I have a table my_friends_cards:
id | name | rare_cards_composite[] |
---+---------+------------------------
1 | 'timmy' | { {1923, 'baberuth'}, {1999, 'jeter'}}
2 |'jimmy' | { {1955, 'Joey D'}, {1995, 'juice_head'}}
3 |'bob' | {{2001, 'mo_jeter'}}
I want to make the a request kinda like this:
Select name, (cards.x).player
FROM SELECT UNNEST(base_ball_card) as x
FROM my_friends_cards
WHERE name=ANY(['timmy', 'jimmy'])) as cards
WHERE (cards.x).year > 1990
(I know this doesn't work that there is no 'name' field in the unnested composite array.)
I am getting the feeling that my composite type array column should just be another table, and then I could do a join, but is there anyway around this?
I would expect this result:
[('timmy', 'jeter')
,('jimmy', 'juice_head')]
version: PostgreSQL 9.3.3
Your feeling is correct: a normalized schema with another table instead of the array of composite types would be the superior approach in many respects.
While stuck with your unfortunate design:
Test setup
(You should have provided this.)
CREATE TYPE card AS (year int, cardname text);
CREATE TABLE my_friends_cards (id int, name text, rare_cards_composite card[]);
INSERT INTO my_friends_cards VALUES
(1, 'timmy', '{"(1923,baberuth)","(1999,jeter)"}')
, (2, 'jimmy', '{"(1955,Joey D)","(1995,juice_head)"}')
, (3, 'bob' , '{"(2001,mo_jeter)"}')
;
Query
Requires Postgres 9.3+.
SELECT t.name, c.cardname
FROM my_friends_cards t
, unnest(t.rare_cards_composite) c
WHERE t.name = ANY('{timmy,jimmy}')
AND c.year > 1990;
db<>fiddle here
Old sqlfiddle
Note that the composite type is decomposed in the unnesting.
Related
I would like to create a product table. This product has unique part numbers. However, each part number has various number of previous part numbers, and various number of machines where the part can be used.
For example the description for part no: AA1007
Previous part no's: AA1001, AA1002, AA1004, AA1005,...
Machine brand: Bosch, Indesit, Samsun, HotPoint, Sharp,...
Machine Brand Models: Bosch A1, Bosch A2, Bosch A3, Indesit A1, Indesit A2,....
I would like to create a table for this, but I am not sure how to proceed. What I have been able to think is to create a table for Previous Part no, Machine Brand, Machine Brand Models individually.
Question: what is the proper way to design these tables?
There are of course various ways to design the tables. A very basic way would be:
You could create tables like below. I added the columns ValidFrom and ValidTill, to identify at which time a part was active/in use.
It depends on your data, if datatype date is enough, or you need datetime to make it more exactly.
CREATE TABLE Parts
(
ID bigint NOT NULL
,PartNo varchar(100)
,PartName varchar(100)
,ValidFrom date
,ValidTill date
)
CREATE TABLE Brands
(
ID bigint NOT NULL
,Brand varchar(100)
)
CREATE TABLE Models
(
ID bigint NOT NULL
,BrandsID bigint NOT NULL
,ModelName varchar(100)
)
CREATE TABLE ModelParts
(
ModelsID bigint NOT NULL
,PartID bigint NOT NULL
)
Fill your data like:
INSERT INTO Parts VALUES
(1,'AA1007', 'Screw HyperFuturistic', '2017-08-09', '9999-12-31'),
(1,'AA1001', 'Screw Iron', '1800-01-01', '1918-06-30'),
(1,'AA1002', 'Screw Steel', '1918-07-01', '1945-05-08'),
(1,'AA1004', 'Screw Titanium', '1945-05-09', '1983-10-05'),
(1,'AA1005', 'Screw Futurium', '1983-10-06', '2017-08-08')
INSERT INTO Brands VALUES
(1,'Bosch'),
(2,'Indesit'),
(3,'Samsung'),
(4,'HotPoint'),
(5,'Sharp')
INSERT INTO Models VALUES
(1,1,'A1'),
(2,1,'A2'),
(3,1,'A3'),
(4,2,'A1'),
(5,2,'A2')
INSERT INTO ModelParts VALUES
(1,1)
To select all parts of a certain date (in this case 2013-03-03) of the "Bosch A1":
DECLARE #ReportingDate date = '2013-03-03'
SELECT B.Brand
,M.ModelName
,P.PartNo
,P.PartName
,P.ValidFrom
,P.ValidTill
FROM Brands B
INNER JOIN Models M
ON M.BrandsID = B.ID
INNER JOIN ModelParts MP
ON MP.ModelsID = M.ID
INNER JOIN Parts P
ON P.ID = MP.PartID
WHERE B.Brand = 'Bosch'
AND M.ModelName = 'A1'
AND P.ValidFrom <= #ReportingDate
AND P.ValidTill >= #ReportingDate
Of course there a several ways to do an historization of data.
