I am trying to write a query that will return counted records from the time they were created.
The primary key is a particular house which is unique. Another variable is bidder. The house to bidder relationship is 1:1 but there can be multiple records for each bidder (different houses). Another variable is a count (CASE) of results of previous bids that were won.
I want to be able to set the count to return the number of previous bids won at the time each house record was created.
Currently, my query (shown below) logs the overall number of previous bids won regardless of the time the house record was created. Any help would be great!
Example:
SELECT h.house_id,
h.bidder_id,
h.created_date,
b.previous_bids_won
FROM house h
LEFT JOIN bid_transactions b
ON h.house_id = b.house_id
LEFT JOIN (
SELECT bidder_id,
COUNT(CASE WHEN created_date IS NOT NULL AND transaction_kind = 'Successful Bid' THEN 1 END) previous_bids_won
FROM bid_transactions
GROUP BY user_id
) b
ON h.bidder_id = b.bidder_id
ORDER BY h.created_date DESC
Example Data:
house_id bidder_id created_date previous_bids_won
1 1 2016-03-21 0
2 2 2016-02-10 1
3 2 2016-01-15 1
4 3 2016-01-01 0
Desired Data:
house_id bidder_id created_date previous_bids_won
1 1 2016-03-21 0
2 2 2016-02-10 1
3 2 2016-01-15 0
4 3 2016-01-01 0
If I understand correctly, you just want a cumulative sum:
SELECT h.house_id, h.bidder_id, h.created_date,
SUM(CASE WHEN created_date IS NOT NULL AND transaction_kind = 'Successful Bid'
THEN 1
ELSE 0
END) OVER (PARTITION BY h.bidder_id ORDER BY h.created_date
) as previous_bids_won
FROM house h LEFT JOIN
bid_transactions b
ON h.house_id = b.house_id;
Related
I have two tables. Data in the first table is:
ID Username
1 Dan
2 Eli
3 Sean
4 John
Second Table Data:
user_id Status_id
1 2
1 3
4 1
3 2
2 3
1 1
3 3
3 3
3 3
. .
goes on goes on
These are my both tables.
I want to find the frequency of individual users doing 'status_id'
My expected result is:
username status_id(1) status_id(2) status_id(3)
Dan 1 1 1
Eli 0 0 1
Sean 0 1 2
John 1 0 0
My current code is:
SELECT b.username , COUNT(a.status_id)
FROM masterdb.auth_user b
left outer join masterdb.xmlform_joblist a
on a.user1_id = b.id
GROUP BY b.username, b.id, a.status_id
This gives me the separate count but in a single row without mentioning which status_id each column represents
This is called pivot and it works in two steps:
extracts the data for the specific field using a CASE statement
aggregates the data on users, to make every field value lie on the same record for each user
SELECT Username,
SUM(CASE WHEN status_id = 1 THEN 1 END) AS status_id_1,
SUM(CASE WHEN status_id = 2 THEN 1 END) AS status_id_2,
SUM(CASE WHEN status_id = 3 THEN 1 END) AS status_id_3
FROM t2
INNER JOIN t1
ON t2.user_id = t1._ID
GROUP BY Username
ORDER BY Username
Check the demo here.
Note: This solution assumes that there are 3 status_id values. If you need to generalize on the amount of status ids, you would require a dynamic query. In any case, it's better to avoid dynamic queries if you can.
DBMS : postgreSQL
my problem :
In my database I have a person table with id and birth date, an events table that links a person, an event (id_event) and a date, an age table used for grouping ages. In the real database the person table is about 40 millions obs, and events 3 times bigger.
I need to produce a report (sum and cumul of X events) by age (age_group) and date (event_date). There isn't any problem to count the number of events by date. The problem lies with the cumul : contrary to other variables (sex for example), a person grow older and changes age group
as time passes, so for a given age group the cumul can increase then decrease. I want that the event's cumul, on every date in my report, uses the age of the persons on these dates.
Example of my inputs and desired output
The only way I found is to do a Cartesian product on the tables person and the dates v_dates, so it's easy to follow an event and make it change age_group. The code below uses this method.
BUT I can't use a cartesian product on my real data (makes a table way too big) and I need to use another method.
reproductible example
In this simplified example I want to produce a report by month from 2020-07-01 to 2022-07-01 (view v_dates). In reality I need to produce the same report by day but the logic remains the same.
