Category Archives: Без рубрики

🔄 1. HikariCP Waits for an Available Connection HikariCP does not immediately throw an error. Instead, it waits up to a configured amount of time (connection-timeout, in milliseconds) for a connection to be returned to the pool. For example: ➡️ … Continue reading →

In HikariCP, the properties spring.datasource.hikari.maximum-pool-size and spring.datasource.hikari.minimum-idle control how many connections the pool maintains and manages. Here’s a detailed breakdown: 🔹 spring.datasource.hikari.maximum-pool-size Definition:The maximum number of connections that can exist in the pool (active + idle). Purpose:Limits the total number … Continue reading →

✅ 2. Configure application.properties or application.yml Spring Boot auto-configures HikariCP when it detects the dependency. You can tune the pool using the spring.datasource.hikari.* properties. Example application.properties: Or using application.yml: ✅ 3. (Optional) Programmatic Configuration If you need custom configuration in … Continue reading →

HikariCP is a high-performance JDBC connection pool library used in Java applications. It’s part of the ecosystem for managing database connections efficiently and is especially popular in Spring Boot applications. 🔹 What is a Connection Pool? A connection pool is … Continue reading →

When you define a Primary Key on a table: Uniqueness: ✅ No two rows can have the same value (or same combination, for composite keys). NOT NULL: ✅ No NULLs allowed in any column that is part of the Primary … Continue reading →

Minimizing replication lag is crucial in systems where read replicas are used for scalability or high availability, especially in distributed databases. Replication lag means the replica is behind the primary, and returning stale data. 🧠 Causes of Replication Lag Cause … Continue reading →

Implementing a priority queue in a relational database involves modeling and querying data in a way that allows you to enqueue items with priorities and dequeue the highest-priority item efficiently. ✅ Step-by-Step Guide 🧱 1. Schema Design Here’s a basic … Continue reading →

Z-ordering (also called Z-indexing or Z-order curves) is a multi-dimensional indexing technique used in databases to optimize queries on multiple columns, especially for big data and time-series workloads. 🧠 What is Z-ordering? Z-ordering transforms multiple dimensions (e.g., columns) into a … Continue reading →

Storing and querying time-series data efficiently requires optimizing for high-ingest write patterns, fast sequential reads, and long-term archival. Here’s a structured approach to designing an efficient time-series system in a relational or NoSQL database: 🧱 1. Data Modeling Principles ✅ … Continue reading →

Amazon Aurora is a high-performance, cloud-native relational database engine built by AWS, compatible with both MySQL and PostgreSQL. It’s designed to overcome the limitations of traditional databases by decoupling storage and compute, offering high availability, performance, and scalability. 🧱 Core … Continue reading →