I sell subscriptions of my online course, as well as the courses in retail.
I would bring the "top 5" of best selling plans / courses. For this, I have a table called "subscriptionPlan", which stores the purchased plan ID, or in the case of a course, the course ID, and the amount spent on this transaction. Example:
table subscriptionPlan
sbpId | subId | plaId | couId | sbpAmount
1 | 1 | 1 | 1 | 499.99
2 | 2 | 1 | 2 | 499.99
3 | 3 | 2 | 0 | 899.99
4 | 4 | 1 | 1 | 499.99
Just for educational purposes, plaId = 1 is a plan called "Single Sale" that I created, to maintain the integrity of the DB. When the couId isn't empty, you also have bought a separate course, not a plan where you can attend any course.
My need is: List the top 5 sales. If it is a plan, display the plan name (plan table, column plaTitle). If it is a course, display its name (table course, colna couTitle). This logic that I can't code. I was able to rank a top 5 of PLANS, but it groups the courses, since the GROUP BY is by the ID of the plan. I believe the prank is here, maybe creating an IF / ELSE in this GROUPBY, but I don't know how to do this.
The query that i code, to rank my top 5 plans is:
SELECT sp.plaId, sp.couId, p.plaTitle, p.plaPermanent, c.couTitle, SUM(sbpAmount) AS sbpTotalAmount
FROM subscriptionPlan sp
LEFT JOIN plan p ON sp.plaId = p.plaId
LEFT JOIN course c ON sp.couId = c.couId
GROUP BY sp.plaId
ORDER BY sbpTotalAmount DESC
LIMIT 5
The result that i expected was:
plaId | couId | plaTitle | couTitle | plaPermanent | sbpTotalAmount
1 | 1 | Venda avulsa | Curso 01 | true | 999.98
2 | 0 | Acesso total | null | false | 899.99
3 | 2 | Venda avulsa | Curso 02 | true | 499.99
How could I get into this query formula?
When grouping you can use:
Simple columns, or
Any [complex] expression.
In your case, it seems you need to group by an expression, such as:
GROUP BY CASE WHEN sp.plaId = 1 THEN -1 ELSE sp.couId END
In this case I chose -1 as the grouping for the "Single Plan". You can replace the value for any other that doesn't match any couId.
Related
I have been tasked to find out the SELECT statement for an explain plan
------------------------------------------
| Id | Operation | Name |
------------------------------------------
| 0 | SELECT STATEMENT | |
| 1 | HASH JOIN RIGHT ANTI | |
| 2 | VIEW | VW_NSO_1 |
| 3 | HASH JOIN RIGHT SEMI| |
| 4 | TABLE ACCESS FULL | PART |
| 5 | TABLE ACCESS FULL | ORDERS |
| 6 | TABLE ACCESS FULL | CUSTOMER |
------------------------------------------
I am able to find the select statement from Id 0-5 but what does the line 6 mean?
This is what I have managed to figure out so far I can't get where the last sentence comes into play.
select *
from customer c join orders o
on c.custkey = o.custkey
where o_totalprice
not in
(select p_retailprice
from part p join orders o
on orders.o_custkey >= 0 and 0.1*o_totalprice >= 0)
I can't get where the last sentence comes into play?
Your query is:
select *
from customer c join orders o
on c.custkey = o.custkey
where o_totalprice
not in
(select p_retailprice
from part p join orders o
on orders.o_custkey >= 0 and 0.1*o_totalprice >= 0)
And your explain plan is
------------------------------------------
| Id | Operation | Name |
------------------------------------------
| 0 | SELECT STATEMENT | |
| 1 | HASH JOIN RIGHT ANTI | |
| 2 | VIEW | VW_NSO_1 |
| 3 | HASH JOIN RIGHT SEMI| |
| 4 | TABLE ACCESS FULL | PART |
| 5 | TABLE ACCESS FULL | ORDERS |
| 6 | TABLE ACCESS FULL | CUSTOMER |
------------------------------------------
In your case, this is what happens:
You are getting all the records from both customer and orders that match the condition based on the custkey field.
