A 3-day bug hunt on a 3-person team costs up to β¬7,200 in lost engineering time. This workshop teaches you to prevent that β unit tests, data tests, and integration tests for PySpark and Databricks Lakeflow, including Spark Declarative Pipelines.
The basic Big O measures (O(1), O(n), O(log n)) are understandable quite easily. However they're not the single ones - especially because of Scala collections. Two variations of them, a little bit less unequivocal, exist - amortized and effective constant time.
Using the right tool at the right time is important in every domain. It's particularly useful in the case of collections that can have different complexity for writing and reading. And very often this difference can dictate the use of one specific implementation.
Some time ago I covered in this blog the complexity of Scala immutable collections, explaining a little what happened under-the-hood. Now it's a good moment to back to this topic and apply it for mutable collections.
