Abstract: Methods and apparatus are described for collecting and storing large volumes of time series data. For example, such data may comprise metrics gathered from one or more large-scale computing clusters over time. Data are gathered from resources which define aspects of interest in the clusters, such as nodes serving web traffic. The time series data are aggregated into sampling intervals, which measure data points from a resource at successive periods of time. These data points are organized in a database according to the resource and sampling interval. Profiles may also be used to further organize data by the types of metrics gathered. Data are kept in the database during a retention period, after which they may be purged. Each sampling interval may define a different retention period, allowing operating records to stretch far back in time while respecting storage constraints.

Abstract: An improved method and system for preserving data constraints during parallel apply in asynchronous transaction replication in a database system have been disclosed. The method and system preserves secondary unique constraints and referential integrity constraints, while also allowing a high degree of parallelism in the application of asynchronous replication transactions. The method and system also detects and resolves ordering problems introduced by referential integrity cascade deletes, and allows the parallel initial loading of parent and child tables of a referential integrity constraint.

Abstract: A method and system for asynchronously replicating data changes in a database system captures update information for a data update in a source table from a database log, where the data value from the data update is not in the database log. A query is built to obtain the data value from the source table using the update information, including a key column value that identifies the row of the source table in which the data resides. When the key column is also updated in the same or different transaction, the data update information is stored, and the updated key column value is replaced with a later captured key column update value. The query is built and executed, and the data update is replicated at a target table. In this manner, data objects whose values are not recorded in a database log can be asynchronously replicated in a database system.

Abstract: A method and system for member initialization to and deactivation from an asynchronous data replication group in a database system is disclosed. The method and system allows new members to be added to the replication group or existing members to be removed from the replication group, without requiring the halting of the asynchronous replication of data. The performance advantages of asynchronous replication are still realized during member initialization or deactivation.

Abstract: An automatic initial data load to a new table copy concurrently with active replication to existing table copies in an asynchronous replication group includes: initiating a data load of the new table copy; creating spill queue(s) at the new table copy; loading the data from a source table copy to the new table copy, where changes for the active table copies are applied during the loading, but changes to the new table copy are stored in a spill storage area; applying the changes in the spill storage area to the new table copy after the loading of the data is done; and removing the spill storage area after the changes have been applied to the new table copy. Thus, a new table copy is initialized into the replication group without requiring that replication be suspended at the source or any of the existing table copies during the initializing process.