I have two doubts:
I have a table as follows:
AUTHOR
(
authorID int NOT NULL,
authName varchar(255) NOT NULL,
authSurname varchar(255),
authPlaceOfBirth varchar(255),
authDOB date(),
authDoD varchar(255),
PRIMARY KEY (authorID)
)
Now, I want to find the authors who have died. That is, if the value of DoD exists in the table, then they have died. How to do this? That is, a particular value in a column exists?
Something like this:
SELECT authName
FROM AUTHOR
WHERE authDoD is not NULL?
Second, I have two tables as follows:
TABLE inventory_genre
{
genreID int NOT NULL,
inventoryID int NOT NULL,
PRIMARY KEY (genreID,inventoryID)
}
TABLE INVENTORY
{
inventoryID int NOT NULL,
title varchar(255),
wholesale int,
markup int,
qtyinStock int,
Discount int,
PRIMARY KEY (inventoryID)
}
I want to list all the genres that have no associated titles in the inventory. I know I have to subtract but I am not able to come up with it exactly. Please guide me in the right direction!
Not sure I understand the criteria you are describing in the first question, but either
select * from author where authDOB is not null;
or
select * from author where authDOB = 'some value that I dont know';
For the second one, you could use exists or in with a nested select:
select * from genre where id not in (select genreId from inventory_genre);
Part 1
Think about it logically:
you're looking for people who are referenced by what?
By their death.
How do you know they're dead?
Because a certain field in the table has been filled in.
Can you quantify this?
Yes, the value of their death exists.
So, yon can construct an SQL search that looks in the table of Authors for rows (people) where the column (authDoD) value is not nothing/null.
As a note for a perfect world you should have IS NULL set in the column authDoD so that if no value is set the column row value is NULL and easier to handle in queries.
SQL (assuming column can be empty but not Null):
SELECT * FROM authors WHERE authDoD > ''
SQL (assuming column can only be null unless dead):
SELECT * FROM authors WHERE authDoD IS NOT NULL
Part 2
You want to return a negative search, a search that turns up no results, so find each genre which does not feature in any inventory table row.
While I'm about to write a longer answer for this, the answer just posted by Tobb does exactly what you need.
Also note that you should ideally have an INDEX on your ID columns to make traversing them smoother and faster.
For the first part of your question, you could use
SELECT * FROM AUTHOR WHERE authDoD IS NOT NULL;
This would SELECT the deceased people
Your first problem is solved, if you check for authorDoD > ''. It will evaluate to false if there's NULL or the empty string ''.
To solve your second problem you could just JOIN your tables, since the inventoryID isn't allowed to be NULL.
JOIN INVENTORY i ON (inventory_genre.inventoryID = i.inventoryID)
After that you can check the existence of an title like above with title > ''.
The previous table this data was stored in approached 3-4gb, but the data wasn't compressed before/after storage. I'm not a DBA so I'm a little out of my depth with a good strategy.
The table is to log changes to a particular model in my application (user profiles), but with one tricky requirement: we should be able to fetch the state of a profile at any given date.
Data (single table):
id, username, email, first_name, last_name, website, avatar_url, address, city, zip, phone
The only two requirements:
be able to fetch a list of changes for a given model
be able to fetch state of model on a given date
Previously, all of the profile data was stored for a single change, even if only one column was changed. But to get a 'snapshot' for a particular date was easy enough.
My first couple of solutions in optimising the data structure:
(1) only store changed columns. This would drastically reduce data stored, but would make it quite complicated to get a snapshot of data. I'd have to merge all changes up to a given date (could be thousands), then apply that to a model. But that model couldn't be a fresh model (only changed data is stored). To do this, I'd have to first copy over all data from current profiles table, then to get snapshot apply changes to those base models.
(2) store whole of data, but convert to a compressed format like gzip or binary or whatnot. This would remove ability to query the data other than to obtain changes. I couldn't, for example, fetch all changes where email = ''. I would essentially have a single column with converted data, storing the whole of the profile.
Then, I would want to use relevant MySQL table options, like ARCHIVE to further reduce space.
