I need to create a system to order some articles by they popularity, like a trend.
I have this table:
| Id | Title | View |
| 1 | aaa | 232 |
| 2 | bbb | 132 |
| 3 | ccc | 629 |
This way I can easilly order by number of view, but if I want to show the populars articles in the last period (not definited) and not the articles that have a lot of views but they are not longer visit? Exist a technique? I have to track all visits?
You could have a daily_views/hourly_views table according to your needs with :
ID startTime endTime number_of_views
and INSERT/UPDATE that table every time you have a new view. That way you don't have to insert a record for each view and you can have queries for different time periods.
Related
I have a table with a column for agent names and a column for each of the skills those agents could possibly have. Each skill the agent is assigned shows a 1 in the field under that skill.
Columns look like this:
+---------+----------+----------+----------+
| Name | 'Skill1' | 'Skill2' | 'Skill3' |
+---------+----------+----------+----------+
| John | 1 | | 1 |
| Sam | 1 | 1 | |
| Roberta | 1 | | 1 |
+---------+----------+----------+----------+
I would like to make a query that returns a list of all agent names that have a 1 for each particular skill. The query would return something like this:
+-----------+
| Skill 1 |
+-----------+
| John |
| Sam |
| Roberta |
+-----------+
Additionally I would like to be able to query a single name and retrieve all skills that agent has (all rows the Name column has a 1 in) like this:
+-----------+
| John |
+-----------+
| Skill 1 |
| Skill 3 |
+-----------+
I've done this in Excel using an index but I'm new to Access and not sure how to complete this task.
Thanks in advance.
One of the reasons that you are finding this task difficult is because your database is not normalised and so due to the way that your database is structured, you are working against MS Access, not with it.
Consequently, whilst a solution is still possible with the current data, the resulting queries will be painful to construct and will either be full of multiple messy iif statements, or several union queries performing the same operations over & over again, one for each 'skill'.
Then, if you every wish to add another Skill to the database, all of your queries have to be rewritten!
Whereas, if your database was normalised (as Gustav has suggested in the comments), the task would be a simple one-liner; and what's more, if you add a new skill later on, your queries will automatically output the results as if the skill had always been there.
Your data has a many-to-many relationship: an agent may have many skills, and a skill may be known by many agents.
As such, the most appropriate way to represent this relationship is using a junction table.
Hence, you would have a table of Agents such as:
tblAgents
+-----+-----------+----------+------------+
| ID | FirstName | LastName | DOB |
+-----+-----------+----------+------------+
| 1 | John | Smith | 1970-01-01 |
| ... | ... | ... | ... |
+-----+-----------+----------+------------+
This would only contain information unique to each agent, i.e. minimising the repeated information between records in the table.
You would then have a table of possible Skills, such as:
tblSkills
+-----+---------+---------------------+
| ID | Name | Description |
+-----+---------+---------------------+
| 1 | Skill 1 | Skill 1 Description |
| 2 | Skill 2 | Skill 2 Description |
| ... | ... | ... |
+-----+---------+---------------------+
Finally, you would have a junction table linking Agents to Skills, e.g.:
tblAgentSkills
+----+----------+----------+
| ID | Agent_ID | Skill_ID |
+----+----------+----------+
| 1 | 1 | 1 |
| 2 | 1 | 2 |
| 3 | 2 | 1 |
| 4 | 3 | 2 |
+----+----------+----------+
Now, say you want to find out which agents have Skill 1, the query is simple:
select Agent_ID from tblAgentSkills where Skill_ID = 1
What if you want to find out the skills known by an agent? Equally as simple:
select Skill_ID from tblAgentSkills where Agent_ID = 1
Of course, these queries will merely return the ID fields as present in the junction table - but since the ID uniquely identifies a record in the tblAgents or tblSkills tables, such ID is all you need to retrieve any other required information:
select
tblAgents.FirstName,
tblAgents.LastName
from
tblAgentSkills inner join tblAgents on
tblAgentSkills.AgentID = tblAgents.ID
where
tblAgentSkills.Skill_ID = 1
To get all agents with skill1, open the query designer and create the following query:
this will generate the following sql
SELECT Skills.AgentName
FROM Skills
WHERE (((Skills.Skill1)=1));
If you adjust the names you can also paste this query into the sql pane of the designer to get the query you want.
