Every table in Tabular has one or more partitions.Every partition defines a set of rows that are read from the source table. Every partition can be processed independently and in parallel with others, so you can use partitions to accelerate the processing of a single table.You define partitions related to the source table, but from the Tabular point of view, every table is made of several columns, and every column is a different object. Some columns are calculated and based on the data of other columns belonging to the same or different tables. The engine knows the dependencies of each calculated column and calculated table. When you process a partition of a table, every dependent calculated table must be completely recalculated. Moreover, every calculated column in the same or other tables must be completely recalculated for the entire table to which it belongs.

So, with 32 cores to play with, we should be looking at the default segment size (8m) or maybe reduce it to 4m to get 40 segments. But the extra compression with 16m segment size may be of benefit. So I ran some timing tests on the distinct count measure, and the results are quite interesting.

External Tools

As I said at the beginning of the guide, I am not an expert on Docker or Security. As with everything on this site, I research, learn, try, and then share what I learned with the community.