Elastic Columnar Cache for Cloud Databases

    公开(公告)号:US20250036567A1

    公开(公告)日:2025-01-30

    申请号:US18915185

    申请日:2024-10-14

    Applicant: Google LLC

    Abstract: A method for providing elastic columnar cache includes receiving cache configuration information indicating a maximum size and an incremental size for a cache associated with a user. The cache is configured to store a portion of a table in a row-major format. The method includes caching, in a column-major format, a subset of the plurality of columns of the table in the cache and receiving a plurality of data requests requesting access to the table and associated with a corresponding access pattern requiring access to one or more of the columns. While executing one or more workloads, the method includes, for each column of the table, determining an access frequency indicating a number of times the corresponding column is accessed over a predetermined time period and dynamically adjusting the subset of columns based on the access patterns, the maximum size, and the incremental size.

    Evaluating row-store expressions on a column-store database

    公开(公告)号:US12038894B2

    公开(公告)日:2024-07-16

    申请号:US18167134

    申请日:2023-02-10

    Applicant: Google LLC

    CPC classification number: G06F16/221 G06F12/023 G06F2212/152

    Abstract: Aspects of the disclosure provide for natively executing row-store expression data structures on column-store databases without rewriting. A database management system (DBMS) configured as described herein can maintain a mapping of row-store results to addresses of where corresponding column data is stored. When executing operators, such as logical operators, comparison operators, and/or function operators of a received query expression, the DBMS can operate on the column data, rather than the individual rows. The DBMS can store the results generated by executing the column operators, for example on a stack, and record the row-store addresses to which the stored results correspond. The DBMS responds with a number of rows corresponding to the processed column data.

    Columnar Cache Query Using Hybrid Query Execution Plan

    公开(公告)号:US20230141902A1

    公开(公告)日:2023-05-11

    申请号:US17521213

    申请日:2021-11-08

    Applicant: Google LLC

    Abstract: Aspects of the disclosure are directed to generating a hybrid query execution plan for executing queries on database systems implementing a columnar cache. A hybrid query execution plan combines a query execution plan for querying and retrieving data from a columnar cache and a base table. A columnar cache stores cached data in column-major format, which is logically represented by the database management system in row-major format. A database management system as described herein can scan valid blocks of column data according to a column scan operation. The system can identify invalidated blocks and execute a different sub-execution plan of the hybrid query execution plan to scan corresponding rows in tables corresponding to the location of data for the invalidated blocks.

    Elastic Columnar Cache for Cloud Databases

    公开(公告)号:US20220019539A1

    公开(公告)日:2022-01-20

    申请号:US16932874

    申请日:2020-07-20

    Applicant: Google LLC

    Abstract: A method for providing elastic columnar cache includes receiving cache configuration information indicating a maximum size and an incremental size for a cache associated with a user. The cache is configured to store a portion of a table in a row-major format. The method includes caching, in a column-major format, a subset of the plurality of columns of the table in the cache and receiving a plurality of data requests requesting access to the table and associated with a corresponding access pattern requiring access to one or more of the columns. While executing one or more workloads, the method includes, for each column of the table, determining an access frequency indicating a number of times the corresponding column is accessed over a predetermined time period and dynamically adjusting the subset of columns based on the access patterns, the maximum size, and the incremental size.

    Columnar cache query using hybrid query execution plan

    公开(公告)号:US12292887B2

    公开(公告)日:2025-05-06

    申请号:US18237490

    申请日:2023-08-24

    Applicant: Google LLC

    Abstract: A hybrid query execution plan is generated for executing queries on database systems implementing a columnar cache. A hybrid query execution plan combines a query execution plan for querying and retrieving data from a columnar cache and a base table. A columnar cache stores cached data in column-major format, which is logically represented by the database management system in row-major format. A database management system as described herein can scan valid blocks of column data according to a column scan operation. The system can identify invalidated blocks and execute a different sub-execution plan of the hybrid query execution plan to scan corresponding rows in tables corresponding to the location of data for the invalidated blocks.

