How do I retrieve 10 days data up to date 'XYZ' from mysql with Perl when some days data are missing, i.e. public holidays - sql

Data is put into a MYSQL DB in the following format:
| 2010-03-18 | 1.580 | 1.590 | 1.560 | 1.580 | 164500 | 1.580 |
| 2010-03-19 | 1.570 | 1.570 | 1.560 | 1.570 | 178300 | 1.570 |
| 2010-03-22 | 1.550 | 1.560 | 1.540 | 1.560 | 309000 | 1.560 |
| 2010-03-23 | 1.560 | 1.560 | 1.550 | 1.550 | 284900 | 1.550 |
I need to select 10 days of data upto date XYZ, the problem is that some days are missing, i.e. public holidays.


If you want a ten-day range of data, use WHERE. As in,
SELECT * FROM table WHERE date >= '2010-03-22' AND date <= '2010-03-31' ;
If you want ten records, ending a certain day, use ORDER BY and LIMIT:
SELECT * FROM table WHERE date <= '2010-03-31' ORDER BY date DESC LIMIT 10 ;

Related

Postgresql query substract from one table

I have a one tables in Postgresql and cannot find how to build a query.
The table contains columns nr_serii and deleteing_time. I trying to count nr_serii and substract from this positions with deleting_time.
My query:
select nr_serii , count(nr_serii ) as ilosc,count(deleting_time) as ilosc_delete
from MyTable
group by nr_serii, deleting_time
output is:
+--------------------+
| "666666";1;1 |
| "456456";1;0 |
| "333333";3;0 |
| "333333";1;1 |
| "111111";1;1 |
| "111111";3;0 |
+--------------------+
The part of table with raw data:
+--------------------------------+
| "666666";"2020-11-20 14:08:13" |
| "456456";"" |
| "333333";"" |
| "333333";"" |
| "333333";"" |
| "333333";"2020-11-20 14:02:23" |
| "111111";"" |
| "111111";"" |
| "111111";"2020-11-20 14:08:04" |
| "111111";"" |
+--------------------------------+
And i need substract column ilosc and column ilosc_delete
example:
nr_serii:333333 ilosc:3-1=2
Expected output:
+-------------+
| "666666";-1 |
| "456456";1 |
| "333333";2 |
| "111111";2 |
| ... |
+-------------+
I think this is very simple solution for this but i have empty in my head.

I see what you want now. You want to subtract the number where deleting_time is not null from the ones where it is null:
select nr_serii,
count(*) filter (where deleting_time is null) - count(deleting_time) as ilosc_delete
from MyTable
group by nr_serii;
Here is a db<>fiddle.

How to define a sub query inside SQL statement to be used several times as a table alias?

