公开(公告)号：US12026129B2

公开(公告)日：2024-07-02

申请号：US17657229

申请日：2022-03-30

Applicant: Snowflake Inc.

Inventor： Selcuk Aya ,  Ju-yi Kuo ,  Jonathan Lee Leang ,  Nitya Kumar Sharma ,  Igor Zinkovsky

IPC: G06F15/16 ,  G06F16/17 ,  G06F16/172 ,  G06F16/176

CPC classification number: G06F16/1774 ,  G06F16/172 ,  G06F16/1734

Abstract: Systems and methods for caching file system collections atomically. The systems and methods perform operations comprising: receiving a request to access a collection of data comprising a plurality of files stored on a storage device; in response to receiving the request, transferring the collection of data from the storage device to a first subfolder in a cache associated with the storage device; generating a lock file comprising a reference to the first subfolder in the cache; and atomically controlling access to the collection of data in the first subfolder and removal of the collection of data in the first subfolder from the cache via the lock file.

公开(公告)号：US20230409430A1

公开(公告)日：2023-12-21

申请号：US18104249

申请日：2023-01-31

Applicant: Snowflake Inc.

Inventor： Selcuk Aya ,  Leonid Baraznenok ,  Jaeha Lee ,  Adrian Peter Neumann ,  Ryan Michael Thomas Shelly ,  Zerui Wei ,  Jiaqi Yan

IPC: G06F11/14 ,  G06F11/07 ,  G06F16/215

CPC classification number: G06F11/1435 ,  G06F16/215 ,  G06F11/079

Abstract: Embodiments of the present disclosure may provide a data protection system that performs identification of errors from queries on a database. The data protection system can further identify corrupted data from additional errors, are difficult to detect, and occur between layers of data in the database system. The data protection system can perform corrections of the error data by rebuilding database data or removing the corrupted data.

公开(公告)号：US20220358128A1

公开(公告)日：2022-11-10

申请号：US17814110

申请日：2022-07-21

Applicant: Snowflake Inc.

Inventor： Mahmud Allahverdiyev ,  Selcuk Aya ,  Bowei Chen ,  Ismail Oukid

IPC: G06F16/2455 ,  G06F16/9035 ,  G06F16/28 ,  G06F17/18 ,  G06F16/22

Abstract: A pruning index is generated for a source table organized into a set of batch units. The source table comprises a column of semi-structured data. The pruning index comprises a set of filters that index distinct values in each column of the source table. Rather than reassembling an entire tree structure of the semi-structured data prior to indexing, the generating of the pruning index comprises traversing a reassembly hook object that represents a first portion of the semi-structured data that is subcolumnarized and traversing a residual object that represents a second portion of the semi-structured data that is not subcolumnarized. The reassembly hook object is traversed to identify values corresponding to the first portion of the semi-structured data and the residual object is traversed to identify values corresponding to the second portion. The pruning index is stored with an association with the source table.

公开(公告)号：US20230139194A1

公开(公告)日：2023-05-04

申请号：US18146912

申请日：2022-12-27

Applicant: Snowflake Inc.

Inventor： Mahmud Allahverdiyev ,  Selcuk Aya ,  Bowei Chen ,  Ismail Oukid

IPC: G06F16/2455 ,  G06F16/9035 ,  G06F16/28 ,  G06F17/18 ,  G06F16/22

Abstract: A pruning index is generated for a source table organized into a set of batch units. The source table comprises a column of semi-structured data. The pruning index comprises a set of filters that index distinct values in each column of the source table. Rather than reassembling an entire tree structure of the semi-structured data prior to indexing, the generating of the pruning index comprises traversing a reassembly hook object that represents a first portion of the semi-structured data that is subcolumnarized and traversing a residual object that represents a second portion of the semi-structured data that is not subcolumnarized. The reassembly hook object is traversed to identify values corresponding to the first portion of the semi-structured data and the residual object is traversed to identify values corresponding to the second portion. The pruning index is stored with an association with the source table.

公开(公告)号：US11567939B2

公开(公告)日：2023-01-31

申请号：US17814110

申请日：2022-07-21

Applicant: Snowflake Inc.

Inventor： Mahmud Allahverdiyev ,  Selcuk Aya ,  Bowei Chen ,  Ismail Oukid

IPC: G06F16/24 ,  G06F16/2455 ,  G06F16/9035 ,  G06F16/28 ,  G06F17/18 ,  G06F16/22

Abstract: A pruning index is generated for a source table organized into a set of batch units. The source table comprises a column of semi-structured data. The pruning index comprises a set of filters that index distinct values in each column of the source table. Rather than reassembling an entire tree structure of the semi-structured data prior to indexing, the generating of the pruning index comprises traversing a reassembly hook object that represents a first portion of the semi-structured data that is subcolumnarized and traversing a residual object that represents a second portion of the semi-structured data that is not subcolumnarized. The reassembly hook object is traversed to identify values corresponding to the first portion of the semi-structured data and the residual object is traversed to identify values corresponding to the second portion. The pruning index is stored with an association with the source table.

