I'm trying to fill a table with data to test a system.
I have two tables
User
+----+----------+
| id | name |
+----+----------+
| 1 | Majikaja |
| 2 | User 2 |
| 3 | Markus |
+----+----------+
Goal
+----+----------+---------+
| id | goal | user_id |
+----+----------+---------+
I want to insert into goal one record for every user only using their IDs (they have to exists) and some fixed or random value.
I was thinking in something like this:
INSERT INTO Goal (goal, user_id) values ('Fixed value', select u.id from user u)
So it will generate:
Goal
+----+-------------+---------+
| id | goal | user_id |
+----+-------------+---------+
| 1 | Fixed value | 1 |
| 2 | Fixed value | 2 |
| 3 | Fixed value | 3 |
+----+-------------+---------+
I could just write a simple PHP script to achieve it but I wonder if is it possible to do using raw SQL only.
I have a table of users that has a column called order that represents the order in they will be elected.
So, for example, the table might look like:
| id | name | order |
|-----|--------|-------|
| 1 | John | 2 |
| 2 | Mike | 0 |
| 3 | Lisa | 1 |
So, say that now Lisa gets destroyed, I would like that in the same transaction that I destroy Lisa, I am able to update the table so the order is still consistent, so the expected result would be:
| id | name | order |
|-----|--------|-------|
| 1 | John | 1 |
| 2 | Mike | 0 |
Or, if Mike were the one to be deleted, the expected result would be:
| id | name | order |
|-----|--------|-------|
| 1 | John | 1 |
| 3 | Lisa | 0 |
How can I do this in PostgreSQL?
If you are just deleting one row, one option uses a cte and the returning clause to then trigger an update
with del as (
delete from mytable where name = 'Lisa'
returning ord
)
update mytable
set ord = ord - 1
from del d
where mytable.ord > d.ord
As a more general approach, I would really recommend trying to renumber the whole table after every delete. This is inefficient, and can get tedious for multi-rows delete.
Instead, you could build a view on top of the table:
create view myview as
select id, name, row_number() over(order by ord) ord
from mytable
Googling for a definition either returns results for a column oriented DB or gives very vague definitions.
My understanding is that wide column stores consist of column families which consist of rows and columns. Each row within said family is stored together on disk. This sounds like how row oriented databases store their data. Which brings me to my first question:
How are wide column stores different from a regular relational DB table? This is the way I see it:
* column family -> table
* column family column -> table column
* column family row -> table row
This image from Database Internals simply looks like two regular tables:
The guess I have as to what is different comes from the fact that "multi-dimensional map" is mentioned along side wide column stores. So here is my second question:
Are wide column stores sorted from left to right? Meaning, in the above example, are the rows sorted first by Row Key, then by Timestamp, and finally by Qualifier?
Let's start with the definition of a wide column database.
Its architecture uses (a) persistent, sparse matrix, multi-dimensional
mapping (row-value, column-value, and timestamp) in a tabular format
meant for massive scalability (over and above the petabyte scale).
A relational database is designed to maintain the relationship between the entity and the columns that describe the entity. A good example is a Customer table. The columns hold values describing the Customer's name, address, and contact information. All of this information is the same for each and every customer.
A wide column database is one type of NoSQL database.
Maybe this is a better image of four wide column databases.
My understanding is that the first image at the top, the Column model, is what we called an entity/attribute/value table. It's an attribute/value table within a particular entity (column).
For Customer information, the first wide-area database example might look like this.
Customer ID Attribute Value
----------- --------- ---------------
100001 name John Smith
100001 address 1 10 Victory Lane
100001 address 3 Pittsburgh, PA 15120
Yes, we could have modeled this for a relational database. The power of the attribute/value table comes with the more unusual attributes.
Customer ID Attribute Value
----------- --------- ---------------
100001 fav color blue
100001 fav shirt golf shirt
Any attribute that a marketer can dream up can be captured and stored in an attribute/value table. Different customers can have different attributes.