I have an MS Access database for rainfall data of several climate stations.
For each day of each station, I want to calculate the rainfall in the previous day (if recorded), and the sum of the rainfall at the previous 3 and 7 days.
Due to the huge amount of data and the limitations of Access, I made a query that takes station by station; Then I applied an auxillary query to find dates first, For each station, The following SQL statement is applied (and named RainFallStudy query):
SELECT
[173].ID, [173].AirportCode, [173].RFmm,
DateSerial([rYear], [rMonth], [rDay]) AS DateSer,
[DateSer]-1 AS DM1,
[DateSer]-2 AS DM2,
[DateSer]-3 AS DM3,
[DateSer]-4 AS DM4,
[DateSer]-5 AS DM5,
[DateSer]-6 AS DM6,
[DateSer]-7 AS DM7
FROM
[173]
WHERE
((([173].AirportCode) = 786660));
I used DM1, DM2, etc as the date serial of the day-1, day-2, etc.
Then I used another query that uses RainFallStudy query with left joints as shown in the figure:
The SQL statement is
SELECT
RainFallStudy.ID, RainFallStudy.AirportCode,
RainFallStudy.RFmm AS RF0, RainFallStudy.DateSer,
RainFallStudy.DM1, RainFallStudy_1.RFmm AS RF1,
RainFallStudy_2.RFmm AS RF2, RainFallStudy_3.RFmm AS RF3,
RainFallStudy_4.RFmm AS RF4, RainFallStudy_5.RFmm AS RF5,
RainFallStudy_6.RFmm AS RF6, RainFallStudy_7.RFmm AS RF7,
Nz([rf1], 0) + Nz([rf2], 0) + Nz([rf3], 0) + Nz([rf4], 0) + Nz([rf5], 0) + Nz([rf6], 0) + Nz([rf7], 0) AS RF_W
FROM
((((((RainFallStudy
LEFT JOIN
RainFallStudy AS RainFallStudy_1 ON RainFallStudy.DM1 = RainFallStudy_1.DateSer)
LEFT JOIN
RainFallStudy AS RainFallStudy_2 ON RainFallStudy.DM2 = RainFallStudy_2.DateSer)
LEFT JOIN
RainFallStudy AS RainFallStudy_3 ON RainFallStudy.DM3 = RainFallStudy_3.DateSer)
LEFT JOIN
RainFallStudy AS RainFallStudy_4 ON RainFallStudy.DM4 = RainFallStudy_4.DateSer)
LEFT JOIN
RainFallStudy AS RainFallStudy_5 ON RainFallStudy.DM5 = RainFallStudy_5.DateSer)
LEFT JOIN
RainFallStudy AS RainFallStudy_6 ON RainFallStudy.DM6 = RainFallStudy_6.DateSer)
LEFT JOIN
RainFallStudy AS RainFallStudy_7 ON RainFallStudy.DM7 = RainFallStudy_7.RFmm;
Now I suffer from the slow performance of this query, as the records of each station range from 1,000 to 750,000 records! Is there any better way to find what I need in a faster SQL statement? The second question, can I make a standalone SQL statement for that (one query without the auxiliary query) as I will use it in python, which requires one SQL statement (as Iof my knowledge).
Thanks in advance.
Update
As requested by #Andre, Here are some sample data of table [173] in HTML
<table><tbody><tr><th>ID</th><th>AirportCode</th><th>rYear</th><th>rMonth</th><th>rDay</th><th>RFmm</th></tr><tr><td>11216</td><td>409040</td><td>2012</td><td>1</td><td>23</td><td>0.51</td></tr><tr><td>11217</td><td>409040</td><td>2012</td><td>1</td><td>24</td><td>0</td></tr><tr><td>11218</td><td>409040</td><td>2012</td><td>1</td><td>25</td><td>0</td></tr><tr><td>11219</td><td>409040</td><td>2012</td><td>1</td><td>26</td><td>2.03</td></tr><tr><td>11220</td><td>409040</td><td>2012</td><td>1</td><td>27</td><td>0</td></tr><tr><td>11221</td><td>409040</td><td>2012</td><td>1</td><td>28</td><td>0</td></tr><tr><td>11222</td><td>409040</td><td>2012</td><td>1</td><td>29</td><td>0</td></tr><tr><td>11223</td><td>409040</td><td>2012</td><td>1</td><td>30</td><td>0</td></tr><tr><td>11224</td><td>409040