公开(公告)号：US11971869B2

公开(公告)日：2024-04-30

申请号：US17974152

申请日：2022-10-26

Applicant: Oracle International Corporation

Inventor： Jesse Kamp ,  Allison L. Holloway ,  Meichun Hsu ,  Hideaki Kimura ,  Boris Klots ,  Vasudha Krishnaswamy ,  Kartik Kulkarni ,  Teck Hua Lee ,  Yunrui Li ,  Aurosish Mishra ,  Ajit Mylavarapu ,  Sukhada Pendse ,  Garret F. Swart ,  Shasank K. Chavan ,  Tirthankar Lahiri ,  Juan R. Loaiza

IPC: G06F16/22 ,  G06F16/11 ,  G06F16/174 ,  G06F16/18 ,  G06F16/21 ,  G06F16/23 ,  G06F16/27

CPC classification number: G06F16/2255 ,  G06F16/128 ,  G06F16/1756 ,  G06F16/1865 ,  G06F16/217 ,  G06F16/2322 ,  G06F16/27

Abstract: A shared-nothing database system is provided in which parallelism and workload balancing are increased by assigning the rows of each table to “slices”, and storing multiple copies (“duplicas”) of each slice across the persistent storage of multiple nodes of the shared-nothing database system. When the data for a table is distributed among the nodes of a shared-nothing system in this manner, requests to read data from a particular row of the table may be handled by any node that stores a duplica of the slice to which the row is assigned. For each slice, a single duplica of the slice is designated as the “primary duplica”. All DML operations (e.g. inserts, deletes, updates, etc.) that target a particular row of the table are performed by the node that has the primary duplica of the slice to which the particular row is assigned. The changes made by the DML operations are then propagated from the primary duplica to the other duplicas (“secondary duplicas”) of the same slice.

公开(公告)号：US20240126816A1

公开(公告)日：2024-04-18

申请号：US18375122

申请日：2023-09-29

Applicant: Oracle International Corporation

Inventor： Jorge Luis Issa Garcia ,  Teck Hua Lee ,  Sheldon Andre Kevin Lewis ,  Bangalore Prashanth ,  Hui Joe Chang ,  Zhen Hua Liu ,  Aurosish Mishra ,  Shasank K. Chavan

IPC: G06F16/903

CPC classification number: G06F16/90335

Abstract: Herein is database query acceleration from dynamic discovery of whether contents of a persistent column can be stored in an accelerated representation in storage-side memory. In an embodiment, based on data type discovery, a storage server detects that column values in a persistent column have a particular data type. Based on storage-side metadata including a frequency of access of the persistent column as an offload input column for offload computation requests on a certain range of memory addresses, the storage server autonomously decides to generate and store, in storage-side memory in the storage server, an accelerated representation of the persistent column that is based on the particular data type. The storage server receives a request to perform an offload computation for the offload input column. Based on the accelerated representation of the persistent column, execution of the offload computation is accelerated.

公开(公告)号：US20220114153A1

公开(公告)日：2022-04-14

申请号：US17070277

申请日：2020-10-14

Applicant: Oracle International Corporation

Inventor： Jesse Kamp ,  Allison L. Holloway ,  Meichun Hsu ,  Hideaki Kimura ,  Boris Klots ,  Vasudha Krishnaswamy ,  Kartik Kulkarni ,  Teck Hua Lee ,  Yunrui Li ,  Aurosish Mishra ,  Ajit Mylavarapu ,  Sukhada Pendse ,  Garret F. Swart ,  Shasank K. Chavan ,  Tirthankar Lahiri ,  Juan R. Loaiza

IPC: G06F16/22 ,  G06F16/21 ,  G06F16/23 ,  G06F16/27 ,  G06F16/11 ,  G06F16/18 ,  G06F16/174

Abstract: A shared-nothing database system is provided in which parallelism and workload balancing are increased by assigning the rows of each table to “slices”, and storing multiple copies (“duplicas”) of each slice across the persistent storage of multiple nodes of the shared-nothing database system. When the data for a table is distributed among the nodes of a shared-nothing system in this manner, requests to read data from a particular row of the table may be handled by any node that stores a duplica of the slice to which the row is assigned. For each slice, a single duplica of the slice is designated as the “primary duplica”. All DML operations (e.g. inserts, deletes, updates, etc.) that target a particular row of the table are performed by the node that has the primary duplica of the slice to which the particular row is assigned. The changes made by the DML operations are then propagated from the primary duplica to the other duplicas (“secondary duplicas”) of the same slice.

