PGConf.Russia 2018

The report reviews approaches and implementattion options for the migration of Parus-Budget 8 client-server application from the Oracle Database platform to the PostgreSQL platform without changing the client application for Desktop and the Web. The proposed solution allows to make transparent transition of the existing users' workplaces.

Pluggable storages is hot subject in PostgreSQL development. The period of heated debates about whether we need them is over. Skepticism about pluggable storages, based on concern that they may be source of inconsistent behavior, was weakened after criticism of PostgreSQL MVCC implementation from Uber side. It became widely understandable that pluggable storages are needed at least for an alternative MVCC implementation. And that is one of way-points for pluggable storages interface design.

At the moment, work on pluggable storages is in the practical stage. There is a thread is pgsql-hackers where few people are developing patchset and several people are doing review.

This talk will cover following subjects:

• overview of pluggable storages interface;
• changes in PostgreSQL core required to implement this interface;
• current and potential implementations of pluggable storages including heap with undo-log and in-memory OLTP engine;
• current state of patchset and prospective of its commit
• further development of interface allowing more possibilities in pluggable storages (columnar, index-organized, LSM and so on).

PostgreSQL looks very competitive with other mainstream databases on OLTP workload (execution of large number of simple queries). But on OLAP queries, requiring processing of larger volumes of data, DBMS-es oriented on analytic queries processing can provide an order of magnitude better speed. The following factors limit Postgres OLAP performance:

• Unpacking tuple overhead (tuple_deform)
• Interpretation overhead (Postgres executor has to interpret query execution plan)
• Abstraction penalty (support of abstract data types)
• Pull model overhead (operators are pulling tuples from heap page one-by-one, resulting numerous repeated accesses to the page)
• MVCC overhead (extra per-tuple storage + visibility check cost)

All this issues can be solved using vectorized executor, which proceed bulk of values at once. In this presentation I will show how vector operations can be implemented in Postgres as standard Postgres extension, not affecting Postgres core. The approach is based on introducing special types: tile types, which can be used instead of normal (scalar) types and implement vector operations. Postgres extension mechanism, such as UDT (user-defined type), FDW (foreign data wrappers), executor hooks are used to let users work with vectorized tables almost in the same way as with normal tables. But more than 10 times faster because of vector operations.

WAL-G is simple and effective disaster recovery tool for PostgreSQL using cloud storages. In its core functionality, WAL-G is the successor of WAL-E rewritten in Go. But there is one new neat feature - delate-backups. WAL-G delta-backups, whenever possible, stores only pages, changed since the previous backup. In this talk, I'm going to describe development process of this feature.

Surprisingly, most important and complicated question was the design of the interface: WAL-e is simple and comprehensive, keeping these properties was goal #1. Technical details of implementation were covering some underwater stones too. Besides these, I want to discuss the perspective of technological development and future coordination of recovery tools developers.