Oracle International Corporation

Nilesh Choudhury

Juan R Loaiza

Yunrui Li

Kothanda Umamageswaran

Alexander Tsukerman

Jia Shi

Selcuk Aya

Kiran Badrinarain Goyal

Zuoyu Tao

Vijay Sridharan

Umesh Panchaksharaiah

Boris Erlikhman

Bharat C V Baddepudi

Poojan Kumar

Sue-Kyoung Lee

Timothy L Shetler

Susy Fan

Scott Martin

Krishnan Meiyyappan

Dmitry Mikhailovich Potapov

Semen Ustimenko

Yiliang Jin

Zuoyo Tao

Mingmin Chen

Kai Zhang

Johnny Quan Zhou

Mehrnoosh Raoufi

Salini Selvaraj Kowsalya

Thakur Vishwesh Singh

Saeed Abedigozalabad

Somayeh Sardashti

Zheren Zhang

Graham Ivey

The illustrative embodiments provide a consensus protocol with a priority-based leadership election approach. Each server or node in the cluster has an associated priority based on the capabilities and capacities of the servers. The leadership election is divided into two phases: a term increase phase and an election voting phase. A candidate sends a message to peers in the cluster to determine whether all peers agree to allow the candidate to increase the term number. If there is no opposition, then the candidate increases the term number and then proceeds to the election voting phase. Each peer determines whether the candidate requesting the term increase has a log that is up to date. If the log of the candidate is equally as advanced as the peer's log, then the peer approves or opposes the term increase based on a priority comparison.

Leadership election in consensus protocol with heterogeneous nodes

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 provided for using an intermediate cache to provide some of the items involved in a scan operation, while other items involved in the scan operation are provided from primary storage. Techniques are also provided for determining whether to service an I/O request for an item with a copy of the item that resides in the intermediate cache based on factors such as a) an identity of the user for whom the I/O request was submitted, b) an identity of a service that submitted the I/O request, c) an indication of a consumer group to which the I/O request maps, d) whether the I/O request is associated with an offloaded filter provided by the database server to the storage system, or e) whether the intermediate cache is overloaded. Techniques are also provided for determining whether to store items in an intermediate cache in response to the items being retrieved, based on logical characteristics associated with the requests that retrieve the items.

Selectively reading data from cache and primary storage based on whether cache is overloaded

Techniques herein are for creating a database snapshot by creating a sparse database. A method involves receiving a creation request to create a sparse database. The creation request has an identity of a parent database. The creation request is processed to create a sparse database. The sparse database has the identity of the parent database. The sparse database does not contain data copied from the parent database. A write request to write data into the sparse database is received. The write request is processed by writing the data into the sparse database. The parent database does not receive the data.

Database snapshots

Techniques herein are for accessing non-materialized blocks of a sparse file. A method involves a storage system receiving a storage command to access a sparse file. A combined content of a set of materialized blocks and a header that identifies one or more non-materialized blocks is assembled. The combined content does not comprise a content of the one or more non-materialized blocks. Responsive to the assembling, the combined content is transferred between the storage system and a computer system.

Sparse file access

Techniques are provided for using an intermediate cache to provide some of the items involved in a scan operation, while other items involved in the scan operation are provided from primary storage. Techniques are also provided for determining whether to service an I/O request for an item with a copy of the item that resides in the intermediate cache based on factors such as a) an identity of the user for whom the I/O request was submitted, b) an identity of a service that submitted the I/O request, c) an indication of a consumer group to which the I/O request maps, or d) whether the intermediate cache is overloaded. Techniques are also provided for determining whether to store items in an intermediate cache in response to the items being retrieved, based on logical characteristics associated with the requests that retrieve the items.

Selectively reading data from cache and primary storage

In a consumer-producer distributed model of computing, consumers request data from producers and perform computing work on the data received from the producers, thereby transforming the data. At least some of the computing work performed by a consumer on data provided by the producer is commutable between the consumer and producer, that is, either the producer as well as the consumer can perform the computing work on the data. A producer redistributes commutable based on the work load of the producer and consumer as well as other factors.

Redistributing computation work between data producers and data consumers

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Redwood City, CA, United States of America

Nilesh Choudhury