To get all the skills an agent has I chose a parameterized query. Open the query designer and create a new query:
When you run this query it will ask you for the name of the agent. Make sure to type the agent name exactly. Here is the resulting sql:
SELECT Skills.AgentName, Skills.Skill1, Skills.Skill2, Skills.Skill3
FROM Skills
WHERE (((Skills.AgentName)=[Agent]));
If you continue working with this query I would improve the table design by breaking your table into a skills table, agents table, skills&agents table. Then link the skills and agents tables to the skills&agents table in a many to many relationship. The query to get all an agents skills would then look like this in the designer:
Here is my current structure:
// posts
+----+--------+----------+-----------+------------+
| id | title | content | author_id | date_time |
+----+--------+----------+-----------+------------+
| 1 | title1 | content1 | 435 | 1468111492 |
| 2 | title2 | content2 | 657 | 1468113910 |
| 3 | title3 | content3 | 712 | 1468113791 |
+----+--------+----------+-----------+------------+
// viewed
+----+---------------+---------+------------+
| id | user_id_or_ip | post_id | date_tiem |
+----+---------------+---------+------------+
| 1 | 324 | 1 | 1468111493 |
| 2 | 546 | 3 | 1468111661 |
| 3 | 135.54.12.1 | 1 | 1468111691 |
| 5 | 75 | 1 | 1468112342 |
| 6 | 56.26.32.1 | 2 | 1468113190 |
| 7 | 56.26.32.1 | 3 | 1468113194 |
| 5 | 75 | 2 | 1468112612 |
+----+---------------+---------+------------+
Here is my query:
SELECT p.*,
(SELECT count(*) FROM viewed WHERE post_id = :id) AS total_viewed
FROM posts p
WHERE id = :id
Currently I've faced with a huge date for viewed table. Well what's wrong with my table structure (or database design)? In other word how can I improve it?
A website like stackoverflow has almost 12 million posts. Each post has (on average) 500 viewed. So the number of viewed's rows should be:
12000000 * 500 = 6,000,000,000 rows
Hah :-) .. Honestly I cannot even read that number (btw that number will grow up per sec). Well how stackoverflow handles the number of viewed for each post? Will it always calculate count(*) from viewed per post showing?
You are not likely to need partitioning, redis, nosql, etc, until you have many millions of rows. Meanwhile, let's see what we can do with what you do have.
Let's start by dissecting your query. I see WHERE id=... but no LIMIT or ORDER BY. Let's add to your table
INDEX(id, timestamp)
and use
WHERE id = :id
ORDER BY timestamp DESC
LIMIT 10
Any index is sorted by what is indexed. That is the 10 rows you are looking for are adjacent to each other. Even if the data is pushed out of cached, there will probably be only one block to provide those 10 rows.
But a "row" in a secondary index in InnoDB does not contain the data to satisfy SELECT *. The index "row" contains a pointer to the actual 'data' row. So, there will be 10 lookups to get them.
As for view count, let's implement that a different way:
CREATE TABLE ViewCounts (
post_id ...,
ct MEDIUMINT UNSIGNED NOT NULL,
PRIMARY KEY post_id
) ENGINE=InnoDB;
Now, given a post_id, it is very efficient to drill down the BTree to find the count. JOINing this table to the other, we get the individual counts with another 10 lookups.
So, you say, "why not put them in the same table"? The reason is that ViewCounts is changing so frequently that those actions will clash with other activity on Postings. It is better to keep them separate.
Even though we hit a couple dozen blocks, that is not bad compared to scanning millions of rows. And, this kind of data is somewhat "cacheable". Recent postings are more frequently accessed. Popular users are more frequently accessed. So, 100GB of data can be adequately cached in 10GB of RAM. Scaling is all about "counting the disk hits".
Edit for future viewers: Aside from the accepted answer which helped me I found some really good info here .