</td><td>2012</td><td>1</td><td>31</td><td>0.25</td></tr><tr><td>11225</td><td>409040</td><td>2012</td><td>2</td><td>1</td><td>0</td></tr><tr><td>11226</td><td>409040</td><td>2012</td><td>2</td><td>2</td><td>0</td></tr><tr><td>11227</td><td>409040</td><td>2012</td><td>2</td><td>3</td><td>4.32</td></tr><tr><td>11228</td><td>409040</td><td>2012</td><td>2</td><td>4</td><td>13.21</td></tr><tr><td>11229</td><td>409040</td><td>2012</td><td>2</td><td>5</td><td>1.02</td></tr><tr><td>11230</td><td>409040</td><td>2012</td><td>2</td><td>6</td><td>0</td></tr><tr><td>11231</td><td>409040</td><td>2012</td><td>2</td><td>7</td><td>0</td></tr><tr><td>11232</td><td>409040</td><td>2012</td><td>2</td><td>8</td><td>0</td></tr><tr><td>11233</td><td>409040</td><td>2012</td><td>2</td><td>9</td><td>0</td></tr><tr><td>11234</td><td>409040</td><td>2012</td><td>2</td><td>10</td><td>5.08</td></tr><tr><td>11235</td><td>409040</td><td>2012</td><td>2</td><td>11</td><td>0</td></tr><tr><td>11236</td><td>409040</td><td>2012</td><td>2</td><td>12</td><td>12.95</td></tr><tr><td>11237</td><td>409040</td><td>2012</td><td>2</td><td>13</td><td>5.59</td></tr><tr><td>11238</td><td>409040</td><td>2012</td><td>2</td><td>14</td><td>0.25</td></tr><tr><td>11239</td><td>409040</td><td>2012</td><td>2</td><td>15</td><td>0</td></tr><tr><td>11240</td><td>409040</td><td>2012</td><td>2</td><td>16</td><td>0</td></tr><tr><td>11241</td><td>409040</td><td>2012</td><td>2</td><td>17</td><td>0</td></tr><tr><td>11242</td><td>409040</td><td>2012</td><td>2</td><td>18</td><td>0</td></tr><tr><td>11243</td><td>409040</td><td>2012</td><td>2</td><td>19</td><td>0</td></tr><tr><td>11244</td><td>409040</td><td>2012</td><td>2</td><td>20</td><td>14.48</td></tr><tr><td>11245</td><td>409040</td><td>2012</td><td>2</td><td>21</td><td>9.65</td></tr><tr><td>11246</td><td>409040</td><td>2012</td><td>2</td><td>22</td><td>3.05</td></tr><tr><td>11247</td><td>409040</td><td>2012</td><td>2</td><td>23</td><td>0</td></tr><tr><td>11248</td><td>409040</td><td>2012</td><td>2</td><td>24</td><td>0</td></tr><tr><td>11249</td><td>409040</td><td>2012</td><td>2</td><td>25</td><td>0</td></tr><tr><td>11250</td><td>409040</td><td>2012</td><td>2</td><td>26</td><td>0</td></tr><tr><td>11251</td><td>409040</td><td>2012</td><td>2</td><td>27</td><td>0</td></tr><tr><td>11252</td><td>409040</td><td>2012</td><td>2</td><td>28</td><td>7.37</td></tr><tr><td>11253</td><td>409040</td><td>2012</td><td>2</td><td>29</td><td>0</td></tr></tbody></table>
And here is sample output (HTML)
<table><tbody><tr><th>ID</th><th>AirportCode</th><th>DateSer</th><th>ThisDay</th><th>Yesterday</th><th>Prev3days</th><th>PrevWeek</th></tr><tr><td>11216</td><td>409040</td><td>23-01-2012</td><td>0.51</td><td>0</td><td>0</td><td>0</td></tr><tr><td>11217</td><td>409040</td><td>24-01-2012</td><td>0</td><td>0.51</td><td>0.51</td><td>0.51</td></tr><tr><td>11218</td><td>409040</td><td>25-01-2012</td><td>0</td><td>0</td><td>0.51</td><td>0.51</td></tr><tr><td>11219</td><td>409040</td><td>26-01-2012</td><td>2.03</td><td>0</td><td>0.51</td><td>0.51</td></tr><tr><td>11220</td><td>409040</td><td>27-01-2012</td><td>0</td><td>2.03</td><td>2.03</td><td>2.54</td></tr><tr><td>11221</td><td>409040</td><td>28-01-2012</td><td>0</td><td>0</td><td>2.03</td><td>2.54</td></tr><tr><td>11222</td><td>409040</td><td>29-01-2012</td><td>0