Author: Nickolay Ihalainen

Parallel queries in PostgreSQL

parallel queries in postgresqlModern CPU models have a huge number of cores. For many years, applications have been sending queries in parallel to databases. Where there are reporting queries that deal with many table rows, the ability for a query to use multiple CPUs helps us with a faster execution. Parallel queries in PostgreSQL allow us to utilize […]

PostgreSQL Streaming Physical Replication With Slots

postgres replication using slotsPostgreSQL streaming physical replication with slots simplifies setup and maintenance procedures. Usually, you should estimate disk usage for the Write Ahead Log (WAL) and provide appropriate limitation to the number of segments and setup of the WAL archive procedure. In this article, you will see how to use replication with slots and understand what problems it […]

PostgreSQL locking, part 3: lightweight locks

LWLocks lightweight locks postgresPostgreSQL lightweight locks, or LWLocks, control memory access. PostgreSQL uses multi-process architecture and should allow only consistent reads and writes to shared memory structures. LWLocks have two levels of locking: shared and exclusive. It’s also possible to release all acquired LWLocks to simplify clean up. Other databases often call primitives similar to LWLocks “latches”. Because […]

PostgreSQL locking, part 2: heavyweight locks

Locking in PostgreSQLPostgreSQL locking visibility for application developers and DBAs is in most cases related to heavyweight locks. Complex database locking operations require full instrumentation using views from the system catalog. It should be clear which object is locked by a specific database “backend” process. An alternative name for any lock is “bottleneck”. In order to make […]

PostgreSQL locking, Part 1: Row Locks

PostgreSQL row level locksAn understanding of PostgreSQL locking is important to build scalable applications and avoid downtime. Modern computers and servers have many CPU cores and it’s possible to execute multiple queries in parallel. Databases containing many consistent structures with changes made by queries or background processes running in parallel could crash a database or even corrupt data. […]

Keep Sensitive Data Secure in a Replication Setup

Keep sensitive data secure

This blog post describes how to keep sensitive data secure on slave servers in a MySQL async replication setup. Almost every web application has a sensitive data: passwords, SNN, credit cards, emails, etc. Splitting the database to secure and “public” parts allows for restricting user and application parts access to sensitive data. Field encryption This is […]

The post Keep Sensitive Data Secure in a Replication Setup appeared first on Percona Database Performance Blog.

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