Oracle International Corporation

Semen Ustimenko

Kothanda Umamageswaran

Krishnan Meiyyappan

Adrian Tsz Him Ng

Wei Zhang

Yunrui Li

Jia Shi

Alex Tsukerman

Dmitry Mikhailovich Potapov

Alexander Tsukerman

Zuoyu Tao

Vijay Sridharan

Nilesh Choudhury

Umesh Panchaksharaiah

Allen Brumm

Adrian Ng

James Stenoish

Daniel McClary

Robert K Abbott

Salini Selvaraj Kowsalya

Somayeh Sardashti

Yiliang Jin

Devang Mundhra

Yinian Qi

Kai Zhang

Zheren Zhang

Graham Ivey

Region summaries of database data are stored in persistent memory of a storage cell. Because the region summaries are stored in persistent memory, when a storage cell is powered off and data in volatile memory is not retained, region summaries are nevertheless preserved in persistent memory. When the storage cell comes online, the region summaries already exist and may be used without the delay attendant to regenerating the region summaries stored in volatile memory.

Storing derived summaries on persistent memory of a storage device

A storage system communicatively coupled to a database management system (DBMS performs storage-side scanning of data sources that are not stored in native database storage format of the DBMS. Data sources for external tables are accessible in a storage system referred to as a distributed data access system (DDAS), e.g. a Hadoop Distributed File System. To execute a query that references an external table, a DBMS first generates an execution plan. The DDAS supplies the DBMS with information that specifies each portion of the data source, and specifies which data node to use to access the portion. The DBMS sends a request for each portion to the respective data node, requesting that the data node generate rows from data in the portion. The request may specify scanning criteria, specifying one or more columns to project and/or filter on, and code modules for the data node to execute to generate records.

Storage-side scanning on non-natively formatted data

A shared storage architecture persistently stores database files in non-volatile random access memories (NVRAMs) of computing nodes of a multi-node DBMS. The computing nodes of the multi-node DBMS not only collectively store database data on NVRAMs of the computing nodes, but also host database server instances that process queries in parallel, host database sessions and database processes, and together manage access to a database stored on the NVRAMs of the computing nodes. To perform a data block read operation from persistent storage, a data block may be transferred directly over a network between NVRAM of a computing node that persistently stores the data block to a database buffer in non-volatile RAM of another computing node that requests the data block. The transfer is accomplished using remote direct memory access ('RDMA).

Database with NVDIMM as persistent storage

Techniques are described herein for supporting multiple versions of a database server within a database machine comprising a separate database layer and storage layer. In an embodiment, the database layer includes compute nodes each hosting one or more instances of a database server. The storage layer includes storage nodes each hosting one or more instances of a storage server, also referred to herein as a 'cell server.' In general, the database servers may receive data requests, such as SQL queries, from client applications and service the requests in coordination with the cell servers of the storage layer.

Systems and methods for supporting multiple database server versions on a database machine

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Sunnyvale, CA, United States of America

Semen Ustimenko