公开(公告)号：US20240289329A1

公开(公告)日：2024-08-29

申请号：US18390005

申请日：2023-12-20

Applicant: Google LLC

Inventor： Anjan Kumar Amirishetty ,  Simhachala Sasikanth Gottapu ,  Niranjan Nilakantan ,  Anthony Hsu ,  Junjie Liang

IPC: G06F16/2453 ,  G06F16/23 ,  G06F16/27

CPC classification number: G06F16/24532 ,  G06F16/2343 ,  G06F16/27

Abstract: Aspects of the disclosure are directed to a parallel recovery mode that applies log records while allowing read queries on read-replica databases. The parallel recovery mode can include applying log records in log sequence number (LSN) order for a block or for multiple blocks, and managing log records affecting multiple blocks. The parallel recovery mode can further manage dependency between different log records and maintain transactional consistency on read queries.

公开(公告)号：US20230401209A1

公开(公告)日：2023-12-14

申请号：US18237490

申请日：2023-08-24

Applicant: Google LLC

Inventor： Xiaobin Ma ,  Xun Cheng ,  Viral Shah ,  Anjan Kumar Amirishetty

IPC: G06F16/2453 ,  G06F16/2455 ,  G06F16/2452

CPC classification number: G06F16/24542 ,  G06F16/24552 ,  G06F16/24524

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.

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

Inventor： Xiaobin Ma ,  Xun Cheng ,  Viral Shah ,  Anjan Kumar Amirishetty

IPC: G06F16/2452 ,  G06F16/245 ,  G06F16/2453 ,  G06F16/2455

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.

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

Inventor： Xiaobin Ma ,  Xun Cheng ,  Viral Shah ,  Anjan Kumar Amirishetty

IPC: G06F16/2453 ,  G06F16/2455

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.

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

Inventor： Anjan Kumar Amirishetty ,  Xun Cheng ,  Viral Shah

IPC: G06F12/08 ,  G06F9/50 ,  G06F12/0871 ,  G06F12/0891 ,  G06F16/22 ,  G06F16/2455 ,  G06F16/27

CPC classification number: G06F12/0871 ,  G06F9/5016 ,  G06F12/0891 ,  G06F16/221 ,  G06F16/24552 ,  G06F16/278

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.

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

Inventor： Xiaobin Ma ,  Xun Cheng ,  Viral Shah ,  Anjan Kumar Amirishetty

IPC: G06F16/2453 ,  G06F16/2455

CPC classification number: G06F16/24544 ,  G06F16/24539 ,  G06F16/2456 ,  G06F16/24557

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.

公开(公告)号：US12158844B2

公开(公告)日：2024-12-03

申请号：US17951193

申请日：2022-09-23

Applicant: Google LLC

Inventor： Anjan Kumar Amirishetty ,  Viral Shah

IPC: G06F12/08 ,  G06F12/02 ,  G06F12/0815 ,  G06F12/0891

Abstract: Aspects of the disclosure are directed to maintaining transaction consistency when using a columnar cache. The columnar cache can be initially loaded with all-visible data, and as the data gets modified, respective data is invalidated in the columnar cache. As more data gets invalidated in the columnar cache, respective data can be refreshed in the columnar cache. As part of the refresh, the latest all-visible data can be populated while the queries are still using the old data in the columnar cache. When all the queries transition to use the newly populated data, old data can be removed from the columnar cache. A query can use valid blocks of columnar cache and go to a row store for invalid blocks. When a query starts to use the columnar cache, a request can be submitted to asynchronously prefetch the invalid blocks from the row store.

公开(公告)号：US11782921B2

公开(公告)日：2023-10-10

申请号：US17521213

申请日：2021-11-08

Applicant: Google LLC

Inventor： Xiaobin Ma ,  Xun Cheng ,  Viral Shah ,  Anjan Kumar Amirishetty

IPC: G06F16/245 ,  G06F16/2453 ,  G06F16/2455 ,  G06F16/2452

CPC classification number: G06F16/24542 ,  G06F16/24524 ,  G06F16/24552

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.

公开(公告)号：US20220253383A1

公开(公告)日：2022-08-11

申请号：US17660374

申请日：2022-04-22

Applicant: Google LLC

Inventor： Anjan Kumar Amirishetty ,  Xun Cheng ,  Viral Shah

IPC: G06F12/0871 ,  G06F16/22 ,  G06F16/2455 ,  G06F16/27 ,  G06F9/50 ,  G06F12/0891

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.

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

Inventor： Anjan Kumar Amirishetty ,  Xun Cheng ,  Viral Shah

IPC: G06F12/0871 ,  G06F9/50 ,  G06F12/0891 ,  G06F16/22 ,  G06F16/2455 ,  G06F16/27

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.