Display values for specific time-frame - sql

Question

when I run below select:
select name, time, value from table1 where name like '%Z' or '%V'
I got result:
I need to do two things:
1) query will be run every hour, so if we have 12.00.00PM range should be between (11 and 12> PM, if it's 02.00.00AM range will be (01 and 02> AM
2) second thing is to display avg(value) for name ending by '%Z' or '%V' into one row, but into two columns
Below is example of desirable result, when query was run at 12.00.00 PM:

Answer 1

You are asking for three things, which can be thought of as three steps. Getting the time window is fairly straightforward, and only slightly complicated by your column being a timestamp rather than a date. You implied this will run on the hour, but it's possible it will be slightly afterwards - maybe a second or two? - so it's probably safer to take that into account. You can use the trunc() function to modify a date value to the required precision, so to only look at the current hour you would truncate to HH[24]. You can then cast that back to a timestamp. And you can use interval arithmetic to find the hour before that:
alter session set nls_date_format = 'YYYY-MM-DD HH24:MI:SS';
alter session set nls_timestamp_format = 'YYYY-MM-DD HH24:MI:SS.FF3';
alter session set nls_timestamp_tz_format = 'YYYY-MM-DD HH24:MI:SS.FF3 TZR';
select systimestamp,
trunc(systimestamp, 'HH24') as a,
cast(trunc(systimestamp, 'HH24') as timestamp) as b,
cast(trunc(systimestamp, 'HH24') as timestamp) - interval '1' hour as c
from dual;
SYSTIMESTAMP A B C
------------------------------ ------------------- ----------------------- -----------------------
2017-03-01 09:25:39.342 +00:00 2017-03-01 09:00:00 2017-03-01 09:00:00.000 2017-03-01 08:00:00.000
The alter session commands are just to control how the different data types are displayed, for comparison. (Don't rely on NLS settings in your real code; use to_char() for final formatting of datetime values as strings).
Notice that the result of the truncation is now a date (A in that output), so I've cast it back to a timestamp (B). The range you want is essentially time >= A and time < B. And you could use sysdate instead of systimestamp as the input to trunc().
For your sample data using systimestamp or sysdate isn't going to find anything, so I'll use a fake fixed time for the rest, generated in a CTE for separation. Where I've used now from the CTE, you would use systimestamp or sysdate.
The second part is to get the average for each name within that time period. That's simple aggregation:
with fake_time(now) as (
select timestamp '2017-02-10 13:01:07' from dual
)
select name,
avg(value) as avg_value,
cast(trunc(now, 'HH24') as timestamp) as time
from fake_time
join table1 on time >= cast(trunc(now, 'HH24') as timestamp) - interval '1' hour
and time < cast(trunc(now, 'HH24') as timestamp)
group by name, now;
NAME AVG_VALUE TIME
------- ---------- -----------------------
QWER1_Z 20 2017-02-10 13:00:00.000
QWER1_V 35 2017-02-10 13:00:00.000
TEST1_Z 15 2017-02-10 13:00:00.000
TEST1_V 10 2017-02-10 13:00:00.000
To pick up the rows you want I've made the fake time 13:00 instead of 12:00. The average you showed for TEST1_V was also wrong.
The next stage it pivoting those into the format you wanted, as a single row. For that you can add the root (i.e. TEST1 or QWER1) and the letter (Z or V) as extra columns in the result set, and then use that as the subquery for the pivot operation - this requires 11g or higher:
with fake_time(now) as (
select timestamp '2017-02-10 13:01:07' from dual
)
select z_name, z_value, v_name, v_value, time
from (
select substr(name, 1, length(name) - 2) as root,
substr(name, -1) as zv,
name,
avg(value) as avg_value,
cast(trunc(now, 'HH24') as timestamp) as time
from fake_time
join table1 on time >= cast(trunc(now, 'HH24') as timestamp) - interval '1' hour
and time < cast(trunc(now, 'HH24') as timestamp)
group by substr(name, 1, length(name) - 2), name, now
)
pivot (max(name) as name, max(avg_value) as value for (zv) in ('Z' as z, 'V' as v));
Z_NAME Z_VALUE V_NAME V_VALUE TIME
------- ---------- ------- ---------- -----------------------
TEST1_Z 15 TEST1_V 10 2017-02-10 13:00:00.000
QWER1_Z 20 QWER1_V 35 2017-02-10 13:00:00.000
There may be another step required; in your sample output you included a list of the original values that were averaged, but didn't confirm if you actually wanted those or if they were just to show how the average was caculated to help us understand what you needed to do. If you really do want to include that you can use listagg() and concatenation to build up the 'average' string before pivoting:
'avg(' || listagg(value, ',') within group (order by value) || ') = ' || avg(value)
as avg_value,
to get
Z_NAME Z_VALUE V_NAME V_VALUE TIME
------- -------------------- ------- -------------------- -----------------------
TEST1_Z avg(10,20) = 15 TEST1_V avg(10) = 10 2017-02-10 13:00:00.000
QWER1_Z avg(20) = 20 QWER1_V avg(30,40) = 35 2017-02-10 13:00:00.000
As I said earlier, I've only used the fake_date CTE to get a date that matches your sample data. Your real query will be more like:
select z_name, z_value, v_name, v_value, time
from (
select substr(name, 1, length(name) - 2) as root,
substr(name, -1) as zv,
name,
avg(value) as avg_value,
cast(trunc(sysdate, 'HH24') as timestamp) as time
from table1
where time >= cast(trunc(sysdate, 'HH24') as timestamp) - interval '1' hour
and time < cast(trunc(sysdate, 'HH24') as timestamp)
group by substr(name, 1, length(name) - 2), name
)
pivot (max(name) as name, max(avg_value) as value for (zv) in ('Z' as z, 'V' as v));

Answer 2

select T1.Z, T1.V from (
(select avg(values) from table1 where name like '%Z' and time between sysdate and sysdate - interval '1' group by INSTR(name,'Z')) Z,
(select avg(values) from table1 where name like '%V' and time between sysdate and sysdate - interval '1' group by INSTR(name,'V')) V ) T1