公开(公告)号：US11675761B2

公开(公告)日：2023-06-13

申请号：US16135748

申请日：2018-09-19

Applicant: Oracle International Corporation

Inventor： Roger Dermot Macnicol ,  Xia Hua ,  Allison Holloway ,  Shasank Kisan Chavan ,  Jesse Kamp ,  Maria Colgan ,  Tirthankar Lahiri

IPC: G06F16/22 ,  G06F16/2458 ,  G06F16/2455 ,  G06F16/25 ,  G06F16/21 ,  G06F16/248

CPC classification number: G06F16/221 ,  G06F16/219 ,  G06F16/2237 ,  G06F16/248 ,  G06F16/2455 ,  G06F16/2456 ,  G06F16/2471 ,  G06F16/256

Abstract: Techniques herein use in-memory column vectors to process data that is external to a database management system (DBMS) and logically join the external data with data that is native to the DBMS. In an embodiment, a computer maintains a data dictionary for native data that is durably stored in an DBMS and external data that is not durably stored in the DBMS. From a client through a connection to the DBMS, the computer receives a query. The computer loads the external data into an in-memory column vector that resides in random access memory of the DBMS. Based on the query and the data dictionary, the DBMS executes a data join of the in-memory column vector with the native data. To the client through said connection, the computer returns results of the query based on the data join.

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：US11520743B2

公开(公告)日：2022-12-06

申请号：US14079507

申请日：2013-11-13

Applicant: Oracle International Corporation

Inventor： Vikram Kapoor ,  Amit Ganesh ,  Jesse Kamp ,  Sachin Kulkarni ,  Vineet Marwah ,  Kam Shergill ,  Roger Macnicol ,  Manosiz Bhattacharyya

IPC: G06F16/174 ,  G06F16/2455 ,  G06F16/901

Abstract: A database server stores compressed units in data blocks of a database. A table (or data from a plurality of rows thereof) is first compressed into a “compression unit” using any of a wide variety of compression techniques. The compression unit is then stored in one or more data block rows across one or more data blocks. As a result, a single data block row may comprise compressed data for a plurality of table rows, as encoded within the compression unit. Storage of compression units in data blocks maintains compatibility with existing data block-based databases, thus allowing the use of compression units in preexisting databases without modification to the underlying format of the database. The compression units may, for example, co-exist with uncompressed tables. Various techniques allow a database server to optimize access to data in the compression unit, so that the compression is virtually transparent to the user.

公开(公告)号：US20200042489A1

公开(公告)日：2020-02-06

申请号：US16055978

申请日：2018-08-06

Applicant: Oracle International Corporation

Inventor： Tirthankar Lahiri ,  Juan R. Loaiza ,  Garret F. Swart ,  Jesse Kamp ,  Avneesh Pant ,  Hideaki Kimura

IPC: G06F15/167 ,  G06F15/173 ,  G06F9/54 ,  G06F9/455

Abstract: Techniques are provided to allow more sophisticated operations to be performed remotely by machines that are not fully functional. Operations that can be performed reliably by a machine that has experienced a hardware and/or software error are referred to herein as Remote Direct Memory Operations or “RDMOs”. Unlike RDMAs, which typically involve trivially simple operations such as the retrieval of a single value from the memory of a remote machine, RDMOs may be arbitrarily complex. The techniques described herein can help applications run without interruption when there are software faults or glitches on a remote system with which they interact.

公开(公告)号：US10346315B2

公开(公告)日：2019-07-09

申请号：US15606327

申请日：2017-05-26

Applicant: Oracle International Corporation

Inventor： Siddharth Teotia ,  Krishna Kunchithapadam ,  Tirthankar Lahiri ,  Jesse Kamp ,  Michael J. Gleeson ,  Juan R. Loaiza ,  Garret F. Swart ,  Neil J. S. MacNaughton ,  Kam Shergill

IPC: G06F16/22 ,  G06F16/901 ,  G06F12/1018 ,  G06F16/2453

Abstract: A hashing scheme includes a cache-friendly, latchless, non-blocking dynamically resizable hash index with constant-time lookup operations that is also amenable to fast lookups via remote memory access. Specifically, the hashing scheme provides each of the following features: latchless reads, fine grained lightweight locks for writers, non-blocking dynamic resizability, cache-friendly access, constant-time lookup operations, amenable to remote memory access via RDMA protocol through one sided read operations, as well as non-RDMA access.