ValidFrom and ValidTill (ValidTo) is one of my favourites, as you can easily do historical reports.
Unfortunately you have to handle the historization: When inserting a new row - in example for your screw - you have to "close" the old record by setting the ValidTill column before inserting the new one. Furthermore you have to develop logic to handle deletes...
Well, thats a quite large topic. You will find tons of information in the world wide web.
For the part number table, you can consider the following suggestion:
id | part_no | time_created
1 | AA1007 | 2017-08-08
1 | AA1001 | 2017-07-01
1 | AA1002 | 2017-06-10
1 | AA1004 | 2017-03-15
1 | AA1005 | 2017-01-30
In other words, you can add a datetime column which versions each part number. Note that I added a primary key id column here, which is invariant over time and keeps track of each part, despite that the part number may change.
For time independent queries, you would join this table using the id column. However, the part number might also serve as a foreign key. Off the top of my head, if you were generating an invoice from a previous date, you might lookup the appropriate part number at that time, and then join out to one or more tables using that part number.
For the other tables you mentioned, I do not see a similar requirement.
How can I create a table without knowing in advance how many and what columns it exactly holds?
The idea is that I have a table DATA that has 3 columns : ID, NAME, and VALUE
What I need is a way to get multiple values depending on the value of NAME - I can't do it with simple WHERE or JOIN (because I'll need other values - with other NAME values - later on in my query).
Because of the way this table is constructed I want to PIVOT it in order to transform every distinct value of NAME into a column so it will be easier to get to it in my later search.
What I want now is to somehow save this to a temp table / variable so I can use it later on to join with the result of another query...
So example:
Columns:
CREATE TABLE MainTab
(
id int,
nameMain varchar(max),
notes varchar(max)
);
CREATE TABLE SecondTab
(
id int,
id_mainTab, int,
nameSecond varchar(max),
notes varchar(max)
);
CREATE TABLE DATA
(
id int,
id_second int,
name varchar(max),
value varchar(max)
);
Now some example data from the table DATA:
| id | id_second_int | name | value |
|-------------------------------------------------------|
| 1 | 5550 | number | 111115550 |
| 2 | 6154 | address | 1, First Avenue |
| 3 | 1784 | supervisor | John Smith |
| 4 | 3467 | function | Marketing |
| 5 | 9999 | start_date | 01/01/2000 |
::::
Now imagine that 'name' has A LOT of different values, and in one query I'll need to get a lot of different values depending on the value of 'name'...
That's why I pivot it so that number, address, supervisor, function, start_date, ... become colums.
This I do dynamically because of the amount of possible columns - it would take me a while to write all of them in an 'IN' statement - and I don't want to have to remember to add it manually every time a new 'name' value gets added...
herefore I followed http://sqlhints.com/2014/03/18/dynamic-pivot-in-sql-server/
the thing is know that I want the result of my execute(#query) to get stored in a tempTab / variable. I want to use it later on to join it with mainTab...
