Calculating concurrency from a set of ranges - sql

Question

I have a set of rows containing a start timestamp and a duration. I want to perform various summaries using the overlap or concurrency.
For example: peak daily concurrency, peak concurrency grouped on another column.
Example data:
timestamp,duration
2016-01-01 12:00:00,300
2016-01-01 12:01:00,300
2016-01-01 12:06:00,300
I would like to know that peak for the period was 12:01:00-12:05:00 at 2 concurrent.
Any ideas on how to achieve this using BigQuery or, less exciting, a Map/Reduce job?

Answer 1

For a per-minute resolution, with session lengths of up to 255 minutes:
SELECT session_minute, COUNT(*) c
FROM (
SELECT start, DATE_ADD(start, i, 'MINUTE') session_minute FROM (
SELECT * FROM (
SELECT TIMESTAMP("2015-04-30 10:14") start, 7 minutes
),(
SELECT TIMESTAMP("2015-04-30 10:15") start, 12 minutes
),(
SELECT TIMESTAMP("2015-04-30 10:15") start, 12 minutes
),(
SELECT TIMESTAMP("2015-04-30 10:18") start, 12 minutes
),(
SELECT TIMESTAMP("2015-04-30 10:23") start, 3 minutes
)
) a
CROSS JOIN [fh-bigquery:public_dump.numbers_255] b
WHERE a.minutes>b.i
)
GROUP BY 1
ORDER BY 1

Answer 2

STEP 1 - First you need find all periods (start and end) with
respective concurrent entries
SELECT ts AS start, LEAD(ts) OVER(ORDER BY ts) AS finish,
SUM(entry) OVER(ORDER BY ts) AS concurrent_entries
FROM (
SELECT ts, SUM(entry)AS entry
FROM
(SELECT ts, 1 AS entry FROM yourTable),
(SELECT DATE_ADD(ts, duration, 'second') AS ts, -1 AS entry FROM yourTable)
GROUP BY ts
HAVING entry != 0
)
ORDER BY ts
Assuming input as below
(SELECT TIMESTAMP('2016-01-01 12:00:00') AS ts, 300 AS duration),
(SELECT TIMESTAMP('2016-01-01 12:01:00') AS ts, 300 AS duration),
(SELECT TIMESTAMP('2016-01-01 12:06:00') AS ts, 300 AS duration),
(SELECT TIMESTAMP('2016-01-01 12:07:00') AS ts, 300 AS duration),
(SELECT TIMESTAMP('2016-01-01 12:10:00') AS ts, 300 AS duration),
(SELECT TIMESTAMP('2016-01-01 12:11:00') AS ts, 300 AS duration)
the output of above query will look somehow like this:
start finish concurrent_entries
2016-01-01 12:00:00 UTC 2016-01-01 12:01:00 UTC 1
2016-01-01 12:01:00 UTC 2016-01-01 12:05:00 UTC 2
2016-01-01 12:05:00 UTC 2016-01-01 12:07:00 UTC 1
2016-01-01 12:07:00 UTC 2016-01-01 12:10:00 UTC 2
2016-01-01 12:10:00 UTC 2016-01-01 12:12:00 UTC 3
2016-01-01 12:12:00 UTC 2016-01-01 12:15:00 UTC 2
2016-01-01 12:15:00 UTC 2016-01-01 12:16:00 UTC 1
2016-01-01 12:16:00 UTC null 0
You might still want to polish above query a little - but mainly it does what you need
STEP 2 - now you can do any stats off of above result
For example peak on whole period:
SELECT
start, finish, concurrent_entries, RANK() OVER(ORDER BY concurrent_entries DESC) AS peak
FROM (
SELECT ts AS start, LEAD(ts) OVER(ORDER BY ts) AS finish,
SUM(entry) OVER(ORDER BY ts) AS concurrent_entries
FROM (
SELECT ts, SUM(entry)AS entry FROM
(SELECT ts, 1 AS entry FROM yourTable),
(SELECT DATE_ADD(ts, duration, 'second') AS ts, -1 AS entry FROM yourTable)
GROUP BY ts
HAVING entry != 0
)
)
ORDER BY peak