</td><td>0</td><td>2.03</td><td>2.54</td></tr><tr><td>11223</td><td>409040</td><td>30-01-2012</td><td>0</td><td>0</td><td>0</td><td>2.54</td></tr><tr><td>11224</td><td>409040</td><td>31-01-2012</td><td>0.25</td><td>0</td><td>0</td><td>2.03</td></tr><tr><td>11225</td><td>409040</td><td>01-02-2012</td><td>0</td><td>0.25</td><td>0.25</td><td>2.28</td></tr><tr><td>11226</td><td>409040</td><td>02-02-2012</td><td>0</td><td>0</td><td>0.25</td><td>2.28</td></tr><tr><td>11227</td><td>409040</td><td>03-02-2012</td><td>4.32</td><td>0</td><td>0.25</td><td>0.25</td></tr><tr><td>11228</td><td>409040</td><td>04-02-2012</td><td>13.21</td><td>4.32</td><td>4.32</td><td>4.57</td></tr><tr><td>11229</td><td>409040</td><td>05-02-2012</td><td>1.02</td><td>13.21</td><td>17.53</td><td>17.78</td></tr><tr><td>11230</td><td>409040</td><td>06-02-2012</td><td>0</td><td>1.02</td><td>18.55</td><td>18.8</td></tr><tr><td>11231</td><td>409040</td><td>07-02-2012</td><td>0</td><td>0</td><td>14.23</td><td>18.8</td></tr><tr><td>11232</td><td>409040</td><td>08-02-2012</td><td>0</td><td>0</td><td>1.02</td><td>18.55</td></tr><tr><td>11233</td><td>409040</td><td>09-02-2012</td><td>0</td><td>0</td><td>0</td><td>18.55</td></tr><tr><td>11234</td><td>409040</td><td>10-02-2012</td><td>5.08</td><td>0</td><td>0</td><td>18.55</td></tr><tr><td>11235</td><td>409040</td><td>11-02-2012</td><td>0</td><td>5.08</td><td>5.08</td><td>19.31</td></tr><tr><td>11236</td><td>409040</td><td>12-02-2012</td><td>12.95</td><td>0</td><td>5.08</td><td>6.1</td></tr><tr><td>11237</td><td>409040</td><td>13-02-2012</td><td>5.59</td><td>12.95</td><td>18.03</td><td>18.03</td></tr><tr><td>11238</td><td>409040</td><td>14-02-2012</td><td>0.25</td><td>5.59</td><td>18.54</td><td>23.62</td></tr><tr><td>11239</td><td>409040</td><td>15-02-2012</td><td>0</td><td>0.25</td><td>18.79</td><td>23.87</td></tr><tr><td>11240</td><td>409040</td><td>16-02-2012</td><td>0</td><td>0</td><td>5.84</td><td>23.87</td></tr><tr><td>11241</td><td>409040</td><td>17-02-2012</td><td>0</td><td>0</td><td>0.25</td><td>23.87</td></tr><tr><td>11242</td><td>409040</td><td>18-02-2012</td><td>0</td><td>0</td><td>0</td><td>18.79</td></tr><tr><td>11243</td><td>409040</td><td>19-02-2012</td><td>0</td><td>0</td><td>0</td><td>18.79</td></tr><tr><td>11244</td><td>409040</td><td>20-02-2012</td><td>14.48</td><td>0</td><td>0</td><td>5.84</td></tr><tr><td>11245</td><td>409040</td><td>21-02-2012</td><td>9.65</td><td>14.48</td><td>14.48</td><td>14.73</td></tr><tr><td>11246</td><td>409040</td><td>22-02-2012</td><td>3.05</td><td>9.65</td><td>24.13</td><td>24.13</td></tr><tr><td>11247</td><td>409040</td><td>23-02-2012</td><td>0</td><td>3.05</td><td>27.18</td><td>27.18</td></tr><tr><td>11248</td><td>409040</td><td>24-02-2012</td><td>0</td><td>0</td><td>12.7</td><td>27.18</td></tr><tr><td>11249</td><td>409040</td><td>25-02-2012</td><td>0</td><td>0</td><td>3.05</td><td>27.18</td></tr><tr><td>11250</td><td>409040</td><td>26-02-2012</td><td>0</td><td>0</td><td>0</td><td>27.18</td></tr><tr><td>11251</td><td>409040</td><td>27-02-2012</td><td>0</td><td>0</td><td>0</td><td>27.18</td></tr><tr><td>11252</td><td>409040</td><td>28-02-2012</td><td>7.37</td><td>0</td><td>0</td><td>12.7</td></tr><tr><td>11253</td><td>409040</td><td>29-02-2012</td><td>0</td><td>7.37</td><td>7.37</td><td>10.42</td></tr></tbody></table>

