I have a table with the fields id, name, birthday, clinic:
id | name | birthday | clinic
1 | mary | 2020-01-01 | clin 1
2 | mary | 2020-01-01 | clin 1
3 | mary | 2020-01-01 | clin 2
4 | john | 2021-01-01 | clin 1
5 | pete | 2020-01-05 | clin 1
6 | pete | 2020-01-05 | clin 2
7 | pete | 2020-01-05 | clin 3
I want to get all records with name, birthday duplicate like:
id | name | birthday | clinic
1 | mary | 2020-01-01 | clin 1
2 | mary | 2020-01-01 | clin 1
3 | mary | 2020-01-01 | clin 2
5 | pete | 2020-01-05 | clin 1
6 | pete | 2020-01-05 | clin 2
7 | pete | 2020-01-05 | clin 3
Mary and Pete have more than one record with same name and birthday
Using COUNT() as an analytical function, we can try:
WITH cte AS (
SELECT *, COUNT(*) OVER (PARTITION BY name, birthday) cnt
FROM yourTable
)
SELECT id, name, birthday, clinic
FROM cte
WHERE cnt > 1;
try
select * from <table> where (name , birthday) in (
select name , birthday from <table> group by name, birthday having count(*)>1)
You can use an EXISTS condition:
select t1.*
from the_table t1
where exists (select *
from the_table t2
where t1.id <> t2.id
and (t1.name, t1.birthday) = (t2.name, t2.birthday));
Related
I'm working on a problem where I need to check if an ID exists in any previous records within another ID set, and create a tag if it does.
Suppose I have the following table
| client_id | order_date | supplier_id |
| 1 | 2022-01-01 | 1 |
| 1 | 2022-02-01 | 2 |
| 1 | 2022-03-01 | 1 |
| 1 | 2022-04-01 | 3 |
| 2 | 2022-05-01 | 1 |
| 2 | 2022-06-01 | 1 |
| 2 | 2022-07-01 | 2 |
And I want to create a column with a "is new supplier" tag (for each client):
| client_id | order_date | supplier_id | is_new_supplier|
| 1 | 2022-01-01 | 1 | True
| 1 | 2022-02-01 | 2 | True
| 1 | 2022-03-01 | 1 | False
| 1 | 2022-04-01 | 3 | True
| 2 | 2022-05-01 | 1 | True
| 2 | 2022-06-01 | 1 | False
| 2 | 2022-07-01 | 2 | True
First I tried doing this by creating a dense_rank and filtering out repeated ranks, but it didn't work:
with aux as (SELECT client_id,
order_date,
supplier_id
FROM table)
SELECT *, dense_rank() over (
partition by client_id
order by supplier_id
) as _dense_rank
FROM aux
Another way I thought about doing this, is by creating an auxiliary id with client_id + supplier_id, ordering by date and checking if the aux id exists in any previous row, but I don't know how to do this in SQL.
You are on the right track.
Instead of dense_rank, you can just use row_number and on your partition by add supplier id..
Don't forget to order by order_date
with aux as (SELECT client_id,
order_date,
supplier_id,
row_number() over (
partition by client_id, supplier_id
order by order_date
) as rank
FROM table)
SELECT client_id,
order_date,
supplier_id,
rank,
(rank = 1) as is_new_supplier
FROM aux
I'm struggling emulating a lead function to calculate the difference of (after date - current date)
I'm currently using mysql 5.7 to accomplish this. I have tried looking at various sources on stack overflow but I'm not sure how to get the result.
This is what I want:
What I currently have now is the same thing without the days column.
I would also like to know how to get a column of dates that grabs the date after the current date.
This seems to work (except for the unclear row=4):
DROP TABLE IF EXISTS table4;
CREATE TABLE table4 (id integer, user_id integer, product varchar(10), `date` date);
INSERT INTO table4 VALUES
(1,1,'item1','2020-01-01'),
(2,1,'item2','2020-01-01'),
(3,1,'item3','2020-01-02'),
(4,1,'item4','2020-01-02'),
(5,2,'item5','2020-01-06'),
(6,2,'item6','2020-01-09'),
(7,2,'item7','2020-01-09'),
(8,2,'item8','2020-01-10');
SELECT
id,
user_id,
product,
date,
(SELECT date FROM table4 t4 WHERE t4.id>t1.id LIMIT 1) x,
COALESCE(DATEDIFF((SELECT date FROM table4 t4 WHERE t4.id>t1.id LIMIT 1),date),0) as days
FROM table4 t1
output:
+ ------- + ------------ + ------------ + --------- + ----------- + --------- +
| id | user_id | product | date | x | days |
+ ------- + ------------ + ------------ + --------- + ----------- + --------- +
| 1 | 1 | item1 | 2020-01-01 | 2020-01-01 | 0 |
| 2 | 1 | item2 | 2020-01-01 | 2020-01-02 | 1 |
| 3 | 1 | item3 | 2020-01-02 | 2020-01-02 | 0 |
| 4 | 1 | item4 | 2020-01-02 | 2020-01-06 | 4 |
| 5 | 2 | item5 | 2020-01-06 | 2020-01-09 | 3 |
| 6 | 2 | item6 | 2020-01-09 | 2020-01-09 | 0 |
| 7 | 2 | item7 | 2020-01-09 | 2020-01-10 | 1 |
| 8 | 2 | item8 | 2020-01-10 | | 0 |
+ ------- + ------------ + ------------ + ---------- + ---------- + --------- +
The column x is only here for to see which date is returned from the subquery, and not really needed for the final result.
