История Postgres
The PostgreSQL community is over 20 years old, but the history of PostgreSQL dates back even farther. In this talk, we'll learn about the roots of the Postgres project, learn about some of the people who contribute to it, study how it has changed over time, and pay special attention to the many contributions of Russian people.
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Видео
Другие доклады
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Ivan Frolkov Postgres Professional
Отчуждаемые таблицы в PostgresPro
With big data threads, even the upload of data to a database can often be problematic – apart from the data upload itself, you need to create indexes, perform VACUUM after the upload for correct Index-only scans, etc. From this talk, you will learn how to avoid most of such problems (if not all of them).
VIDEO
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Vadim Yatsenko ООО Прогресс Софт
Очень большие таблицы в PostgreSQL. Или как превратить 60+ Tb в 10+ Tb
The talk will describe how we have implemented storage of large tables (+1 billion rows per day). The project exists in production 2 years. The total amount of data - 300 Tb (25 PostgreSQL servers * 2 Data Center). I'll tell about mistakes in organization of large tables storage in the initial phase of the project, and how these mistakes were corrected. I'll also talk about how to organize the data rotation and archiving. I voiced questions about what we were missing in PostgreSQL 9.4 out of what appeared in the 9.5 and 9.6. And also, what new features we are waiting for new releases of PostgreSQL.
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Radoslav Glinsky Skype (Microsoft)
Тестовая среда по требованию
Do you test your PostgreSQL releases prior to Production in a dedicated test environment? Are you sure that your test environment (shortly Test) is equal to Production and in an appropriate state?
In Skype we were facing multiple challenges associated with database testing:
- Simplifying complex Production architecture of thousands of PostgreSQL instances, interconnected with RPCs and replications, infrastructure servers and external DB scripts, into their Test counterparts.
- Constantly growing hardware requirements, insufficient cleanup of data generated in Test.
- Differences between Test and Production were appearing and accumulating. Recognizing and fixing them required lots of effort.