I created an additional column rDate (DateTime) and filled it with this query:
UPDATE Rainfall SET Rainfall.rDate = DateSerial([rYear],[rMonth],[rDay]);
Then your desired result can be achieved with several subqueries, using SUM() for the last two columns:
SELECT r.ID, r.AirportCode, r.rDate, r.RFmm,
(SELECT RFmm FROM Rainfall r1 WHERE r1.AirportCode = r.AirportCode AND r1.rDate = r.rDate-1) AS Yesterday,
(SELECT SUM(RFmm) FROM Rainfall r3 WHERE r3.AirportCode = r.AirportCode AND r3.rDate BETWEEN r.rDate-3 AND r.rDate-1) AS Prev3days,
(SELECT SUM(RFmm) FROM Rainfall r7 WHERE r7.AirportCode = r.AirportCode AND r7.rDate BETWEEN r.rDate-7 AND r.rDate-1) AS PrevWeek
FROM Rainfall r
Make sure AirportCode and rDate are indexed for larger numbers of records.
Result:
+-------+-------------+------------+-------+-----------+-----------+----------+
| ID | AirportCode | rDate | RFmm | Yesterday | Prev3days | PrevWeek |
+-------+-------------+------------+-------+-----------+-----------+----------+
| 11216 | 409040 | 23.01.2012 | 0,51 | | | |
| 11217 | 409040 | 24.01.2012 | 0 | 0,51 | 0,51 | 0,51 |
| 11218 | 409040 | 25.01.2012 | 0 | 0 | 0,51 | 0,51 |
| 11219 | 409040 | 26.01.2012 | 2,03 | 0 | 0,51 | 0,51 |
| 11220 | 409040 | 27.01.2012 | 0 | 2,03 | 2,03 | 2,54 |
| 11221 | 409040 | 28.01.2012 | 0 | 0 | 2,03 | 2,54 |
| 11222 | 409040 | 29.01.2012 | 0 | 0 | 2,03 | 2,54 |
| 11223 | 409040 | 30.01.2012 | 0 | 0 | 0 | 2,54 |
| 11224 | 409040 | 31.01.2012 | 0,25 | 0 | 0 | 2,03 |
| 11225 | 409040 | 01.02.2012 | 0 | 0,25 | 0,25 | 2,28 |
| 11226 | 409040 | 02.02.2012 | 0 | 0 | 0,25 | 2,28 |
| 11227 | 409040 | 03.02.2012 | 4,32 | 0 | 0,25 | 0,25 |
| 11228 | 409040 | 04.02.2012 | 13,21 | 4,32 | 4,32 | 4,57 |
| 11229 | 409040 | 05.02.2012 | 1,02 | 13,21 | 17,53 | 17,78 |
+-------+-------------+------------+-------+-----------+-----------+----------+
Use Nz() to avoid NULL values in the first row.

