I have a query that counts associated records AND associated status
SELECT
orders.id,
SUM(CASE WHEN s.shipment_status='CLOSED' THEN 1 ELSE 0 END) as closed,
COUNT(*) as shipment_count
FROM orders as po
JOIN shipments as s ON s.order_id = po.id
GROUP BY po.id
I am attempting to query all orders, where all the shipments are CLOSED.
Essentially looking at the above, just returning when closed = shipment_count .
If I add an AND clause to the join then it will simply limit the number of shipments.
I figured this out with a HAVING clause, which doesn't use the select attrs.
SELECT
orders.id
FROM orders as po
JOIN shipments as s ON s.order_id = po.id
GROUP BY po.id
HAVING SUM(CASE WHEN s.shipment_status='CLOSED' THEN 1 ELSE 0 END) = COUNT(*)
Leaving my answer up in case it helps others. Maybe better answers available to come from the community.
Related
So this is my table structure
learning_paths
id
name
version
created_at
updated_at
learning_path_levels
id
name
learning_path_id
order
created_at
updated_at
learning_path_level_nodes
id
name
description
documentation_links
evaluation_methodology
learning_path_level_id
created_at
updated_at
learning_path_node_users
id
learning_path_level_node_id
user_id
evaluated_by
evaluated_at
is_successful
created_at
updated_at
I'm writing a query to retrieve the learning_path_name, count of the amount of levels each learning path has, the pending and completed nodes per level for the user, and the total amount of nodes per level.
I have the following query
select learning_paths."name",
sum(case when learning_path_node_users.is_successful and learning_path_node_users.user_id is not null then 1 else 0 end) as completed_nodes,
sum(case when learning_path_node_users.is_successful = false or learning_path_node_users.user_id is null then 1 else 0 end) as pending_nodes,
count(learning_path_levels.id) as total_levels,
count(*) as total_nodes
from learning_path_level_nodes
inner join learning_path_levels on learning_path_levels.id = learning_path_level_nodes.learning_path_level_id
inner join learning_paths on learning_paths.id = learning_path_levels.learning_path_id
left join learning_path_node_users on learning_path_node_users.learning_path_level_node_id = learning_path_level_nodes.id
group by learning_paths."name"
which returns:
name
completed_nodes
pending_nodes
total_levels
total_nodes
Devops
5
3
8
8
QA
0
1
1
1
Project manager
3
3
6
6
AI
0
5
5
5
Everything is correct, except for the levels count,
for example, for Devops,it should be 2, and it is returning 8
for Project Manager it should be 2, and it is returning 6
a pattern I see is that it returns the amount of nodes as the amount of levels,
How can I fix this?
I'd really appreciate any help or suggestions, as I've been struggling with this.
Thanks in advance
EDIT: As per your suggestion, I'm attaching a fiddle with the tables and data.
https://dbfiddle.uk/?rdbms=postgres_14&fiddle=f29676ff7051686a28de96928db1e3a6
While I don't get the exact results you want, I think you want to add a distinct to your count for the total levels:
select
lp.name,
sum(case when u.is_successful and u.user_id is not null then 1 else 0 end) as completed_nodes,
sum(case when u.is_successful = false or u.user_id is null then 1 else 0 end) as pending_nodes,
count(distinct lpl.id) as total_levels, -- added "distinct"
array_agg (lpl.id) as level_detail, -- debugging aid
count(*) as total_nodes
from
learning_path_level_nodes n
join learning_path_levels lpl on lpl.id = n.learning_path_level_id
join learning_paths lp on lp.id = lpl.learning_path_id
left join learning_path_node_users u on u.learning_path_level_node_id = n.id
group by
lp.name
To help expose the rationale, I added the field level_detail, which you can delete, to show why the results are what they are. You can obviously remove that once the results are what you want.
If it's not what you expect, perhaps you can explain or give by example what I might be missing.
I have two tables that look like the following:
Orders
------
id
tracking_number
ShippingLogs
------
tracking_number
created_at
stage
I would like to select the IDs of Orders that have ONLY ONE ShippingLog associated with it, and the stage of the ShippingLog must be error. If it has two ShippingLog entries, I don't want it. If it has one ShippingLog bug its stage is shipped, I don't want it.
This is what I have, and it doesn't work, and I know why (it finds the log with the error, but has no way of knowing if there are others). I just don't really know how to get it the way I need it.
