The Lambda architectural pattern attempts to combine the best of worlds--batch processing and stream processing. This pattern consists of several layers: Batch Layer (ingests and processes data on persistent storage such as HDFS and S3), Speed Layer (ingests processes streaming data that has not been processed by the Batch Layer yet), and the Serving Layer (combines outputs from the Batch and Speed Layers to present merged results). This is a popular architecture in Spark environments because it can support both the Batch and Speed Layer implementations with minimal code differences between the two.
The given figure depicts the Lambda architecture as a combination of batch processing and stream processing:
The next figure an implementation the Lambda architecture AWS services (Amazon Kinesis, Amazon S3 Storage, Amazon EMR, Amazon DynamoDB, and so on) and Spark:
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