公开(公告)号：US10810208B2

公开(公告)日：2020-10-20

申请号：US15702431

申请日：2017-09-12

Applicant: Oracle International Corporation

Inventor： Shasank K. Chavan ,  Dennis Lui ,  Allison L Holloway ,  Sheldon A. K. Lewis

IPC: G06F16/2455 ,  G06F16/22 ,  G06F16/2458 ,  G06F16/2453 ,  G06F9/30 ,  G06F9/38

Abstract: Techniques related to efficient evaluation of queries with multiple predicate expressions are disclosed. A first predicate expression (PE) is evaluated against a plurality of rows in a first column vector (CV) to determine that a subset of rows does not satisfy the first PE. The subset comprises less than all of the plurality of rows. When a query specifies the first PE in conjunction with a second PE, a selectivity of the first PE is determined. If the selectivity meets a threshold, the second PE is evaluated against all of the plurality of rows in a second CV. If the selectivity does not meet the threshold, the second PE is evaluated against only the subset of rows in the second CV. When a query specifies the first PE in disjunction with the second PE, the second PE may be evaluated against only the subset of rows in the second CV.

公开(公告)号：US10229089B2

公开(公告)日：2019-03-12

申请号：US15639110

申请日：2017-06-30

Applicant: Oracle International Corporation

Inventor： Amit Ganesh ,  Shasank K. Chavan ,  Vineet Marwah ,  Jesse Kamp ,  Anindya C. Patthak ,  Michael J. Gleeson ,  Allison L. Holloway ,  Roger Macnicol

IPC: G06F9/30 ,  G06F15/80 ,  G06F17/30

Abstract: A method and apparatus for efficiently processing data in various formats in a single instruction multiple data (“SIMD”) architecture is presented. Specifically, a method to unpack a fixed-width bit values in a bit stream to a fixed width byte stream in a SIMD architecture is presented. A method to unpack variable-length byte packed values in a byte stream in a SIMD architecture is presented. A method to decompress a run length encoded compressed bit-vector in a SIMD architecture is presented. A method to return the offset of each bit set to one in a bit-vector in a SIMD architecture is presented. A method to fetch bits from a bit-vector at specified offsets relative to a base in a SIMD architecture is presented. A method to compare values stored in two SIMD registers is presented.

公开(公告)号：US09881048B2

公开(公告)日：2018-01-30

申请号：US14881356

申请日：2015-10-13

Applicant: Oracle International Corporation

Inventor： Jesse Kamp ,  Amit Ganesh ,  Vineet Marwah ,  Vivekanandhan Raja ,  Tirthankar Lahiri ,  Allison L. Holloway ,  Sanket Hase ,  Shasank K. Chavan ,  Niloy Mukherjee ,  Teck Hua Lee ,  Michael J. Gleeson ,  Krishna Kunchithapadam

IPC: G06F17/30 ,  G06F3/06 ,  G06F11/20

CPC classification number: G06F17/30377 ,  G06F3/0619 ,  G06F3/065 ,  G06F3/0665 ,  G06F3/0689 ,  G06F11/2058 ,  G06F17/30315 ,  G06F17/30442 ,  G06F17/30575 ,  G06F17/30581 ,  G06F2201/80 ,  G06F2201/855

Abstract: Techniques are provided for maintaining data persistently in one format, but making that data available to a database server in more than one format. For example, one of the formats in which the data is made available for query processing is based on the on-disk format, while another of the formats in which the data is made available for query processing is independent of the on-disk format. Data that is in the format that is independent of the disk format may be maintained exclusively in volatile memory to reduce the overhead associated with keeping the data in sync with the on-disk format copies of the data.

公开(公告)号：US20170255675A1

公开(公告)日：2017-09-07

申请号：US15602009

申请日：2017-05-22

Applicant: Oracle International Corporation

Inventor： Shasank K. Chavan ,  Dina Thomas ,  Ajit Mylavarapu ,  Prashant Gaharwar ,  Tirthankar Lahiri ,  Jesse Kamp

IPC: G06F17/30

Abstract: Techniques are described for encoding join columns that belong to the same domain with a common dictionary. The tables are encoded with dictionary indexes that make the comparison operation of a join query a quick equality check of two integers and there is no need to compute any hashes during execution. Additionally, the techniques described herein minimize the bloom filter creation and evaluation cost as well because the dictionary indexes serve as hash values into the bloom filter. If the bloom filter is as large as the range of dictionary indexes, then the filter is no longer a probabilistic structure and can be used to filter rows in the probe phase with full certainty without any significant overhead.

