Good afternoon everyone,
I wonder if I can get help with this example in a database.
I have listings delivered as:
------------------------------------
| Id | name | price |
-------------------------------
| 1 | Hawaii | 20.58 |
| 2 | Hawaii VIP | 45.58 |
| 3 | Aruba | 13.58 |
| 4 | Aruba VIP | 34.58 |
| 5 | Japon | 14.58 |
| 6 | Japon VIP | 34.58 |
| 7 | Alemania | 14.58 |
| 8 | Alemania VIP | 14.58 |
But I need them to be shown as follows:
-----------------------------------------------------
| Id | name | price basic | price vip
-----------------------------------------------------
| 1 | Hawaii | 20.58 | 45.34 |
| 5 | Japon | 14.58 | 34.58 |
etc etc etc
What I need are the two prices of the same country in a different column in the same query.
As I can catch the "VIP" based on this field and put it in a column with its value
It would be better to store IS_VIP as a separate column in the first table instead of adding it to the name, but since it's not a perfect world, you could solve it like this until then. :)
SELECT
t.Id,
t.name,
t.price as "price basic",
v.price as "price VIP"
FROM YourTable t
JOIN YourTable v ON v.name = CONCAT(t.name, ' VIP')
Sql Fiddle Example
Related
I am working on a small database that records rentals of different properties for different periods of time to different clients. I leave a summary example of the structures of my tables below.
+--------------+
| customer |
|--------------|
| id |
| name |
+--------------+
+--------------+
| property |
|--------------|
| id |
| number |
| address |
+--------------+
+--------------+
| rental |
|--------------|
| id |
| date_init |
| date_end |
| month_payment|
| customer_id |
| property_id |
+--------------+
What I am trying to find out now through a consultation is the following: in my rental table I keep the client, property and amount that I agree to cancel each month for the rental, so there are clients who rent different properties, during the year. How can I know how much money my clients have generated during a certain period of time, for example if I have the following records:
customer
+--------------+
| id | name |
|--------------|
| 1 | jhon doe|
| 2 | alex gs |
| 3 | martha |
+--------------+
property
+------------------------------------+
| id | number | address |
--------------------------------------
| 1 | 5643 | chicago |
| 2 | 1023 | toronto |
| 3 | 3445 | atlanta |
+------------------------------------+
rental
+-------------------------------------------------------------------+
| id | customer_id | property_id | date_init | date_end | amount |
---------------------------------------------------------------------
| 1 | 1 | 1 | 2019-01-05 | 2019-06-05 |3000 |
| 2 | 2 | 2 | 2019-04-10 | 2019-10-10 |1800 |
| 3 | 1 | 3 | 2019-02-14 | 2019-11-14 |1000 |
+-------------------------------------------------------------------+
then given as a parameter a period of time for example: 2019-01-01 to 2019-12-30 get only the records that match and have the following result:
+---------------------+
| customer | total |
|----------------------
| jhon doe | 24,000 |
| alex gs | 10,800 |
+---------------------+
In this case, the John Doe client has rented 2 properties the first for 5 months for an amount of 3000 total of 15000 and the other property for 9 months to 1000 total of 9000, so is it possible to make a query with this type of data? I don't have a query as an example yet, since I don't know how to deal with this problem. I am working on it, as soon as I have something I will update my question, thank you!
edited--
You need to use SUM() and a JOIN then specify the fields you want returned.
SELECT c.name AS customer, SUM(r.amount) AS total
FROM rentals r
INNER JOIN customer c ON c.id = r.customer_id
WHERE r.date_end >= $START AND r.date_end <= $END
GROUP BY r.customer_id
http://www.sqlservertutorial.net/sql-server-aggregate-functions/sql-server-sum/
I am stuck in this situation where I need to use Row Number and Column Number values from table's columns to derive the output mentioned below. I have tried everything - if/else, case when/then but not helping.
Any help/suggestions are really appreciated!