公开(公告)号：US10296462B2

公开(公告)日：2019-05-21

申请号：US13840811

申请日：2013-03-15

Applicant: Oracle International Corporation

Inventor： Juan Loaiza ,  Amit Ganesh ,  Roger Macnicol ,  Jesse Kamp ,  Allison Holloway ,  Adrian Ng ,  Vineet Marwah

IPC: G06F12/08 ,  G06F12/0875 ,  G06F16/22 ,  G06F16/2455

Abstract: A method for accelerating queries using dynamically generated columnar data in a flash cache is provided. In an embodiment, a method comprises a storage device receiving a first request for data that is stored in the storage device in a base major format in one or more primary storage devices. The storage device comprises a cache. The base major format is any one of: a row-major format, a column-major format and a hybrid-columnar format. Based on first one or more criteria, it is determined whether to rewrite the data into rewritten data in a rewritten major format. In response to determining to rewrite the data into rewritten data in a rewritten major format, the storage device rewrites at least a portion of the data into particular rewritten data in the rewritten major format. The rewritten data is stored in the cache.

公开(公告)号：US10204135B2

公开(公告)日：2019-02-12

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

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.

公开(公告)号：US09342314B2

公开(公告)日：2016-05-17

申请号：US14023265

申请日：2013-09-10

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 ,  G06F9/38 ,  G06F17/30

CPC classification number: G06F9/3887 ,  G06F9/30018 ,  G06F9/30032 ,  G06F9/30036 ,  G06F9/30109 ,  G06F9/30112 ,  G06F9/3836 ,  G06F9/3842 ,  G06F9/3851 ,  G06F9/3867 ,  G06F9/3885 ,  G06F17/30315

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.

Abstract translation: 提出了一种在单指令多数据（“SIMD”）结构中有效处理各种格式的数据的方法和装置。 具体地说，提出了一种在SIMD架构中将位流中的固定宽度位值解包为固定宽度字节流的方法。 介绍了一种解码SIMD架构中字节流中可变长度字节打包值的方法。 提出了一种在SIMD架构中解压缩运行长度编码的压缩位向量的方法。 提出了一种在SIMD架构中将位设置为1的偏移量返回到位向量中的方法。 提出了一种从SIMD架构中相对于基址指定的偏移量从位向量获取位的方法。 提出了一种比较存储在两个SIMD寄存器中的值的方法。

公开(公告)号：US09201944B2

公开(公告)日：2015-12-01

申请号：US13916284

申请日：2013-06-12

Applicant: Oracle International Corporation

Inventor： Lawrence J. Ellison ,  Amit Ganesh ,  Vineet Marwah ,  Jesse Kamp ,  Anindya C. Patthak ,  Shasank K. Chavan ,  Michael J. Gleeson ,  Allison L. Holloway ,  Manosiz Bhattacharyya

IPC: G06F17/30 ,  G06F15/82

CPC classification number: G06F17/30315 ,  G06F9/3887 ,  G06F17/30339 ,  G06F17/30595

Abstract: Techniques are provided for more efficiently using the bandwidth of the I/O path between a CPU and volatile memory during the performance of database operation. Relational data from a relational table is stored in volatile memory as column vectors, where each column vector contains values for a particular column of the table. A binary-comparable format may be used to represent each value within a column vector, regardless of the data type associated with the column. The column vectors may be compressed and/or encoded while in volatile memory, and decompressed/decoded on-the-fly within the CPU. Alternatively, the CPU may be designed to perform operations directly on the compressed and/or encoded column vector data. In addition, techniques are described that enable the CPU to perform vector processing operations on the column vector values.

Abstract translation: 在执行数据库操作期间，提供了技术来更有效地使用CPU和易失性存储器之间的I / O路径的带宽。 来自关系表的关系数据作为列向量存储在易失性存储器中，其中每个列向量包含表的特定列的值。 可以使用二进制可比较的格式来表示列向量中的每个值，而不管与列相关联的数据类型如何。 列向量可以在易失性存储器中被压缩和/或编码，并且在CPU内部实时解压缩/解码。 或者，CPU可以被设计为直接对压缩和/或编码的列向量数据执行操作。 另外，描述使CPU能够对列向量值执行向量处理操作的技术。

公开(公告)号：US20230050727A1

公开(公告)日：2023-02-16

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 ,  G06F16/27 ,  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.