Make Your PostgreSQL 10x Faster on Cloud in Minutes

Cloud storage has some unique characteristics compared to traditional storage mainly because it is virtualized and controlled by software. One example is that AWS EBS shows higher throughput with larger I/O size up to 256 KiB without hurting latency. Hence, a user can get only about 4 MiB/sec with 1,000 IOPS EBS volume if the I/O request size is 4 KiB, whereas a user can get about 250 MiB/sec if the I/O request size is 256 KiB. This is because EBS consumes one I/O in a given IOPS budget for every I/O request regardless of the I/O size (up to 256 KiB). Unfortunately, PostgreSQL cannot exploit the full potential of cloud storage because PostgreSQL has designed without considering the unique characteristics of cloud storage.

In this talk, I will introduce the AppOS extension that improves the throughput of a write-intensive workload by 10x by transparently making PostgreSQL cloud storage-native. AppOS works like a storage driver that efficiently exploits the characteristics of cloud storage, such as I/O size dependency to storage throughput and latency, atomic write support in cloud block storage, and fast, but non-durable local SSDs. To do this, AppOS comprises a Linux-compatible file I/O stack including virtual file system, page cache, block I/O layer, cloud storage driver. On top of the file I/O stack, syscall module supports registering pre- and post-handler for file I/O-related system calls in order to transparently work without modifying PostgreSQL codes.

I will focus on presenting key use cases and performance results of the AppOS extension after explaining the internals. Specifically, I will show the performance results of OLTP and some batch workloads using standard benchmarking tools like pgbench and sysbench. I will also present performance results and implications on multiple clouds including AWS, GCP, and Azure.

Extending PostgreSQL in C: A Tutorial

PostgreSQL is one of the most readily extensible databases in the world. Custom data types, aggregations, functions, and more can be easily and safely written in C.

This hands-on tutorial covers the basics of writing functions, data types, and aggregates in C. It is recommended (though not strictly required) that bring their own laptops and be prepared to actually try the exercises.

Topics covered include: 1. The PostgreSQL type system 2. Creating a simple custom type in C 3. Common errors for non-C programmers 4. Creating a simple aggregate in C

There will be many opportunities for questions and discussion through the tutorial.

MobilityDB: Managing Mobility Data in PostgreSQL

MobilityDB is an open source moving object database system (https://github.com/ULB-CoDE-WIT/MobilityDB). Its core function is to efficiently store and query mobility tracks, such as vehicle GPS trajectories. It implements the Moving Features specification from the Open Geospatial Consortium (OGC). MobiltyDB is engineered up from PostgreSQL and PostGIS, providing spatiotemporal data management via SQL. It thus integrates with the postgreSQL eco-system allowing for complex architectures such as mobility stream processing and cloud deployments.

The presentation will explain the architecture of MobilityDB, its database types, indexes, and operations. We will highlight the PostgreSQL features that enable this extension, and the would like to have features. This presentation will be of special interest to the PostgreSQL community, and to professionals in the transportation domain.

Простой инструмент исторического анализа производительности - pg_profile

В поиске проблем производительности администраторам баз данных необходим инструмент исторического анализа нагрузки. Особенно важен подобный инструмент в случаях, когда было зафиксировано время нехарактерного снижения производительности системы, и вам надо выяснить что больше всего нагружало вашу СУБД в это время. Это и поиск ресурсозатратных запросов, и поиск активных и растущих объектов в схеме данных, статистики использования пользовательских функций и использования temp. Существует несколько инструментов, так или иначе решающих эту задачу. Я расскажу об одном таком инструменте, который легко устанавливается в виде расширения к СУБД Postgres, легко настриавается и позволяет получить отчет о нагрузке за некоторый период в прошлом, который будет неплохой начальной точкой дальнейшего расследования.