My inputs
/* create table person*/
DROP TABLE IF EXISTS person;
CREATE TABLE person
(
person_id varchar(1),
person_birth_date date
);
INSERT INTO person
VALUES ('A', '2017-01-01'),
('B', '2016-07-01');
person_id
person_birth_date
A
2000-10-01
B
2010-02-01
/* create table events*/
DROP TABLE IF EXISTS events;
CREATE TABLE events
(
person_id varchar(1),
event_id integer,
event_date date
);
INSERT INTO events
VALUES ('A', 1, '2020-07-01'),
('A', 2, '2021-07-01'),
('B', 1, '2021-01-01'),
('B', 2, '2022-01-01');
person_id
event_id
event_date
A
1
2020-01-01
A
2
2021-01-01
B
1
2020-07-01
B
2
2021-01-01
/* create table age*/
DROP TABLE IF EXISTS age;
CREATE TABLE age
(
age integer,
age_group varchar(8)
);
INSERT INTO age
VALUES (0,'[0-4]'),
(1,'[0-4]'),
(2,'[0-4]'),
(3,'[0-4]'),
(4,'[0-4]'),
(5,'[5-9]'),
(6,'[5-9]'),
(7,'[5-9]'),
(8,'[5-9]'),
(9,'[5-9]');
/* create view dates : contains monthly dates from 2020-07-01 to 2022-07-01*/
CREATE or replace view v_dates AS
SELECT GENERATE_SERIES('2020-07-01'::date, '2022-07-01'::date, '6 month')::date as event_date;
age
age_group
0
[0-4]
1
[0-4]
5
[5-9]
My current method using a cartesian product
CROSS JOIN person * v_dates
with a LEFT JOIN to get info from table events
with a LEFT JOIN to get age_group from table age
CREATE or replace view v_person_event AS
SELECT
pdev.person_id,
pdev.event_date,
pdev.age,
ag.age_group,
pdev.event1,
pdev.event2
FROM
(
SELECT pd.person_id,
pd.event_date,
date_part('year', age(pd.event_date::TIMESTAMP, pd.person_birth_date::TIMESTAMP)) as age,
CASE WHEN ev.event_id = 1 THEN 1 else 0 END as event1,
CASE WHEN ev.event_id = 2 THEN 1 else 0 END as event2
FROM
(
SELECT *
FROM person
CROSS JOIN v_dates
) pd
LEFT JOIN events ev
on pd.person_id = ev.person_id
and pd.event_date = ev.event_date
) pdev
Left JOIN age as ag on pdev.age = ag.age
ORDER by pdev.person_id, pdev.event_date;
add columns event1_cum and event2_cum
CREATE or replace view v_person_event_cum AS
SELECT *,
SUM(event1) OVER (PARTITION BY person_id ORDER BY event_date) event1_cum,
SUM(event2) OVER (PARTITION BY person_id ORDER BY event_date) event2_cum
FROM v_person_event;
SELECT * FROM v_person_event_cum;
person_id
event_date
age
age_group
event1
event2
event1_cum
event2_cum
A
2020-07-01
3
[0-4]
1
0
1
0
A
2021-01-01
4
[0-4]
0
0
1
0
A
2021-07-01
4
[0-4]
0
1
1
1
A
2022-01-01
5
[5-9]
0
0
1
1
A
2022-07-01
5
[5-9]
0
0
1
1
B
2020-07-01
4
[0-4]
0
0
0
0
B
2021-01-01
4
[0-4]
1
0
1
0
B
2021-07-01
5
[5-9]
0
0
1
0
B
2022-01-01
5
[5-9]
0
1
1
1
B
2022-07-01
6
[5-9]
0
0
1
1
desired output : create a report grouped by variables age_group and event_date
SELECT
age_group,
event_date,
SUM(event1) as event1,
SUM(event2) as event2,
SUM(event1_cum) as event1_cum,
SUM(event2_cum) as event2_cum
FROM v_person_event_cum
GROUP BY age_group, event_date
ORDER BY age_group, event_date;
age_group
event_date
event1
event2
event1_cum
event2_cum
[0-4]
2020-07-01
1
0
1
0
[0-4]
2021-01-01
1
0
2
0
[0-4]
2021-07-01
0
1
1
1
[5-9]
2021-07-01
0
0
1
0
[5-9]
2022-01-01
0
1
2
2
This is why this is not an ordinary cumul : for the age_group [0-4], event1_cum goes from 2 at '2021-01-01' to 1 at '2021-07-01' because A was in [0-4] at the time of the event 1, still in [0-4] at '2021-01-01' but in [5-9] at 2021-07-01
When we read the report:
the 2021-01-01, there was 2 person between 0 and 4 (at that date) who had event1 and 0 person who had event2.
the 2021-07-01, there was 1 person between 0 and 4 who had event1 and 1 person who had event2.
I can't get a solution to this problem without using a cartesian Product...
Thanks in advance!
