Overview
I aim to intercept Spark SQL commands at runtime and dynamically change them without extra client input. Previous listener modifications only output query plans instead of raw SQL.
hey, try hooking into spark’s catalyst optimizer. you might be able to change the logical plan before it converts to the physical one. not sure if it’ll give u raw sql, but its a workarund worth exploring.
hey, im curoius if intercepting the parse phase might yield raw sql befor its aggresively compiled. has any1 tried that path? i think early interception could be a game changer. what challenges did u bump into?
Considering the requirement to modify Spark SQL commands dynamically, it is possible to approach this challenge by introducing custom transformations during the query planning process. One effective practice is to implement a custom extension that hooks into the query analysis phase rather than relying solely on the catalyst optimizer. In past experiences, creating a SparkListener that monitors the query flow and triggers alterations before execution has proven beneficial. Extensive testing is paramount to ensure the modifications do not adversely affect query performance or integrity.