stored procedure mysql - php

I have a database call that i am not sure if i am doing it the most efficient way. Basically the call queries a table of events with zip codes and then joins a zip code database that gives the lat/lon of that events zip. Then it joins the logged in user to the query and that user has a lat/lon of upon logging in. So the whole query pulls events from within so many miles of of the users lat/lon.
My question, is there a better way to do it then calling this query each time the page is loaded? would a stored procedure be faster? I dont have any experience with them. I am using MySQL.
$this->db->select('*');
$this->db->from('events');
$this->db->join('zipcodes', 'zipcodes.zipcode = courses.courseZip');
$this->db->join('eventTypes', 'eventTypes.eventTypeID = events.eventType');
$this->db->where('eventApproved', 1);
$this->db->select('(DEGREES(ACOS(SIN(RADIANS('.$this->user['userLat'].'))
* SIN(RADIANS(latitude))
+ COS(RADIANS('.$this->user['userLat'].'))
* COS(RADIANS(latitude))
* COS(RADIANS('.$this->user['userLon'].' - longitude))))) * 69.09 AS distance');
$this->db->having('distance <', 100);

Yes it will help to have a stored procedure here.
Reasons are
1. it makes your Database layer more managable
2. SP are precompiled. When you run then first them the engine will create a execution plan and save the plan. Next time when it runs it will reuse the plan. So you get some performance benifit. In your case you might get lot of benifit if the underlined table is not changing (updated/deleted) too much after SP is made. If it is then you can RECOMPILE the sp(Running it WITH RECOMPILE OPTION) and it will create and save a new plan.
How you do it .
Well it is quite easy. If you are using HeidiSQL for MySQL Front End or the query browser of MYSQL enterprise 5.0 you might be able to generate the SP graphically . But even if you want to code it from scratch it is easy.
http://dev.mysql.com/doc/refman/5.0/en/stored-routines-syntax.html
Sp also are advisible from Security point of view because they can stop SQL Injection attacks.
Once you have the SP you can tune the table to make the SP faster.
1. Create a Index (nonclustered ) on the columns in where clause
2. Include the column that you bringing in SELECT in this Index.
In Microsoft SQL Server you can do this usign covering index. I am not sure if you can do it in MYSQL or not. But even if you can you should try to create a index covering as many columns as you can in either clustered or non clustered index.
HTH

Your going to want to store as much data (such as the user's lat/long) in Session as possible. This way your not querying for this data, that's isn't really changing, on every page load.

Related

Using SELECT * or SELECT all, cols is better for Queries [duplicate]

