- Deep Dive into Spark Jobs and Stages
- Balancing the RUM Conjecture: Navigating Database Trade-Offs
- The CAP Theorem: Balancing the Big Three in Distributed Databases
- Fine-Tuning Shuffle Partitions in Apache Spark for Maximum Efficiency
- Handling Large Broadcast Joins in Apache Spark
- Symptoms of Bad Code
- Docker - the right way
- GitOps - the easy way
- Finger Detection and Tracking using OpenCV and Python
- What is Google Summer of Code? How to prepare for it?
#Apache
#Apache-Spark
#Availability
#Best-Practices
#Big-Data
#Brewers Theorem
#Broadcast
#CAP Theorem
#Cleancode
#Codesmells
#Consistency
#Containers
#Data
#Data Engineering
#Data-Processing
#Database Design
#Devops
#Distributed Systems
#Distributed-Computing
#Docker
#Gitops
#Google
#Gsoc
#Iac
#Infrastructure
#Join
#Network Partitions
#Open-Source
#Open-Source-Software
#Oss
#Partition Tolerance
#Partitions
#Performance
#Performance-Optimization
#RUM Conjecture
#Security
#Shuffle
#Softwareengineering
#Softwarequality
#Spark
#Spark-Optimization
#System Design
#Tech Tradeoffs