Supercharging Data Ingestion: How I Loaded 160 Million Records from Redshift into Spark in Just 6…IntroductionSep 4Sep 4
The Growth and Future Prospects of India’s Steel SectorIntroduction: The Indian steel sector has witnessed significant growth and development in recent years, despite the challenges posed by the…Jul 15, 2023Jul 15, 2023
Unveiling Dataset Structure: Analyzing Length Counts in Each Column with Apache SparkIntroduction: When working with large datasets, it is often essential to gain insights into the data’s characteristics. One important…May 31, 2023May 31, 2023
Achieving Peak Performance with Apache HiveIntroduction: Apache Hive is a popular data warehousing infrastructure built on top of Apache Hadoop. It provides a high-level interface…May 2, 2023May 2, 2023
Data Engineering System Design: Best Practices for Building Scalable Data PipelinesIntroduction:May 1, 2023May 1, 2023
Ensuring Data Accuracy: The Importance of Testing in Data EngineeringData engineering testing is the process of ensuring that the data pipelines, infrastructure, and systems that move and process data are…Apr 24, 2023Apr 24, 2023
Published inDev GeniusAdvanced Techniques for RDBMS Sharding and Scatter-Gather: Maximizing Efficiency and ScalabilityData sharding is a technique used to horizontally partition large databases into smaller, more manageable subsets called shards. Each shard…Apr 14, 20231Apr 14, 20231
Performing Ranking Analysis with Window Functions in SparkApache Spark is a powerful big data processing framework that supports various features such as batch processing, stream processing, and…Apr 11, 2023Apr 11, 2023