I've heard that SELECT * is generally bad practice to use when writing SQL commands because it is more efficient to SELECT columns you specifically need.
If I need to SELECT every column in a table, should I use
SELECT * FROM TABLE
or
SELECT column1, colum2, column3, etc. FROM TABLE
Does the efficiency really matter in this case? I'd think SELECT * would be more optimal internally if you really need all of the data, but I'm saying this with no real understanding of database.
I'm curious to know what the best practice is in this case.
UPDATE: I probably should specify that the only situation where I would really want to do a SELECT * is when I'm selecting data from one table where I know all columns will always need to be retrieved, even when new columns are added.
Given the responses I've seen however, this still seems like a bad idea and SELECT * should never be used for a lot more technical reasons that I ever though about.
One reason that selecting specific columns is better is that it raises the probability that SQL Server can access the data from indexes rather than querying the table data.
Here's a post I wrote about it: The real reason select queries are bad index coverage
It's also less fragile to change, since any code that consumes the data will be getting the same data structure regardless of changes you make to the table schema in the future.
Given your specification that you are selecting all columns, there is little difference at this time. Realize, however, that database schemas do change. If you use SELECT * you are going to get any new columns added to the table, even though in all likelihood, your code is not prepared to use or present that new data. This means that you are exposing your system to unexpected performance and functionality changes.
You may be willing to dismiss this as a minor cost, but realize that columns that you don't need still must be:
Read from database
Sent across the network
Marshalled into your process
(for ADO-type technologies) Saved in a data-table in-memory
Ignored and discarded / garbage-collected
Item #1 has many hidden costs including eliminating some potential covering index, causing data-page loads (and server cache thrashing), incurring row / page / table locks that might be otherwise avoided.
Balance this against the potential savings of specifying the columns versus an * and the only potential savings are:
Programmer doesn't need to revisit the SQL to add columns
The network-transport of the SQL is smaller / faster
SQL Server query parse / validation time
SQL Server query plan cache
For item 1, the reality is that you're going to add / change code to use any new column you might add anyway, so it is a wash.
For item 2, the difference is rarely enough to push you into a different packet-size or number of network packets. If you get to the point where SQL statement transmission time is the predominant issue, you probably need to reduce the rate of statements first.
For item 3, there is NO savings as the expansion of the * has to happen anyway, which means consulting the table(s) schema anyway. Realistically, listing the columns will incur the same cost because they have to be validated against the schema. In other words this is a complete wash.
For item 4, when you specify specific columns, your query plan cache could get larger but only if you are dealing with different sets of columns (which is not what you've specified). In this case, you do want different cache entries because you want different plans as needed.
So, this all comes down, because of the way you specified the question, to the issue resiliency in the face of eventual schema modifications. If you're burning this schema into ROM (it happens), then an * is perfectly acceptable.
However, my general guideline is that you should only select the columns you need, which means that sometimes it will look like you are asking for all of them, but DBAs and schema evolution mean that some new columns might appear that could greatly affect the query.
My advice is that you should ALWAYS SELECT specific columns. Remember that you get good at what you do over and over, so just get in the habit of doing it right.
If you are wondering why a schema might change without code changing, think in terms of audit logging, effective/expiration dates and other similar things that get added by DBAs for systemically for compliance issues. Another source of underhanded changes is denormalizations for performance elsewhere in the system or user-defined fields.
You should only select the columns that you need. Even if you need all columns it's still better to list column names so that the sql server does not have to query system table for columns.
Also, your application might break if someone adds columns to the table. Your program will get columns it didn't expect too and it might not know how to process them.
Apart from this if the table has a binary column then the query will be much more slower and use more network resources.
There are four big reasons that select * is a bad thing:
The most significant practical reason is that it forces the user to magically know the order in which columns will be returned. It's better to be explicit, which also protects you against the table changing, which segues nicely into...
If a column name you're using changes, it's better to catch it early (at the point of the SQL call) rather than when you're trying to use the column that no longer exists (or has had its name changed, etc.)
Listing the column names makes your code far more self-documented, and so probably more readable.
If you're transferring over a network (or even if you aren't), columns you don't need are just waste.
Specifying the column list is usually the best option because your application won't be affected if someone adds/inserts a column to the table.
Specifying column names is definitely faster - for the server. But if
performance is not a big issue (for example, this is a website content database with hundreds, maybe thousands - but not millions - of rows in each table); AND
your job is to create many small, similar applications (e.g. public-facing content-managed websites) using a common framework, rather than creating a complex one-off application; AND
flexibility is important (lots of customization of the db schema for each site);
then you're better off sticking with SELECT *. In our framework, heavy use of SELECT * allows us to introduce a new website managed content field to a table, giving it all of the benefits of the CMS (versioning, workflow/approvals, etc.), while only touching the code at a couple of points, instead of a couple dozen points.
I know the DB gurus are going to hate me for this - go ahead, vote me down - but in my world, developer time is scarce and CPU cycles are abundant, so I adjust accordingly what I conserve and what I waste.
SELECT * is a bad practice even if the query is not sent over a network.
Selecting more data than you need makes the query less efficient - the server has to read and transfer extra data, so it takes time and creates unnecessary load on the system (not only the network, as others mentioned, but also disk, CPU etc.). Additionally, the server is unable to optimize the query as well as it might (for example, use covering index for the query).
After some time your table structure might change, so SELECT * will return a different set of columns. So, your application might get a dataset of unexpected structure and break somewhere downstream. Explicitly stating the columns guarantees that you either get a dataset of known structure, or get a clear error on the database level (like 'column not found').
Of course, all this doesn't matter much for a small and simple system.
Lots of good reasons answered here so far, here's another one that hasn't been mentioned.
Explicitly naming the columns will help you with maintenance down the road. At some point you're going to be making changes or troubleshooting, and find yourself asking "where the heck is that column used".
If you've got the names listed explicitly, then finding every reference to that column -- through all your stored procedures, views, etc -- is simple. Just dump a CREATE script for your DB schema, and text search through it.
Performance wise, SELECT with specific columns can be faster (no need to read in all the data). If your query really does use ALL the columns, SELECT with explicit parameters is still preferred. Any speed difference will be basically unnoticeable and near constant-time. One day your schema will change, and this is good insurance to prevent problems due to this.
definitely defining the columns, because SQL Server will not have to do a lookup on the columns to pull them. If you define the columns, then SQL can skip that step.
It's always better to specify the columns you need, if you think about it one time, SQL doesn't have to think "wtf is *" every time you query. On top of that, someone later may add columns to the table that you actually do not need in your query and you'll be better off in that case by specifying all of your columns.
