cloud-fan commented on a change in pull request #30144:
URL: https://github.com/apache/spark/pull/30144#discussion_r605473810
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File path: docs/sql-ref-syntax-qry-select-groupby.md
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@@ -88,6 +89,41 @@ aggregate_name ( [ DISTINCT ] expression [ , ... ] ) [
FILTER ( WHERE boolean_ex
(product, warehouse, location), (warehouse), (product), (warehouse,
product), ())`.
The N elements of a `CUBE` specification results in 2^N `GROUPING SETS`.
+* **Partial Grouping Analytics**
+
+ Partial grouping analytics means there are both `group_expression` and
`CUBE|ROLLUP|GROUPING SETS`
+ in GROUP BY clause. For example:
+ `GROUP BY warehouse, CUBE(product, location)` is equivalent to
+ `GROUP BY GROUPING SETS((warehouse, product, location), (warehouse,
product), (warehouse, location), (warehouse))`.
+ `GROUP BY warehouse, ROLLUP(product, location)` is equivalent to
+ `GROUP BY GROUPING SETS((warehouse, product, location), (warehouse,
product), (warehouse))`.
+ `GROUP BY warehouse, GROUPING SETS((product, location), (producet), ())`
is equivalent to
+ `GROUP BY GROUPING SETS((warehouse, product, location), (warehouse,
location), (warehouse))`.
+
+* **Concatenated Groupings**
+
+ Concatenated grouping analytics offer a concise way to generate useful
combinations of groupings. Groupings specified
+ with concatenated groupings yield the cross-product of groupings from each
grouping set. The cross-product
+ operation enables even a small number of concatenated groupings to
generate a large number of final groups.
+ The concatenated groupings are specified simply by listing multiple
`GROUPING SETS`, `CUBES`, and `ROLLUP`,
Review comment:
We can just say that CUBE/ROLLUP are just syntax sugar for GROUPING
SETS, then the document can just focus on GROUPING SETS.
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