I have a table of the following form:
Date | Value
01/01 | 10
01/02 | 11
01/03 | 12
and so on for distinct dates of a month. I need to rotate this view and show all the dates as columns and corresponding values underneath each of the dates as column headers. The idea is to join such a rotated table against a reference table:
Product ID | Name
A123 | Axle
B234 | Bearing
and repeat across all the rows something like:
Product ID | Name | 01/01 | 01/02 | ... | 01/31
A123 | Axle | 10 | 11 | ... | 100
B234 | Bearing | 10 | 11 | ... | 100
The values above 10,11,..etc, can be static as in the first table of dates above. Suggestions? I tried using pivot but I do not want an aggregation.
Related
I have tables "T1" in the database that are broken down by month of the form (table_082020, table_092020, table_102020). Each contains several million records.
+----+----------+-------+
| id | date | value |
+----+----------+-------+
| 1 | 20200816 | abc |
+----+----------+-------+
| 2 | 20200817 | xyz |
+----+----------+-------+
+----+----------+-------+
| id | date | value |
+----+----------+-------+
| 1 | 20200901 | cba |
+----+----------+-------+
| 2 | 20200901 | zyx |
+----+----------+-------+
There is a second table "T2" that stores a reference to the primary key of the first one and actually to the table itself only without the word "table_".
+------------+--------+--------+--------+--------+
| rec_number | period | field1 | field2 | field3 |
+------------+--------+--------+--------+--------+
| 777 | 092020 | aaa | bbb | ccc |
+------------+--------+--------+--------+--------+
| 987 | 102020 | eee | fff | ggg |
+------------+--------+--------+--------+--------+
| 123456 | 082020 | xxx | yyy | zzz |
+------------+--------+--------+--------+--------+
There is also a third table "T3", which is the ratio of the period and the table name.
+--------+--------------+
| period | table_name |
+--------+--------------+
| 082020 | table_082020 |
+--------+--------------+
| 092020 | table_092020 |
+--------+--------------+
| 102020 | table_102020 |
+--------+--------------+
Tell me how you can combine 3 tables to get dynamic data for several periods. For example: from 15082020 to 04092020, where the data will be located in different tables, respectively
There really is no good reason for storing data in this format. It makes querying a nightmare.
If you cannot change the data format, then add a view each month that combines the data:
create view t as
select '202010' as YYYYMM, t.*
from table_102020
union all
select '202008' as YYYYMM, t.*
from table_092020
union all
. . .;
For a once-a-month effort, you can spend 10 minutes writing the code and do so with a calendar reminder. Or, better yet, set up a job that uses dynamic SQL to generate the code and run this as a job after the underlying tables are using.
What should you be doing? Well, 5 million rows a months isn't actually that much data. But if you are concerned about it, you can use table partitioning to store the data by month. This can be a little tricky; for instance, the primary key needs to include the partitioning key.
Say in MonetDB (specifically, the embedded version from the "MonetDBLite" R package) I have a table "events" containing entity ID codes and event start and end dates, of the format:
| id | start_date | end_date |
| 1 | 2010-01-01 | 2010-03-30 |
| 1 | 2010-04-01 | 2010-06-30 |
| 2 | 2018-04-01 | 2018-06-30 |
| ... | ... | ... |
The table is approximately 80 million rows of events, attributable to approximately 2.5 million unique entities (ID values). The dates appear to align nicely with calendar quarters, but I haven't thoroughly checked them so assume they can be arbitrary. However, I have at least sense-checked them for end_date > start_date.
I want to produce a table "nonevent_qtrs" listing calendar quarters where an ID has no event recorded, e.g.:
| id | last_doq |
| 1 | 2010-09-30 |
| 1 | 2010-12-31 |
| ... | ... |
| 1 | 2018-06-30 |
| 2 | 2010-03-30 |
| ... | ... |
(doq = day of quarter)
If the extent of an event spans any days of the quarter (including the first and last dates), then I wish for it to count as having occurred in that quarter.
To help with this, I have produced a "calendar table"; a table of quarters "qtrs", covering the entire span of dates present in "events", and of the format:
| first_doq | last_doq |
| 2010-01-01 | 2010-03-30 |
| 2010-04-01 | 2010-06-30 |
| ... | ... |
And tried using a non-equi merge like so:
create table nonevents
as select
id,
last_doq
from
events
full outer join
qtrs
on
start_date > last_doq or
end_date < first_doq
group by
id,
last_doq
But this is a) terribly inefficient and b) certainly wrong, since most IDs are listed as being non-eventful for all quarters.
How can I produce the table "nonevent_qtrs" I described, which contains a list of quarters for which each ID had no events?
