Get last known record per month in BigQuery - google-bigquery

Question

Account balance collection, that shows the account balance of a customer at a given day:
+---------------+---------+------------+
| customer_id | value | timestamp |
+---------------+---------+------------+
| 1 | -500 | 2019-10-12 |
| 1 | -300 | 2019-10-11 |
| 1 | -200 | 2019-10-10 |
| 1 | 0 | 2019-10-09 |
| 2 | 200 | 2019-09-10 |
| 1 | 600 | 2019-09-02 |
+---------------+---------+------------+
Notice, that customer #2 had no updates to his account balance in October.
I want to get the last account balance per customer per month. If there has been no account balance update for a customer in a given month, the last known account balance should be transferred to the current month. The result should look like that:
+---------------+---------+------------+
| customer_id | value | timestamp |
+---------------+---------+------------+
| 1 | -500 | 2019-10-12 |
| 2 | 200 | 2019-10-10 |
| 2 | 200 | 2019-09-10 |
| 1 | 600 | 2019-09-02 |
+---------------+---------+------------+
Since the account balance of customer #2 was not updated in October but in September, we create a copy of the row from September changing the date to October. Any ideas how to achieve this in BigQuery?

Answer 1

Below is for BigQuery Standard SQL
#standardSQL
WITH customers AS (
SELECT DISTINCT customer_id FROM `project.dataset.table`
), months AS (
SELECT month FROM (
SELECT DATE_TRUNC(MIN(timestamp), MONTH) min_month, DATE_TRUNC(MAX(timestamp), MONTH) max_month
FROM `project.dataset.table`
), UNNEST(GENERATE_DATE_ARRAY(min_month, max_month, INTERVAL 1 MONTH)) month
)
SELECT customer_id,
IFNULL(value, LEAD(value) OVER(win)) value,
IFNULL(timestamp, DATE_ADD(LEAD(timestamp) OVER(win), INTERVAL DATE_DIFF(month, LEAD(month) OVER(win), MONTH) MONTH)) timestamp
FROM months, customers
LEFT JOIN (
SELECT DATE_TRUNC(timestamp, MONTH) month, customer_id,
ARRAY_AGG(STRUCT(value, timestamp) ORDER BY timestamp DESC LIMIT 1)[OFFSET(0)].*
FROM `project.dataset.table`
GROUP BY month, customer_id
) USING(month, customer_id)
WINDOW win AS (PARTITION BY customer_id ORDER BY month DESC)
if to apply to sample data from your question - as it is in below example
#standardSQL
WITH `project.dataset.table` AS (
SELECT 1 customer_id, -500 value, DATE '2019-10-12' timestamp UNION ALL
SELECT 1, -300, '2019-10-11' UNION ALL
SELECT 1, -200, '2019-10-10' UNION ALL
SELECT 2, 200, '2019-09-10' UNION ALL
SELECT 2, 100, '2019-08-11' UNION ALL
SELECT 2, 50, '2019-07-12' UNION ALL
SELECT 1, 600, '2019-09-02'
), customers AS (
SELECT DISTINCT customer_id FROM `project.dataset.table`
), months AS (
SELECT month FROM (
SELECT DATE_TRUNC(MIN(timestamp), MONTH) min_month, DATE_TRUNC(MAX(timestamp), MONTH) max_month
FROM `project.dataset.table`
), UNNEST(GENERATE_DATE_ARRAY(min_month, max_month, INTERVAL 1 MONTH)) month
)
SELECT customer_id,
IFNULL(value, LEAD(value) OVER(win)) value,
IFNULL(timestamp, DATE_ADD(LEAD(timestamp) OVER(win), INTERVAL DATE_DIFF(month, LEAD(month) OVER(win), MONTH) MONTH)) timestamp
FROM months, customers
LEFT JOIN (
SELECT DATE_TRUNC(timestamp, MONTH) month, customer_id,
ARRAY_AGG(STRUCT(value, timestamp) ORDER BY timestamp DESC LIMIT 1)[OFFSET(0)].*
FROM `project.dataset.table`
GROUP BY month, customer_id
) USING(month, customer_id)
WINDOW win AS (PARTITION BY customer_id ORDER BY month DESC)
-- ORDER BY month DESC, customer_id
result is
Row customer_id value timestamp
1 1 -500 2019-10-12
2 2 200 2019-10-10
3 1 600 2019-09-02
4 2 200 2019-09-10
5 1 null null
6 2 100 2019-08-11
7 1 null null
8 2 50 2019-07-12

Answer 2

The following query should mostly answer your question by creating a 'month-end' record for each customer for every month and getting the most recent balance:
with
-- Generate a set of months
month_begins as (
select dt from unnest(generate_date_array('2019-01-01','2019-12-01', interval 1 month)) dt
),
-- Get the month ends
month_ends as (
select date_sub(date_add(dt, interval 1 month), interval 1 day) as month_end_date from month_begins
),
-- Cross Join and group so we get 1 customer record for every month to account for
-- situations where customer doesn't change balance in a month
user_month_ends as (
select
customer_id,
month_end_date
from `project.dataset.table`
cross join month_ends
group by 1,2
),
-- Fan out so for each month end, you get all balances prior to month end for each customer
values_prior_to_month_end as (
select
customer_id,
value,
timestamp,
month_end_date
from `project.dataset.table`
inner join user_month_ends using(customer_id)
where timestamp <= month_end_date
),
-- Order by most recent balance before month end, even if it was more than 1+ months ago
ordered as (
select
*,
row_number() over (partition by customer_id, month_end_date order by timestamp desc) as my_row
from values_prior_to_month_end
),
-- Finally, select only the most recent record for each customer per month
final as (
select
* except(my_row)
from ordered
where my_row = 1
)
select * from final
order by customer_id, month_end_date desc
A few caveats:
I did not order results to match your desired result set, and I also kept a month-end date to illustrate the concept. You can easily change the ordering and exclude unneeded fields.
In the month_begins CTE, I set a range of months into the future, so your result set will contain the most recent balance of 'future months'. To make this a bit prettier, consider changing '2019-12-01' to 'current_date()' and your query will always return to the end of the current month.
Your timestamp field looks to be dates, so I used date logic, but you should be able to apply the same principles to use timestamp logic if your underlying fields are actual timestamps.
In your result set, I'm not sure why your 2nd row (customer 2) would have a timestamp of '2019-10-10', that seems arbitrary as customer 2 has no 2nd balance record.
I purposefully split the logic into several CTEs so I could comment on each step easier, you could definitely perform several steps in the same code block for a more condensed query.