Engineering productivity investments depend on inflection points, scale, controls, data ... for only primitive types and Java objects; no way to deterministically free memory; a limited addressing ...

An ADT doesn’t care about the memory representation of its values or how its operations are implemented. It’s like a Java interface, which is a data type that’s disconnected from any ...

Every column is considered a Java object. Another Spark data type, the Dataset, adds typing guarantees for columns as a way to enable optimized processing. Another under-the-hood example ...

If all of the values fall within the range of a float, it makes sense to use the smaller Java data type in this situation, otherwise the array elements needlessly consume memory.