I've got a database with a single table for displaying inventory on a website (RVs). It stores the typical info: year, make, model, etc. I originally made it with 6 extra columns for storing "special features", but I don't like having such a hard limit on what options can be listed. Since I've never messed with more than a single table my gut instinct was to just add 24 or so more columns to cover everything, but something in my head told me that there might be a better way. So when do I decide N columns is too many? The data in these columns will commonly not be unique.
(Sorry for crappy diagram)
Current table design:
-----------------------------------------------------------------------
| id | year | make | model | price | ft_1 | ft_2 | ft_3 | ft_4 | ft_5 |
-----------------------------------------------------------------------
| | | | | | | | | | |
-----------------------------------------------------------------------
Possible better design:
table #1
------------------------------------
| id | year | make | model | price |
------------------------------------
| | | | | |
------------------------------------
table #2
---------------------------------------------
| unique_id(?) | feature | unit_ref |
---------------------------------------------
| 0 | "Diesel Pusher" | 2,6,14 |
---------------------------------------------
I feel like a bonus of the second table might be that I could more easily propagate a dropdown containing all the previously entered features to speed up adding new units to inventory.
Is this the right way to go about it, or should I just add more columns and be content?
Thanks.
Believe it or not, your best option would likely be to add a third table.
Since each record in your rvs table can be linked to multiple rows in the features table, and each feature can correspond to multiple rvs, you have a many-to-many relationship which is inherently difficult to maintain in a relational dbms. By adding a third "intersection" table you convert it to a one-to-many-to-one relationship which can be enforced declaratively by the dbms.
Your table structure would then become something like
rvs
------------------------------------
| id | year | make | model | price |
------------------------------------
| | | | | |
------------------------------------
features
--------------------------
| id | feature |
--------------------------
| 1192 | "Diesel Pusher" |
--------------------------
rv_features
----------------------
| rv_id | feature_id |
----------------------
| | |
----------------------
How do you make use of this? Suppose you want to record the fact that the 2016 Travelmore CampMaster has a 25kW diesel generator. You would first add a record to rvs like
--------------------------------------------------
| id | year | make | model | price |
--------------------------------------------------
| 0231 | 2016 | Travelmore | CampMaster | 750000 |
| 2101 | 2016 | Travelmore | Domestant | 650000 |
--------------------------------------------------
(Note the value in the id column is entirely arbitrary; its sole purpose is to serve as the primary key which uniquely identifies the record. It can encode meaningful information, but it must be something that will not change throughout the life of the record it identifies.)
You then add (or already have) the generator in the features table:
--------------------------------
| id | feature |
--------------------------------
| 1192 | Diesel Pusher 450hp |
| 3209 | diesel generator 25kW |
--------------------------------
Finally, you associate the rv to the feature with a record in rv_features:
----------------------
| rv_id | feature_id |
----------------------
| 0231 | 3209 |
| 0231 | 1192 |
| 2101 | 3209 |
----------------------
(I've added a few other records to each table for context.)
Now, to retrieve the features of the 2016 CampMaster, you use the following SQL query:
SELECT r.year, r.make, r.model, f.feature
FROM rvs r, features f, rv_features rf
WHERE r.id = rf.rv_id
AND rv.feature_id = f.id
AND r.id = '2031';
to get
----------------------------------------------------------
| year | make | model | feature |
----------------------------------------------------------
| 2016 | Travelmore | CampMaster | diesel generator 25kW |
| 2016 | Travelmore | CampMaster | Diesel Pusher 450hp |
----------------------------------------------------------
To see the rvs with a 25kW generator, change the query to
SELECT r.year, r.make, r.model, f.feature
FROM rvs r, features f, rv_features rf
WHERE r.id = rf.rv_id
AND rv.feature_id = f.id
AND f.id = '3209';
Sherantha's link to A Quick-Start Tutorial on Relational Database Design actually looks like a good intro to table design and normalization; you might find it useful.
There is a thing calles "third normal form" it says that everything without the unique ids shuld be unique. This means you need to make a table for year, a table for make a table for models etc and a table where you can combine all these ids to one connected dataset.
But this is not always practical, io think the best way to take this is something in between, like tables for entrys that repeat very often, but there dont need to be an extra table for price with unique ids, that would be overkill i think.
