Master-Slave Replication
Master-Slave Replication is a technique used in data science and artificial intelligence to replicate data from a master database to one or more slave databases. In this technique, the master database is the primary database that receives all the write operations, while the slave databases are read-only copies of the master database. The replication process is asynchronous, meaning that changes made to the master database are not immediately reflected in the slave databases. Instead, changes are propagated periodically or in real-time, depending on the configuration. Master-Slave Replication is commonly used to improve the performance and availability of databases, as it allows read operations to be distributed across multiple databases, reducing the load on the master database. Additionally, it provides a backup mechanism in case the master database fails, as one of the slave databases can be promoted to become the new master.
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