The problem with "select *" is the possibility of bringing data you don't really need. During the actual database query, the selected columns don't really add to the computation. What's really "heavy" is the data transport back to your client, and any column that you don't really need is just wasting network bandwidth and adding to the time you're waiting for you query to return.
Even if you do use all the columns brought from a "select *...", that's just for now. If in the future you change the table/view layout and add more columns, you'll start bring those in your selects even if you don't need them.
Another point in which a "select *" statement is bad is on view creation. If you create a view using "select *" and later add columns to your table, the view definition and the data returned won't match, and you'll need to recompile your views in order for them to work again.
I know that writing a "select *" is tempting, 'cause I really don't like to manually specify all the fields on my queries, but when your system start to evolve, you'll see that it's worth to spend this extra time/effort in specifying the fields rather than spending much more time and effort removing bugs on your views or optimizing your app.
While explicitly listing columns is good for performance, don't get crazy.
So if you use all the data, try SELECT * for simplicity (imagine having many columns and doing a JOIN... query may get awful). Then - measure. Compare with query with column names listed explicitly.
Don't speculate about performance, measure it!
Explicit listing helps most when you have some column containing big data (like body of a post or article), and don't need it in given query. Then by not returning it in your answer DB server can save time, bandwidth, and disk throughput. Your query result will also be smaller, which is good for any query cache.
You should really be selecting only the fields you need, and only the required number, i.e.
SELECT Field1, Field2 FROM SomeTable WHERE --(constraints)
Outside of the database, dynamic queries run the risk of injection attacks and malformed data. Typically you get round this using stored procedures or parameterised queries. Also (although not really that much of a problem) the server has to generate an execution plan each time a dynamic query is executed.
It is NOT faster to use explicit field names versus *, if and only if, you need to get the data for all fields.
Your client software shouldn't depend on the order of the fields returned, so that's a nonsense too.
And it's possible (though unlikely) that you need to get all fields using * because you don't yet know what fields exist (think very dynamic database structure).
Another disadvantage of using explicit field names is that if there are many of them and they're long then it makes reading the code and/or the query log more difficult.
So the rule should be: if you need all the fields, use *, if you need only a subset, name them explicitly.
The result is too huge. It is slow to generate and send the result from the SQL engine to the client.
The client side, being a generic programming environment, is not and should not be designed to filter and process the results (e.g. the WHERE clause, ORDER clause), as the number of rows can be huge (e.g. tens of millions of rows).
Naming each column you expect to get in your application also ensures your application won't break if someone alters the table, as long as your columns are still present (in any order).
Performance wise I have seen comments that both are equal. but usability aspect there are some +'s and -'s
When you use a (select *) in a query and if some one alter the table and add new fields which do not need for the previous query it is an unnecessary overhead. And what if the newly added field is a blob or an image field??? your query response time is going to be really slow then.
In other hand if you use a (select col1,col2,..) and if the table get altered and added new fields and if those fields are needed in the result set, you always need to edit your select query after table alteration.
But I suggest always to use select col1,col2,... in your queries and alter the query if the table get altered later...
This is an old post, but still valid. For reference, I have a very complicated query consisting of:
12 tables
6 Left joins
9 inner joins
108 total columns on all 12 tables
I only need 54 columns
A 4 column Order By clause
When I execute the query using Select *, it takes an average of 2869ms.
When I execute the query using Select , it takes an average of 1513ms.
Total rows returned is 13,949.
There is no doubt selecting column names means faster performance over Select *
Select is equally efficient (in terms of velocity) if you use * or columns.
The difference is about memory, not velocity. When you select several columns SQL Server must allocate memory space to serve you the query, including all data for all the columns that you've requested, even if you're only using one of them.
What does matter in terms of performance is the excecution plan which in turn depends heavily on your WHERE clause and the number of JOIN, OUTER JOIN, etc ...
For your question just use SELECT *. If you need all the columns there's no performance difference.
It depends on the version of your DB server, but modern versions of SQL can cache the plan either way. I'd say go with whatever is most maintainable with your data access code.
One reason it's better practice to spell out exactly which columns you want is because of possible future changes in the table structure.
If you are reading in data manually using an index based approach to populate a data structure with the results of your query, then in the future when you add/remove a column you will have headaches trying to figure out what went wrong.
As to what is faster, I'll defer to others for their expertise.
As with most problems, it depends on what you want to achieve. If you want to create a db grid that will allow all columns in any table, then "Select *" is the answer. However, if you will only need certain columns and adding or deleting columns from the query is done infrequently, then specify them individually.
It also depends on the amount of data you want to transfer from the server. If one of the columns is a defined as memo, graphic, blob, etc. and you don't need that column, you'd better not use "Select *" or you'll get a whole bunch of data you don't want and your performance could suffer.
To add on to what everyone else has said, if all of your columns that you are selecting are included in an index, your result set will be pulled from the index instead of looking up additional data from SQL.
SELECT * is necessary if one wants to obtain metadata such as the number of columns.
Gonna get slammed for this, but I do a select * because almost all my data is retrived from SQL Server Views that precombine needed values from multiple tables into a single easy to access View.
I do then want all the columns from the view which won't change when new fields are added to underlying tables. This has the added benefit of allowing me to change where data comes from. FieldA in the View may at one time be calculated and then I may change it to be static. Either way the View supplies FieldA to me.
The beauty of this is that it allows my data layer to get datasets. It then passes them to my BL which can then create objects from them. My main app only knows and interacts with the objects. I even allow my objects to self-create when passed a datarow.
Of course, I'm the only developer, so that helps too :)
What everyone above said, plus:
If you're striving for readable maintainable code, doing something like:
SELECT foo, bar FROM widgets;
is instantly readable and shows intent. If you make that call you know what you're getting back. If widgets only has foo and bar columns, then selecting * means you still have to think about what you're getting back, confirm the order is mapped correctly, etc. However, if widgets has more columns but you're only interested in foo and bar, then your code gets messy when you query for a wildcard and then only use some of what's returned.
And remember if you have an inner join by definition you do not need all the columns as the data in the join columns is repeated.
It's not like listing columns in SQl server is hard or even time-consuming. You just drag them over from the object browser (you can get all in one go by dragging from the word columns). To put a permanent performance hit on your system (becasue this can reduce the use of indexes and becasue sending unneeded data over the network is costly) and make it more likely that you will have unexpected problems as the database changes (sometimes columns get added that you do not want the user to see for instance) just to save less than a minute of development time is short-sighted and unprofessional.
Absolutely define the columns you want to SELECT every time. There is no reason not to and the performance improvement is well worth it.
They should never have given the option to "SELECT *"
If you need every column then just use SELECT * but remember that the order could potentially change so when you are consuming the results access them by name and not by index.
I would ignore comments about how * needs to go get the list - chances are parsing and validating named columns is equal to the processing time if not more. Don't prematurely optimize ;-)

