Question

I have the following Oracle query:

SELECT id,
       DECODE(state, 'Open', state_in, NULL) AS open_in,
       DECODE(state, 'Not Open', state_in, NULL) AS open_out,
FROM (
       SELECT id,
              CASE WHEN state = 'Open'
                   THEN 'Open'
                   ELSE 'Not Open'
              END AS state,
              TRUNC(state_time) AS state_in
       FROM ...
     )

This gives me data like the following:

id  open_in              open_out
1   2009-03-02 00:00:00
1                        2009-03-05 00:00:00
1   2009-03-11 00:00:00
1                        2009-03-26 00:00:00
1                        2009-03-24 00:00:00
1                        2009-04-13 00:00:00

What I would like is data like this:

id  open_in              open_out
1   2009-03-02 00:00:00  2009-03-05 00:00:00
1   2009-03-11 00:00:00  2009-03-24 00:00:00

That is, keep all the unique pairs of id/open_in and pair with them the earliest open_out that follows open_in. There can be any number of unique open_in values for a given id, and any number of unique open_out values. It is possible that a unique id/open_in will not have a matching open_out value, in which case open_out should be null for that row.

I feel like some analytic function, maybe LAG or LEAD, would be useful here. Perhaps I need MIN used with a PARTITION.

Answer 1

It can be done a little bit simpler. First let’s create a sample table:

SQL> create table mytable (id,state,state_time)
  2  as
  3  select 1, 'Open', date '2009-03-02' from dual union all
  4  select 1, 'Closed', date '2009-03-05' from dual union all
  5  select 1, 'Open', date '2009-03-11' from dual union all
  6  select 1, 'Shut down', date '2009-03-26' from dual union all
  7  select 1, 'Wiped out', date '2009-03-24' from dual union all
  8  select 1, 'Demolished', date '2009-04-13' from dual
  9  /

Table created.

The data equals the output of your select statement:

SQL> SELECT id,
  2         DECODE(state, 'Open', state_in, NULL) AS open_in,
  3         DECODE(state, 'Not Open', state_in, NULL) AS open_out
  4  FROM (
  5         SELECT id,
  6                CASE WHEN state = 'Open'
  7                     THEN 'Open'
  8                     ELSE 'Not Open'
  9                END AS state,
 10                TRUNC(state_time) AS state_in
 11         FROM mytable
 12       )
 13  /

        ID OPEN_IN             OPEN_OUT
---------- ------------------- -------------------
         1 02-03-2009 00:00:00
         1                     05-03-2009 00:00:00
         1 11-03-2009 00:00:00
         1                     26-03-2009 00:00:00
         1                     24-03-2009 00:00:00
         1                     13-04-2009 00:00:00

6 rows selected.

And here is the slightly easier query:

SQL> select id
  2       , min(case when state = 'Open' then state_time end)  open_in
  3       , min(case when state != 'Open' then state_time end) open_out
  4    from ( select id
  5                , state
  6                , state_time
  7                , max(x) over (partition by id order by state_time) grp
  8             from ( select id
  9                         , state
 10                         , state_time
 11                         , case state
 12                           when 'Open' then
 13                             row_number() over (partition by id order by state_time)
 14                           end x
 15                      from mytable
 16                  )
 17         )
 18   group by id
 19       , grp
 20   order by id
 21       , open_in
 22  /

        ID OPEN_IN             OPEN_OUT
---------- ------------------- -------------------
         1 02-03-2009 00:00:00 05-03-2009 00:00:00
         1 11-03-2009 00:00:00 24-03-2009 00:00:00

2 rows selected.

Regards,
Rob.