180 points by data_ninja 1 year ago flag hide 14 comments
johnsmith 1 year ago next
Fascinating read! How did you manage to ensure data accuracy during processing at such a large scale?
johnsmith 1 year ago next
@johnsmith We leveraged advanced data validation techniques and multiple levels of data validation layers.
jane_dataengineer 1 year ago next
@johnsmith I see, could you elaborate more on the data validation layers and techniques used?
originalposter 1 year ago next
@jane_dataengineer Sure, one approach that really worked was the marrying of probabilistic and deterministic data validation techniques.
codingfanatic 1 year ago prev next
Impressive! What were some of the tools and technologies used in this project?
originalposter 1 year ago next
@codingfanatic We utilized Spark for data processing, Kafka for real-time data ingestion, and Cassandra for storage.
handsontypist 1 year ago next
@originalposter Awesome, could you share more on how Spark, Kafka, and Cassandra integrate for such a large scale?
originalposter 1 year ago next
@handsontypist Certainly! Spark and Cassandra are integrated over Dataframes while Kafka processes data in real-time and feeds it to Spark for batch processing.
gnulinuxlover 1 year ago prev next
Great article! Any challenges faced during the distribution of data among nodes?
originalposter 1 year ago next
@gnulinuxlover Yes, distributing data posed challenges with initial node failure. We implemented auto-healing and auto-scaling strategies using Kubernetes.
scriptfrenzy 1 year ago next
@originalposter Impressive, thanks for sharing! Were there any benchmarks or metrics around the improved performance? If so, would love to hear!
originalposter 1 year ago next
@scriptfrenzy For every million requests processed, the time taken reduced by about 33% as compared to our initial implementation. We also ensured 99.99% availability and reduced downtime by 50%.
techquest 1 year ago prev next
Can someone ELI5 how Big Data processing at scale works in this example?
helpfulhelen 1 year ago next
Sure! First, data is ingested using Kafka in real-time. Next, Spark processes the data in Batches and feeds Cassandra for long-term storage. Auto-healing nodes help keep the cluster healthy.