Storing count in the main table - sql

I have three database tables,
Users ( UserID, ... )
Entries ( EntryID, ... )
Likes ( UserID, EntryID, ... )
My question is easy. Should I use a LikeCount column in the table Entries or use a SELECT COUNT(*) statement everytime I need it from Likes table? Which one is the better practice?
It's probably duplicate with this question: storing the count of rows or just count the rows? The given answer to that question is basically don't use LikeCount and count every time you need instead. However they do not give satisfactory answers to the following questions:
What is the bad consequences of storing count in the table
What is the performance analyzes of these two different approaches if I need to count likes very frequently in my application
PS: I use SQL Server 2008 if it is important

What is the bad consequences of storing count in the table:
There are 2 problems with this approach:
You have to use database triggers or application code to keep the count up to date as the Likes table changes.
If you ever get #1 wrong, you have to deal with the fact that the LikeCount might not actually match the number of likes.
What is the performance analyzes of these two different approaches if I need to count likes very frequently in my application:
I believe that if you created an index for the Likes table, most database engines will be able to answer a COUNT(*) query very quickly without referencing the actual table. Basically, in the index the database keeps track of how many rows match a given key, which is the same thing as your LikeCount.
If you are going to write a query like:
SELECT count(*) from Likes where EntryID=45;
Then your index has to be on EntryID.
But, if you are going to write a query like:
SELECT count(*) from Likes where EntryID=45 and deleted=False;
Then your index has to be on (EntryID, deleted).

Related

Quickly find a record appearing more than twice in a table

Title pretty much says it all, using Oracle SQL, I'd like to get, as quickly as possible, three records that share an ID from a very large table. The rows are not duplicates, they share one ID (rID) but differ in another (mID).
One approach I know I could do (that would be very slow) would be to load the first say 1000 records into a C# program, then execute a COUNT query to count the number of records with each ID until I hit one with 3 records and return that ID. I know this is a terrible approach but should give an idea of what I want to get out of this.
I've tried using GROUP BY, and this would work but would be unacceptably slow, I don't care about the state of the rest of the table, I just need a single ID that has three records. Ideally I'd do something like a GROUP BY that would stop after finding the first ID with three or more records and just return that one. There are over a million records in the table so efficiency is important.
What you describe translates to:
select the_id
from the_table
group by the_id
having count(*) >= 3
fetch first row only;
This should be as fast as it gets. You can help Oracle by providing an index on the id. That's about it.

SQLite: How to SELECT "most recent record for each user" from single table with composite key?

I'm not a database guru and feel like I'm missing some core SQL knowledge to grok a solution to this problem. Here's the situation as briefly as I can explain it.
Context:
I have a SQLite database table that contains timestamped user event records. The records can be uniquely identified by the combination of timestamp and user ID (i.e., when the event took place and who the event is about). I understand this situation is called a "composite primary key." The table looks something like this (with a bunch of other columns removed, of course):
sqlite> select Last_Updated,User_ID from records limit 4;
Last_Updated User_ID
------------- --------
1434003858430 1
1433882146115 3
1433882837088 3
1433964103500 2
Question: How do I SELECT a result set containing only the most recent record for each user?
Given the above example, what I'd like to get back is a table that looks like this:
Last_Updated User_ID
------------- --------
1434003858430 1
1433882837088 3
1433964103500 2
(Note that the result set only includes user 3's most recent record.)
In reality, I have approximately 2.5 million rows in this table.
Bonus: I've been reading answers about JOINs, de-dupe procedures, and a bunch more, and I've been googling for tutorials/articles in the hopes that I would find what I'm missing. I have extensive programming background so I could de-dupe this dataset in procedural code like I've done a hundred times before, but I'm tired of writing scripts to do what I believe should be possible in SQL. That's what it's for, right?
So, what do you think is missing from my understand of SQL, conceptually, that I need in order to understand why the solution you've provided to my question actually works? (A reference to a good article that actually explains the theory behind the practice would suffice.) I want to know WHY the solution actually works, not just that it does.
Many thanks for your time!
You could try this:
select user_id, max(last_updated) as latest
from records
group by user_id
This should give you the latest record per user. I assume you have an index on user_id and last_updated combined.
In the above query, generally speaking - we are asking the database to group user_id records. If there are more than 1 records for user_id 1, they will all be grouped together. From that recordset, maximum last_updated will be picked for output. Then the next group is sought and the same operation is applied there.
If you have a composite index, sqlite will likely just use the index because the index contains both fields addressed in the query. Indexes are smaller than the table itself, so scanning or seeking is faster.
Well, in true "d'oh!" fashion, right after I ask this question, I find the answer.
For my case, the answer is:
SELECT MAX(Last_Updated),User_ID FROM records GROUP BY User_ID
I was making this more complicated than it needed to be by thinking I needed to use JOINs and stuff. Applying an aggregate function like MAX() is all that's needed to select only those rows whose content matches the function result. That means this statement…
SELECT MAX(Last_Updated),User_ID FROM records
…would therefor return a result set containing only 1 row, the most recent event.
By adding the GROUP BY clause, however, the result set contains a row for each "group" of results, i.e., for each user. My programmer-brain did not understand that GROUP BY is how we say "for each" in SQL. I think I get it now.
Note to self: keep it simple, stupid. :)

