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Features for use with replicationFor applications that employ replication, you can improve performance by using parallel replication, which uses multiple threads acting in parallel to replicate and apply transactional changes to nodes in a replication scheme. TimesTen supports the following types of parallel replication:Automatic parallel replication (ReplicationApplyOrdering=0): Parallel replication over multiple threads that automatically enforces transactional dependencies and all changes applied in commit order. This is the default.Automatic parallel replication with disabled commit dependencies (ReplicationApplyOrdering=2): Parallel replication over multiple threads that automatically enforces transactional dependencies, but does not enforce transactions to be committed in the same order on the subscriber database as on the master database. In this mode, you can optionally specify replication tracks.User-defined parallel replication (ReplicationApplyOrdering=1): For applications that use a classic replication scheme, have very predictable transactional dependencies, and do not require that the commit order on the receiver is the same as that on the originating database. You can specify the number of transaction tracks and apply specific transactions to each track. All tracks are read, transmitted and applied in parallel.See "Configuring parallel replication" in Oracle TimesTen In-Memory Database Replication Guide for additional information and usage scenarios.For JDBC applications that use parallel replication and specify replication tracks, you can specify the track number for transactions on a connection through the following TimesTenConnection method. (Alternatively, use the general connection attribute ReplicationTrack or the ALTER SESSION parameter REPLICATION_TRACK.)void setReplicationTrack(int track)TimesTenConnection also has the corresponding getter method:int getReplicationTrack()Refer to Oracle TimesTen In-Memory Database JDBC Extensions Java API Reference for additional information.Note:User-defined parallel replication is generally not advisable, because special care must be taken to avoid data divergence between replication nodes.
Features for use with replication