Your predicate information is delimiting the output to those where o_totalprice ( by the way it should clarified for reading easiness where this field is coming from, although I guess is from orders table ) is not part of the dataset retrieved from the subquery.
the subquery is getting all values of p_retailprice that match the join between part and orders using orders.o_custkey >= 0 and 0.1*o_totalprice >= 0
Getting this in consideration the CBO is:
Accessing ( Line 6 ) by TABLE FULL SCAN the table CUSTOMER, which is logical as you are getting all fields from the table and probably you have no index over custkey.
Making a HASH SEMI JOIN ( line 3 ) between PARTS and ORDERS. In general, a semi join is used for an in or exists clause, and the join stops as soon as the exists condition or the in condition is satisfied.
The HASH JOIN ANTI of line 1 is when the optimizer push the join predicate into a view, normally when an anti join ( not in ) is in place. This is then join to the CUSTOMER TABLE in line 6.
You are filtering only in the right table of the join ( ORDERS ) that is why the access are reflecting that.
This is just an overview of your execution plan and the reasons why the CBO is using those access paths.
I want to create an analysis table in AWS Quicksight that shows the quantity sold in a given month and it's subsequent month based on users who made a purchase on the given month.
Let's say I have a dataset called user_orders with the following data:
+---------+----------+------------+
| user_id | quantity | order_date |
+---------+----------+------------+
| 1 | 2 | 2020-04-01 |
+---------+----------+------------+
| 1 | 3 | 2020-04-02 |
+---------+----------+------------+
| 1 | 1 | 2020-05-23 |
+---------+----------+------------+
| 1 | 2 | 2020-06-02 |
+---------+----------+------------+
| 2 | 1 | 2020-05-03 |
+---------+----------+------------+
| 2 | 1 | 2020-05-04 |
+---------+----------+------------+
| 3 | 2 | 2020-04-07 |
+---------+----------+------------+
| 3 | 1 | 2020-04-10 |
+---------+----------+------------+
| 3 | 1 | 2020-06-23 |
+---------+----------+------------+
For example, using the table above I want to be able to show how many quantities sold in April, May, June, and so on (max 12 months) by users who made a purchase in April.
The resulting table should look like this:
+-----------+----------+
| | quantity |
+-----------+----------+
| 04-2020 | 8 |
+-----------+----------+
| 05-2020 | 1 |
+-----------+----------+
| 06-2020 | 3 |
+-----------+----------+
8 sold in April because user_id 1 made 5 purchase and user_id 3 made 3 purchase while user_id 2 did not make any purchase.
There is only 1 item sold in May because only user_id 1 made the purchase in May, but also made a purchase in April. user_id 2 also made a purchase in May but didn't in April so it's not counted.
I can make the table above using PHP and MySQL fairly easily using the following code:
# first get all the user ids who made a purchase in April
$user_ids = sql_query("SELECT DISTINCT user_id FROM user_orders WHERE order_date BETWEEN '2020-04-01' AND '2020-04-30'");
# get the quantity sold for each month by users who made a purchase in April
$purchases = sql_query("SELECT MONTH(order_date), SUM(quantity) FROM user_orders WHERE user_id IN ({$user_ids}) AND order_date BETWEEN '2020-04-01' AND '2021-03-31' GROUP BY MONTH(order_date);")
(Obviously, April is just an example, I'd like to be able to change the starting month dynamically using QuickSight control)
As my above example shown, it requires two queries to perform this analysis. First, is to get the user_ids of the users, and the next is to actually get the quantity sold by the users.
I have been trying to achieve this using Quicksight for the last 3 days but hasn't found any way yet.
I hope someone can point me in the right direction.
Thank you!
You can achieve this by creating a calculated field like this and filtering on it
distinctCountOver(ifelse(truncDate('MM', {order_Date}) = parseDate('2020-04-01'), 1, NULL), [{user_id}], PRE_AGG)
(ofcourse, you can change the parseDate portion to be your date parameter)
Now, lets say the name of the above calculated field is SpecificMonthUser. You can add a filter sum(SpecificMonthUser) != 0.
And then create a pivot table visualization with OrderDate, user id in the rows and sum(quantity) in the values. You should get the desired result.
I have one table that need to split into several other tables.
But the main table is just like a transitive table.
I dump data from a excel into it (from 5k to 200k rows) , and using insert into select, split into the correct tables (Five different tables).
However, the latest dataset that my client sent has records with duplicates values.
