PGConf.Russia 2018

In this talk I will share the experience of migration, NoSQL data to a relational view convert, and tell you how we managed to speed up the application in 2 times.

Initially, we used PosgtgreSQL and MongoDB to store all the data. In practice, we found out that the separation is extremely inconvenient. We spent a lot of time and attention on it.

My talk will describe how we moved the data from MongoDB to PostgreSQL using mosql. As a result, all the data can be received by one query now, and the table schema ensures data consistency.

• Spatial and advanced spatial analysis with pure PostGIS (including cutting edge PostGIS functions available)
• How could we mix and tied efficiently PostgreSQL and Python data types (as NumPy ndarray, and Pandas DataFrames)
• Tools to improve our data manipulation environment (Jupyter tricks, easy dataviz...)
• How to go further throught GeoDataScience, with Python libs and framework tied with PostgreSQL/PostGIS (including Machine and DeepLearning)

In the pitch I will talk about the most important nuances of deployment and operations of the distributed analytical open-source database based on PostgreSQL - Greenplum. I will analyze the typical mistakes in its use, give the best practices and warn about bottlenecks.

What is a real cost of not paying for Windows for 1C-user? Is there life without COM? Addressing and other issues for the bunch of PostgreSQL. Scheduling disk resources. How to overcome OS CentOS crash.