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Learning with Jupyter Notebook

Download interactive notebooks to learn how to read from and write to Aerospike using Spark DataFrames in Scala and Python languages. You will also see how you can provide or infer schemas, use flexible schemas, configure connector properties, use predicates with and without primary keys, use complex types such as maps, visualize data that is in a DataFrame, and build predictive models using scikit-learn.

Learning to read from and write to Dataframes

Walk through a detailed example in Scala of loading data from Aerospike into a Spark DataFrame, and vice-versa.

Learning to use Spark Structured Streaming with Aerospike

Learn how to do streaming reads from Aerospike by using Kafka source, and how to do writes to Aerospike, using highly performant Spark Structured Streaming. You can also learn how to build a streaming pipeline.

Learning to load subsets of Aerospike data into Spark using aerolookup

Learn a performant way to load a subset of Aerospike data in Scala/Python using ultrafast lookup.