It would be nice if I could use #cols (which holds the values of DATA.name) but I can't seem to figure out a way to do this.
ADDITIONALLY:
If I use the not dynamic way (write down all the values manually after 'IN') I still need to create a column called status. Now in this column (so far it's NULL everywhere because that value doesn't exist in my unpivoted table) i want to have 'open' or 'closed', depending on the date (let's say i have start_date and end_date,
CASE end_date
WHEN end_date < GETDATE() THEN pivotTab.status = 'closed'
ELSE pivotTab.status = 'open'
Where can I put this statement? Let's say my main query looks like this:
SELECT * FROM(
(SELECT id_second, name, value, id FROM TABLE_DATA) src
PIVOT (max(value) FOR name IN id, number, address, supervisor, function, start_date, end_date, status) AS pivotTab
JOIN SecondTab ON SecondTab.id = pivotTab.id_second
JOIN MainTab ON MainTab.id = SecondTab.id_mainTab
WHERE pivotTab.status = 'closed';
Well, as far as I can understand - you have some select statement and just need to "dump" its result to some temporary table. In this case you can use select into syntax like:
select .....
into #temp_table
from ....
This will create temporary table according to columns in select statement and populate it with data returned by select datatement.
See MDSN for reference.
I've got four tables in a PostgreSQL 9.3.6 database:
sections
fields (child of sections)
entries (child of sections)
data (child of entries)
CREATE TABLE section (
id serial PRIMARY KEY,
title text,
"group" integer
);
CREATE TABLE fields (
id serial PRIMARY KEY,
title text,
section integer,
type text,
"default" json
);
CREATE TABLE entries (
id serial PRIMARY KEY,
section integer
);
CREATE TABLE data (
id serial PRIMARY KEY,
data json,
field integer,
entry integer
);
I'm trying to generate a page that looks like this:
section title
field 1 title | field 2 title | field 3 title
entry 1 | data 'as' json | data 1 json | data 3 json <-- table
entry 2 | data 'df' json | data 5 json | data 6 json
entry 3 | data 'gh' json | data 8 json | data 9 json
The way I have it set up right now each piece of 'data' has an entry it's linked to, a corresponding field (that field has columns that determine how the data's json field should be interpreted), a json field to store different types of data, and an id (1-9 here in the table).
In this example there are 3 entries, and 3 fields and there is a data piece for each of the cells in between.
It's set up like this because one section can have different field types and quantity than another section and therefore different quantities and types of data.
Challenge 1:
I'm trying to join the table together in a way that it's sortable by any of the columns (contents of the data for that field's json column). For example I want to be able to sort field 3 (the third column) in reverse order, the table would look like this:
section title
field 1 title | field 2 title | field 3 title
entry 3 | data 'gh' json | data 8 json | data 9 json
entry 2 | data 'df' json | data 5 json | data 6 json
entry 1 | data 'as' json | data 1 json | data 3 json <-- table
I'm open to doing it another way too if there's a better one.
Challenge 2:
Each field has a 'default value' column - Ideally I only have to create 'data' entries when they have a value that isn't that default value. So the table might actually look like this if field 2's default value was 'asdf':
section title
field 1 title | field 2 title | field 3 title
entry 3 | data 'gh' json | data 8 json | data 9 json
entry 2 | data 'df' json | 'asdf' | data 6 json
entry 1 | data 'as' json | 'asdf' | data 3 json <-- table
The key to writing this query is understanding that you just need to fetch all the data for single section and the rest you just join. You also can't with your schema directly filter data by section so you'll need to join entry just for that:
SELECT d.* FROM data d JOIN entries e ON (d.entry = e.id)
WHERE e.section = ?
You can then join field to each row to get defaults, types and titles:
SELECT d.*, f.title, f.type, f."default"
FROM data d JOIN entries e ON (d.entry = e.id)
JOIN fields f ON (d.field = f.id)
WHERE e.section = ?
