Earlier quoted context omitted.
I would love to know an alternative to that superbly integrated stack . [be aware that none of those tools require coding knowledge, nor any DB administration, nor scalability consideration. But for me the most important part is that the data workflow is not dataFrame driven, but semantic entity/relationship driven. Think of that as if you had an ORM magically wrapping your Spark cluster, and make it look like a grap…
> be aware that none of those tools require coding knowledge, nor any DB administration, nor scalability consideration. These are slogans with marketing grade truth, not engineering truth. The moment you leave the happy path wizards you run straight into Python, SQL, JVM knobs, and cluster limits. The visual Pipeline Builder drops you into a Code node the second you need anything beyond basic joins/filters. Here is a…
Having most of those PySpark functions exposed visually as building blocks with debug points available at each step simply outperforms a codeWorkbook in term of maintainability and readability.