So my question is, are there any other options which you feel are a better approach than 1/2 above, and, if not, which would be better?
First of all, I wouldn't worry at all about a 3GB table (unless it grew to this size in a very short period of time). MySQL can take it. Space shouldn't be a concern, keep in mind that a 500 GB hard disk costs about 4 man-hours (in my country).
That being said, in order to lower your storage requirements, create one table for each field of the table you want to monitor. Assuming a profile table like this:
CREATE TABLE profile (
profile_id INT PRIMARY KEY,
username VARCHAR(50),
email VARCHAR(50) -- and so on
);
... create two history tables:
CREATE TABLE profile_history_username (
profile_id INT NOT NULL,
username VARCHAR(50) NOT NULL, -- same type as profile.username
changedAt DATETIME NOT NULL,
PRIMARY KEY (profile_id, changedAt),
CONSTRAINT profile_id_username_fk
FOREIGN KEY profile_id_fkx (profile_id)
REFERENCES profile(profile_id)
);
CREATE TABLE profile_history_email (
profile_id INT NOT NULL,
email VARCHAR(50) NOT NULL, -- same type as profile.email
changedAt DATETIME NOT NULL,
PRIMARY KEY (profile_id, changedAt),
CONSTRAINT profile_id_fk
FOREIGN KEY profile_id_email_fkx (profile_id)
REFERENCES profile(profile_id)
);
Everytime you change one or more fields in profile, log the change in each relevant history table:
START TRANSACTION;
-- lock all tables
SELECT #now := NOW()
FROM profile
JOIN profile_history_email USING (profile_id)
WHERE profile_id = [a profile_id]
FOR UPDATE;
-- update main table, log change
UPDATE profile SET email = [new email] WHERE profile_id = [a profile_id];
INSERT INTO profile_history_email VALUES ([a profile_id], [new email], #now);
COMMIT;
You may also want to set appropriate AFTER triggers on profile so as to populate the history tables automatically.
Retrieving history information should be straightforward. In order to get the state of a profile at a given point in time, use this query:
SELECT
(
SELECT username FROM profile_history_username
WHERE profile_id = [a profile_id] AND changedAt = (
SELECT MAX(changedAt) FROM profile_history_username
WHERE profile_id = [a profile_id] AND changedAt <= [snapshot date]
)
) AS username,
(
SELECT email FROM profile_history_email
WHERE profile_id = [a profile_id] AND changedAt = (
SELECT MAX(changedAt) FROM profile_history_email
WHERE profile_id = [a profile_id] AND changedAt <= [snapshot date]
)
) AS email;
You can't compress the data without having to uncompress it in order to search it - which is going to severely damage the performance. If the data really is changing that often (i.e. more than an average of 20 times per record) then it would be more efficient to for storage and retrieval to structure it as a series of changes:
Consider:
CREATE TABLE profile (
id INT NOT NULL autoincrement,
PRIMARY KEY (id);
);
CREATE TABLE profile_data (
profile_id INT NOT NULL,
attr ENUM('username', 'email', 'first_name'
, 'last_name', 'website', 'avatar_url'
, 'address', 'city', 'zip', 'phone') NOT NULL,
value CARCHAR(255),
starttime DATETIME DEFAULT CURRENT_TIME,
endtime DATETIME,
PRIMARY KEY (profile_id, attr, starttime)
INDEX(profile_id),
FOREIGN KEY (profile_id) REFERENCES profile(id)
);
When you add a new value for an existing record, set an endtime in the masked record.
Then to get the value at a date $T:
SELECT p.id, attr, value
FROM profile p
INNER JOIN profile_date d
ON p.id=d.profile_id
WHERE $T>=starttime
AND $T<=IF(endtime IS NULL,$T, endtime);
Alternately just have a start time, and:
SELECT p.id, attr, value
FROM profile p
INNER JOIN profile_date d
ON p.id=d.profile_id
WHERE $T>=starttime
AND NOT EXISTS (SELECT 1
FROM prodile_data d2
WHERE d2.profile_id=d.profile_id
AND d2.attr=d.attr
AND d2.starttime>d.starttime
AND d2.starttime>$T);
(which will be even faster with the MAX concat trick).
