Oracle International Corporation

Jonghyun Lee

Yunrui Li

Chi Cao Minh

Vinay H Srihari

Kumar Rajamani

Mahesh Baburao Girkar

Jaebock Lee

Giridhar Ravipati

Sanket Jain

Amrish Srivastava

William Havinden Bridge, Jr

Jia Shi

Margaret Susairaj

Roger J Hansen

Vsevolod Panteleenko

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

Techniques are provided for managing cached data objects in a mixed workload environment. In an embodiment, a system, log data is stored in one or more buffers. In response to receiving a request to perform a logical write, a first process writes a first portion of the log data to a log file in persistent storage. While the first portion of the log data is being written to the log file, a second process writes a second portion of the log data in the one or more buffers to the log file in persistent storage. In another embodiment, a request to perform a second logical write may be received before the first logical write completes. While the first log data is being written to the log file, one or more processes write second log data for the second logical write to the log file.

Techniques to parallelize CPU and IO work of log writes

A container database stores redo records and logical timestamps for multiple pluggable databases. When it is detected that a first read-write instance of the pluggable database is opened and no other read-write instances of the pluggable database are open, offline range data associated with the pluggable database is updated. When it is detected that a second read-write instance of the pluggable database is closed, and the second read-write instance is the last open read-write instance, the offline range data associated with the pluggable database is updated. The pluggable database is restored to a logical timestamp associated with a restore request based on the offline range data.

Techniques for backup restore and recovery of a pluggable database

A method, system, and computer program product for adaptive high-performance database redo log synchronization. The method commences upon performing a write operation of a redo log entry, the write operation concluding with an indication of completion of the write operation of the redo log entry. Any number of committing processes may be waiting for the indication of completion, and upon indication of completion, then (using a first synchronization mode) the processes or proxy measures the waiting time as experienced by the committing processes (e.g., while waiting for the indication of completion of the write operation of the redo log entry). In some cases a second synchronization mode would introduce less latency than the first synchronization mode, so the system changes to a second synchronization mode. The system can also change mode when a predicted second mode waiting time is smaller than the measured waiting time.

Adaptive high-performance database redo log synchronization

A pluggable database is transported between a source DBMS and a destination DBMS, in a way that minimizes downtime of the pluggable database. While a copy of the pluggable database is being made at the destination DBMS, transactions continue to execute against the pluggable database at the source DBMS and change the pluggable database. Eventually, the transactions terminate or cease executing. Redo records generated for the transactions are applied to the copy of the pluggable database at the source DBMS. Undo records generated for at least some of the transactions may be stored in a separate undo log and transported to the destination DBMS. The transported pluggable database is synchronized at a destination DBMS in a 'pluggable-ready state', where it may be plugged into the destination container DBMS.

Instantaneous unplug of pluggable database from one container database and plug into another container database

Techniques for moving data files without interrupting access are described. A first process moves a database file from a first location to a second location while the database file is accessible to one or more other processes for read or write operations. According to one technique, the first process communicates a move status and a copy range into the database file to one or more database server instances executing the one or more other processes. The one or more other processes then perform input/output (IO) operations on the database file based at least in part on the move status and the copy range communicated by the first process.

Techniques for moving data files without interrupting access

An improved approach is described for implementing transformations of data records in high concurrency environments. Each transformation is performed in parallel at the source when the data record is first generated. According to one approach for data integrity validation, record generators compute an integrity checksum for a newly generated record before copying into a data unit in shared memory. Subsequent generators may aggregate integrity checksums for data records into checksums for data units incrementally. This approach achieves end-to-end protection of data records against corruption using an efficient method of maintaining verifiable data integrity. In another approach, compression and encryption data transformations may be performed by themselves, or in combination with an integrity checksum transformation.

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San Jose, CA, United States of America

Jonghyun Lee