    Late Materialization of Queried Data in Database Cache

    公开(公告)号:US20250036625A1

    公开(公告)日:2025-01-30

    申请号:US18915485

    申请日:2024-10-15

    Applicant: Google LLC

    Abstract: Aspects of the disclosure are directed to late materialization of attributes in response to queries to a database implementing a database cache. Queried data is materialized in temporary memory before the data is projected as part of generating a result to the query. Instead of materializing all of the attributes referenced in a query before executing the query, a database management system materializes attributes as “late” as possible—when the operation needing the attributes is executed. The operation needing the attributes can be performed sooner, as opposed to materializing all referenced attributes are materialized before executing the query.

    Elastic columnar cache for cloud databases

    公开(公告)号:US12124376B2

    公开(公告)日:2024-10-22

    申请号:US17660374

    申请日:2022-04-22

    Applicant: Google LLC

    Abstract: A method for providing elastic columnar cache includes receiving cache configuration information indicating a maximum size and an incremental size for a cache associated with a user. The cache is configured to store a portion of a table in a row-major format. The method includes caching, in a column-major format, a subset of the plurality of columns of the table in the cache and receiving a plurality of data requests requesting access to the table and associated with a corresponding access pattern requiring access to one or more of the columns. While executing one or more workloads, the method includes, for each column of the table, determining an access frequency indicating a number of times the corresponding column is accessed over a predetermined time period and dynamically adjusting the subset of columns based on the access patterns, the maximum size, and the incremental size.

    Autonomous Column Selection for Columnar Cache

    公开(公告)号:US20230141891A1

    公开(公告)日:2023-05-11

    申请号:US17523520

    申请日:2021-11-10

    Applicant: Google LLC

    CPC classification number: G06F16/24539 G06F16/2264 G06F16/24552 G06F16/221

    Abstract: Aspects of the disclosure are directed to generating cache configurations for caching data for a database. A database management system (DBMS) can search for column data to cache in a database cache to improve performance of the DBMS in resolving queries. Column data selection can be performed automatically and in the background of a deployed DBMS. Periodically, the DBMS can assess the performance benefit of having certain data cached in the database cache and select data for caching based on the assessed performance benefit. The DBMS can also determine the performance benefit of cached data when not cached, as well as select some portions of data to cache over others. The DBMS can also select data for caching based on different degrees of compression, to further improve query resolution performance.

    Late Materialization of Queried Data in Database Cache

    公开(公告)号:US20230141190A1

    公开(公告)日:2023-05-11

    申请号:US17522504

    申请日:2021-11-09

    Applicant: Google LLC

    Abstract: Aspects of the disclosure are directed to late materialization of attributes in response to queries to a database implementing a database cache. Queried data is materialized in temporary memory before the data is projected as part of generating a result to the query. Instead of materializing all of the attributes referenced in a query before executing the query, a database management system materializes attributes as “late” as possible—when the operation needing the attributes is executed. The operation needing the attributes can be performed sooner, as opposed to materializing all referenced attributes are materialized before executing the query.

    Database Join Operations With Early Filtering

    公开(公告)号:US20240078237A1

    公开(公告)日:2024-03-07

    申请号:US17939141

    申请日:2022-09-07

    Applicant: Google LLC

    CPC classification number: G06F16/2456 G06F11/3409 G06F16/24537 G06F16/24544

    Abstract: Aspects of the disclosure are directed to early filtering of candidate rows for a join operator of a query statement before the join operator is evaluated to generate a result set. Early filtering, e.g., before execution of the join operator, reduces the number of candidate rows fetched from a database during a join operator, which can improve the rate at which queries including join operators are executed by a DBMS for the database. One or more Bloom filters or other probabilistic data structures can be produced and consumed according to different join conditions, allowing for early pruning of unqualified rows during a database scan operation.

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