PgConf.Russia 2017

ZSON is a PostgreSQL extension for transparent JSONB compression. Compression is based on a shared dictionary of strings most frequently used in specific JSONB documents (not only keys, but also values, array elements, etc). In some cases ZSON can save half of your disk space and give you about 10% more TPS.

VIDEO

Nowadays one can make a decent urban research based simply on public datasets, making interesting and unexpected insights. In the presentation, I'll show examples of these calculations in PostGIS, the industry standard de-facto.

But just PostGIS is not enough. You need tools to import, verify and visualize the data. It's critically important to visualize the data live, to debug your calculations and shorten iterations. I'll describe all these steps:

1. Collecting the data: public API, OpenStreetMap; direct user input.
2. 3rd party APIs for calculations.
3. Visualization of GIS and other sorts of data: QGIS, Matplotlib, Zeppelin integrated with PostGIS.
4. Debugging the calculations: live visualization (Arc, QGIS, NextGIS Web)
5. Scripting and minimizing the chores: Makefile, Gulp

Overview of the architecture of Greenplum MPP (Massively Parallel Processing) database. Explain the internals of GPDB. Show how to configure and setup GPDB. How to distribute data effectively for MPP

VIDEO

Sets are apparently a useful data type for many kinds of applications. While PostgreSQL offers no built-in set data type, sets may be emulated to some degree with its built-in array and JSONB data types. Also, acceleration of respective containment (subset) queries is readily available as a built-in feature of the GIN index type.

Starting with the above, we will then explore the performance gains enabled by custom set data types, and especially by customisation code in C ("operator classes") for the GIN and GiST index types.