DBFIDDLE
EDIT: when there are no "gaps" in the numbering of id, you could do this to get a solution which should have more performance:
SELECT
t1.id,
t1.user_id,
t1.product,
t1.date,
COALESCE(DATEDIFF(t2.date,t1.date),0) as days
FROM table4 t1
LEFT JOIN table4 t2 on t2.id = t1.id+1
I added this to the DBFIDDLE
I have two tables and I am wanting to do an inner join between table_1 and table_2 but only when there is one row in table_2 that meets the join criteria.
For example:
table_1
id | name | age |
-----------------+------------------+--------------+
1 | john jones | 10 |
2 | pete smith | 15 |
3 | mary lewis | 12 |
4 | amy roberts | 13 |
table_2
id | name | age | hair | height |
-----------------+------------------+--------------+--------------+--------------+
1 | john jones | 10 | brown | 100 |
2 | john jones | 10 | blonde | 132 |
3 | mary lewis | 12 | brown | 146 |
4 | pete smith | 15 | black | 171 |
So I want to do a join when name is equal, but only when there is one corresponding matching name in table_2
So my results would look like this:
id | name | age | hair |
-----------------+------------------+--------------+--------------+
2 | pete smith | 15 | black |
3 | mary lewis | 12 | brown |
As you can see, John Jones isn't in the results as there are two corresponding rows in table_2.
My initial code looks like this:
select tb.id,tb.name,tb.age,sc.hair
from table_1 tb
inner join table_2 sc
on tb.name = sc.name and tb.age = sc.age
Can I apply a clause within the join so that it only joins on rows which are unique matches?
Group by all columns and apply having count(*) = 1
select tb.id,tb.name,tb.age,sc.hair
from table_1 tb
join table_2 sc
on tb.name = sc.name and tb.age = sc.age
group by tb.id,tb.name,tb.age,sc.hair
having count(*) = 1
The interesting thing to note is that you don’t need the aggregate expression (in the case count(*) )in the select clause.
TIL about tablefunc and crosstab. At first I wanted to "group data by columns" but that doesn't really mean anything.
My product sales look like this
product_id | units | date
-----------------------------------
10 | 1 | 1-1-2018
10 | 2 | 2-2-2018
11 | 3 | 1-1-2018
11 | 10 | 1-2-2018
12 | 1 | 2-1-2018
13 | 10 | 1-1-2018
13 | 10 | 2-2-2018
I would like to produce a table of products with months as columns
product_id | 01-01-2018 | 02-01-2018 | etc.
-----------------------------------
10 | 1 | 2
11 | 13 | 0
12 | 0 | 1
13 | 20 | 0
First I would group by month, then invert and group by product, but I cannot figure out how to do this.
After enabling the tablefunc extension,
SELECT product_id, coalesce("2018-1-1", 0) as "2018-1-1"
, coalesce("2018-2-1", 0) as "2018-2-1"
FROM crosstab(
$$SELECT product_id, date_trunc('month', date)::date as month, sum(units) as units
FROM test
GROUP BY product_id, month
ORDER BY 1$$
, $$VALUES ('2018-1-1'::date), ('2018-2-1')$$
) AS ct (product_id int, "2018-1-1" int, "2018-2-1" int);
yields
| product_id | 2018-1-1 | 2018-2-1 |
|------------+----------+----------|
| 10 | 1 | 2 |
| 11 | 13 | 0 |
| 12 | 0 | 1 |
| 13 | 10 | 10 |
I have one table name called Tab1. I would like to get all date even if any one of the days is missing also.
+-------------------+--------------------------+
|Name | dateCheck |
+-------------------+--------------------------+
| 1 | 2016-01-01 00:00:00.000 |
| 2 | 2016-01-02 00:00:00.000 |
| 3 | 2016-01-05 00:00:00.000 |
| 4 | 2016-01-07 00:00:00.000 |
+-------------------+--------------------------+
I need output like below :
+-------------------+--------------------------+
|Name | dateCheck |
+-------------------+--------------------------+
| 1 | 2016-01-01 00:00:00.000 |
| 2 | 2016-01-02 00:00:00.000 |
| 0 | 2016-01-03 00:00:00.000 |
| 0 | 2016-01-04 00:00:00.000 |
| 3 | 2016-01-05 00:00:00.000 |
| 0 | 2016-01-06 00:00:00.000 |
| 4 | 2016-01-07 00:00:00.000 |
You may use a calendar table:
SELECT
COALESCE(t2.Name, 0) AS Name,
t1.dateCheck
FROM
(
SELECT '2016-01-01' AS dateCheck UNION ALL
SELECT '2016-01-02' UNION ALL
SELECT '2016-01-03' UNION ALL
SELECT '2016-01-04' UNION ALL
SELECT '2016-01-05' UNION ALL
SELECT '2016-01-06' UNION ALL
SELECT '2016-01-07'
) t1
LEFT JOIN yourTable t2
ON t1.dateCheck = t2.dateCheck;