Policy driven data placement and information lifecycle management

    公开(公告)号:US11556505B2

    公开(公告)日:2023-01-17

    申请号:US17159070

    申请日:2021-01-26

    Abstract: A method, apparatus, and system for policy driven data placement and information lifecycle management in a database management system are provided. A user or database application can specify declarative policies that define the movement and transformation of stored database objects. The policies are associated with a database object and may also be inherited. A policy defines, for a database object, an archiving action to be taken, a scope, and a condition before the archiving action is triggered. Archiving actions may include compression, data movement, table clustering, and other actions to place the database object into an appropriate storage tier for a lifecycle phase of the database object. Conditions based on access statistics can be specified at the row level and may use segment or block level heatmaps. Policy evaluation occurs periodically in the background, with actions queued as tasks for a task scheduler.

    On-demand cache management of derived cache

    公开(公告)号:US11354252B2

    公开(公告)日:2022-06-07

    申请号:US16144926

    申请日:2018-09-27

    Abstract: Techniques related to automatic cache management are disclosed. In some embodiments, one or more non-transitory storage media store instructions which, when executed by one or more computing devices, cause performance of an automatic cache management method when a determination is made to store a first set of data in a cache. The method involves determining whether an amount of available space in the cache is less than a predetermined threshold. When the amount of available space in the cache is less than the predetermined threshold, a determination is made as to whether a second set of data has a lower ranking than the first set of data by at least a predetermined amount. When the second set of data has a lower ranking than the first set of data by at least the predetermined amount, the second set of data is evicted. Thereafter, the first set of data is cached.

    Optimize workload performance by automatically discovering and implementing in-memory performance features

    公开(公告)号:US12229160B2

    公开(公告)日:2025-02-18

    申请号:US18374852

    申请日:2023-09-29

    Abstract: Techniques are provided for optimizing workload performance by automatically discovering and implementing performance optimizations for in-memory units (IMUs). A system maintains a set of IMUs for processing database operations in a database. The system obtains a database workload information for the database system and filters the database workload information to identify database operations in the database workload information that may benefit from performance optimizations. The system analyzes the database operations to identify a set of performance optimizations and ranks the performance optimizations based on their potential benefit. The system selects a subset of the performance optimizations, based on their ranking, and generates new versions of IMUs that reflect the performance optimizations. The system performs verification tests on the new versions of IMUs and analyzes the tests to determine whether the new versions of IMUs yield expected performance benefits. The system then categorizes the new set of IMUs into a first set of IMUs to be retained and a second set of IMUs to be discarded. The system then makes the first set of IMUs available to the current workload and discards the second set of IMUs.

    Automated information lifecycle management of indexes

    公开(公告)号:US11379410B2

    公开(公告)日:2022-07-05

    申请号:US16926425

    申请日:2020-07-10

    Abstract: Techniques are provided for a DBMS automating ILM on indexes, based on index composition, to efficiently reduce index storage footprints. According to an embodiment, a user sets an index-specific ILM (ISILM) policy, which comprises one or both of an index-test requirement and a time requirement. Based on the ISILM policy being met, or on some other way of initiating analysis, the DBMS automatically analyzes the data blocks storing the index to determine an index condition metric (e.g., percentage of free space). This analysis is performed on a sample of data blocks storing the index without blocking the index from other operations during the analysis. The condition metric for the entire index is estimated based on analysis of the sample data blocks. Using the determined condition metric for an index, the DBMS automatically selects an option for optimally managing the index (e.g., coalesce, shrink space, index rebuild, no action, etc.).

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