james-willis commented on code in PR #24:
URL:
https://github.com/apache/sedona-spatialbench/pull/24#discussion_r2365277246
##########
print_queries.py:
##########
@@ -404,23 +405,15 @@ def q5() -> str:
return """
-- Q5 (SedonaDB): In SedonaDB ST_Collect is an aggregate function so no need
to use ARRAY_AGG first.
-- ST_Collect does not accept an array as input so we cannot use the query
with ARRAY_AGG.
-WITH per AS (
- SELECT
- c.c_custkey,
- c.c_name AS customer_name,
- DATE_TRUNC('month', t.t_pickuptime) AS pickup_month,
- COUNT(t.t_tripkey) AS n_trips,
- ST_Area(ST_ConvexHull(
- ST_Collect(ST_GeomFromWKB(t.t_dropoffloc))
- )) AS monthly_travel_hull_area
- FROM trip t
- JOIN customer c ON t.t_custkey = c.c_custkey
- GROUP BY c.c_custkey, c.c_name, pickup_month
-)
-SELECT *
-FROM per
-WHERE n_trips > 5
-ORDER BY n_trips DESC, c_custkey ASC;
+SELECT
+ c.c_custkey, c.c_name AS customer_name,
+ DATE_TRUNC('month', t.t_pickuptime) AS pickup_month,
+ ST_Area(ST_ConvexHull(ST_Collect(ST_GeomFromWKB(t.t_dropoffloc)))) AS
monthly_travel_hull_area,
Review Comment:
I tried running sedona spark benchmarks this afternoon. The order by clause
of q5 was invalid spark sql.
Once I updated that query I felt it was important to update all
implementations of q5 to match as closely as possible.
I believe it is essential for the queries to match as closely as possible
across engines to have both a perception and a reality of fairness.
Do you think we should make a different change in order to get a working
sedona spark q5 implementation?
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