Here is a mocked up sample data present in db table -
+--------+--------+--------+----------+-------------+
| Record | ColNbr | RowNbr | ColTitle | CellContent |
+--------+--------+--------+----------+-------------+
| 1 | 1 | 1 | Unit | sqf |
| 1 | 1 | 2 | Unit | cm |
| 1 | 2 | 1 | Desc | roof |
| 1 | 2 | 2 | Desc | rod |
| 1 | 3 | 1 | Material | concrete |
| 1 | 3 | 2 | Material | steel |
| 1 | 4 | 1 | Quantity | 100 |
| 1 | 4 | 2 | Quantity | 12 |
| 1 | 1 | 1 | Unit | liter |
| 1 | 1 | 2 | Unit | ml |
| 1 | 2 | 1 | Desc | bowl |
| 1 | 2 | 2 | Desc | plate |
| 1 | 3 | 1 | Material | plastic |
| 1 | 3 | 2 | Material | glass |
| 1 | 4 | 1 | Quantity | 2 |
| 1 | 4 | 2 | Quantity | 250 |
+--------+--------+--------+----------+-------------+
Expected Output -
+--------+--------+--------+----------+-------------+
| Record | Unit | Desc | Material | Quantity |
+--------+--------+--------+----------+-------------+
| 1 | sqf | roof | concrete | 100 |
| 1 | cm | rod | steel | 12 |
| 2 | liter | bowl | plastic | 2 |
| 2 | ml | plate | glass | 250 |
+--------+--------+--------+----------+-------------+
If your actual data is like that, I suggest that you consider to separate the data to; for example, 4 different tables (unit,description,material & a table to store all that ids+quantity). The former 3 tables will store the prerequisite info that get minor updates throughout time and the last table will store all the quantity records. Let's say your tables will look something like this:
CREATE TABLE `Unit` (
unit_id INT,
unit_name VARCHAR(50));
+---------+-----------+
| unit_id | unit_name |
+---------+-----------+
| 1 | sqf |
| 2 | cm |
| 3 | liter |
| 4 | ml |
+---------+-----------+
CREATE TABLE `Description` (
desc_id INT,
desc_name VARCHAR(50));
+---------+-----------+
| desc_id | desc_name |
+---------+-----------+
| 1 | roof |
| 2 | rod |
| 3 | bowl |
| 4 | plate |
+---------+-----------+
CREATE TABLE `Material` (
mat_id INT,
mat_name VARCHAR(50));
+--------+----------+
| mat_id | mat_name |
+--------+----------+
| 1 | concrete |
| 2 | steel |
| 3 | plastic |
| 4 | glass |
+--------+----------+
CREATE TABLE `Records` (
unit_id INT,
desc_id INT,
mat_id INT,
quantity DECIMAL(14,4));
+---------+---------+--------+----------+
| unit_id | desc_id | mat_id | Quantity |
+---------+---------+--------+----------+
| 1 | 1 | 1 | 100 |
| 2 | 2 | 2 | 12 |
| 3 | 3 | 3 | 2 |
| 4 | 4 | 4 | 250 |
+---------+---------+--------+----------+
Then you insert the data accordingly.
Anyhow, for your existing data example, it could be done but there are some concern over whether the unit+desc+material+quantity matching are correct. The only way I can maybe at least think that it's correctly matched is by giving all of the query a similar ORDER BY clause. Hence, the following:
SELECT A.record,A.unit,B.Desc,C.Material,D.Quantity FROM
(SELECT #rn:=#rn+1 AS record,CASE WHEN coltitle='unit' THEN cellcontent END AS Unit
FROM yourtable, (SELECT #rn :=0 ) v
HAVING unit IS NOT NULL
ORDER BY colnbr) A LEFT JOIN
(SELECT #rn1:=#rn1+1 AS record,CASE WHEN coltitle='Desc' THEN cellcontent END AS `Desc`
FROM yourtable, (SELECT #rn1 :=0 ) v
HAVING `Desc` IS NOT NULL
ORDER BY colnbr) B ON a.record=b.record LEFT JOIN
(SELECT #rn2:=#rn2+1 AS record,CASE WHEN coltitle='material' THEN cellcontent END AS Material
FROM yourtable, (SELECT #rn2:=0 ) v
HAVING Material IS NOT NULL
ORDER BY colnbr) C ON a.record=c.record LEFT JOIN
(SELECT #rn3:=#rn3+1 AS record,CASE WHEN coltitle='Quantity' THEN cellcontent END AS Quantity
FROM yourtable, (SELECT #rn3:=0 ) v
HAVING Quantity IS NOT NULL
ORDER BY colnbr) D ON a.record=d.record;
The idea here is to make a sub-query based on COLTITLE then assign a numbering/ranking (#rn,#rn1,#rn2,#rn3) variable to each of the sub-query and join them up using LEFT JOIN. Now, this experiment works to exactly return the output that you need but its not a definite answer because there are some part that is questionable especially on matching the combination correctly. Hopefully, this will give you some idea.
i have 2 tables.
