Oracle International Corporation

Amrish Srivastava

Mahesh Baburao Girkar

Yunrui Li

Juan R Loaiza

Wei-Ming Hu

Jonghyun Lee

Garret Frederick Swart

James William Stamos

J William Lee

Adam Y Lee

Sachin Vijaykumar Sonawane

Carlos Ruiz

Sachin Vijakumar Sonawane

Techniques are described herein for an integrated in-front database cache ('IIDC') providing an in-memory, consistent, and automatically managed cache for primary database data. An IIDC comprises a database server instance that (a) caches data blocks from a source database managed by a second database server instance, and (b) performs recovery on the cached data using redo records for the database data. The IIDC instance implements relational algebra and is configured to run any complexity of query over the cached database data. Any cache miss results in the IIDC instance fetching the needed block(s) from a second database server instance managing the source database that provides the IIDC instance with the latest version of the requested data block(s) that is available to the second instance. Because redo records are used to continuously update the data blocks in an IIDC cache, the IIDC guarantees consistency of query results.

Diskless active data guard as cache

Herein are high throughput techniques for incorporating cryptographic blockchains into relational data. In an embodiment, a computer indicates, in a database dictionary in a database, that a relational table is for blockchain storage. The relational table contains application column(s). In response to that indication, the relational table is associated with system column(s) that are unmodifiable by administrators and clients of the database. The system column(s) include a cryptographic hash column. A request to store a particular value in a particular application column is received from a client. In response to receiving the request, a cryptographic hash value is calculated for a new row for the relational table. In the relational table, the computer stores the new row that contains: the particular value in the particular application column, and the cryptographic hash value in the cryptographic hash column.

Supporting blockchain collections in a database

A method, apparatus, and system for a time-based checkpoint target is provided for standby databases. Change records received from a primary database are applied for a standby database, creating dirty buffer queues. As the change records are applied, a mapping is maintained, which maps timestamps to logical times of change records that were most recently applied at the timestamp for the standby database. On a periodic dirty buffer queue processing interval, the mapping is used to determine a target logical time that is mapped to a target timestamp that is prior to a present timestamp by at least a checkpoint delay. The dirty buffer queues are then processed up to the target logical time, creating an incremental checkpoint. On a periodic header update interval, file headers reflecting a consistent logical time for the checkpoint are also updated. The intervals and the checkpoint delay are adjustable by user or application.

Time-based checkpoint target for database media recovery

A method, apparatus, and system for multi-instance redo apply is provided for standby databases. A multi-instance primary database generates a plurality of redo records, which are received and applied by a physical standby running a multi-instance standby database. Each standby instance runs a set of processes that utilize non-blocking, single-task threads for high parallelism. At each standby instance for the multi-instance redo, the plurality of redo records are merged into a stream from one or more redo strands in logical time order, distributed to standby instances according to determined apply slave processes using an intelligent workload distribution function, remerged after receiving updates from remote instances, and applied in logical time order by the apply slave processes. Redo apply progress is tracked at each instance locally and also globally, allowing a consistent query logical time to be maintained and published to service database read query requests concurrently with the redo apply.

Multi-instance redo apply

A method, apparatus, and system for multi-instance redo apply is provided for standby databases. A multi-instance primary database generates a plurality of redo records, which are received and applied by a physical standby running a multi-instance standby database. Each standby instance runs a set of processes that utilize non-blocking, single-task threads for high parallelism. At each standby instance for the multi-instance redo, the plurality of redo records are merged into a stream from one or more redo strands in logical time order, distributed to standby instances according to determined apply slave processes using an intelligent workload distribution function, reemerged after receiving updates from remote instances, and applied in logical time order by the apply slave processes. Redo apply progress is tracked at each instance locally and also globally, allowing a consistent query logical time to be maintained and published to service database read query requests concurrently with the redo apply.

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San Ramon, CA, United States of America

Amrish Srivastava