PgConf.Russia 2016

Multicorn is a generic Foreign Data Wrapper which goal is to simplify development of FDWs by writing them in Python.

We will see:

• what is an FDW what Multicorn is trying to solve how to use it, with a brief tour of the FDWs shipping with Multicorn.
• how to write your own FDW in python, including the new 9.5 IMPORT FOREIGN SCHEMA api.
• the internals: what Multicorn is doing for you behind the scenes, and what it doesn't

After a presentation of FDWs in general, and what the Multicorn extension really is, we will take a look at some of the FDWs bundled with Multicorn.

Then, a complete tour of the Multicorn API will teach you how to write a FDW in python, including the following features:

• using the table definition
• WHERE clauses push-down
• output columns restrictions
• influencing the planner
• writing to a foreign table
• IMPORT FOREIGN SCHEMA
• ORDER BY clauses pushdown
• transaction management

This will be a hands-on explanation, with code snippets allowing you to build your own FDW in python from scratch.

Enterprises need enterprise-level databases. The existing Postgres clustering solutions are not supported by the community. Postgres needs a community-supported cluster solution. There have been multiple attempts like Postgres-XC/XL, but they are still being developed separately and have low chance to be accepted by the community. Other solutions, like pg_shard, plproxy, FDW-based, etc. lack the notion of global transactions. We developed a Distributed Transaction Manager (DTM) as a Postgres extension to achieve global consistency over a number of Postgres instances. To demonstrate the capabilities of the DTM we present examples of distributed transaction processing using pg_shard and postgres_fdw. We hope that the proposed approach will be included into Postgres 9.6. This will make the development of the clustering solutions easier for all interested parties.