Or you can select fields in a separate query to save some network traffic.
So this was an answer, here come bonuses:
Use foreign keys instead of integers to refer to other tables, it will make database check consistency for you.
Relations (tables) should be called in singular by convention, so it's section, entry and field.
Referring fields are called <name>_id, e.g. field_id or section_id also by convention.
The whole point of JSON fields is to store a collection with not statically defined data, so it would made much more sense to not use entries and data tables, but single table with JSON containing all the fields instead.
Like this:
CREATE TABLE row ( -- less generic name would be even better
id int primary key,
section_id int references section (id),
data json
)
With data fields containing something like:
{
"title": "iPhone 6",
"price": 650,
"available": true,
...
}
#Suor has provided good advice, some of which you already accepted. I am building on the updated schema.
Schema
CREATE TABLE section (
section_id serial PRIMARY KEY,
title text,
grp integer
);
CREATE TABLE field (
field_id serial PRIMARY KEY,
section_id integer REFERENCES section,
title text,
type text,
default_val json
);
CREATE TABLE entry (
entry_id serial PRIMARY KEY,
section_id integer REFERENCES section
);
CREATE TABLE data (
data_id serial PRIMARY KEY,
field_id integer REFERENCES field,
entry_id integer REFERENCES entry,
data json
);
I changed two more details:
section_id instead of id, etc. "id" as column name is an anti-pattern that's gotten popular since a couple of ORMs use it. Don't. Descriptive names are much better. Identical names for identical content is a helpful guideline. It also allows to use the shortcut USING in join clauses:
Don't use reserved words as identifiers. Use legal, lower-case, unquoted names exclusively to make your life easier.
Are PostgreSQL column names case-sensitive?
Referential integrity?
There is another inherent weakness in your design. What stops entries in data from referencing a field and an entry that don't go together? Closely related question on dba.SE
Enforcing constraints “two tables away”
Query
Not sure if you need the complex design at all. But to answer the question, this is the base query:
SELECT entry_id, field_id, COALESCE(d.data, f.default_val) AS data
FROM entry e
JOIN field f USING (section_id)
LEFT JOIN data d USING (field_id, entry_id) -- can be missing
WHERE e.section_id = 1
ORDER BY 1, 2;
The LEFT JOIN is crucial to allow for missing data entries and use the default instead.
SQL Fiddle.
crosstab()
The final step is cross tabulation. Cannot show this in SQL Fiddle since the additional module tablefunc is not installed.
Basics for crosstab():
PostgreSQL Crosstab Query
SELECT * FROM crosstab(
$$
SELECT entry_id, field_id, COALESCE(d.data, f.default_val) AS data
FROM entry e
JOIN field f USING (section_id)
LEFT JOIN data d USING (field_id, entry_id) -- can be missing
WHERE e.section_id = 1
ORDER BY 1, 2
$$
,$$SELECT field_id FROM field WHERE section_id = 1 ORDER BY field_id$$
) AS ct (entry int, f1 json, f2 json, f3 json) -- static
ORDER BY f3->>'a'; -- static
The tricky part here is the return type of the function. I provided a static type for 3 fields, but you really want that dynamic. Also, I am referencing a field in the json type that may or may not be there ...
So build that query dynamically and execute it in a second call.
More about that:
Dynamic alternative to pivot with CASE and GROUP BY
I want to add some string with the primary key value while creating the table in sql?
Example:
my primary key column should automatically generate values like below:
'EMP101'
'EMP102'
'EMP103'
How to achieve it?
