PGConf.Russia 2018

This report is about my PostgreSQL extension pg_profile. This extension all you need to create periodic statistics snapshots and to keep them. You can build a report on one or many serial snapshots. This report will contain statistics information about database workload in specified time period. It is very useful to start investigation on performance degragation or excessive resoure consumption in the past.

Bringing the provability and immutability of blockchain to performance and efficiency of traditional DBMS.

Blockchain technology has several unique properties including provability and immutability. Every blockchain transaction is signed by its author, and it could be verified by any blockchain network member. Also, once data is stored in blockchain, it can't be altered in the future. Many databases operating traditional DBMS would also benefit from provability and immutability properties. However, inclusion of all the transaction data in the public blockchain is very expensive.

Credereum is the platform, which allows creation and maintaining of databases, whose contents and history are provable and immutable without sacrifice the performance and efficiency of traditional DBMS. Thanks to Credereum, database owner can prove the validity of query results, while users can verify them. Database owner don't have to reveal the whole database contents or full history of transactions to provide the proof of database query results. Therefore, Credereum database may contain private sensitive information. Credereum utilized bleeding-edge technologies including, but not limited to decentralized cloud, public blockchain with sharding. Credereum is an emerging technology of trusted and private databases.

We will explain why PostgreSQL is suitable database for Credereum and what we need to develop in Postgres to support signed transactions and cryptographic storage.

I would like to share experience in runing PostgreSQL in dockerized environments, describe the specific issues and tools you will need to solve them.

• Which problems could be solved by Docker for PostgreSQL, e.g. PostgreSQLPro.9.6
• Work of IT team with Docker in development, testing and production environments
  • Using image repository and build servers for image testing
• Issues in production environment:
  • With network activity
  • With persistent repositories for Docker
  • With additional services
  • With load balancing and fail-safety
• Running PostgreSQL-base applications, such as:
  • SonarQube
  • Gitlab
  • 1С platform

Developers are often challenged to deliver results that are hard to implement using simple SQL queries. Fortunately, complex SQL capabilities exist in the SQL standards — common table expressions and window functions.

SQL is a declarative language, meaning the user submits an SQL command and the database determines the optimal execution. Common Table Expressions (CTEs) allow queries to be more imperative, allowing looping and processing hierarchical structures that are normally associated only with imperative languages.

Normal SQL queries return rows where each row is independent of the other returned rows. SQL window functions allow queries to return computed columns based on values in other rows in the result set.

This tutorial will help developers use CTE queries in their applications and allow operations that normally could only be done in application code to be done via SQL queries. It also explains the many window function facilities and how they can be used to produce useful SQL query results.

Video

Part I «Programming the SQL Way with CTE»

Part II «Postgres Window Magic»