It appears that you store the day in separate fields (rYear, rMonth, rDay). So, in order to get the date you use the DateSerial function. This means that in order to use the date for a join or where clause, Access must calculate the date for the entire table. You need to store the date in a separate field and index it to avoid the calculation.

SQL query to get most recent row use asp.net+access

select and get or retrieve a date from calendar control in ASP.Net to the table and select time from checkbox to the table.
output :: The most recent date and time is .....
table TEST
Date_From_Calendar | TIME |
---------------------|--------------|
15/12/2014 | 09.00-12.00 |
18/12/2014 | 15.00-18.00 |
18/12/2014 | 15.00-18.00 |
19/12/2014 | 15.00-18.00 |
19/12/2014 | 12.00-15.00 |
19/12/2014 | 12.00-15.00 |
19/12/2014 | 12.00-15.00 |
19/12/2014 | 09.00-12.00 |
20/12/2014 | 09.00-12.00 |
24/12/2014 | 09.00-12.00 |

SELECT Date_From_Calendar , MAX(TIME) AS TIME
FROM Table
GROUP BY Date_From_Calendar

Multiple Rows in to One Row

I have a result set in oracle as below: let the table name t1
Name | phase| a_plan | a_actual | b_plan | b_actual | c_plan | c_actual
===================================================================================
RKM | m5-m6| 1/1/2014|1/6/2014 | 2/2/2014 | | 3/3/2014|
RKM | m5-m6| 1/1/2014| | 2/2/2014 | 4/2/2014 | 3/3/2014|
RKM | m5-m6| 1/1/2014| | 2/2/2014 | | 3/3/2014| 5/3/2014
Whereas I need the result set as below in a single row:(a-Plan, b_plan,c_plan will be same across all 3 rows only actual column chnages per row)
Name | phase| a_plan | a_actual | b_plan | b_actual | c_plan | c_actual
===================================================================================
RKM | m5-m6| 1/1/2014|1/6/2014 | 2/2/2014 | 4/2/2014 | 3/3/2014| 5/3/2014
Help in framing the query?

SELECT NAME,
phase,
a_plan,
Max(a_actual),
b_plan,
Max(b_actual),
c_plan,
Max(c_actual)
FROM table
GROUP BY NAME,
phase,
a_plan,
b_plan,
c_plan
/

How to check date in postgresql

my table name is tbl1. The fileds are id,name,txdate.
| ID | NAME | TXDATE |
| 1 | RAJ | 1-1-2013 |
| 2 | RAVI | |
| 3 | PRABHU | 25-3-2013 |
| 4 | SAT | |
Now i want to use select query for check txdate < 2-2-2013 in which rows have txdate not empty and the select also retrun which rows have txdate empty.
The Result is like this
| ID | NAME | TXDATE |
| 1 | RAJ | 1-1-2013 |
| 2 | RAVI | |
| 4 | SAT | |
Any feasible solution is there?.
With out using union it is possible?.

Assuming that the TXDATE is of data type DATE then you can use WHERE "TXDATE" < '2013-2-2' OR "TXDATE" IS NULL. Something like:
SELECT *
FROM table1
WHERE "TXDATE" < '2013-2-2'
OR "TXDATE" IS NULL;
See it in action:
SQL Fiddle Demo

I don't now what database your are using and what data type the TXDATE is.
I just tried on my postgreSQL 9.2, with a field "timestamp without time zone".
I have three rows in the table , like:
ac_device_name | ac_last_heartbeat_time
----------------+-------------------------
Nest-Test1 |
Nest-Test3 |
Nest-Test2 | 2013-04-10 15:06:18.287
Then use below statement
select ac_device_name,ac_last_heartbeat_time
from at_device
where ac_last_heartbeat_time<'2013-04-11';
It is ok to return only one record:
ac_device_name | ac_last_heartbeat_time
----------------+-------------------------
Nest-Test2 | 2013-04-10 15:06:18.287
I think you can try statement like:
select * from tbl1 where TXDATE<'2-2-2013' and TXDATE is not NULL
this statement also works in my environment.