Is it possible to replace a cross apply with a join? - sql

Question

I am reverse engineering some legacy SQL algorithms to move to apache spark.
I have encountered a across apply which I understand is TSQL specific and there is no direct equivalent in ANSII or Spark SQL.
The sanitized algorithm is:
SELECT
Id_P ,
Monthindex ,
(
SELECT
100 * (STDEV(ResEligible.num_valid) / AVG(ResEligible.num_valid)) AS Pre_Coef_Var
FROM
tbl_p a CROSS APPLY
(
SELECT
e.Monthindex ,
e.num AS num_valid
FROM
dbo.tbl_p e
WHERE
e.Monthindex = a.MonthIndex
AND e.Id_P = a.Id_P
UNION ALL
SELECT DISTINCT
B1.[MonthIndex ] ,
Tr.num AS num_valid
FROM
#tbl_pr B1
INNER JOIN
#tbl_pr B2
ON
B1.[Id_P] = B2.[Id_P]
AND B2.Rang - B1.Rang BETWEEN 0 AND 2
INNER JOIN
dbo.tbl_p Tr
ON
Tr.Id_P = B1.Id_P
AND Tr.Monthindex = B1.Monthindex
WHERE
a.Id_P = B1.[Id_P]
AND B2.[MonthIndex] =
(
SELECT
MAX([MonthIndex])
FROM
#tbl_pr
WHERE
[MonthIndex] < a.MonthIndex
AND [Id_P] = a.Id_P) ) AS ResEligible
WHERE
a.Id_P = result.Id_P
AND a.MonthIndex = result.MonthIndex) AS Coeff
FROM
tbl_p AS result
WHERE
1 = 1
AND MonthIndex = #CurrentMonth
GROUP BY
Id_P ,
Monthindex) AS CC
so for every row in alias b we cross apply to the inner queries.
Is it possible to re-write the cross apply in terms of join operations (or otherwise) so I can re-implement in spark sql?
Cheers
Terry

Answer 1

Seems like you could rewrite your query as the below:
SELECT T1.col1,
T1.col2,
sq.col3Sum
FROM tbl1 T1
CROSS JOIN (SELECT SUM(T1sq.Col3) AS col3Sum
FROM tbl1 T1sq
JOIN tbl2 T2 ON T1sq.Col1 = T2.Col2
JOIN tbl3 T3 ON T2.col1 = T3.Col1) sq;
Seems odd, however, that there was no JOIN criteria between the 2 references to tbl1.