1.home_shop
+---+------------+
|id | product |
+---+------------+
| 1 | soap |
| 2 | cake |
| 3 | biscuit |
+---+------------+
2.office_shop
+---+------------+
|id | product |
+---+------------+
| 1 | key |
| 2 | lock |
| 3 | pen |
+---+------------+
what i want is union this two tables into a new table "complete_shop" with a flag indicating "home" and "office"
for example:
+---+------------+-------------+
|id | product | flag |
+---+------------+-------------+
| 1 | soap | home |
| 1 | key | office |
| 2 | cake | home |
| 2 | lock | office |
| 3 | biscuit | home |
| 3 | pen | office |
+---+------------+-------------+
how do i do this union in mysql please help me. i am a beginner
Do a UNION query and introduce the flag column using the appropriate values.
SELECT id, product, 'home' AS flag
FROM home_shop
UNION ALL
SELECT id, product, 'office' AS flag
FROM office_shop
ORDER BY id, flag
Note that you don't need to use a subquery to order here, you can just specify the columns you want to use.
I am looking to overwrite a column name in a table with an existing column name.
I am Looking for a way to get the remaining unspecified columns in the tables.
Note:
The query could have more joins in the future.
eg
Person
+-----------+----------+---------+
| firstname | lastname | pers_id |
+-----------+----------+---------+
| Joe | Soap | 1 |
| Bobby | Pin | 2 |
| Janet | Jackson | 3 |
+-----------+----------+---------+
Category
+----------+-------------------+--------+
| type | description | cat_id |
+----------+-------------------+--------+
| customer | people who pay us | 1 |
| employee | people we pay | 2 |
| director | people who direct | 3 |
+----------+-------------------+--------+
Person_Cat
(=^ェ^=)
+---------+--------+
| pers_id | cat_id |
+---------+--------+
| 3 | 1 |
| 2 | 2 |
| 1 | 3 |
+---------+--------+
Query
SELECT *, CONCAT(p.firstname, ' '
, p.lastname) as full_name
, c.cat_id AS category_id
, p.pers_id AS cat_id
FROM Person AS p
JOIN Person_Cat AS pc ON(p.pers_id = pc.pers_id)
JOIN Category AS c ON (pc.cat_id = c.cat_id)
OUTPUT
(Apologies for the length but the table after is more important)
+-----------+----------+---------+---------+--------+----------+-------------------+--------+---------------+-------------+--------+
| p | p | p | pc | pc | c | c | c | Select | Select | Select |
+-----------+----------+---------+---------+--------+----------+-------------------+--------+---------------+-------------+--------+
| firstname | lastname | pers_id | pers_id | cat_id | type | description | cat_id | full_name | category_id | cat_id |
+-----------+----------+---------+---------+--------+----------+-------------------+--------+---------------+-------------+--------+
| Janet | Jackson | 3 | 3 | 1 | customer | people who pay us | 1 | Janet jackson | 1 | 3 |
| Bobby | Pin | 2 | 2 | 2 | employee | people who we pay | 2 | Bobby Pin | 2 | 2 |
| Joe | Soap | 1 | 1 | 3 | director | people who direct | 3 | Joe Soap | 3 | 1 |
+-----------+----------+---------+---------+--------+----------+-------------------+--------+---------------+-------------+--------+
The headers above column names are there for reference
to where they comes from.
Column summary -
firstname, lastname, pers_id, pers_id, cat_id, type,
description, cat_id, full_name ,category_id, cat_id
Wanted output
+-----------+----------+---------+--------+----------+-------------------+---------------+-------------+--------+
| p | p | pc | pc | c | c | Select | Select | Select |
+-----------+----------+---------+--------+----------+-------------------+---------------+-------------+--------+
| firstname | lastname | pers_id | cat_id | type | description | full_name | category_id | cat_id |
+-----------+----------+---------+--------+----------+-------------------+---------------+-------------+--------+
| Janet | Jackson | 3 | 1 | customer | people who pay us | Janet jackson | 1 | 3 |
| Bobby | Pin | 2 | 2 | employee | people who we pay | Bobby Pin | 2 | 2 |
| Joe | Soap | 1 | 3 | director | people who direct | Joe Soap | 3 | 1 |
+-----------+----------+---------+--------+----------+-------------------+---------------+-------------+--------+
Column summary -
firstname, lastname, pers_id, cat_id, type,
description, full_name ,category_id, cat_id
Notice:
The p.pers_id and the c.cat_id are not present. I would like to think this would be because the were called directly and unmodified unlike the first and lastname used in ConCat
When the short answer is that there is no such concept as Select [remaining columns]at this time (2015-06-17), if you want to use SELECT * but only remove redundant columns,
then you will need to explicitly remove (ignore) those redundant columns when rendering your view.
