I'm new to SQL and have been battling for days to understand how to search backwards through previous rows based on time.
I found the Windows Lag Function may help me here but I have not found a way to define a time period for it to search back though.
If I enter: -
SELECT food_word_1,
date,
lead(food_word_1,2) OVER (ORDER BY date DESC) as prev_food_word_1
FROM bookmark
WHERE mood = 'allergies'"
The result looks like the following: -
food_word_1 | date | prev_food_word_1
-------------+----------------------------+------------------
burritos | 2019-02-01 09:56:40.943341 |
burritos | 2019-02-01 09:56:31.56869 |
burritos | 2019-02-01 09:56:31.34883 | burritos
cereal bar | 2019-01-10 07:24:29.602226 | burritos
almonds | 2019-01-09 08:37:34.223448 | burritos
fennel | 2019-01-09 08:35:44.186134 | cereal bar
I get a result searching back 2 rows but what I would like to do is have this searching backwards (lag) for rows 36 hours previous instead of me having to define the number of rows with no time associated with them.
Does anyone know the best approach for this please?
Thanks
This answer is for Oracle, because the question was originally tagged Oracle.
Oracle supports range between with number ranges, but these can also be used for dates. Try this:
SELECT food_word_1,
date,
lead(food_word_1) OVER (ORDER BY date DESC RANGE BETWEEN 1.5 PRECEDING AND CURRENT ROW) as prev_food_word_1
FROM bookmark
WHERE mood = 'allergies';
Related
I'm currently running timescaleDB. I have a table that looks similar to the following
one_day | name | metric_value
------------------------+---------------------
2022-05-30 00:00:00+00 | foo | 400
2022-05-30 00:00:00+00 | bar | 200
2022-06-01 00:00:00+00 | foo | 800
2022-06-01 00:00:00+00 | bar | 1000
I'd like a query that returns the % growth and raw growth of metric, so something like the following.
name | % growth | growth
-------------------------
foo | 200% | 400
bar | 500% | 800
I'm fairly new to timescaleDB and not sure what the most efficient way to do this is. I've tried using LAG, but the main problem I'm facing with that is OVER (GROUP BY time, url) doesn't respect that I ONLY want to consider the same name in the group by and can't seem to get around it. The query works fine for a single name.
Thanks!
Use LAG to get the previous value for the same name using the PARTITION option:
lag(metric_value,1,0) over (partition by name order by one_day)
This says, when ordered by 'one_day', within each 'name', give me the previous (the second parameter to LAG says 1 row) value of 'metric_value'; if there is no previous row, give me '0'.
I get stuck generating a SQL query. I have a Table in a Firebird DB like the following one:
ID | PROCESS | STEP | TIME
654 | 1 | 1 | 09:08:40
655 | 1 | 2 | 09:09:32
656 | 1 | 3 | 09:10:04
...
670 | 2 | 15 | 09:30:05
671 | 2 | 16 | 09:31:00
and so on.
I need the subtotals for each process group (It's about 7 of these). The table has the "time"-type for the TIME column.I have been trying it with DATEDIFF, but it doesn't work.
You need to use SUM
This question has been answered here.
How to sum up time field in SQL Server
and here.
SUM total time in SQL Server
For more specific Firebird documentation. Read up on the sum function here.
Sum() - Firebird Official Documentation
I think you should use "GROUP BY" to get max time and min time, and to use them in the datediff function. Something like that:
select process, datediff(second, max(time), min(time)) as nb_seconds
from your_table
group by process;
My data is like -
+-----------+------------------+-----------------+-------------+
| Issue Num | Created On | Closed at | Issue Owner |
+-----------+------------------+-----------------+-------------+
| 1 | 12/21/2016 15:26 | 1/13/2017 9:48 | Name 1 |
| 2 | 1/10/2017 7:38 | 1/13/2017 9:08 | Name 2 |
| 3 | 1/13/2017 8:57 | 1/13/2017 8:58 | Name 2 |
| 4 | 12/20/2016 20:30 | 1/13/2017 5:46 | Name 2 |
| 5 | 12/21/2016 19:30 | 1/13/2017 1:14 | Name 1 |
| 6 | 12/20/2016 20:30 | 1/12/2017 9:11 | Name 1 |
| 7 | 1/9/2017 17:44 | 1/12/2017 1:52 | Name 1 |
| 8 | 12/21/2016 19:36 | 1/11/2017 16:59 | Name 1 |
| 9 | 12/20/2016 19:54 | 1/11/2017 15:45 | Name 1 |
+-----------+------------------+-----------------+-------------+
What I am trying to achieve is
Number of issues created per week
Number of issues closed per week
Net number of issues remaining per week
I am able to resolve the top two points but unable to approach the last.
