spark

Why we included this project

Teams that already write C# or F# but need to process datasets far too large for a single machine will find this the missing bridge between their codebase and Apache Spark. It exposes the core Spark surface through .NET APIs, covering DataFrames, SparkSQL, and Structured Streaming, so a .NET shop can run distributed analytics, batch ETL, and streaming pipelines without learning Scala or Python. Because it targets .NET Standard, the same skills and libraries you already use carry over, and it deploys to the usual managed Spark environments like Azure HDInsight, Amazon EMR, and Databricks. It also pairs with ML.NET for training and prediction inside Spark jobs, which matters if you want to scale model scoring across a cluster. For a .NET-centric data team, this is the practical way into big data analytics while staying in a familiar language.