The primary key usually is ENI for my table. But even this record is duplicated because the same company can be a customer and a service provider, so they have two different registers but use the same ENI.
What i have so far.
I found a script that uses merge and modified it to find same eni and update the same main_id to all
|Main_id| ENI | company_name| Type
| 1 | 1864 | JOHN | C
| 2 | 351485 | JOEL | C
| 3 | 16546 | MICHEL | C
| 2 | 351485 | JOEL J. | S
| 1 | 1864 | JOHN E. E. | C
Main_id: Primarykey that the main BD uses
ENI: Unique company number
Type: 'C' - COSTUMER 'S' - SERVICE PROVIDERR
Some Cases it can have the same type. just like id 1
there are several other Columns...
What i need:
insert any of the main_id my other script already sorted, and set a flag on the others that they were not inserted. i cant delete any data i'll need to send these info to the costumer validate.
or i just simply cant make this way and go back to the good old excel
Edit: as a question below this is a example
|Main_id| ENI | company_name| Type| RANK|
| 1 | 1864 | JOHN | C | 1 |
| 2 | 351485 | JOEL | C | 1 |
| 3 | 16546 | MICHEL | C | 1 |
| 2 | 351485 | JOEL J. | S | 2 |
| 1 | 1864 | JOHN E. E. | C | 2 |
RANK - would be like the 1864 appears 2 times,
1st one found gets 1 second 2 and so on. i tryed using
RANK() OVER (PARTITION BY MAIN_ID ORDER BY ENI)
RANK() OVER (PARTITION BY company_name ORDER BY ENI)
Thanks to TEJASH i was able to come up with this solution
MERGE INTO TABLEA S
USING (Select ROWID AS ID,
row_number() Over(partition by eniorder by eni, type) as RANK_DUPLICATED
From TABLEA
) T
ON (S.ROWID = T.ID)
WHEN MATCHED THEN UPDATE SET S.RANK_DUPLICATED= T.RANK_DUPLICATED;
As far as I understood your problem, you just need to know the duplicate based on 2 columns. You can achieve it using analytical function as follows:
Select t.*,
row_number() Over(partition by main_id, eni order by company_name) as rnk
From your_table t
I'm trying to use this recursive SQL feature but can't get it to do what I want, not even close. I've coded up the logic in an unrolled loop, asking if it can be converted into a single recursive SQL query, not the table update style I've used.
http://sqlfiddle.com/#!4/b7217/1
There are six players to be ranked. They have id, group id, score and rank.
Initial state
+----+--------+-------+--------+
| id | grp_id | score | rank |
+----+--------+-------+--------+
| 1 | 1 | 100 | (null) |
| 2 | 1 | 90 | (null) |
| 3 | 1 | 70 | (null) |
| 4 | 2 | 95 | (null) |
| 5 | 2 | 70 | (null) |
| 6 | 2 | 60 | (null) |
+----+--------+-------+--------+
I want to take the person with the highest initial score and give them rank 1. Then I apply 10 bonus points to the score of everyone who has the same group id. Take the next highest, assign rank 2, distribute bonus points and so on until there are no players left.
User id breaks ties.
The bonus points changes the ranking. id=4 initially appears to be second placed with 95, behind the leader with 100 but with the 10 pts bonus, id=2 moves up and takes the spot.
