![]() The decoding plugin type determines the encoding used when streaming records to logical replication subscribers. When you configure logical replication, you specify a replication slot name and decoding plugin type of each replication slot. Logical replication in PostgreSQL works by decoding the write-ahead log (WAL) into a stream of records that can be consumed by the subscriber. The goal of the cache is to decrease latency and reduce the CPU overhead of PostgreSQL logical replication. This performance improvement is implemented via a write-through cache specifically designed to improve the latency of logically replicated data to clients. With Aurora PostgreSQL versions 11.17, 12.12, 13.8, and 14.5, a new feature is provided that improves performance for workloads that rely on Aurora PostgreSQL logical replication. An Aurora PostgreSQL cluster can use logical replication to perform a logical export of data to take advantage of managed services like AWS Database Migration Service (AWS DMS), Amazon Kinesis, and others. Logical replication is a publication/subscriber capability that provides fine-grained control of replication for Aurora PostgreSQL clusters. ![]() In this post, we show you how to monitor and tune the write-through cache so your cluster realizes the full benefits of the cache. ![]() By reducing the amount of storage I/O, the default write-through cache realizes an improvement of up to 17x in replication lag with a pgbench workload without a drop in Transactions Per Second (TPS). ![]() When you use the write-through cache, the logical decoder looks in the cache first for data to satisfy queries if the data is found, it is returned directly from the cache. The logical replication write-through cache helps improve performance by reducing the amount of Aurora storage I/O that takes place during logical decoding. Amazon Aurora PostgreSQL-Compatible Edition recently added the logical replication write-through cache. ![]()
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