PHP if comparison vs MySQL Where (Which is more efficient)

My situation: My website will look at a cookie for a remember me token and a user ID. If the cookie exists it will unhash it and look up the user ID and compare the token. with a "WHERE userid = '' and rememberme = ''".
My question is: Will MySQL optimize this query on the unique userid so that the query does not scan the entire database for this 20+ character token? Or instead should I just select the token from the database and then use a php if comparison to check if the tokens are the same?
In short (tl;dr): Would it be better to check if a token matches in with a MySQL select query, or to grab all the tokens from a databases database and compare the values with a php if conditional?
Thanks!
Simple answer:
YES, the database will definitely optimism your search AS LONG AS THE variable you are searching in the WHERE ... portion is indexed! You definitely should not retrieve all the information via SQL and then do a PHP conditional if you are worried about performance.
So if the id column in your table is not indexed, you should index it. If you have let say... 1 million rows already in your table and run a command like SELECT * FROM user WHERE id = 994321, you would see a definite increase in performance.
Elaborating:
A database (like MySQL) is made to be much faster at executing queries/commands than you would expect that to happen in php for instance. In your specific situation, lets say you are executing this SQL statement:
$sql = "SELECT * FROM users WHERE id = 4";
If you have 1 million users, and the id column is not indexed, MySQL will look through all 1 million users to find all the rows with id = 4. However, if it is indexed, there is something called a b tree that MySQL makes (behind the scenes) which works similarly to how the indexing of a dictionary work.
If you try to find the world slowly in a dictionary, you might open the book in the middle, find words that start with the letter M and then look in the middle again of the pages on your right side hoping to find a letter closer to S. This method of looking for a word is much faster than looking at each single page from the beginning 1 by 1.
For that very reason, MySQL has created indexes to help performance and this feature should definitely be taken advantage of to help increase the speed of your queries.
Comparing it on MySQL-side should be fast. It should find the corresponding row by ID first (fast) and then compare the hash (also fast, since there will be only 1 row to check).
Try analyzing the query with EXPLAIN to find out the actual execution plan.
In my opinion it will be always faster to use WHERE clause no matter what (real) database server will be used. Database engines have strong algorithms for searching data written in language that is compiling to low-level code dedicated to platform, so it cannot be even compared with some loop written in interpreted PHP.
And remember that for PHP loop you will have to send all records from DB to PHP.
If you Data Base its on a separate server than you Apache PHP there is not doubt it would be faster if you write a query in MySQL.
If your PHP and MySQL server is on the same physical server probably PHP would be faster cause the comparison will be made on the RAM But have all the User Id array into RAM would be a waste of RAM so you can use Indexes that would speed up your query
ALTER TABLE table ADD INDEX idx__tableName__fieldName (field)