I want to create a rank column using existing rank and binary columns. Suppose for example a table with ID, RISK, CONTACT, DATE. The existing rank is RISK, say 1,2,3,NULL, with 3 being the highest. The binary-valued is CONTACT with 0,1 or FAILURE/SUCESS. I want to create a new RANK that will order by RISK once a certain number of successful contacts has been exceeded.
For example, suppose the constraint is a minimum of 2 successful contacts. Then the rank should be created as follows in the two instances below:
Instance 1. Three ID, all have a min of two successful contacts. In that case the rank mirrors the risk:
ID risk contact date rank
1 3 S 1 3
1 3 S 2 3
1 3 F 3 3
1 3 F 4 3
2 2 S 1 2
2 2 S 2 2
2 2 F 3 2
2 2 F 4 2
3 1 S 1 1
3 1 S 2 1
3 1 S 3 1
Instance 2. Suppose ID=1 has only one successful contact. In that case it is relegated to the lowest rank, rank=1, while ID=2 gets the highest value, rank=3, and ID=3 maps to rank=2 because it satisfies the constraint but has a lower risk value than ID=2:
ID risk contact date rank
1 3 S 1 1
1 3 F 2 1
1 3 F 3 1
1 3 F 4 1
2 2 S 1 3
2 2 S 2 3
2 2 F 3 3
2 2 F 4 3
3 1 S 1 2
3 1 S 2 2
3 1 S 3 2
This is SQL, specifically Hive. Thanks in advance.
Edit - I think Gordon Linoff's code does it correctly. In the end, I used three interim tables. The code looks like that:
First,
--numerize risk, contact
select A.* ,
case when A.risk = 'H' then 3
when A.risk = 'M' then 2
when A.risk = 'L' then 1
when A.risk is NULL then NULL
when A.risk = 'NULL' then NULL
else -999 end as RISK_RANK,
case when A.contact = 'Successful' then 1
else NULL end as success
Second,
-- sum_successes_by_risk
select A.* ,
B.sum_successes_by_risk
from T as A
inner join
(select A.person, A.program, A.risk, sum(a.success) as sum_successes_by_risk
from T as A
group by A.person, A.program, A.risk
) as B
on A.program = B.program
and A.person = B.person
and A.risk = B.risk
Third,
--Create table that contains only max risk category
select A.* ,
B.max_risk_rank
from T as A
inner join
(select A.person, max(A.risk_rank) as max_risk_rank
from T as A
group by A.person
) as B
on A.person = B.person
and A.risk_rank = B.max_risk_rank
This is hard to follow, but I think you just want window functions:
select t.*,
(case when sum(case when contact = 'S' then 1 else 0 end) over (partition by id) >= 2
then risk
else 1
end) as new_risk
from t;
I have a table with data as shown below (the table is built every day with current date, but I left off that field for ease of reading).
This table keeps track of people and the doors they enter on a daily basis.
Table entrance_t:
id entrance entered
------------------------
1 a 0
1 b 0
1 c 0
1 d 0
2 a 1
2 b 0
2 c 0
2 d 0
3 a 0
3 b 1
3 c 1
3 d 1
My goal is to report on people and count entrances not used(grouping on people), but ONLY if they entered(entered=1).
So using the above table, I would like the results of query to be...
id count
----------
2 3
3 1
(id=2 did not use 3 of the entrances and id=3 did not use 1)
I tried queries(some with inner joins on two instances of same table) and I can get the entrances not used, but it's always for everybody. Like this...
id count
----------
1 4
2 3
3 1
How do I not display results id=1 since they did not enter at all?
Thank you,
You could use conditional aggregation:
SELECT id, count(CASE WHEN entered = 0 THEN 1 END) AS cnt
FROM entrance_t
GROUP BY id
HAVING count(CASE WHEN entered = 1 THEN 1 END) > 0;
DBFiddle Demo
I m working on weird SQL query
Patient_ID Count order_no
1 1 1
2 1 2
2 0 3
2 0 4
3 1 5
3 0 6
where I need to count the patient as above, for every new patient , the count column is 1.
If repeated , the below entry it should be 0
I m confused how should make that work in SQL
In order to make the first entry 1 and all subsuqent entries 0, I believe you need a ranking with partition by the order number. Please checkout the sqlfiddle below to test results.
http://www.sqlfiddle.com/#!3/4e2e2/17/0
SELECT
patient_id
,CASE WHEN r.rank = 1
THEN 1
ELSE 0
END
, order_number
FROM
(
SELECT
order_number
,patient_id
,ROW_NUMBER() OVER (PARTITION BY patient_id ORDER BY order_number)[rank]
FROM
PatientTable
)r