The Super Column model keeps the same information in a different format.
Customer ID: 100001
Attribute Value
--------- --------------
fav color blue
fav shirt golf shirt
You can have as many Super Column models as you have entities. They can be in separate NoSQL tables or put together as a Super Column family.
The Column Family and Super Column family simply gives a row id to the first two models in the picture for quicker retrieval of information.
Most (if not all) Wide-column stores are indeed row-oriented stores in that every parts of a record are stored together. You can see that as a 2-dimensional key-value store. The first part of the key is used to distribute the data across servers, the second part of the key lets you quickly find the data on the target server.
Wide-column stores will have different features and behaviors. However, Apache Cassandra, for example, allows you to define how the data will be sorted. Take this table for example:
| id | country | timestamp | message |
|----+---------+------------+---------|
| 1 | US | 2020-10-01 | "a..." |
| 1 | JP | 2020-11-01 | "b..." |
| 1 | US | 2020-09-01 | "c..." |
| 2 | CA | 2020-10-01 | "d..." |
| 2 | CA | 2019-10-01 | "e..." |
| 2 | CA | 2020-11-01 | "f..." |
| 3 | GB | 2020-09-01 | "g..." |
| 3 | GB | 2020-09-02 | "h..." |
|----+---------+------------+---------|
If your partitioning key is (id) and your clustering key is (country, timestamp), the data will be stored like this:
[Key 1]
1:JP,2020-11-01,"b..." | 1:US,2020-09-01,"c..." | 1:US,2020-10-01,"a..."
[Key2]
2:CA,2019-10-01,"e..." | 2:CA,2020-10-01,"d..." | 2:CA,2020-11-01,"f..."
[Key3]
3:GB,2020-09-01,"g..." | 3:GB,2020-09-02,"h..."
Or in table form:
| id | country | timestamp | message |
|----+---------+------------+---------|
| 1 | JP | 2020-11-01 | "b..." |
| 1 | US | 2020-09-01 | "c..." |
| 1 | US | 2020-10-01 | "a..." |
| 2 | CA | 2019-10-01 | "e..." |
| 2 | CA | 2020-10-01 | "d..." |
| 2 | CA | 2020-11-01 | "f..." |
| 3 | GB | 2020-09-01 | "g..." |
| 3 | GB | 2020-09-02 | "h..." |
|----+---------+------------+---------|
If you change the primary key (composite of partitioning and clustering key) to (id, timestamp) WITH CLUSTERING ORDER BY (timestamp DESC) (id is the partitioning key, timestamp is the clustering key in descending order), the result would be:
[Key 1]
1:US,2020-09-01,"c..." | 1:US,2020-10-01,"a..." | 1:JP,2020-11-01,"b..."
[Key2]
2:CA,2019-10-01,"e..." | 2:CA,2020-10-01,"d..." | 2:CA,2020-11-01,"f..."
[Key3]
3:GB,2020-09-01,"g..." | 3:GB,2020-09-02,"h..."
Or in table form:
| id | country | timestamp | message |
|----+---------+------------+---------|
| 1 | US | 2020-09-01 | "c..." |
| 1 | US | 2020-10-01 | "a..." |
| 1 | JP | 2020-11-01 | "b..." |
| 2 | CA | 2019-10-01 | "e..." |
| 2 | CA | 2020-10-01 | "d..." |
| 2 | CA | 2020-11-01 | "f..." |
| 3 | GB | 2020-09-01 | "g..." |
| 3 | GB | 2020-09-02 | "h..." |
|----+---------+------------+---------|
I suspect this question is already well-answered but perhaps due to limited SQL vocabulary I have not managed to find what I need. I have a database with many code:description mappings in a single 'parameter' table. I would like to define a query or procedure to return the descriptions for all (or an arbitrary list of) coded values in a given 'content' table with their descriptions from the parameter table. I don't want to alter the original data, I just want to display friendly results.
