be reclustered. The subject technology constructs a data structure for the table. The subject technology extracts minimum and maximum endpoints for each micro-partition in the data structure. The subject technology sorts each of one or more peaks in the data structure based on height. The subject technology sorts overlapping micro-partitions based on width. The subject technology selects based on which micro-partitions are within the tallest peaks of the one or more peaks and further based on which of the overlapping micro-partitions have the widest widths.

Abstract: Automatic clustering of a database table is disclosed. A method for automatic clustering of a database table includes receiving an indication that a data modification task has been executed on a table and determining whether the table is sufficiently clustered. The method includes, in response to determining the table is not sufficiently clustered, selecting one or more micro-partitions of the table to be reclustered. The method includes assigning each of the one or more micro-partitions to an execution node to be reclustered.

Abstract: The subject technology determines whether a table is sufficiently clustered. The subject technology in response to determining the table is not sufficiently clustered, selects one or more micro-partitions of the table to be reclustered. The subject technology constructs a data structure for the table. The subject technology extracts minimum and maximum endpoints for each micro-partition in the data structure. The subject technology sorts each of one or more peaks in the data structure based on height. The subject technology sorts overlapping micro-partitions based on width. The subject technology selects based on which micro-partitions are within the tallest peaks of the one or more peaks and further based on which of the overlapping micro-partitions have the widest widths.

Abstract: Automatic clustering of a database table is disclosed. A method for automatic clustering of a database table includes receiving an indication that a data modification task has been executed on a table and determining whether the table is sufficiently clustered. The method includes, in response to determining the table is not sufficiently clustered, selecting one or more micro-partitions of the table to be reclustered. The method includes assigning each of the one or more micro-partitions to an execution node to be reclustered.

Abstract: Resource provisioning systems and methods are described. In an embodiment, a system includes a plurality of shared storage devices collectively storing database data, an execution platform, and a compute service manager. The compute service manager is configured to determine a task to be executed in response to a trigger event and determine a query plan for executing the task, wherein the query plan comprises a plurality of discrete subtasks. The compute service manager is further configured to assign the plurality of discrete subtasks to one or more nodes of a plurality of nodes of the execution platform, determine whether execution of the task is complete, and in response to determining the execution of the task is complete, store a record in the plurality of shared storage devices indicating the task was completed.

Abstract: Resource provisioning systems and methods are described. In an embodiment, a system includes a plurality of shared storage devices collectively storing database data, an execution platform, and a compute service manager. The compute service manager is configured to determine a task to be executed in response to a trigger event and determine a query plan for executing the task, wherein the query plan comprises a plurality of discrete subtasks. The compute service manager is further configured to assign the plurality of discrete subtasks to one or more nodes of a plurality of nodes of the execution platform, determine whether execution of the task is complete, and in response to determining the execution of the task is complete, store a record in the plurality of shared storage devices indicating the task was completed.

Abstract: Automatic clustering of a database table is disclosed. A method for automatic clustering of a database table includes receiving an indication that a data modification task has been executed on a table and determining whether the table is sufficiently clustered. The method includes, in response to determining the table is not sufficiently clustered, selecting one or more micro-partitions of the table to be reclustered. The method includes assigning each of the one or more micro-partitions to an execution node to be reclustered.

Abstract: Automatic clustering of a database table is disclosed. A method for automatic clustering of a database table includes receiving an indication that a data modification task has been executed on a table and determining whether the table is sufficiently clustered. The method includes, in response to determining the table is not sufficiently clustered, selecting one or more micro-partitions of the table to be reclustered. The method includes assigning each of the one or more micro-partitions to an execution node to be reclustered.

Abstract: Embedded Performance Monitoring is an “out-of-box” approach for performance monitoring of a DBMS. Performance monitoring of a DBMS is achieved through use of a browser to access the DBMS once a DBMS is installed and configured. The approach exploits a DBMS configured with the native capability to provide performance monitoring data and software via a browser. To retrieve and use the performance monitoring data from the DBMS, a browser executes software downloaded to the browser from the DBMS using web-based technologies.

Abstract: Techniques for generating and processing composite active reports are provided. An active report is a report that can be displayed and interacted with at a client device even though the client device is not connected to a database from which data for the report originates. A composite active report is an active report that includes multiple reports embedded in the same file. Each report in a composite active report may be separately compressed to allow a client device to decompress a report on demand. A composite active report may include, for each report indicated in the composite active report, executable identification data that is used to retrieve, from a remote source, an executable that is used to generate, based on report data of the report, display data, which is displayed on a computer display of a client device.

Abstract: Embedded Performance Monitoring is an “out-of-box” approach for performance monitoring of a DBMS. Performance monitoring of a DBMS is achieved through use of a browser to access the DBMS once a DBMS is installed and configured. The approach exploits a DBMS configured with the native capability to provide performance monitoring data and software via a browser. To retrieve and use the performance monitoring data from the DBMS, a browser executes software downloaded to the browser from the DBMS using web-based technologies.

Abstract: Techniques for generating and processing composite active reports are provided. An active report is a report that can be displayed and interacted with at a client device even though the client device is not connected to a database from which data for the report originates. A composite active report is an active report that includes multiple reports embedded in the same file. Each report in a composite active report may be separately compressed to allow a client device to decompress a report on demand. A composite active report may include, for each report indicated in the composite active report, executable identification data that is used to retrieve, from a remote source, an executable that is used to generate, based on report data of the report, display data, which is displayed on a computer display of a client device.

Abstract: An assembly (1) for mounting a lens onto a housing comprising a housing (3) with aperture (5) providing a passage between a housing outer surface (11) and a housing inner surface (12). There is also a lens (2) complementarily engaging the aperture (5) thereby preventing the lens (5) from passing through the aperture (5). A seal (4) is adhered to both said a lens inner surface (14) and the housing inner surface (12) to thereby provide a water resistant seal.