公开(公告)号：US20170031975A1

公开(公告)日：2017-02-02

申请号：US15146799

申请日：2016-05-04

Applicant: Oracle International Corporation

Inventor： Aurosish Mishra ,  Shasank K. Chavan ,  Allison L. Holloway ,  Jesse Kamp ,  Ramesh Kumar ,  Zhen Hua Liu ,  Niloy Mukherjee ,  Amit Ganesh ,  Tirthankar Lahiri ,  Vineet Marwah

IPC: G06F17/30

CPC classification number: G06F17/30383 ,  G06F17/30339 ,  G06F17/3046 ,  G06F17/30477

Abstract: Techniques are described for materializing pre-computed results of expressions. In an embodiment, a set of one or more column units are stored in volatile or non-volatile memory. Each column unit corresponds to a column that belongs to an on-disk table within a database managed by a database server instance and includes data items from the corresponding column. A set of one or more virtual column units, and data that associates the set of one or more column units with the set of one or more virtual column units, are also stored in memory. The set of one or more virtual column units includes a particular virtual column unit storing results that are derived by evaluating an expression on at least one column of the on-disk table.

Abstract translation: 描述了用于实现预先计算的表达式结果的技术。 在一个实施例中，一组一个或多个列单元存储在易失性或非易失性存储器中。 每个列单元对应于属于由数据库服务器实例管理的数据库中的磁盘表上的列，并包括来自相应列的数据项。 一组一个或多个虚拟列单元以及将一个或多个列单元的集合与一个或多个虚拟列单元的集合相关联的数据也存储在存储器中。 一个或多个虚拟列单元的集合包括存储通过评估磁盘表的至少一列上的表达而导出的结果的特定虚拟列单元。

公开(公告)号：US11550771B2

公开(公告)日：2023-01-10

申请号：US17070277

申请日：2020-10-14

Applicant: Oracle International Corporation

Inventor： Jesse Kamp ,  Allison L. Holloway ,  Meichun Hsu ,  Hideaki Kimura ,  Boris Klots ,  Vasudha Krishnaswamy ,  Kartik Kulkarni ,  Teck Hua Lee ,  Yunrui Li ,  Aurosish Mishra ,  Ajit Mylavarapu ,  Sukhada Pendse ,  Garret F. Swart ,  Shasank K. Chavan ,  Tirthankar Lahiri ,  Juan R. Loaiza

IPC: G06F16/22 ,  G06F16/27 ,  G06F16/21 ,  G06F16/174 ,  G06F16/18 ,  G06F16/23 ,  G06F16/11

Abstract: A shared-nothing database system is provided in which parallelism and workload balancing are increased by assigning the rows of each table to “slices”, and storing multiple copies (“duplicas”) of each slice across the persistent storage of multiple nodes of the shared-nothing database system. When the data for a table is distributed among the nodes of a shared-nothing system in this manner, requests to read data from a particular row of the table may be handled by any node that stores a duplica of the slice to which the row is assigned. For each slice, a single duplica of the slice is designated as the “primary duplica”. All DML operations (e.g. inserts, deletes, updates, etc.) that target a particular row of the table are performed by the node that has the primary duplica of the slice to which the particular row is assigned. The changes made by the DML operations are then propagated from the primary duplica to the other duplicas (“secondary duplicas”) of the same slice.

公开(公告)号：US11294816B2

公开(公告)日：2022-04-05

申请号：US15397714

申请日：2017-01-03

Applicant: Oracle International Corporation

Inventor： Shasank K. Chavan ,  Dina Thomas ,  Ajit Mylavarapu ,  Prashant Gaharwar ,  Dennis Lui ,  Sheldon A. K. Lewis

IPC: G06F12/0875 ,  G06F16/2452 ,  G06F7/24

Abstract: Techniques are described herein for reducing the number of redundant evaluations that occur when an expression is evaluated against an encoded column vector by caching results of expression evaluations. When executing a query that includes an expression that references columns for which dictionary-encoded column vectors exist, the database server performs a cost-based analysis to determine which expressions (or sub-expressions) would benefit from caching the expression's evaluation result. For each such expression, the database server performs the necessary computations and caches the results for each of the possible distinct input values. When evaluating an expression for a row with a particular set of input codes, a look-up is performed based on the input code combination to retrieve the pre-computed results of that evaluation from the cache.