Is there a standard way to do this?
Can it be accomplished with SELECT or are other statements required?
Here is a sample query for a single coded field:
SELECT TOP (5)
newid() as id,
B.BRIDGE_STATUS,
P.SHORTDESC
FROM
BRIDGE B
LEFT JOIN PARAMTRS P ON P.TABLE_NAME = 'BRIDGE'
AND P.FIELD_NAME = 'BRIDGE_STATUS'
AND P.PARMVALUE = B.BRIDGE_STATUS
ORDER BY
id
I want to produce 'decoded' results like:
| id | BRIDGE_STATUS |
|--------------------------------------|------------ |
| BABCEC1E-5FE2-46FA-9763-000131F2F688 | Active |
| 758F5201-4742-43C6-8550-000571875265 | Active |
| 5E51634C-4DD9-4B0A-BBF5-00087DF71C8B | Active |
| 0A4EA521-DE70-4D04-93B8-000CD12B7F55 | Inactive |
| 815C6C66-8995-4893-9A1B-000F00F839A4 | Proposed |
Rather than original, coded data like:
| id | BRIDGE_STATUS |
|--------------------------------------|---------------|
| F50214D7-F726-4996-9C0C-00021BD681A4 | 3 |
| 4F173E40-54DC-495E-9B84-000B446F09C3 | 3 |
| F9C216CD-0453-434B-AFA0-000C39EFA0FB | 3 |
| 5D09554E-201D-4208-A786-000C537759A1 | 1 |
| F0BDB9A4-E796-4786-8781-000FC60E200C | 4 |
but for an arbitrary number of columns.
I have two tables, CompanyAddresses & MyCompanyAddresses. (Names changed to protect the guilty).
CompanyAddresses holds a list of default addresses for companies. These records are immutable. The user can change the details of a company address, but those changes are stored MyCompanyAddresses.
How can I produce a single list of addresses from both tables, excluding records from CompanyAddresses where a corresponding record exists in MyCompanyAddresses?
Sample Data
CompanyAddresses
DatabaseId | Id | Code | Name | Street | City | Zip | Maint Date
1 | Guid1 | APL | Apple | 1 Infinite Loop | Cupertino | 95014 | 11/1/2012
2 | Guid2 | MS | Microsoft | One Microsoft Way | Redmond | 98052 | 11/1/2012
MyCompanyAddresses
DatabaseId | Id | Code | Name | Street | City | Zip | Maint Date
5 | Guid3 | APL | Apple | Updated Address | Cupertino | 95014 | 11/6/2012
Desired Results
DatabaseId | Id | Code | Name | Street | City | Zip | Maint Date
2 | Guid2 | MS | Microsoft | One Microsoft Way | Redmond | 98052 | 11/1/2012
5 | Guid3 | APL | Apple | Updated Address | Cupertino | 95014 | 11/6/2012
I've tried various permutations of MS SQL's UNION, EXCEPT & INTERSECT to no avail. Also, I don't believe JOIN's are the answer either, but I'll be happily proven wrong.
The database design can be changed, but it would be preferable if it stayed the same.
Use a LEFT JOIN in combination with COALESCE. If the JOIN finds a match, the COALESCE will select values from the overridden row. If no match is found, the original values are returned.
SELECT ca.DatabaseId,
COALESCE(mca.Id, ca.Id) AS Id,
COALESCE(mca.Name, ca.Name) AS Name,
COALESCE(mca.Street, ca.Street) AS Street,
COALESCE(mca.City, ca.City) AS City,
COALESCE(mca.Zip, ca.Zip) AS Zip,
COALESCE(mca.MaintDate, ca.MaintDate) AS MaintDate,
FROM CompanyAddresses ca
LEFT JOIN MyCompanyAddresses mca
ON ca.Code = mca.Code;