PGConf.Russia 2018

DBeaver is the Universal Databases Manager. We creating DBeaver using Open Source Software model. We pay special attention to the PotgreSQL because of its capabilities, popularity and OSS nature. We will talk about DBeaver evolution and structure, will demonstrate the basic functionality. We are going to cover challenges of PostgreSQL client creation. Also we will discuss requirements management model and interaction with the PostgreSQL community. We will show in details how to debug the PL/pgSQL stored procedures interactively. We are going to introduce some new features of the nearest DBeaver release and to share our plans.

«KNOPKA» («The button»), the largest outsourcing of accounting, will tell you about your experience of transferring 500Gb of 1C Fresh databases to PostgreSQL. The report touches on the choice of DBMS and the fight against stereotypes, where we started and how developed the use of PostgreSQL, the approaches to backup and recovery of information security, our current performance of DBMS and 1C, a look into the future. Let us share why we believe that 1C + PostgreSQL is simple, reliable and fast.

Jsonb is a popular data type in PostgreSQL, it provides the web developers an ability to work with ubiquitous json inside the database and use all the power of proven relational database. Fast querying of jsonb data is a challenge for database and PostgreSQL provides several options for indexing jsonb. We present the new way of efficient indexing of jsonb, based on improvement of indexing infrastructure.

It's known, that json is a greedy data type, it may contains many auxiliary data not interesting for searching and that affects the size of index. Partial index will not helps, since it filters the rows before indexing, while we are interested in extracting of parts of jsonb. Functional indexes on specific keys could introduce too big overhead. We present an improvement of indexing infrastructure, which allows to control the index behaviour by passing parameters to operator class at index creation. For example, to index a user-defined subset of jsonb it is possible to pass to operator class the powerful path expression (either jsonpath of upcoming sql/json or jspath from jsquery extension), which can be used to extract the parts of jsonb tree. That makes index more effective and reduces the overhead of its maintaining.

Another use of parameterized operator classes is to allow a user to specify parameters instead of hard coding them, for example, the GiST signature size is currently hard coded inside the implementations of several opclasses (tsvector, hstore, intarray, pg_trgm, ltree), while it is natural to use different signature length for different data to have optimal size of index and its performance.

Full text search on parts of document can be improved by passing labels to the operator class and letting him index only specified parts of document, that allow to avoid currently used recheck of the rows returned by the index.

Last year we announced Skala-SR / Postgres Pro database machine with a hardware and software support for remote direct memory access (RDMA) as a key feature. The first appliances have been already installed at customer sites, and even with the first version customers got some constructions, that were impossible without RDMA and CPU offload (got with Mellanox networking). However, capabilities of this equipment are much wider, and this talk is dedicated to current works and prospective developments for this topic.