公开(公告)号：US20240220456A1

公开(公告)日：2024-07-04

申请号：US18607857

申请日：2024-03-18

Applicant: Snowflake Inc

Inventor： Selcuk Aya ,  Bowei Chen ,  Florian Andreas Funke

IPC: G06F16/174 ,  G06F16/22 ,  G06F16/27

CPC classification number: G06F16/1744 ,  G06F16/221 ,  G06F16/27

Abstract: Data in a micro-partition of a table is stored in a compressed form. In response to a database query on the table comprising a filter, the portion of the data on which the filter operates is decompressed, without decompressing other portions of the data. Using the filter on the decompressed portion of the data, the portions of the data that are responsive to the filter are determined and decompressed. The responsive data is returned in response to the database query. When a query is run on a table that is compressed using dictionary compression, the uncompressed data may be returned along with the dictionary look-up values. The recipient of the data may use the dictionary look-up values for memoization, reducing the amount of computation required to process the returned data.

公开(公告)号：US11816107B2

公开(公告)日：2023-11-14

申请号：US18146912

申请日：2022-12-27

Applicant: Snowflake Inc.

Inventor： Mahmud Allahverdiyev ,  Selcuk Aya ,  Bowei Chen ,  Ismail Oukid

IPC: G06F16/24 ,  G06F16/2455 ,  G06F16/9035 ,  G06F16/28 ,  G06F17/18 ,  G06F16/22

CPC classification number: G06F16/24557 ,  G06F16/2272 ,  G06F16/283 ,  G06F16/9035 ,  G06F17/18

Abstract: A pruning index is generated for a source table organized into a set of batch units. The source table comprises a column of semi-structured data. The pruning index comprises a set of filters that index distinct values in each column of the source table. Rather than reassembling an entire tree structure of the semi-structured data prior to indexing, the generating of the pruning index comprises traversing a reassembly hook object that represents a first portion of the semi-structured data that is subcolumnarized and traversing a residual object that represents a second portion of the semi-structured data that is not subcolumnarized. The reassembly hook object is traversed to identify values corresponding to the first portion of the semi-structured data and the residual object is traversed to identify values corresponding to the second portion. The pruning index is stored with an association with the source table.

公开(公告)号：US20240427755A1

公开(公告)日：2024-12-26

申请号：US18517744

申请日：2023-11-22

Applicant: Snowflake Inc.

Inventor： Selcuk Aya ,  Thierry Cruanes ,  Istvan Cseri ,  Benoit Dageville ,  Marcia Feitel ,  Steven P. Herbert ,  Dennis Huo ,  Xinglian Liu ,  Nithin Mahesh ,  James Malone ,  Subramanian Muralidhar ,  Muthunagappan Muthuraman ,  Ronald Lee Ortloff ,  Polita Paulus ,  Marianne Shaw ,  Nileema Shingte ,  Wai Sing Wong ,  Jiaqi Yan

IPC: G06F16/22 ,  G06F16/215 ,  G06F16/2457

Abstract: The subject technology provides embodiments for supporting a unified table which may be a managed table or an unmanaged table. Managed tables are those where the subject technology manages the metastore/catalog for the table, whereas unmanaged tables are tables where an external catalog controls the table and the subject technology integrates with that catalog to work with the table, but does not assume control of the table.

公开(公告)号：US12050582B1

公开(公告)日：2024-07-30

申请号：US18498463

申请日：2023-10-31

Applicant: Snowflake Inc.

Inventor： Selcuk Aya ,  Thierry Cruanes ,  Istvan Cseri ,  Benoit Dageville ,  Marcia Feitel ,  Steven P. Herbert ,  Dennis Huo ,  Xinglian Liu ,  Nithin Mahesh ,  James Malone ,  Subramanian Muralidhar ,  Muthunagappan Muthuraman ,  Ronald Lee Ortloff ,  Polita Paulus ,  Marianne Shaw ,  Nileema Shingte ,  Wai Sing Wong ,  Jiaqi Yan

IPC: G06F16/22 ,  G06F16/215 ,  G06F16/2457

CPC classification number: G06F16/2282 ,  G06F16/215 ,  G06F16/24573

Abstract: The subject technology provides embodiments for supporting a unified table which may be a managed table or an unmanaged table. Managed tables are those where the subject technology manages the metastore/catalog for the table, whereas unmanaged tables are tables where an external catalog controls the table and the subject technology integrates with that catalog to work with the table, but does not assume control of the table.

公开(公告)号：US11971856B2

公开(公告)日：2024-04-30

申请号：US16779366

申请日：2020-01-31

Applicant: Snowflake Inc.

Inventor： Selcuk Aya ,  Bowei Chen ,  Florian Andreas Funke

IPC: G06F16/174 ,  G06F16/22 ,  G06F16/27

CPC classification number: G06F16/1744 ,  G06F16/221 ,  G06F16/27

Abstract: Data in a micro-partition of a table is stored in a compressed form. In response to a database query on the table comprising a filter, the portion of the data on which the filter operates is decompressed, without decompressing other portions of the data. Using the filter on the decompressed portion of the data, the portions of the data that are responsive to the filter are determined and decompressed. The responsive data is returned in response to the database query. When a query is run on a table that is compressed using dictionary compression, the uncompressed data may be returned along with the dictionary look-up values. The recipient of the data may use the dictionary look-up values for memoization, reducing the amount of computation required to process the returned data.