But if the data is not changing with that frequency then keep it in the current structure.
You need a slow changing dimension:
i will do this only for e-mail and telephone so you understand (pay attention to the fact of i use two keys, 1 as unique in the table, and another that is unique to the user that it concerns. This is, the table key identifies the the record, and the user key identifies the user):
table_id, user_id, email, telephone, created_at,inactive_at,is_current
1, 1, mario#yahoo.it, 123456, 2012-01-02, , 2013-04-01, no
2, 2, erik#telecom.de, 123457, 2012-01-03, 2013-02-28, no
3, 3, vanessa#o2.de, 1234568, 2012-01-03, null, yes
4, 2, erik#telecom.de, 123459, 2012-02-28, null, yes
5, 1, super.mario#yahoo.it, 654321,2013-04-01, 2013-04-02, no
6, 1, super.mario#yahoo.it, 123456,2013-04-02, null, yes
most recent state of the database
select * from FooTable where inactive_at is null
or
select * from FooTable where is_current = 'yes'
All changes to mario (mario is user_id 1)
select * from FooTable where user_id = 1;
All changes between 1 jan 2013 and 1 of may 2013
select * from FooTable where created_at between '2013-01-01' and '2013-05-01';
and you need to compare with the old versions (with the help of a stored procedure, java or php code... you chose)
select * from FooTable where incative_at between '2013-01-01' and '2013-05-01';
if you want you can do a fancy sql statement
select f1.table_id, f1.user_id,
case when f1.email = f2.email then 'NO_CHANGE' else concat(f1.email , ' -> ', f2.email) end,
case when f1.phone = f2.phone then 'NO_CHANGE' else concat(f1.phone , ' -> ', f2.phone) end
from FooTable f1 inner join FooTable f2
on(f1.user_id = f2.user_id)
where f2.created_at in
(select max(f3.created_at) from Footable f3 where f3.user_id = f1.user_id
and f3.created_at < f1.created_at and f1.user_id=f3.user_id)
and f1.created_at between '2013-01-01' and '2013-05-01' ;
As you can see a juicy query, to compare the user_with the previews user row...
the state of the database on 2013-03-01
select * from FooTable where table_id in
(select max(table_id) from FooTable where inactive_at <= '2013-03-01' group by user_id
union
select id from FooTable where inactive_at is null group by user_id having count(table_id) =1 );
I think this is the easiest way of implement what you want... you could implement a multi-million tables relational model, but then it would be a pain in the arse to query it
Your database is not big enough, I work everyday with one even bigger. Now tell me is the money you save in a new server worthy the time you spend on a super-complex relational model?
BTW if the data changes too fast, this approach cannot be used...
BONUS: optimization:
create indexes on created_at, inactive_at, user_id and the pair
perform partition (both horizontal and vertical)
if you try and put all occurring changes in different tables and later if you require an instance on some date you join them along and display by comparing dates, for example if you want an instance at 1st of july you can run a query with condition where date is equal or less than 1st of july and order it in asc ordering limiting the count to 1. that way the joins will produce exactly the instance it was at 1st of july. in this manner you can even figure out the most frequently updated module.
also if you want to keep all the data flat try range partitioning on the basis of month that way mysql will handle it pretty easily.
Note: by date i mean storing unix timestamp of the date its pretty easier to compare.
I'll offer one more solution just for variety.
Schema
PROFILE
id INT PRIMARY KEY,
username VARCHAR(50) NOT NULL UNIQUE
PROFILE_ATTRIBUTE
id INT PRIMARY KEY,
profile_id INT NOT NULL FOREIGN KEY REFERENCES PROFILE (id),
attribute_name VARCHAR(50) NOT NULL,
attribute_value VARCHAR(255) NULL,
created_at DATETIME NOT NULL DEFAULT GETTIME(),
replaced_at DATETIME NULL
For all attributes you are tracking, simply add PROFILE_ATTRIBUTE records when they are updated, and mark the previous attribute record with the DATETIME it was replaced at.