You will have to explicitly configure logic of which columns to ignore, which is pretty much the same thing as explicitly listing the columns that you are interested in, so you get back to the argument against selecting all columns that I made in the comments above.
Unless your table schema is changing all the time, there really isn't reason for this.
I am looking to take data from multiple mysql tables with different structures and insert it into one master table containing different columns/data from the sources,
I have created a column name mapping table with the following data:
TABLE: affiliate_datafeed_magento_mapping
+----+-------------+----------------+
| id | datafeed | magento |
+----+-------------+----------------+
| 1 | SKU | sku |
| 1 | Name | name |
| 1 | Description | description |
| 1 | Url | affiliate_link |
| 1 | Price | price |
| 1 | Brand | brand |
| 1 | ModelNumber | model |
| 2 | SKU | sku |
| 2 | Name | name |
| 2 | Description | description |
| 2 | Url | affiliate_link |
| 2 | Price | price |
| 2 | Currency | affiliate_cur |
+----+-------------+----------------+
id corresponds to the id of the affiliate program in the table affiliate_programs
datafeed corresponds the column name in the source table with the corresponding id in the table affiliate_program
magento corresponds the the column name in the table to receive the data
TABLE: affiliate_programs
+----+-------------------+-------------------------+------------------------+------------------------+-------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------+-------------------------------------+-------+
| id | affiliate_network | affiliate_network_short | affiliate_program | affiliate_program_long | affiliate_program_short | affiliate_program_datafeed_url | affiliate_program_datafeed_csv_filename | affiliate_program_datafeed_last_get | order |
+----+-------------------+-------------------------+------------------------+------------------------+-------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------+-------------------------------------+-------+
| 1 | CommissionFactory | cf_ | Lifestyle Clotheslines | lifestyleclotheslines | lcl | http://dashboard.commissionfactory.com.au/Affiliate/Creatives/DataFeeds/jPuB5NPigbec7prnjLCX5MHygO$A5sTlhOHb8t3nmufzta#k5uyn5qqxrLDr86GysLTj$bTyoKaj77Pltfmh9dvnkOCS4MHzjvTSlK6Dfg==/ | cf_lifestyleclotheslines.csv | 2013-08-12 22:23:02 | NULL |
| 2 | CommissionFactory | cf_ | MacArthur Baskets | macarthurbaskets | mcb | http://dashboard.commissionfactory.com.au/Affiliate/Creatives/DataFeeds/jPSA4dbg17SY7svvjeSX5Jf1iO#b5JXshOfY#ovjzeKj4PGivuyn5qqxrLDr86GysLTj$bTyoKaj77Pltfmh9dvnkOCS4MHzjvTSlK6Dfg==/ | cf_macarthurbaskets.csv | 2013-08-12 22:23:02 | NULL |
| 3 | ClixGalore | cg_ | Boutique Wineries | boutiquewineries | btw | http://www.is1.clixGalore.com/DataFileRequest.aspx?AdID=9522&AfID=264058 | cg_boutiquewineries.csv | 2013-08-12 22:23:02 | NULL |
| 4 | ClixGalore | cg_ | Brewtopia | brewtopia | bwt | http://www.is1.clixGalore.com/DataFileRequest.aspx?AdID=4817&AfID=264058 | cg_brewtopia.csv | 2013-08-12 22:23:02 | NULL |
| 5 | ClixGalore | cg_ | MacArthur Baskets | macarthurbaskets | mcb2 | http://www.is1.clixGalore.com/DataFileRequest.aspx?AdID=4909&AfID=264058 | cg_macarthurbaskets.csv | 2013-08-12 22:23:02 | NULL |
| 6 | ClixGalore | cg_ | Winemakers Choice | winemakerschoice | wmc | http://www.is1.clixGalore.com/DataFileRequest.aspx?AdID=4282&AfID=264058 | cg_winemakerschoice.csv | 2013-08-12 22:23:02 | NULL |
+----+-------------------+-------------------------+------------------------+------------------------+-------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------+-------------------------------------+-------+
id corresponds to the same id in the table affiliate_datafeed_magento_mapping
the concatenation of affiliate_programs.affiliate_network_short and affiliate_programs.affiliate_program_long make up the name of the source table
TABLE: cf_lifestyleclotheslines
+----+---------------------+---------------------+------+------------------------------------------------------+--------------------------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------+---------------------------------------------------------------------------------------------------+-------------------------------------------------------------------+-------------------------------------------------------------------------+---------------------------------------------------------------------------+---------------------------------------------------------------------------+---------------------------------------------------------------------------+---------------------------------------------------------------------------+---------------------------------------------------------------------------+--------------+-------------+-------------+