Store results of SQL Server query for pagination

In my database I have a table with a rather large data set that users can perform searches on. So for the following table structure for the Person table that contains about 250,000 records:
firstName|lastName|age
---------|--------|---
John | Doe |25
---------|--------|---
John | Sams |15
---------|--------|---
the users would be able to perform a query that can return about 500 or so results. What I would like to do is allow the user see his search results 50 at a time using pagination. I've figured out the client side pagination stuff, but I need somewhere to store the query results so that the pagination uses the results from his unique query and not from a SELECT * statement.
Can anyone provide some guidance on the best way to achieve this? Thanks.
Side note: I've been trying to use temp tables to do this by using the SELECT INTO statements, but I think that might cause some problems if, say, User A performs a search and his results are stored in the temp table then User B performs a search shortly after and User A's search results are overwritten.
In SQL Server the ROW_NUMBER() function is great for pagination, and may be helpful depending on what parameters change between searches, for example if searches were just for different firstName values you could use:
;WITH search AS (SELECT *,ROW_NUMBER() OVER (PARTITION BY firstName ORDER BY lastName) AS RN_firstName
FROM YourTable)
SELECT *
FROM search
WHERE RN BETWEEN 51 AND 100
AND firstName = 'John'
You could add additional ROW_NUMBER() lines, altering the PARTITION BY clause based on which fields are being searched.
Historically, for us, the best way to manage this is to create a complete new table, with a unique name. Then, when you're done, you can schedule the table for deletion.
The table, if practical, simply contains an index id (a simple sequenece: 1,2,3,4,5) and the primary key to the table(s) that are part of the query. Not the entire result set.
Your pagination logic then does something like:
SELECT p.* FROM temp_1234 t, primary_table p
WHERE t.pkey = p.primary_key
AND t.serial_id between 51 and 100
The serial id is your paging index.
So, you end up with something like (note, I'm not a SQL Server guy, so pardon):
CREATE TABLE temp_1234 (
serial_id serial,
pkey number
);
INSERT INTO temp_1234
SELECT 0, primary_key FROM primary_table WHERE <criteria> ORDER BY <sort>;
CREATE INDEX i_temp_1234 ON temp_1234(serial_id); // I think sql already does this for you
If you can delay the index, it's faster than creating it first, but it's a marginal improvement most likely.
Also, create a tracking table where you insert the table name, and the date. You can use this with a reaper process later (late at night) to DROP the days tables (those more than, say, X hours old).
Full table operations are much cheaper than inserting and deleting rows in to an individual table:
INSERT INTO page_table SELECT 'temp_1234', <sequence>, primary_key...
DELETE FROM page_table WHERE page_id = 'temp_1234';
That's just awful.
First of all, make sure you really need to do this. You're adding significant complexity, so go & measure whether the queries and pagination really hurts or you just "feel like you should". The pagination can be handled with ROW_NUMBER() quite easily.
Assuming you go ahead, once you've got your query, clearly you need to build a cache so first you need to identify what the key is. It will be the SQL statement or operation identifier (name of stored procedure perhaps) and the criteria used. If you don't want to share between users then the user name or some kind of session ID too.
Now when you do a query, you first look up in this table with all the key data then either
a) Can't find it so you run the query and add to the cache, storing the criteria/keys and the data or PK of the data depending on if you want a snapshot or real time. Bear in mind that "real time" isn't really because other users could be changing data under you.
b) Find it, so remove the results (or join the PK to the underlying tables) and return the results.
Of course now you need a background process to go and clean up the cache when it's been hanging around too long.
Like I said - you should really make sure you need to do this before you embark on it. In the example you give I don't think it's worth it.

What is the most efficient way to count rows in a table in SQLite?