Select Current Profile
SELECT *
FROM PROFILE p
LEFT JOIN PROFILE_ATTRIBUTE pa
ON p.id = pa.profile_id
WHERE p.username = 'username'
AND pa.replaced_at IS NULL
Select Profile At Date
SELECT *
FROM PROFILE p
LEFT JOIN PROFIILE_ATTRIBUTE pa
ON p.id = pa.profile_id
WHERE p.username = 'username'
AND pa.created_at < '2013-07-01'
AND '2013-07-01' <= IFNULL(pa.replaced_at, GETTIME())
When Updating Attributes
Insert the new attribute
Update the previous attribute's replaced_at value
It would probably be important that the created_at for a new attribute match the replaced_at for the corresponding old attribute. This would be so that there is an unbroken timeline of attribute values for a given attribute name.
Advantages
Simple two-table architecture (I personally don't like a table-per-field approach)
Can add additional attributes with no schema changes
Easily mapped into ORM systems, assuming an application lives on top of this database
Could easily see the history for a certain attribute_name over time.
Disadvantages
Integrity is not enforced. For example, the schema doesn't restrict on multiple NULL replaced_at records with the same attribute_name... perhaps this could be enforced with a two-column UNIQUE constraint
Let's say you add a new field in the future. Existing profiles would not select a value for the new field until they save a value to it. This is opposed to the value coming back as NULL if it were a column. This may or may not be an issue.
If you use this approach, be sure you have indexes on the created_at and replaced_at columns.
There may be other advantages or disadvantages. If commenters have input, I'll update this answer with more information.
So i have been looking around and not finding much. I appologize ahead of time because this is probably the wrong way to do this but it is what it is.
So i have to track class's that co-workers have completed. This is done through a excel sheet that feeds the MS access database. There is 3 fields that are supplied to me.
Full name, Course Name, and Completion Date.
I know that i dont have a primary key here so i am trying to create a query that will only append the unique records pulled from the excel sheet. I can do it based on a single field but need help making my query append it only when both the Full name and Course Name are not the same for example
Joe Somebody, Course#1, 14feb13
Joe Somebody, Course#2, 15feb13
Joe Somebody, Course#1, 15feb13
I need a query that will append the first 2 rows to a table but ignore the third one due to the person already completing course#1. this is what i have so far that basicly turns my name field into a Primary key.
INSERT INTO table [Full name], [Course], [Date]
SELECT excel_table.[Full name], excel_table.[Course], excel_table.[Date]
FROM excel_table
WHERE excel_table.[Full name] Not in (SELECT table.[Full Name] FROM table)
I also have some Is Not Null stuff at the end but i didnt think it would be relevent to the question.
The easiest way to do this so you do not get duplicates is to add an index. In this case, a composite primary key would seem to be the answer. Just select all of the fields you want included in the composite key and click the Primary Key button:
You will not be allowed nulls in any of the fields comprising the primary key, but as long as the combination of the fields is not matched, data in each of the fields can be repeated. So:
Joe Somebody, Course#1, 14feb13 <-- good
Joe Somebody, Course#2, 15feb13 <-- good
Joe Somebody, Course#1, 15feb13 <-- fails
Joe SomebodyElse, Course#1, 14feb13 <-- good
Now, if you run an ordinary append query build with the query design window, you will get an error if the record exists twice in the Excel import table or already exists in Access:
You don't actually need a composite primary key. In fact there are a few places in Access where you are encouraged to not use a composite primary key. You can create your Access table with a simple integer primary key:
create table CourseCompletions (
ID autoincrement primary key
, FullName varchar(100)
, CourseName varchar(100)
, CompletionDate date
);
Then you can gulp in all the data from the Excel file:
insert into CourseCompletions (
, FullName
, CourseName
, CompletionDate
) select
[Full name]
, [Course]
, [Date]
from excel_table;
This will give each row of your input Excel table a unique number and stash it in the Access table. Now you need to decide how you want to reject conflicting rows from your CourseCompletions table. (The following queries show only the records that you decide to not reject.) If you want to reject completions by the same person of the same course at a later date:
select
ID
, FullName
, CourseName
, min(CompletionDate)
from CourseCompletions
group by
ID
, FullName
, CourseName;
If you want to reject completions at an earlier date simply change the MIN to MAX.
