Новое развитие LUI (Live Universal Interface) - LUI4ORA2PG, инструмент миграции

The report will talk about a new tool for migrating application systems from the Oracle environment to the Postgres environment. The tool is developed on the basis of the ora2pg tool (by Gill Darold) and the domestic LUI application development tool. Talks on LUI were given at past PGConfs in 2019 and 2020:

• https://pgconf.ru/en/2019/118109
• https://pgconf.ru/en/2020/262456

История одной миграции

In this talk we want to present how Microsoft team composed of people from two different teams approached the project and solved the migration issues using ora2pg and was able to prove that Postgres Single Server can perform equally well as Oracle Exadata. We will present our ways of working and also some main technical challenges that we faced including migration of BULK COLLECT’s, hierarchical queries, refcursors and others more complicated Oracle constructs.

The story about a challenging PoC that proved that Postgres can achieve the same performance as Oracle Exadata. The schema that was migrated wasn’t the simplest one you might see. It was quite the opposite. The code was loaded with dynamic queries, BULK COLLECT’s, nested loops, CONNECT BY statements, global variables and lot of dependencies. Ora2pg did a great job converting the schema but left a lot of work to do manually. Also estimates produced by the tool were highly inaccurate since the logic required not the migration but total re-architecture of the code. In this talk we want to present how Microsoft team composed of people from two different teams approached the project and solved the migration issues using ora2pg and was able to prove that Postgres Single Server can perform equally well as Oracle Exadata. We will present our ways of working and also some main technical challenges that we faced including:

• How estimates do (not) work
• How we handled BULK COLLECT’s
• Why we got rid of refcursors
• How we got stuck with testing of one the packages and how the help from a friend solved the problem
• How we handled hierarchical queries and drilling down the hierarchy

Современное хранилище данных на основе PostgreSQL

PostgreSQL has a long history in DWH. Netezza, Redshift, and Greenplum have turned specific PostgreSQL releases into DWH solutions. Nowadays, with the trends in PostgreSQL towards performance improvements (better partitioning, better statistics, JIT Compilation, etc.) and advanced PostgreSQL extensions, like the Swarm64 Data Accelerator, you can create a forward-looking, no lock-in, versatile, and reliable DWH. This talk will cover the PostgreSQL and DWH trends and touch on key arguments for choosing open source PostgreSQL for DWH.

Формирование отчетов и аналитики в реальном времени с PostgreSQL.

In today's world, operational reporting and real-time analytics are becoming a basic need. There are a huge number of tools, practices, and approaches, which in turn require different expertise and resources. In this talk, I will tell you how to transform your analytics using PostgreSQL. We'll discuss pitfalls when using different schemes. We'll talk about data quality and performance. I expect this talk to be of interest to both beginners and seasoned practitioners with many years of experience (Discussions and questions after the talk will be highly appreciated). The talk outline is as follows. 1. The evolution of reporting - migration from OLTP to OLAP. 2. Data delivery to DWH and related challenges. 3. Scaling architecture in response to growing data volumes. 4. Data quality issues. 5. Maintaining stability with a large number of changes. 6. Different approaches to organizing the work of the DWH team. 7. And, finally, we'll list the challenges we have successfully responded to with various solutions (pgAgent, PGWatch, working with the file system, the new reading of postgresql.conf).