I've always just used "SELECT COUNT(1) FROM X" but perhaps this is not the most efficient. Any thoughts? Other options include SELECT COUNT(*) or perhaps getting the last inserted id if it is auto-incremented (and never deleted).
How about if I just want to know if there is anything in the table at all? (e.g., count > 0?)
The best way is to make sure that you run SELECT COUNT on a single column (SELECT COUNT(*) is slower) - but SELECT COUNT will always be the fastest way to get a count of things (the database optimizes the query internally).
If you check out the comments below, you can see arguments for why SELECT COUNT(1) is probably your best option.
To follow up on girasquid's answer, as a data point, I have a sqlite table with 2.3 million rows. Using select count(*) from table, it took over 3 seconds to count the rows. I also tried using SELECT rowid FROM table, (thinking that rowid is a default primary indexed key) but that was no faster. Then I made an index on one of the fields in the database (just an arbitrary field, but I chose an integer field because I knew from past experience that indexes on short fields can be very fast, I think because the index is stored a copy of the value in the index itself). SELECT my_short_field FROM table brought the time down to less than a second.
If you are sure (really sure) that you've never deleted any row from that table and your table has not been defined with the WITHOUT ROWID optimization you can have the number of rows by calling:
select max(RowId) from table;
Or if your table is a circular queue you could use something like
select MaxRowId - MinRowId + 1 from
(select max(RowId) as MaxRowId from table) JOIN
(select min(RowId) as MinRowId from table);
This is really really fast (milliseconds), but you must pay attention because sqlite says that row id is unique among all rows in the same table. SQLite does not declare that the row ids are and will be always consecutive numbers.
The fastest way to get row counts is directly from the table metadata, if any. Unfortunately, I can't find a reference for this kind of data being available in SQLite.
Failing that, any query of the type
SELECT COUNT(non-NULL constant value) FROM table
should optimize to avoid the need for a table, or even an index, scan. Ideally the engine will simply return the current number of rows known to be in the table from internal metadata. Failing that, it simply needs to know the number of entries in the index of any non-NULL column (the primary key index being the first place to look).
As soon as you introduce a column into the SELECT COUNT you are asking the engine to perform at least an index scan and possibly a table scan, and that will be slower.
I do not believe you will find a special method for this. However, you could do your select count on the primary key to be a little bit faster.
sp_spaceused 'table_name' (exclude single quote)
this will return the number of rows in the above table, this is the most efficient way i have come across yet.
it's more efficient than select Count(1) from 'table_name' (exclude single quote)
sp_spaceused can be used for any table, it's very helpful when the table is exceptionally big (hundreds of millions of rows), returns number of rows right a way, whereas 'select Count(1)' might take more than 10 seconds. Moreover, it does not need any column names/key field to consider.

Semi-Distinct MySQL Query

I have a MySQL table called items that contains thousands of records. Each record has a user_id field and a created (datetime) field.
Trying to put together a query to SELECT 25 rows, passing a string of user ids as a condition and sorted by created DESC.
In some cases, there might be just a few user ids, while in other instances, there may be hundreds.
If the result set is greater than 25, I want to pare it down by eliminating duplicate user_id records. For instance, if there were two records for user_id = 3, only the most recent (according to created datetime) would be included.
In my attempts at a solution, I am having trouble because while, for example, it's easy to get a result set of 100 (allowing duplicate user_id records), or a result set of 16 (using GROUP BY for unique user_id records), it's hard to get 25.
One logical approach, which may not be the correct MySQL approach, is to get the most recent record for each for each user_id, and then, if the result set is less than 25, begin adding a second record for each user_id until the 25 record limit is met (maybe a third, fourth, etc. record for each user_id would be needed).
Can this be accomplished with a MySQL query, or will I need to take a large result set and trim it down to 25 with code?
I don't think what you're trying to accomplish is possible as a SQL query. Your desire is to return 25 rows, no matter what the normal data groupings are whereas SQL is usually picky about returning based on data groupings.
If you want a purely MySQL-based solution, you may be able to accomplish this with a stored procedure. (Supported in MySQL 5.0.x and later.) However, it might just make more sense to run the query to return all 100+ rows and then trim it programmatically within the application.
This will get you the most recent for each user --
SELECT user_id, create
FROM items AS i1
LEFT JOIN items AS i2
ON i1.user_id = i2.user_id AND i1.create > i2.create
WHERE i2.id IS NULL
his will get you the most recent two records for each user --
SELECT user_id, create
FROM items AS i1
LEFT JOIN items AS i2
ON i1.user_id = i2.user_id AND i1.create > i2.create
LEFT JOIN items IS i3
ON i2.user_id = i3.user_id AND i2.create > i3.create
WHERE i3.id IS NULL
Try working from there.
You could nicely put this into a stored procedure.
My opinion is to use application logic, as this is very much application layer logic you are trying to implement at the DB level, i.e. filtering down the results to make the search more useful to the end user.
You could implement a stored procedure (personally I would never do such a thing) or just get the application to decide which 25 results.
One approach would be to get the most recent item from each user, followed by the most recent items from all users, and limit that. You could construct pathological examples where this probably isn't what you want, but it should be pretty good in general.
Unfortunately, there is no easy way :( I had to do something similar when I built a report for my company that would pull up customer disables that were logged in a database. Only problem was that the disconnect is ran and logged every 30 minutes. Therefore, the rows would not be distinct since the timestamp was different in every disconnect. I solved this problem with sub queries. I don't have the exact code anymore, but I beleive this is how I implemented it:
SELECT CORP, HOUSE, CUST,
(
SELECT TOP 1 hsd
FROM #TempTable t2
WHERE t1.corp = t2.corp
AND t1.house = t2.house
AND t1.cust = t2.cust
) DisableDate
FROM #TempTable t1
GROUP BY corp, house, cust -- selecting distinct
So, my answer is to elimante the non-distinct column from the query by using sub queries. There might be an easier way to do it though. I'm curious to see what others post.
Sorry, i keep editing this, I keep trying to find ways to make it easier to show what I did.