If you want to reject any course completion that appeared earlier in the Excel table:
select
cc1.ID
, cc1.FullName
, cc1.CourseName
, cc1.CompletionDate
from CourseCompletions as cc1
inner join (
select
max(ID) as WantedID
, FullName
, CourseName
from CourseCompletions
group by FullName, CourseName
) as cc2
on cc1.ID = cc2.WantedID;
And to reject course completions that appeared later in the Excel table, simply replace MAX with MIN.
So using an integer primary key gives you some options.
I'm trying to figure out how to query the numbers that belong to a particular group in a table for statistic purposes.
The table in question is this:
create table MEMBER
( id int not null,
name varchar(10),
bdate date,
sex char,
pc_id int not null,
PRIMARY KEY (mid),
FOREIGN KEY (pc_id) REFERENCES PLEDGECLASS(id))
I want to come up with a query that checks all the rows and returns a count of common pc_ids and those corresponding pc_ids.
For example, if the table Member contains the following data:
{1,'jon',02091985,'M',02
2,'don',03091985,'M',03
3,'kon',03091985,'M',02
4,'tron',03091985,'M',03)
I would want the following to be returned:
count pc_id
2 02
2 03
I figured I had to compare two of the same table to figure it out, but that didn't quite work for me. I came up with the following:
Select count(p.pc_id), P.pc_id
From MEMBER p, MEMBER x
Where p.pc_id=x.pc_id AND NOT p.name = x.name;
I know my obvious error with count, but not quite sure how to resolve it.
GROUP BY will do the trick
Select count(p.pc_id), p.pc_id
From MEMBER p
Group By p.pc_id
What's the best way to query one-to-many in MySQL? This is a simplified version of the database I am working on (if anything doesn't look right tell me):
CREATE TABLE Tenant(
tenant_id int NOT NULL,
first_name varchar(20),
last_name varchar(20),
PRIMARY KEY (tenant_id)
);
CREATE TABLE Rent(
tenant_id int NOT NULL,
month enum('JAN', 'FEB', ...),
date_paid date NOT NULL,
amount_paid int NOT NULL,
FOREIGN KEY (tenant_id) REFERENCES Tenant(tenant_id)
);
(The reason that there is month and date_paid in the Rent table is because the tenant does not necessarily pay the rent all at once). What I want the tenant's name to appear once which would just be a Left Join, but I want all the amount paid in a particular month listed as columns for each tenant, I am not sure how to go about that. I am not really sure how to do that since your are dealing with an unknown amount of columns, haven't touched that yet in MySQL. Or is there a better strategy? Also, how would I go about creating my own variable like MONTH-YEAR (I don't think that exists as a native variable in MySQL). Thank you!
Edit:
Just to simplify it further I am using this format:
create table rent(
tenant_id int not null,
year year,
amount_paid int,
foreign key (tenant_id) references tenant(tenant_id)
);
If I understand what duffymo said below I should use group by (I know I am misunderstanding somewhere because it only shows the first example for each year):
SELECT Tenant.first_name, Rent.year, Rent.amount_paid
FROM Tenant
LEFT JOIN Rent
ON Tenant.tenant_id = Rent.tenant_id
GROUP BY year;
This is what I want the query to look like, the number under each year is the amount paid (I actually just realized it's a little bit more complex than what I how explained):
first_name 2009 2008 2007
John 500 500 NULL
Ann 1000 NULL NULL
Bob NULL 700 700
If you have MONTH and YEAR columns, you can do a GROUP BY to select amount paid broken out as you'd wish. If you have a PAID_DATE column, one way to do this would be to have a BEFORE INSERT trigger that runs when the PAID_DATE is set. That way users don't have to enter values, and data integrity can be guaranteed.