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Stephan Kottler

Martin Heidel

Peter Steinemann

Vivek Kandiyanallur

Colin Florendo

Thorsten Glebe

Michael Muehle

Rolando Blanco

Kai Stammerjohann

Chaitanya Gottipati

Christoph Roterring

Carsten Thiel

Shiping Chen

Joern Schmidt

Nico Bohnsack

Sarika Iyer

Xin Liu

Johannes Haeussler

Jörn Schmidt

A method, a system, and a computer program product for performing testing of continuous log replays in a database system. A redo log generated for a data record in a database is received. The redo log is indicative of a change in persistency of the data record in the database. Based on the change in persistency recorded in the redo log, a redo handler in the plurality of handlers is selected for execution of a replay of the received redo log. Using the selected redo log, replay of the redo log is executed to generate a state of the data record prior to the change in persistency recoded in the redo log.

Test continuous log replay

Disclosed herein are system, method, and computer program product embodiments for a database recovery and optimization with batch processing system. An embodiment operates by retrieving a database log that includes a plurality of operations for modifying data of a database stored across a plurality of tables. From the database log, a plurality of consecutive insert operations for inserting data into the database are identified. The consecutive insert operations are sorted by table. The sorted insert operations are grouped into a batch message. The batch message is transmit to the database for replay. An acknowledgement is received that the replay has completed.

Database recovery and optimization with batch processing

Objects across multiple database manipulation language (DML) redo log records are cached, during continuous replay of redo log records on a secondary system, for the same table partition to enable reuse of such cached objects. Later, these cached objects can be reused as they are accessed during the sequential processing of DML redo records for a specific table partition.

Caching DML statement context during asynchronous database system replication

A new dictionary can be created for a result column in a query plan operation executed on a database. The result column can be generated by multiple worker jobs running in parallel to read tasks from a shared queue as part of a query plan operation that includes a group-by column within an input set of input columns. The group-by column can include an original dictionary for all values contained within the group-by column If the new dictionary has fewer entries than the original dictionary for the group-by column such that mapping is required between old value identifiers within the group-by column and new value identifiers within the result column, the old value identifiers are renamed to the new value identifiers using a mapping vector.

Lock-free generation of columns with minimal dictionaries after parallel aggregation

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Gaggenau, Germany

Stephan Kottler