PgConf.Russia 2017

Citus allows you to distribute postgres tables across many servers. It extends postgres to transparently delegate or parallelise work across a set of worker nodes, enabling you to scale out the CPU and memory available for queries.

One year ago, we began a long journey to allow Citus to scale out another dimension: write throughput. With writes being routed through a single postgres node, write throughput in Citus was ultimately bottlenecked on the CPUs of a single node. Citus MX is a new edition of Citus which allows distributed tables to be used from from any of the nodes, enabling NoSQL-like write-scalability.

Streaming replication has been introduced in 2010 and quickly became one of the most popular features of PostgreSQL. Today, it is hard to imagine PostgreSQL installation without streaming replication. With its stability, high efficiency and ease of configuration one would have thought it is an optimal feature. However, while using it you might sometimes enter murky waters. This often can be resolved by using a combination of built-in and third party troubleshooting tools. In my talk I will provide an overview of these tools and explain how with their help one can diagnose, understand and eliminate problems related to streaming replication. I will also go through the most frequent issues occurring when streaming replication is used and will propose possible solutions. This talk is primarily aimed at DBAs and system administrators who use PostgreSQL in their day-to-day.

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1. 1C:Enterprise 8 and PostgreSQL 9 interoperability 1.1 Changes in new 1C platform versions 1.2 v81c_data and v81c_index schemas 1.3 Sending 1C queries to SQL 1.4 Using 1C technological log events for PostgreSQL diagnostics
2. Analyzing queries that affect PostgreSQL performance 2.1 A free tool for automating log parsing 2.2 Pareto principle in action 2.3 Installation and configuration of the tool 2.4 A case study of query optimization 2.4.1 An issue in a PostgreSQL query 2.4.2 Finding non-optimal operations in a query 2.4.3 Resolving inefficiencies
3. PostgreSQL statistics for performance diagnostics 3.1 Comparing Postgres with MS SQL Server 3.2 Troubleshooting locks 3.3 Operating load diagnostics 4 Case studies by the gilev.ru team

This talk is about migrating an electronic document management system from MS SQL to PostgreSQL 9.5 or higher as part of the import phaseout initiative. We will touch upon architecture specifics, as well as describe the problems we encountered when migrating T-SQL code to pgsql, and how we resolved them.

Learn more at https://pgconf.ru/news/94168

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