As i am a junior PHP Developer growing day by day stuck in a performance problem described here:
I am making a search engine in PHP ,my database has one table with 41 column and million's of rows obviously it is a very large dataset. In index.php i have a form for searching data.When user enters search keyword and hit submit the action is on search.php with results.The query is like this.
SELECT * FROM TABLE WHERE product_description LIKE '%mobile%' ORDER BY id ASC LIMIT 10
This is the first query.After result shows i have to run 4 other query like this:
SELECT DISTINCT(weight_u) as weight from TABLE WHERE product_description LIKE '%mobile%'
SELECT DISTINCT(country_unit) as country_unit from TABLE WHERE product_description LIKE '%mobile%'
SELECT DISTINCT(country) as country from TABLE WHERE product_description LIKE '%mobile%'
SELECT DISTINCT(hs_code) as hscode from TABLE WHERE product_description LIKE '%mobile%'
These queries are for FILTERS ,the problem is this when i submit search button ,all queries are running simultaneously at the cost of Performance issue,its very slow.
Is there any other method to fetch weight,country,country_unit,hs_code speeder or how can achieve it.
The same functionality is implemented here,Where the filter bar comes after table is filled with data,How i can achieve it .Please help
Full Functionality implemented here.
I have tried to explain my full problem ,if there is any mistake please let me know i will improve the question,i am also new to stackoverflow.
Firstly - are you sure this code is working as you expect it? The first query retrieves 10 records matching your search term. Those records might have duplicate weight_u, country_unit, country or hs_code values, so when you then execute the next 4 queries for your filter, it's entirely possible that you will get values back which are not in the first query, so the filter might not make sense.
if that's true, I would create the filter values in your client code (PHP)- finding the unique values in 10 records is going to be quick and easy, and reduces the number of database round trips.
Finally, the biggest improvement you can make is to use MySQL's fulltext searching features. The reason your app is slow is because your search terms cannot use an index - you're wild-carding the start as well as the end. It's like searching the phonebook for people whose name contains "ishra" - you have to look at every record to check for a match. Fulltext search indexes are designed for this - they also help with fuzzy matching.
I'll give you some tips that will show useful in many situations when querying a large dataset, or mostly any dataset.
If you can list the fields you want instead of querying for '*' is a better practice. The weight of this increases as you have more columns and more rows.
Always try to use the PK's to look for the data. The more specific the filter, the less it will cost.
An index in this kind of situation would come pretty handy, as it will make the search more agile.
LIKE queries are generally pretty slow and resource heavy, and more in your situation. So again, the more specific you are, the better it will get.
Also add, that if you just want to retrieve data from this tables again and again, maybe a VIEW would fit nicely.
Those are just some tips that came to my mind to ease your problem.
Hope it helps.
I am currently building a site for a car dealership. I would like to allow the user to refine the search results similar to amazon or ebay. The ability to narrow down the results with a click would be great. The problem is the way I am doing this now there are many different queries that need to be done each with a COUNT total.
So the main ways to narrow down the results are:
Vehicle Type
Year
Make
Price Range
New/Used
Currently I am doing 5 queries every time this page is loaded to get the numbers of results while passing in the set values.
Query 1:
SELECT vehicle_type, COUNT(*) AS total FROM inventory
[[ Already Selected Search Parameters]]
GROUP BY vehicle_type
ORDER BY vehicle_type ASC
Query 2:
SELECT make, COUNT(*) AS total FROM inventory
[[ Already Selected Search Parameters]]
GROUP BY make
ORDER BY make ASC
Query 3,4,5...
Is there any way to do this in one query? Is it faster?
Your queries seem reasonable.
You can do it in a single query using UNION ALL:
SELECT 'vehicle_type' AS query_type, vehicle_type, COUNT(*) AS total
FROM inventory
...
GROUP BY vehicle_type
UNION ALL
SELECT 'make', make, COUNT(*) AS total FROM inventory ... GROUP BY make
UNION ALL
SELECT ... etc ...
The performance benefit of this will not be huge.
If you find that you are firing off these queries a lot and the results don't change often, you might want to consider caching the results. Consider using something like memcache.
There are a couple ways to rank data along the lines of data warehousing but what you are trying to accomplish in search terms is called facets. A real search engine (which would be used with the sites you mentioned) performs this.
SEE: Faceted searching and categories in MySQL and Solr
Many sites use Lucene (Java-based) search engine with SOLR to accomplish what you are referring to. There is a newer solution called ElasticSearch that has a RESTful API and offers facets but you'd need to install Java, ES, and then could make calls to search engine that returns native JSON.
SEE: http://www.elasticsearch.org/guide/reference/api/search/facets/
Doing it in MySQL without requiring so many joins might need additional tables and perhaps triggers and gets complex. If the car dealership isn't expecting Cars.com traffic (millions/day) then you may be trying to optimize something before it actually needs it. Your recursive query might be fast enough and you haven't reported that there is an actual issue or bottleneck.
Use JOIN syntax:
http://dev.mysql.com/doc/refman/5.6/en/join.html
Or, I think you could write MySQL function for that. Where you will pass your search Parameters.
http://dev.mysql.com/doc/refman/5.1/en/create-function.html
To find where is faster you should do your own speed tests. That helped me to find out that some of my queries faster without joining them.