Based upon your scenario, if you believe no. of features columns remain same then no need for second table. And in case if there any possibility that features can be increased at any time in future then you should break up your table into two. (RVS & Features). Then create a third table that identify RVS & features as it seems there is many-to-many relationship. So I suggest you to use three tables.
I think it is better for you to be more familiar with relational database design. This is a short but great article I have found earlier.
I am quite new to MySQL, I know most of the basic functions and how to send queries etc. However, I am trying to learn about structuring it for optimal searches for user information and wanted to get some ideas.
Right now I just have one table (for functionality purposes and testing) called user_info which holds the users information and another table that stores photos linked to the user. Ideally id like most of this information to be as quickly as accessible as possible
In creating a database which is primarily used to store and retrieve user information (name, age, phone, messages, etc.) would it be a good idea to create a NEW TABLE for each new user that stores all the information so the one table user_info does not become bogged down by multiple queries, locking, etc. So for example user john smith would have his very own table in the database holding all his information including photos, messages etc.
OR
is it better to have just a few tables such as user_info, user_photos, user_messages,etc. and accessing data in this manner.
I am not concerned about redundancy in the tables such as the users email address being repeated multiple times.
The latter is the best way. You declare one table for users, and several columns with the data you want.
Now if you want users to have photos, you'd require a new table with photos and a Foreign Key attribute that links to the user table's Primary Key.
You should definitely NOT create a new table for each user. Create one table for user_info, one for photos if each user can have many photos. A messages table would probably contain two user_id columns (user_to, user_from) and a message column. Try to normalize the data as much as possible.
Users
====
id
email
etc
Photos
====
id
user_id
meta_data
etc
Messages
====
id
user_id_to
user_id_from
message
timestamp
etc
I agree with both the answers supplied here, but one thing they haven't mentioned yet is lookup tables.
Going with the general examples here consider this: you have a users table, and a photos table. Now you want to introduce a featre on your site that allows users to "Favorite" photos from other users.
Rather than making a new table called "Favorites" and adding in all your data about the image (fiel location, metadata, score/whatever) all over again, have a table that effectively sits BETWEEN the other two.
+-----------------------+ +-------------------------------------+
| ++ users | | ++ photos |
| userID | email | name | | photoID | ownerID | fileLo | etc... |
+--------+-------+------| +---------+---------+--------+--------+
| 1 | .... | Tom | | 35 | 1 | ..... | .......|
| 2 | .... | Rob | | 36 | 2 | ..... | .......|
| 3 | .... | Dan | | 37 | 1 | ..... | .......|
+--------+-------+------+ | 43 | 3 | ..... | .......|
| 48 | 2 | ..... | .......|
| 49 | 3 | ..... | .......|
| 53 | 2 | ..... | .......|
+---------+---------+--------+--------+
+------------------+
| ++ Favs |
| userID | photoID |
+--------+---------+
| 1 | 37 |
| 1 | 48 |
| 2 | 37 |
+--------+---------+
With this approach, you link the data you have cleanly, efficiently and without too much data replication.
Just after some opinions on the best way to achieve the following outcome:
I would like to store in my MySQL database products which can be voted on by users (each vote is worth +1). I also want to be able to see how many times in total a user has voted.
To my simple mind, the following table structure would be ideal:
table: product table: user table: user_product_vote
+----+-------------+ +----+-------------+ +----+------------+---------+
| id | product | | id | username | | id | product_id | user_id |
+----+-------------+ +----+-------------+ +----+------------+---------+
| 1 | bananas | | 1 | matthew | | 1 | 1 | 2 |
| 2 | apples | | 2 | mark | | 2 | 2 | 2 |
| .. | .. | | .. | .. | | .. | .. | .. |
This way I can do a COUNT of the user_product_vote table for each product or user.
For example, when I want to look up bananas and the number of votes to show on a web page I could perform the following query:
SELECT p.product AS product, COUNT( v.id ) as votes
FROM product p
LEFT JOIN user_product_vote v ON p.id = v.product_id
WHERE p.id =1
If my site became hugely successful (we can all dream) and I had thousands of users voting on thousands of products, I fear that performing such a COUNT with every page view would be highly inefficient in terms of server resources.