Try this: (For SQL Server 2012)
UPDATE MyTable
SET EMPID = CONCAT('EMP' , EMPID)
Or this: (For SQL Server < 2012)
UPDATE MyTable
SET EMPID = 'EMP' + EMPID
SQLFiddle for SQL Server 2008
SQLFiddle for SQL Server 2012
Since you want to set auto increment in VARCHAR type column you can try this table schema:
CREATE TABLE MyTable
(EMP INT NOT NULL IDENTITY(1000, 1)
,[EMPID] AS 'EMP' + CAST(EMP AS VARCHAR(10)) PERSISTED PRIMARY KEY
,EMPName VARCHAR(20))
;
INSERT INTO MyTable(EMPName) VALUES
('AA')
,('BB')
,('CC')
,('DD')
,('EE')
,('FF')
Output:
| EMP | EMPID | EMPNAME |
----------------------------
| 1000 | EMP1000 | AA |
| 1001 | EMP1001 | BB |
| 1002 | EMP1002 | CC |
| 1003 | EMP1003 | DD |
| 1004 | EMP1004 | EE |
| 1005 | EMP1005 | FF |
See this SQLFiddle
Here you can see EMPID is auto incremented column with Primary key.
Source: HOW TO SET IDENTITY KEY/AUTO INCREMENT ON VARCHAR COLUMN IN SQL SERVER (Thanks to #bvr)
What the rule of thumb is, is that never use meaningful information in primary keys (like Employee Number / Social Security number). Let that just be a plain autoincremented integer. However constant the data seems - it may change at one point (new legislation comes and all SSNs are recalculated).
it seems the only reason you are want to use a non-integer keys is that the key is generated as string concatenation with another column to make it unique.
From a best practice perspective, it is strongly recommended that integer primary keys are used, but often, this guidance is ignored.
May be going through the following posts might be of help:
Should I design a table with a primary key of varchar or int?
SQL primary key: integer vs varchar
You can achieve it at least in two ways:
Generate new id on the fly when you insert a new record
Create INSTEAD OF INSERT trigger that will do that for you
If you have a table schema like this
CREATE TABLE Table1
([emp_id] varchar(12) primary key, [name] varchar(64))
For the first scenario you can use a query
INSERT INTO Table1 (emp_id, name)
SELECT newid, 'Jhon'
FROM
(
SELECT 'EMP' + CONVERT(VARCHAR(9), COALESCE(REPLACE(MAX(emp_id), 'EMP', ''), 0) + 1) newid
FROM Table1 WITH (TABLOCKX, HOLDLOCK)
) q
Here is SQLFiddle demo
For the second scenario you can a trigger like this
CREATE TRIGGER tg_table1_insert ON Table1
INSTEAD OF INSERT AS
BEGIN
DECLARE #max INT
SET #max =
(SELECT COALESCE(REPLACE(MAX(emp_id), 'EMP', ''), 0)
FROM Table1 WITH (TABLOCKX, HOLDLOCK)
)
INSERT INTO Table1 (emp_id, name)
SELECT 'EMP' + CONVERT(VARCHAR(9), #max + ROW_NUMBER() OVER (ORDER BY (SELECT 1))), name
FROM INSERTED
END
Here is SQLFiddle demo
I am looking to do something similar but don't see an answer to my problem here.
I want a primary Key like "JonesB_01" as this is how we want our job number represented in our production system.
--ID | First_Name | Second_Name | Phone | Etc..
-- Bob Jones 9999-999-999
--ID = "Second_Name"+"F"irst Initial+"_(01-99)"
The number 01-99 has been included to allow for multiple instances of a customer with the same surname and first initial. In our industry it's not unusual for the same customer to have work done on multiple occasions but are not repeat business on an ongoing basis. I expect this convention to last a very long time. If we ever exceed it, then I can simply add a third interger.
I want this to auto populate to keep data entry as simple as possible.
I managed to get a solution to work using Excel formulars and a few helper cells but am new to SQL.
--CellA2 = JonesB_01 (=concatenate(D2+E2))
--CellB2 = "Bob"
--CellC2 = "Jones"
--CellD2 = "JonesB" (=if(B2="","",Concatenate(C2,Left(B2)))
--CellE2 = "_01" (=concatenate("_",Text(F2,"00"))
--CellF2 = "1" (=If(D2="","",Countif($D$2:$D2,D2))
Thanks.