Improve SQL query results when running php app on GAE and DB on Amazon RDS

Here is something that hit me and wanted to know if I was right or if it could be done better? I am currently running the PHP part on GAE and use Amazon RDS since it is cheaper than google cloud SQL. And also since PHP on GAE does not have native api for Datastore. I know there is a work around but hey this is simpler and I bet a lot of others want their GAE app to sync with their DB than move the who stuff.
I run two queries
This is a join statement that runs when the page loads
$STH = $DBH->prepare("SELECT .....a few selected colmns with time coversion.....
List of Associates.Supervisor FROM Box Scores INNER JOIN
List of Associates ON Box Scores.Initials = List of
Associates.Initials WHERE str_to_date(Date, '%Y-%m-%d') BETWEEN
'{$startDate}' AND '{$endDate}' AND Box Scores.Initials LIKE
'{$initials}%' AND List of Associates.Supervisor LIKE'{$team}%'
GROUP BY Login");
What I get I calculate and then display as a table with each username as link
echo("<td >$row[0]</td>");
So when some one clicks on this link it will call another PHP and using AJAX to display the output I run the second query
2.Second query. This time I am getting everything.
$STH = $DBH->prepare("SELECT * FROM `Box Scores` INNER JOIN `List of Associates` ON
`Box Scores`.`Initials` = `List of Associates`.`Initials`
WHERE str_to_date(`Date`, '%Y-%m-%d') BETWEEN '{$startDate}' AND '{$endDate}'
AND `V2 Box Scores`.`Initials` LIKE '{$Agent}%'
AND `List of Associates`.`Supervisor` LIKE '{$team}%'");
The output I display in a small pop up as a light box after formatting the output as a table.
I find that the first query to be faster. So it got me thinking should I do something to the second part to make it faster.
Would only selecting the needed columns make it faster. OR should I do a SELECT * FROM as the first and then save it all to a unique file in Google bucket and then make the corresponding SELECT calls from that file?
I trying to make it such that it scale and not slow then when the query has to go through tens of thousands of rows in the DB. The above Queries are executed using PDO or PHP Data Objects.
so what are your thoughts?
Amazon Red Shift stores each column in a separate partition -- something called a columnar database or vertical partitioning. This results in some unusual performance issues.
For instance, I have run a query like this on a table will hundreds of millions of row, and it took about minute to return:
select *
from t
limit 10;
On the other hand, a query like this would return in a few seconds:
select count(*), count(distinct field)
from t;
This takes some getting used to. But, you should explicitly limit the columns you refer to in the query to get the best performance on Amazon (and other columnar databases). Each additional referenced column requires reading in that data from disk to memory.
Also, limiting the number of columns also reduces the I/O needed to the application. This can be significant, if you are storing wide-ish data in some of the columns, and you don't use the data.

