Salesforce Com, Inc.

Salesforce, Inc.

Akshay Manchale Sridhar

James E Mace

Gary J Baker

Patrick James Helland

Matthew Woicik

Techniques are disclosed relating to a database recovery routine to start up a database system in response to a database failure. The database system accesses checkpoint information identifying a set of active database transactions that were active at a flush point that occurred before the database failure. As a part of the database recovery routine, the database system replays database transactions that occurred between a recovery point and the flush point. The database transactions include the set of active database transactions but exclude any committed or aborted database transactions that occurred between the recovery point and the flush point such that less than a total number of database transactions occurring between the recovery point and the flush point are replayed. The database system further replays, without excluding committed or aborted database transactions, database transactions occurring between the flush point and a recovery end point at which the database failure occurred.

Redo avoidance during database recovery

Techniques are disclosed relating to using different process groups to control allocation of execution resources for database connection processes that handle application requests. In disclosed embodiments, a database server receives a request from an application server for database resources, including application information specifying one or more attributes of the request. The server may assign a database connection process to access a database for the request and assign the database connection process to a process group based on the application information. The server may assign execution resources based on resource allocation parameters that are associated with the assigned process group. In disclosed embodiments, tenants that are using inappropriate amounts of resources are identified and requests from the identified tenants may be assigned to process groups whose processes are allocated a smaller amounts of resources per process than other process groups, which may reduce performance degradation in a database system.

Assignment of resources to database connection processes based on application information

Techniques are disclosed relating to efficiently managing skip list data structures. In some embodiments, a computing system stores a skip list including a plurality of key-value records that include one or more pointers to others of the plurality of key-value records. The computing system scans the plurality of key-value records in key order to identify key-value records to be purged from the skip list. The scanning includes maintaining a list of key-value records that include pointers that point to key-value records that have not yet been scanned by the scanning. In response to identifying a key-value record for purging, the computing system purges the key-value record by substituting the pointers included the key-value records of the list with pointers included in the key-value record being purged.

Fast skip list purge

Techniques are disclosed relating to using different process groups to control allocation of execution resources for database connection processes that handle application requests. In disclosed embodiments, a database server receives a request from an application server for one or more database resources, including application information specifying one or more attributes of the request. The database server may assign a database connection process to access a database for the request and assign the database connection process to a process group based on the application information. The database server may assign execution resources based on resource allocation parameters that are associated with the assigned process group. In disclosed embodiments, tenants that are using inappropriate amounts of resources may be identified and requests from the identified tenants may be assigned to process groups whose processes are allowed to use smaller amounts of resources per process than other process groups, which may reduce performance degradation in a database system.

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San Francisco, CA, United States of America

Akshay Manchale Sridhar