SELECT 'EMP' || TO_CHAR(NVL(MAX(TO_NUMBER(SUBSTR(A.EMP_NO, 4,3))), '000')+1) AS NEW_EMP_NO
FROM
(SELECT 'EMP101' EMP_NO
FROM DUAL
UNION ALL
SELECT 'EMP102' EMP_NO
FROM DUAL
UNION ALL
SELECT 'EMP103' EMP_NO
FROM DUAL
) A
Using PostgreSQL 9.0
I have the following table setup
CREATE TABLE person (age integer, last_name text, first_name text, address text);
CREATE TABLE my_people (mperson person[]);
INSERT INTO my_people VALUES(array[ROW(44, 'John', 'Smith', '1234 Test Blvd.')::person]);
Now, i want to be able to write a select statement that can search and compare values of my composite types inside my mperson array column.
Example:
SELECT * FROM my_people WHERE 20 > ANY( (mperson) .age);
However when trying to execute this query i get the following error:
ERROR: column notation .age applied to type person[], which is not a composite type
LINE 1: SELECT mperson FROM my_people WHERE 20 > ANY((mperson).age);
So, you can see i'm trying to test the values of the composite type inside my array.
I know, i'm not supposed to use arrays and composites in my tables, but this best suites our applications requirements.
Also, we have several nested composite arrays, so a generic solution that would allow me to search many levels would be appreciated.
The construction ANY in your case looks redundant. You can write the query that way:
SELECT * FROM my_people WHERE (mperson[1]).age < 20;
Of course, if you have multiple values in this array, that won't work, but you can't get the exact array element the other way neither.
Why do you need arrays at all? You can just write one element of type person per row.
Check also the excellent HStore module, which might better suit your generic needs.
Temporary test setup:
CREATE TEMP TABLE person (age integer, last_name text, first_name text
, address text);
CREATE TEMP TABLE my_people (mperson person[]);
-- test-data, demonstrating 3 different syntax styles:
INSERT INTO my_better_people (mperson)
VALUES
(array[(43, 'Stack', 'Over', '1234 Test Blvd.')::person])
,(array['(44,John,Smith,1234 Test Blvd.)'::person,
'(21,Maria,Smith,1234 Test Blvd.)'::person])
,('{"(33,John,Miller,12 Test Blvd.)",
"(22,Frank,Miller,12 Test Blvd.)",
"(11,Bodi,Miller,12 Test Blvd.)"}');
Call (almost the solution):
SELECT (p).*
FROM (
SELECT unnest(mperson) AS p
FROM my_people) x
WHERE (p).age > 33;
Returns:
age | last_name | first_name | address
-----+-----------+------------+-----------------
43 | Stack | Over | 1234 Test Blvd.
44 | John | Smith | 1234 Test Blvd.
key is the unnest() function, that's available in 9.0.
Your mistake in the example is that you forget about the ARRAY layer in between. unnest() returns one row per base element, then you can access the columns in the complex type as demonstrated.
Brave new world
IF you actually want a whole people instead of an individual that fits the criteria, I propose you add a primary key to the table and proceed as follows:
CREATE TEMP TABLE my_better_people (id serial, mperson person[]);
-- shortcut to populate the new world by emigration from the old world ;)
INSERT INTO my_better_people (mperson)
SELECT mperson FROM my_people;
Find individuals:
SELECT id, (p).*
FROM (
SELECT id, unnest(mperson) AS p
FROM my_better_people) x
WHERE (p).age > 20;
Find whole people (solution):
SELECT *
FROM my_better_people p
WHERE EXISTS (
SELECT 1
FROM (
SELECT id, unnest(mperson) AS p
FROM my_better_people
) x
WHERE (p).age > 20
AND x.id = p.id
);
You can do it without a primary key, but that would be foolish.