My attempt -
This gives me number of issues created every week.
Similarly I have done for Closed per week.
For Net number of issues (Created-Closed) -
I tried adding Closed At column along with Created On but I can't see second bar in the chart along with Created On either.
Something like this
I tried doing the same in excel -
I want something of this sort but with another column as the difference of
number of issues created that week - number of issues closed that week.
In this case, 8-6=2.
You could use a calculated field(Analysis->Create Calculated Field). Something like this:
{FIXED [Create Date]:Count(if DATEPART('year',[Create Date]) = 2016 then [Number of Records] end)} - {FIXED [Closed Date]:Count(if DATEPART('year',[Closed Date]) = 2016 then [Number of Records] end)}
This function is using LOD expressions to pull back both sets of values. It will filter on all 2016 results for both date sets and then minus them from each other.
For more on LOD's see here:
https://www.tableau.com/about/blog/LOD-expressions
Use this as your measure and pull in one of your date fields as the dimension.
The normal way to solve this problem is to reshape the data so you have one row per status change instead of one row per issue, with a column named [Date] and a column named [Action]. The action can be submit and close (or in a more complex world include approve, reject, whatever - tracking the history.
You can do the reshaping without modifying your source data by using a UNION to get two copies of each row with appropriate calculated fields to make the visible columns make sense (e.g., create calculated a field called Date that returns the submission date or closing date depending on whether the row is from the first or second union, with a similar one called Action whose value depends on that as well. Filter out Close actions that have a null date)
Or you can preprocess the data to reshape it.
Or you can use data blending to make two sources that point to the same data source but customizing the linking fields to line up the submit and close dates (e.g., duplicate the data connection and rename both date fields to have the same name). But in this case, you probably want to create scaffolding source that has every date, but no other data, to use as the primary data source to avoid filtering out data from the secondary for dates that don't appear in the primary. The blending approach can be brittle.
Assuming you used the UNION approach instead of Data Blending, then you can count the number of submissions and closures within a certain date range, or compute a running total of the difference to see the backlog size over time.
I'm going to do my best to explain this so I apologize in advance if my explanation is a little awkward. If I am foggy somewhere, please tell me what would help you out.
I have a table filled with circuits and dates. Each circuit gets trimmed on a time cycle of about 36 months or 48 months. I have a column that gives me this info. I have one record for every time the a circuit's trim cycle has been completed. I am attempting to link a known circuit outage list, to a table with their outage data, to a table with the circuit's trim history. The twist is the following:
I only want to get back circuits that have exceeded their trim cycles by 6 months. So I would need to take all records for a circuit, look at each individual record, find the most recent previous record relative to the record currently being examined (I will need every record examined invididually), calculate the difference between the two records in months, then return only the records that exceeded 6 months of difference between any two entries for a given feeder.
Here is an example of the data:
+----+--------+----------+-------+
| ID | feeder | comp | cycle |
| 1 | 123456 | 1/1/2001 | 36 |
| 2 | 123456 | 1/1/2004 | 36 |
| 3 | 123456 | 7/1/2007 | 36 |
| 4 | 123456 | 3/1/2011 | 36 |
| 5 | 123456 | 1/1/2014 | 36 |
+----+--------+----------+-------+
Here is an example of the result set I would want (please note: cycle can vary by circuit, so the value in the cycle column needs to be in the calculation to determine if I exceeded the cycle by 6 months between trimmings):
+----+--------+----------+-------+
| ID | feeder | comp | cycle |
| 3 | 123456 | 7/1/2007 | 36 |
| 4 | 123456 | 3/1/2011 | 36 |
+----+--------+----------+-------+
This is the query I started but I'm failing really hard at determining how to make the date calculations correctly:
SELECT temp_feederList.Feeder, Temp_outagesInfo.causeType, Temp_outagesInfo.StormNameThunder, Temp_outagesInfo.deviceGroup, Temp_outagesInfo.beginTime, tbl_Trim_History.COMP, tbl_Trim_History.CYCLE
FROM (temp_feederList
LEFT JOIN Temp_outagesInfo ON temp_feederList.Feeder = Temp_outagesInfo.Feeder)
LEFT JOIN tbl_Trim_History ON Temp_outagesInfo.Feeder = tbl_Trim_History.CIRCUIT_ID;
I wasn't really able to figure out where I need to go from here to get that most recent entry and perform the mathematical comparison. I've never been asked to do SQL this complex before, so I want to thank all of you for your patience and any assistance you're willing to lend.