Final state
+-----+---------+--------+------+
| ID | GRP_ID | SCORE | RANK |
+-----+---------+--------+------+
| 1 | 1 | 100 | 1 |
| 2 | 1 | 100 | 2 |
| 4 | 2 | 95 | 3 |
| 3 | 1 | 90 | 4 |
| 5 | 2 | 80 | 5 |
| 6 | 2 | 80 | 6 |
+-----+---------+--------+------+
This is a quite a bit late, but I'm not sure this can be done using Recursive CTE. I did however come up with a solution using the MODEL clause:
WITH SAMPLE (ID,GRP_ID,SCORE,RANK) AS (
SELECT 1,1,100,NULL FROM DUAL UNION
SELECT 2,1,90,NULL FROM DUAL UNION
SELECT 3,1,70,NULL FROM DUAL UNION
SELECT 4,2,95,NULL FROM DUAL UNION
SELECT 5,2,70,NULL FROM DUAL UNION
SELECT 6,2,60,NULL FROM DUAL)
SELECT ID,GRP_ID,SCORE,RANK FROM SAMPLE
MODEL
DIMENSION BY (ID,GRP_ID)
MEASURES (SCORE,0 RANK,0 LAST_RANKED_GRP,0 ITEM_COUNT,0 HAS_RANK)
RULES
ITERATE (1000) UNTIL (ITERATION_NUMBER = ITEM_COUNT[1,1]) --ITERATE ONCE FOR EACH ITEM TO BE RANKED
(
RANK[ANY,ANY] = CASE WHEN SCORE[CV(),CV()] = MAX(SCORE) OVER (PARTITION BY HAS_RANK) THEN RANK() OVER (ORDER BY SCORE DESC,ID) ELSE RANK[CV(),CV()] END, --IF THE CURRENT ITEM SCORE IS EQUAL TO THE MAX SCORE OF UNRANKED, ASSIGN A RANK
LAST_RANKED_GRP[ANY,ANY] = FIRST_VALUE(GRP_ID) OVER (ORDER BY RANK DESC),
SCORE[ANY,ANY] = CASE WHEN RANK[CV(),CV()] = 0 AND CV(GRP_ID) = LAST_RANKED_GRP[CV(),CV()] THEN SCORE[CV(),CV()]+10 ELSE SCORE[CV(),CV()] END,
ITEM_COUNT[ANY,ANY] = COUNT(*) OVER (),
HAS_RANK[ANY,ANY] = CASE WHEN RANK[CV(),CV()] <> 0 THEN 1 ELSE 0 END --TO SEPARATE RANKED/UNRANKED ITEMS
)
ORDER BY RANK;
It's not very pretty, and I suspect there is a better way to go about this, but it does give the expected output.
Caveats:
You'd have to increase the iteration count if you have more than that number of rows.
This does a full re-ranking based on the score after each iteration. So if we took your sample data, but changed the initial score of item 2 to 95 rather than 90: after ranking item 1 and giving the 10 point bonus to item 2, it now has a score of 105. So we rank it as 1st and move item 1 down to 2nd. You'd have to make a few modifications if this is not the desired behavior.
This is a bit hard to explain in words ... I'm trying to calculate a sum of grouped distinct values in a matrix. Let's say I have the following data returned by a SQL query:
------------------------------------------------
| Group | ParentID | ChildID | ParentProdCount |
| A | 1 | 1 | 2 |
| A | 1 | 2 | 2 |
| A | 1 | 3 | 2 |
| A | 1 | 4 | 2 |
| A | 2 | 5 | 3 |
| A | 2 | 6 | 3 |
| A | 2 | 7 | 3 |
| A | 2 | 8 | 3 |
| B | 3 | 9 | 1 |
| B | 3 | 10 | 1 |
| B | 3 | 11 | 1 |
------------------------------------------------
There's some other data in the query, but it's irrelevant. ParentProdCount is specific to the ParentID.
Now, I have a matrix in the MS Report Designer in which I'm trying to calculate a sum for ParentProdCount (grouped by "Group"). If I just add the expression
=Sum(Fields!ParentProdCount.Value)
I get a result 20 for Group A and 3 for Group B, which is incorrect. The correct values should be 5 for group A and 1 for group B. This wouldn't happen if there wasn't ChildID involved, but I have to use some other child-specific data in the same matrix.
I tried to nest FIRST() and SUM() aggregate functions but apparently it's not possible to have nested aggregation functions, even when they have scopes defined.
I'm pretty sure there is some way to calculate the grouped distinct sum without needing to create another SQL query. Anyone got an idea how to do that?
Ok I got this sorted out by adding a ROW_NUMBER() function my SQL query:
SELECT Group, ParentID, ROW_NUMBER() OVER (PARTITION BY ParentID ORDER BY ChildID ASC) AS Position, ChildID, ParentProdCount FROM Table
and then I replaced the SSRS SUM function with
=SUM(IIF(Position = 1, ParentProdCount.Value, 0))
Put a grouping over the ParentID and use a summation over that group,
eg:
if group over ParentID = "ParentIDGroup"
then
column sum of ParentPrdCount = SUM(Fields!ParentProdCount.Value,"ParentIDGroup")