| id | DateCreated | DateModified | SKU | Name | Category | Description | Url | OriginalUrl | Image | Image50 | Image100 | Image120 | Image200 | Image300 | Image400 | Price | Brand | ModelNumber |
+----+---------------------+---------------------+------+------------------------------------------------------+--------------------------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------+---------------------------------------------------------------------------------------------------+-------------------------------------------------------------------+-------------------------------------------------------------------------+---------------------------------------------------------------------------+---------------------------------------------------------------------------+---------------------------------------------------------------------------+---------------------------------------------------------------------------+---------------------------------------------------------------------------+--------------+-------------+-------------+
| 1 | 2012-10-19 10:52:50 | 2013-06-20 02:07:37 | 30 | Airaus Ceiling Mounted Clothes Airer | Home & Garden > Household Supplies > Laundry Supplies > Drying Racks & Hangers | Watch the Product Video Just arrived from Europe! Lifestyle Clotheslines is now stocking the latest ceiling mounted clothes airers from Europe. Ceiling mounted clothes airers are the perfect alternative for those with limited space situations or who need the benefit of an indoor clothesline or airer. Boasting 6 individually adjustable drying rods which are made of steel not plastic, these indoor airers can be used in a range of situations and are ideally suited for the disabled as they can easily be lowered or raised to the height of the user. An indoor airer can also help extend the life of your clothes by reducing the exposure to harsh UV rays and they can also be a big power saver for your home when used to dry your washing instead of a tumble dryer. Discover today how one of our new ceiling mounted clothes airers can save you money and take all the hard work and fuss out of drying your washing. // Customer Video Reviews  ... | https://track.commissionfactory.com.au/p/10604/1718691 | http://www.lifestyleclotheslines.com.au/airaus-ceiling-mounted-clothes-airer/ | http://content.commissionfactory.com.au/Products/7228/1718691.jpg | http://content.commissionfactory.com.au/Products/7228/1718691#50x50.jpg | http://content.commissionfactory.com.au/Products/7228/1718691#100x100.jpg | http://content.commissionfactory.com.au/Products/7228/1718691#120x120.jpg | http://content.commissionfactory.com.au/Products/7228/1718691#200x200.jpg | http://content.commissionfactory.com.au/Products/7228/1718691#300x300.jpg | http://content.commissionfactory.com.au/Products/7228/1718691#400x400.jpg | 99.0000 AUD | | AIRAUS |
+----+---------------------+---------------------+------+------------------------------------------------------+--------------------------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------+---------------------------------------------------------------------------------------------------+-------------------------------------------------------------------+-------------------------------------------------------------------------+---------------------------------------------------------------------------+---------------------------------------------------------------------------+---------------------------------------------------------------------------+---------------------------------------------------------------------------+---------------------------------------------------------------------------+--------------+-------------+-------------+
So with the data provided I'm looking to go through all the tables (concatenation of affiliate_programs.affiliate_network_short and affiliate_programs.affiliate_program_long columns in affiliate_programs and build a insert query for them all based on the mapped columns in the table affiliate_datafeed_magento_mapping to insert the data into the table magento_export
Any assistance would be awesome!
Tim
I dont think you need the mapping table at all
I would use a series of UNION queries. One query per source. In the SELECT clause for each of those queries you should have a 1:1 column for each coulmn in your destination table, including mapping the value NULL where that destination column is not applicable to that source. (This is where the mapping really happens)
Then your INSERT statement is a straight-forward mapping of all the UNIONED queries into the destination table.
Pseudo code
INSERT INTO Destination(Col1, Col2, Col3, Col4)
SELECT T1.Field1 as Col1
,NULL as Col2
,T1.Field7 as Col3
,T1.Field2 as Col4
FROM FirstSource T1
UNION
SELECT T2.Field1 as Col1
,Some Calulation as Col2
,T2.Field3 as Col3
,NULL as Col4
FROM FirstSource T1