I'm making some assumptions, but this uses a subquery to give you rows in the feeder list where the previous completed date was greater than the number of months ago indicated by the cycle:
SELECT tbl_Trim_History.ID, tbl_Trim_History.feeder,
tbl_Trim_History.comp, tbl_Trim_History.cycle
FROM tbl_Trim_History
WHERE tbl_Trim_History.comp>
(SELECT Max(DateAdd("m", tbl_Trim_History.cycle, comp))
FROM tbl_Trim_History T2
WHERE T2.feeder = tbl_Trim_History.feeder AND
T2.comp < tbl_Trim_History.comp)
If you needed to check for longer than 36 months you could add an arbitrary value to the months calculated by the DateAdd function.
Also I don't know if the value of cycle specified the number of month from the prior cycle or the number of months to the next one. If the latter I would change tbl_Trim_History.cycle in the DateAdd function to just cycle.
SELECT tbl_trim_history.ID, tbl_trim_history.Feeder,
tbl_trim_history.Comp, tbl_trim_history.Cycle,
(select max(comp) from tbl_trim_history T
where T.feeder=tbl_trim_history.feeder and
t.comp<tbl_trim_history.comp) AS PriorComp,
IIf(DateDiff("m",[priorcomp],[comp])>36,"x") AS [Select]
FROM tbl_trim_history;
This query identifies (with an X in the last column) the records from tbl_trim_history that exceed the cycle time - but as noted in the comments I'm not entirely sure if this is what you need or not, or how to incorporate the other 2 tables. Once you see what it is doing you can modify it to only keep the records you need.
I have a table containing a large amount of data which is stored on change.
tbl_bigOne
----------
timestamp | var01 | var02 | ...
2016-01-14 15:20:21 | 10.1 | 100.6 | ...
2016-01-14 15:20:26 | 11.2 | 110.3 | ...`
2016-01-14 15:21:27 | 52.1 | 620.1 | ...
2016-01-14 15:35:00 | 13.5 | 230.6 | ...
...
2016-01-15 09:18:01 | 94.4 | 140.0 | ...
2016-01-15 10:01:15 | 105.3 | 188.7 | ...
...
and so on for years of data
What I would like to obtain is a query/stored procedure that given two datetime references (date_from and date_to) gives the required selected data.
Now, the query just mentioned is pretty straight forward what I would also like to achieve is to set the maximum number of rows returned per day (if data is available) while doing the average of the values.
Let's give a few examples:
date_from: 2016-01-14 00:00:00
date_to: 2016-01-20 23:59:59
max_points:12
in this case the time windows is of 7 days and in this one i would like to have a maximum of 12 rows for each days of the 7 day window, giving a max total of 84 rows whilst doing the average from all the grouping done since, the data for each day is now partitioned by 12.
It is possible to see this partitioning as if every hour worth of data for that specific day is averaged, generating one row of the 12 required for a day.
date_from: 2016-01-14 00:00:00
date_to: 2016-01-14 23:59:59
max_points:1440
in this case the time window is one day worth and, if available, i would like to have a maximum of 1440 rows (for each day) for the selected period.
In this way the parameter defines the maximum number of rows for each day. The minimum time window is one day nothing below that.
Can something like this be achieved just using TSQL?
Thank you.
edit for taking care of the observations raised by #Thorsten Kettner
Use the analytic function ROW_NUMBER() to number the matching rows per day. Then only keep rows up to the given limit. If you want the rows arbitrarily chosen when there exist more than needed, then number the rows in random order using NEWID().
select timestmp, var01, var02, var03
from
(
select
mytable.*,
row_number() over (partition by convert(date, timestmp) order by newid()) as rn
from mytable
where convert(date, timestmp) between #start_date and #end_date
) numbered
where rn <= #limit
order by timestmp;