Performance of MySQL

MyPHP Application sends a SELECT statement to MySQL with HTTPClient.
It takes about 20 seconds or more.
I thought MySQL can’t get result immediately because MySQL Administrator shows stat for sending data or copying to tmp table while I'd been waiting for result.
But when I send same SELECT statement from another application like phpMyAdmin or jmater it takes 2 seconds or less.10 times faster!!
Dose anyone know why MySQL perform so difference?
Like #symcbean already said, php's mysql driver caches query results. This is also why you can do another mysql_query() while in a while($row=mysql_fetch_array()) loop.
The reason MySql Administrator or phpMyAdmin shows result so fast is they append a LIMIT 10 to your query behind your back.
If you want to get your query results fast, i can offer some tips. They involve selecting only what you need and when you need:
Select only the columns you need, don't throw select * everywhere. This might bite you later when you want another column but forget to add it to select statement, so do this when needed (like tables with 100 columns or a million rows).
Don't throw a 20 by 1000 table in front of your user. She cant find what she's looking for in a giant table anyway. Offer sorting and filtering. As a bonus, find out what she generally looks for and offer a way to show that records with a single click.
With very big tables, select only primary keys of the records you need. Than retrieve additional details in the while() loop. This might look like illogical 'cause you make more queries but when you deal with queries involving around ~10 tables, hundreds of concurrent users, locks and query caches; things don't always make sense at first :)
These are some tips i learned from my boss and my own experince. As always, YMMV.
Dose anyone know why MySQL perform so difference?
Because MySQL caches query results, and the operating system caches disk I/O (see this link for a description of the process in Linux)

Problem with simultaneous clicks from different users

I've got a website that allows users to join a "team". The team has a member limit defined in $maxPlayersPerTeam.
When the user clicks the link to join a team this code gets executed
//query to get players count
if ($players < $maxPlayersPerTeam) {
// query to insert the player
}
However, if two users click the join link at the same time, both can join the team even if $players is equal to $maxPlayersPerTeam.
What can I do to avoid this?
You should acquire a lock on the dataset (i hope you're using a database, right?), execute your check and eventually update the dataset. So if two people really execute the code simultaneously, one of both has to wait for the lock of the other one. After acquiring the lock a second time the dataset has already been updated and the person can't join your team also.
Be happy some people have already worked on this kind of problems and offer you some possible solution : database transactions.
The best to handle those is to use PDO and its beginTransaction, commit and rollBack methods.
Your tables will have to be using a database engine which accept transactions (so innoDb instead of MyISAM).
Assuming you're using a database to store the information your database system should have method for transactional processing and managing them which would cater for the events of multiple transactions occuring at the same time (even if this is an incredibly rare case). There's a wiki article on this (even if I hestitate to link to it). http://en.wikipedia.org/wiki/Transaction_processing.
MySQL has methods for doing this: http://dev.mysql.com/doc/refman/5.0/en/commit.html. As does PostgreSQL: http://www.postgresql.org/docs/8.3/static/tutorial-transactions.html.

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