PostgreSQL Podcast Summaries
PostgreSQL on Yedapo: 9 summarized podcast and YouTube episodes. Each includes key takeaways, core concepts and notable quotes with timestamps.
Can You Solve These Advanced PostgreSQL Queries? 🔥 Joins, GROUP BY, HAVING
Thapa Technical
Jun 21, 2026
This tutorial demonstrates how to perform complex multi-table joins in PostgreSQL to solve real-world business problems. By connecting Courses, Users, and Enrollments tables, you can isolate high-value metrics like premium course popularity and departmental cost averages, moving beyond simple queries to actionable database analysis.
Key insight: When using aggregate functions alongside non-aggregated columns in a SELECT statement, you must include the non-aggregated columns in the GROUP BY clause to ensure accurate data grouping.
Advanced PostgreSQL Practice Session | Real SQL Interview Questions & Solutions
Thapa Technical
Jun 19, 2026
This session bridges the gap between basic SQL theory and complex enterprise requirements. It demonstrates how to combine multiple Joins, Aggregate functions, Grouping, and complex filtering via Having clauses into a single, high-level query to solve real business problems like identifying top-spending students.
Key insight: When building complex business queries, filtering before aggregation requires the 'WHERE' clause, while filtering on aggregate results (like a specific total spent amount) must be performed using the 'HAVING' clause after the 'GROUP BY' statement.
PostgreSQL GROUP BY & HAVING Clause Explained with Practical Questions
Thapa Technical
Jun 18, 2026
The instructor clarifies the functional divide between 'Group By' and 'Having' in PostgreSQL. He explains that 'Group By' is used to organize data into aggregate sets, while 'Having' acts as a secondary filter specifically for those aggregated results. Adhering to the logical query execution sequence—Select, From, Where, Group By, Having—is critical to avoiding syntax errors.
Key insight: The golden rule of SQL: Any column listed in a SELECT statement that is not inside an aggregate function must be included in the GROUP BY clause to prevent execution errors.
Kenapa Koneksi PostgreSQL Itu Mahal?
Programmer Zaman Now
Jun 17, 2026
Koneksi PostgreSQL bersifat mahal karena setiap klien membutuhkan proses OS terpisah. Saat menggunakan connection pooler seperti PgBouncer dalam 'transaction mode', penggunaan 'prepared statements' menyebabkan eksekusi query gagal secara acak karena koneksi yang berganti-ganti. Strategi ini krusial bagi arsitektur serverless yang membutuhkan efisiensi koneksi tinggi.
Key insight: Bug 404 pada data yang baru di-insert seringkali disebabkan oleh 'prepared statement' yang tidak ditemukan di koneksi baru saat PgBouncer melakukan pooling dalam transaction mode.
PostgreSQL Aggregate Functions Tutorial | COUNT, SUM, AVG, MIN, MAX with Real Examples
Thapa Technical
Jun 15, 2026
एग्रीगेट फंक्शन्स जैसे COUNT, SUM, और AVG किसी भी कॉलम के विशाल डेटा को प्रोसेस कर केवल एक समराइज्ड आउटपुट देते हैं। यह ट्यूटोरियल इन फंक्शन्स के सटीक सिंटैक्स, एलीयासेस के महत्व, और नल वैल्यूज को संभालने की बेस्ट प्रैक्टिसेस को स्पष्ट करता है, जो डेटा एनालिटिक्स में सटीकता के लिए अनिवार्य है।
Key insight: COUNT(*) और COUNT(column) के बीच का अंतर यह है कि स्टार नल वैल्यूज को भी शामिल करता है, जबकि स्पेसिफिक कॉलम का उपयोग करने पर नल वैल्यूज को एक्सक्लूड कर दिया जाता है।
PostgreSQL FULL OUTER JOIN vs CROSS JOIN Explained with Real Database Examples
Thapa Technical
Jun 14, 2026
Full outer joins effectively reconcile mismatched datasets by retaining unmatched records with NULL placeholders, whereas cross joins generate Cartesian products of tables. While powerful for SKU combinations or scheduling grids, cross joins carry severe performance risks, as joining large tables without filters can crash database systems.
Key insight: Cross joins require no 'ON' clause because their purpose is to generate every possible combination between two tables—a feature that can inadvertently trigger system-freezing performance degradation if the row counts are large.
Build Your Own AI Agent – Full Course with OpenAI, Langchain, Render Deployment
freeCodeCamp.org
Jun 2, 2026
Anna Kuber demonstrates how to build a production-ready Slackbot that autonomously researches new community members and scores their lead quality using OpenAI and PostgreSQL. This end-to-end guide covers development, database integration, and deployment on Render using Infrastructure-as-Code.
Key insight: You can use GitHub's public API and company email domains as a lightweight, automated 'background check' to score potential customer fit in real-time.
Comment ChatGPT tourne sur UN SEUL serveur de base de données ??
cocadmin
Apr 17, 2026
Face à une croissance fulgurante, OpenAI a dû optimiser drastiquement son architecture PostgreSQL au lieu de tenter un sharding complexe. En minimisant les écritures, en cascadeant la réplication et en isolant les tâches, ils parviennent à servir des centaines de millions d'utilisateurs sans sacrifier la stabilité du système.
Key insight: OpenAI interdit tout changement de schéma de base de données dépassant 5 secondes et privilégie des migrations en plusieurs étapes sur plusieurs jours pour éviter de corrompre les données via le mécanisme MVCC de Postgres.
Configurando Docker Compose, Postgres, com Testes de Carga - Parte Final da Rinha de Backend
Fabio Akita
Dec 16, 2023
Otimizações prematuras em sistemas backend costumam ser inúteis e custosas. Fábio Akita demonstra que, sem métricas de monitoramento e testes de carga, decisões técnicas baseadas em intuição — como adicionar caches ou filas desnecessárias — apenas escondem falhas de infraestrutura e aumentam a complexidade sem ganhos reais de performance.
Key insight: Uma simples mudança de 'bridge network' para 'host network' no Docker resolveu erros de 'IO Exception' e aumentou a capacidade de processamento de 108 mil para 115 mil requisições, superando ganhos de otimizações complexas no código.