A more simple approach would be to have a 'votes' column in the product table that is incremented each time a vote is added.
table: product
+----+-------------+-------+
| id | product | votes |
+----+-------------+-------+
| 1 | bananas | 2 |
| 2 | apples | 5 |
| .. | .. | .. |
While this is more resource friendly - I lose data (eg. I can no longer prevent a person from voting twice as there is no record of their voting activity).
My questions are:
i) am I being overly worried about server resources and should just stick with the three table option? (ie. do I need to have more faith in the ability of the database to handle large queries)
ii) is their a more efficient way of achieving the outcome without losing information
You can never be over worried about resources, when you first start building an application you should always have resources, space, speed etc. in mind, if your site's traffic grew dramatically and you never built for resources then you start getting into problems.
As for the vote system, personally I would keep the votes like so:
table: product table: user table: user_product_vote
+----+-------------+ +----+-------------+ +----+------------+---------+
| id | product | | id | username | | id | product_id | user_id |
+----+-------------+ +----+-------------+ +----+------------+---------+
| 1 | bananas | | 1 | matthew | | 1 | 1 | 2 |
| 2 | apples | | 2 | mark | | 2 | 2 | 2 |
| .. | .. | | .. | .. | | .. | .. | .. |
Reasons:
Firstly user_product_vote does not contain text, blobs etc., it's purely integer so it takes up less resources anyways.
Secondly, you have more of a doorway to new entities within your application such as Total votes last 24 hr, Highest rated product over the past 24 hour etc.
Take this example for instance:
table: user_product_vote
+----+------------+---------+-----------+------+
| id | product_id | user_id | vote_type | time |
+----+------------+---------+-----------+------+
| 1 | 1 | 2 | product |224.. |
| 2 | 2 | 2 | page |218.. |
| .. | .. | .. | .. | .. |
And a simple query:
SELECT COUNT(id) as total FROM user_product_vote WHERE vote_type = 'product' AND time BETWEEN(....) ORDER BY time DESC LIMIT 20
Another thing is if a user voted at 1AM and then tried to vote again at 2PM, you can easily check when the last time they voted and if they should be allowed to vote again.
There are so many opportunities that you will be missing if you stick with your incremental example.
In regards to your count(), no matter how much you optimize your queries it would not really make a difference on a large scale.
With an extremely large user-base your resource usage will be looked at from a different perspective such as load balancers, mainly server settings, Apache, catching etc., there's only so much you can do with your queries.
If my site became hugely successful (we can all dream) and I had thousands of users voting on thousands of products, I fear that performing such a COUNT with every page view would be highly inefficient in terms of server resources.
Don't waste your time solving imaginary problems. mysql is perfectly able to process thousands of records in fractions of a second - this is what databases are for. Clean and simple database and code structure is far more important than the mythical "optimization" that no one needs.
Why not mix and match both? Simply have the final counts in the product and users tables, so that you don't have to count every time and have the votes table , so that there is no double posting.
Edit:
To explain it a bit further, product and user table will have a column called "votes". Every time the insert is successfull in user_product_vote, increment the relevant user and product records. This would avoid dupe votes and you wont have to run the complex count query every time as well.
Edit:
Also i am assuming that you have created a unique index on product_id and user_id, in this case any duplication attempt will automatically fail and you wont have to check in the table before inserting. You will just to make sure the insert query ran and you got a valid value for the "id" in the form on insert_id
You have to balance the desire for your site to perform quickly (in which the second schema would be best) and the ability to count votes for specific users and prevent double voting (for which I would choose the first schema). Because you are only using integer columns for the user_product_vote table, I don't see how performance could suffer too much. Many-to-many relationships are common, as you have implemented with user_product_vote. If you do want to count votes for specific users and prevent double voting, a user_product_vote is the only clean way I can think of implementing it, as any other could result in sparse records, duplicate records, and all kinds of bad things.
You don't want to update the product table directly with an aggregate every time someone votes - this will lock product rows which will then affect other queries which are using products.
Assuming that not all product queries need to include the votes column, you could keep a separate productvotes table which would retain the running totals, and keep your userproductvote table as a means to enforce your user voting per product business rules / and auditing.