SELECT DISTINCT
orders.id, shipping_logs.created_at, COUNT(shipping_logs.*)
FROM
orders
JOIN
shipping_logs ON orders.tracking_number = shipping_logs.tracking_number
WHERE
shipping_logs.created_at BETWEEN '2021-01-01 23:40:00'::timestamp AND '2021-01-26 23:40:00'::timestamp AND shipping_logs.stage = 'error'
GROUP BY
orders.id, shipping_logs.created_at
HAVING
COUNT(shipping_logs.*) = 1
ORDER BY
orders.id, shipping_logs.created_at DESC;
If you want to retain every column from the join of the two tables given your requirements, then I would suggest using COUNT here as an analytic function:
WITH cte AS (
SELECT o.id, sl.created_at,
COUNT(*) OVER (PARTITION BY o.id) num_logs,
COUNT(*) FILTER (WHERE sl.stage <> 'error')
OVER (PARTITION BY o.id) non_error_cnt
FROM orders o
INNER JOIN shipping_logs sl ON sl.tracking_number = o.tracking_number
WHERE sl.created_at BETWEEN '2021-01-01 23:40:00'::timestamp AND
'2021-01-26 23:40:00'::timestamp
)
SELECT id AS order_id, created_at
FROM cte
WHERE num_logs = 1 AND non_error_cnt = 0
ORDER BY id, created_at DESC;
select id, wk0_count
from teams
left join
(select team_id, count(team_id) as wk0_count
from (
select created_at, team_id, trunc(EXTRACT(EPOCH FROM age(CURRENT_TIMESTAMP,created_at)) / 604800) as wk_offset
from loan_files
where loan_type <> 2
order by created_at DESC) as t1
where wk_offset = 0
group by team_id) as t_wk0
on teams.id = t_wk0.team_id
I've created the query above that shows me how many loans each team did in a given week. Week 0 is the past seven days.
Ideally I want a table that shows how many loans each team did in the last 8 weeks, grouped by week. The output would look like:
Any ideas on the best way to do this?
select
t.id,
count(week = 0 or null) as wk0,
count(week = 1 or null) as wk1,
count(week = 2 or null) as wk2,
count(week = 3 or null) as wk3
from
teams t
left join
loan_files lf on lf.team_id = t.id and loan_type <> 2
cross join lateral
(select (current_date - created_at::date) / 7 as week) w
group by 1
In 9.4+ versions use the aggregate filter syntax:
count(*) filter (where week = 0) as wk0,
lateral is from 9.3. In a previous version move the week expression to the filter condition.
How about the following query?
SELECT team_id AS id, count(team_id) AS wk0_count
FROM teams LEFT JOIN loan_files ON teams.id = team_id
WHERE loan_type <> 2
AND trunc(EXTRACT(epoch FROM age(CURRENT_TIMESTAMP, created_at)) / 604800) = 0
GROUP BY team_id
Notable changes are:
ORDER BY clause in subquery was pointless;
created_at in innermost subquery was never used;
wk_offset test is moved on the WHERE clause and not done in two distinct steps;
outermost subquery was not needed.
I have a difficulty dealing with a SQL query. I use PostgreSQL.
The query says: Show the customers that have done at least an order that contains products from 3 different categories. The result will be 2 columns, CustomerID, and the amount of orders. I have written this code but I don't think it's correct.
select SalesOrderHeader.CustomerID,
count(SalesOrderHeader.SalesOrderID) AS amount_of_orders
from SalesOrderHeader
inner join SalesOrderDetail on
(SalesOrderHeader.SalesOrderID=SalesOrderDetail.SalesOrderID)
inner join Product on
(SalesOrderDetail.ProductID=Product.ProductID)
where SalesOrderDetail.SalesOrderDetailID in
(select DISTINCT count(ProductCategoryID)
from Product
group by ProductCategoryID
having count(DISTINCT ProductCategoryID)>=3)
group by SalesOrderHeader.CustomerID;
Here are the database tables needed for the query:
where SalesOrderDetail.SalesOrderDetailID in
(select DISTINCT count(ProductCategoryID)
Is never going to give you a result as an ID (SalesOrderDetailID) will never logically match a COUNT (count(ProductCategoryID)).
This should get you the output I think you want.
SELECT soh.CustomerID, COUNT(soh.SalesOrderID) AS amount_of_orders
FROM SalesOrderHeader soh
INNER JOIN SalesOrderDetail sod ON soh.SalesOrderID = sod.SalesOrderID
INNER JOIN Product p ON sod.ProductID = p.ProductID
HAVING COUNT(DISTINCT p.ProductCategoryID) >= 3
GROUP BY soh.CustomerID
Try this :
select CustomerID,count(*) as amount_of_order from
SalesOrder join
(
select SalesOrderID,count(distinct ProductCategoryID) CategoryCount
from SalesOrderDetail JOIN Product using (ProductId)
group by 1
) CatCount using (SalesOrderId)
group by 1
having bool_or(CategoryCount>=3) -- At least on CategoryCount>=3
i wants to show rows data into columns. suppose if rows type increased then number of columns also increased. Information as follow:
Please see picture to get idea
You can use COUNT with CASE WHEN:
SELECT t.Name AS Type,
COUNT(*) AS NumberOfCase,
COUNT(CASE WHEN s.Name = 'Resolved' THEN 1 END) AS Resolved,
COUNT(CASE WHEN s.Name = 'Pending' THEN 1 END) AS Pending,
COUNT(CASE WHEN s.Name = 'Waiting' THEN 1 END) AS Waiting
FROM Type t
LEFT JOIN "Case" c
ON c.CaseType = t.TypeId
LEFT JOIN "Status" s
ON c.CaseStatus = s.StatusId
GROUP BY t.Name;
SqlFiddleDemo