Spark After Dark is a mock dating site that uses the latest Spark libraries including Spark SQL, BlinkDB, Spark Streaming, MLlib, and GraphX to generate high-quality dating recommendations for its members and blazing fast analytics for its operators. We begin with brief overview of Spark, Spark Libraries, and Spark Use Cases. In addition, we'll discuss the modern day Lambda Architecture that combines real-time and batch processing into a single system. Lastly, we present best practices for monitoring and tuning a highly-available Spark and Spark Streaming cluster. There will be many live demos covering everything from basic topics such as ETL and data ingestion to advanced topics such as streaming, sampling, approximations, machine learning, textual analysis, and graph processing.