If it's relevant, the ultimate use-case is to calculate runs of non-events to look at time-till-event analysis and prediction. Feels like run length encoding will be required. If there's a more direct approach than what I've described above then I'm all ears. The only reason I'm focusing on non-event runs to begin with is to try to limit the size of the cross-product. I've also considered producing something like:
| id | last_doq | event |
| 1 | 2010-01-31 | 1 |
| ... | ... | ... |
| 1 | 2018-06-30 | 0 |
| ... | ... | ... |
But although more useful this may not be feasible due to the size of the data involved. A wide format:
| id | 2010-01-31 | ... | 2018-06-30 |
| 1 | 1 | ... | 0 |
| 2 | 0 | ... | 1 |
| ... | ... | ... | ... |
would also be handy, but since MonetDB is column-store I'm not sure whether this is more or less efficient.
Let me assume that you have a table of quarters, with the start date of a quarter and the end date. You really need this if you want the quarters that don't exist. After all, how far back in time or forward in time do you want to go?
Then, you can generate all id/quarter combinations and filter out the ones that exist:
select i.id, q.*
from (select distinct id from events) i cross join
quarters q left join
events e
on e.id = i.id and
e.start_date <= q.quarter_end and
e.end_date >= q.quarter_start
where e.id is null;
I'm using Business Objects to construct a simple report on whether a unit is on or off for a given day. When constructing a vertical table, the data is correct and looks like such:
Unit ID | Status | Date
1 | On | 2016-09-10
1 | On | 2016-09-11
1 | Off | 2016-09-12
2 | Off | 2016-09-10
2 | Off | 2016-09-11
2 | On | 2016-09-12
However the cross table I've created, with columns of "date" and rows of "Unit ID" is duplicating Unit ID and having an entire row of 'On' followed by an entire row of 'Off' like:
____| 2016-09-10 | 2016-09-11 | 2016-09-12
1 | On | On | On
1 | Off | Off | Off
2 | On | On | On
2 | Off | Off | Off
instead of what it should be as:
____| 2016-09-10 | 2016-09-11 | 2016-09-12
1 | On | On | Off
2 | Off | Off | On
Any suggestions as to why it's doing this? The table isn't particularly useful if it has these duplicate rows and I can't understand why it's resulting in this odd table.
Turns out what happened is the "Status" field was a dimension type, but the cross table requires the data field to be a measure type. Simply making a new variable that was a measure equal to "Status" solved the issue.
I have data on approx 1000 individuals, where each individual can have multiple rows, with multiple dates and where the columns indicate the program admitted to and a code number.
I need each row to contain a distinct date, so I need to delete the rows of duplicate dates from my table. Where there are multiple rows with the same date, I need to keep the row that has the lowest code number. In the case of more than one row having both the same date and the same lowest code, then I need to keep the row that also has been in program (prog) B. For example;
| ID | DATE | CODE | PROG|
--------------------------------
| 1 | 1996-08-16 | 24 | A |
| 1 | 1997-06-02 | 123 | A |
| 1 | 1997-06-02 | 123 | B |
| 1 | 1997-06-02 | 211 | B |
| 1 | 1997-08-19 | 67 | A |
| 1 | 1997-08-19 | 23 | A |
So my desired output would look like this;
| ID | DATE | CODE | PROG|
--------------------------------
| 1 | 1996-08-16 | 24 | A |
| 1 | 1997-06-02 | 123 | B |
| 1 | 1997-08-19 | 23 | A |
I'm struggling to come up with a solution to this, so any help greatly appreciated!
Microsoft SQL Server 2012 (X64)
The following works with your test data
SELECT ID, date, MIN(code), MAX(prog) FROM table
GROUP BY date
You can then use the results of this query to create a new table or populate a new table. Or to delete all records not returned by this query.
SQLFiddle http://sqlfiddle.com/#!9/0ebb5/5
You can use min() function: (See the details here)
select ID, DATE, min(CODE), max(PROG)
from table
group by DATE
I assume that your table has a valid primary key. However i would recommend you to take IDas Primary key. Hope this would help you.
is it possible to have a sum in detail band in iReport?
It is important to have cells merged vertically after export to excel like this:
-----------------------------
| id | year | value | sum |
-----------------------------
| | 2010 | 55 | |
| 1 | 2011 | 65 | 180 |
| | 2012 | 60 | |
-----------------------------
| 2 | 2010 | 70 | 70 |
-----------------------------
My idea is to have the main query with GROUP BY clause and for "year" and "value" use table component with another query. Problem is that my query is long running and i need to have only one in whole report.
First have a look at here. It's about grouping rows.
You will see that you should create a group in your report, not in the query depending on your id field.
For calculating the sum field, drag the value field to the column footer, and then you will see a pop-up menu. Click to the result of an aggregation function radio button, then choose sum function. This will create a variable to calculate the sum of the value field. Change this variable's reset type to group (to id_group). Use this field in your sum field.
For grouping rows depending on id, click on the sum field and set this field's print when group changes to id_group.
this should help :)
when you group your fields your table will look like this. The grouped fields are at the top.
-----------------------------
| id | year | value | sum |
-----------------------------
| 1 | 2010 | 55 | 180 |
| | 2011 | 65 | |
| | 2012 | 60 | |
-----------------------------
| 2 | 2010 | 70 | 70 |
-----------------------------