I have a search form which provides searching properties for holiday in a specific country based on it's availability specific date. Search section has 2 sections "basic search" & "advance search".
Basic search contains country dropdown and date field. In advance search we have multiple filters for hotels like "Bedrooms" (1 bedroom, 2 bedroom etc) and then property type (apartment, villa, etc)
I want to show the search filter options with a count such as "1 bedroom (23 properties)" and same for other search filter options.
I am using php/mysql to create this application, so what comes first in my mind is to run multiple queries for all search filters and get the COUNT result from mysql and show it. I have about 10-12 different filters on my page. Also I have to show count records dynamically based on all search options (basic and advanced) selected.
Running multiple queries on the page will make it load forever and it will not show content due to multiple query load. Is there any better & faster way to do this?
Please help, thanks!
I've tried to do this before, and it can get very slow depending on how many filters you allow and how many hotels you list, not to mention how you deal with duplicate hotels.
Ultimately though you will have very few filter options
Property type : normalise this in a separate table
Bedrooms : store this as a tinyint or smallint (either unsigned), can't imagine there being properties above 255 bedrooms, and definitely not above 65k
Location : normalise this in a separate table, ideally in a tree format to ensure relationships are noted
Star rating : this can be stored as a tinyint unsigned
Now your problem here is that if someone applies a filter for 3 bedrooms upwards, you still should be getting values for 2 bedrooms, 1 bedroom, as changing the filter back to that will yield results.
At the end of the day I addressed this using a very large memory table, some logic to build WHERE and JOIN statements, and an individual query counting up records within a set grouping. This was for doing similar to users holiday search results though, and as such the data was considered entirely transient. For your purposes a far smaller memory table is likely to be acceptable, however the principle is similar.
Use the GROUP BY clause in conjunction with COUNT on your SELECT statement. For example, I defined a little test table such as
create table rooms (
rooms INT NOT NULL,
name VARCHAR(10)
)
And then ran the query
SELECT rooms,COUNT(*) FROM rooms GROUP BY rooms;
This gives you a result with each room count and the number of entries with that value.
What you're trying to achieve is called faceted search.
This isn't a problem suited to a relational database like MySQL.
You can use ElasticSearch or AWS CloudSearch and their facet features.
Just remember that these are search servers and don't replace your main database. They only perform search operations that return the IDs that correspond to the actual records stored in your database. You still need MySQL (or MongoDB etc).
I am trying to create a script that finds a matching percentage between my table rows. For example my mySQL database in the table products contains the field name (indexed, FULLTEXT) with values like
LG 50PK350 PLASMA TV 50" Plasma TV Full HD 600Hz
LG TV 50PK350 PLASMA 50"
LG S24AW 24000 BTU
Aircondition LG S24AW 24000 BTU Inverter
As you may see all of them have some same keyword. But the 1st name and 2nd name are more similar. Additionally, 3rd and 4th have more similar keywords between them than 1st and 2nd.
My mySQL DB has thousands of product names. What I want is to find those names that have more than a percentage (let's say 60%) of similarity.
For example, as I said, 1st, 2nd (and any other name) that match between them with more than 60%, will be echoed in a group-style-format to let me know that those products are similar. 3rd and 4th and any other with more than 60% matching will be echoed after in another group, telling me that those products match.
If it is possible, it would be great to echo the keywords that satisfy all the grouped matching names. For example LG S24AW 24000 BTU is the keyword that is contained in 3rd and 4th name.
At the end I will create a list of all those keywords.
What I have now is the following query (as Jitamaro suggested)
Select t1.name, t2.name From products t1, products t2
that creates a new name field next to all other names. Excuse me that I don't know how to explain it right but this is what it does: (The real values are product names like above)
Before the query
-name-
A
B
C
D
E
After the query
-name- -name-
A A
B A
C A
D A
E A
A B
B B
C B
D B
E B
.
.
.
Is there a way either with mySQL or PHP that will find me the matching names and extract the keywords as I described above? Please share code examples.
Thank you community.
Query the DB with LIKE OR REGEXP:
SELECT * FROM product WHERE product_name LIKE '%LG%';
SELECT * FROM product WHERE product_name REGEXP "LG";
Loop the results and use similar_text():
$a = "LG 50PK350 PLASMA TV 50\" Plasma TV Full HD 600Hz"; // DB value
$b = "LG TV 50PK350 PLASMA 50\"" ; // USER QUERY
$i = similar_text($a, $b, $p);
echo("Matched: $i Percentage: $p%");
//outputs: Matched: 21 Percentage: 58.3333333333%
Your second example matches 62.0689655172%:
$a = "LG S24AW 24000 BTU"; // DB value
$b = "Aircondition LG S24AW 24000 BTU Inverter" ; // USER QUERY
$i = similar_text($a, $b, $p);
echo("Matched: $i Percentage: $p%");
You can define a percentage higher than, lets say, 40%, to match products.
Please note that similar_text() is case SensItivE so you should lower case the string.
As for your second question, the levenshtein() function (in MySQL) would be a good candidate.
When I look at your examples, I consider how I would try to find similar products based on the title. From your two examples, I can see one thing in each line that stands out above anything else: the model numbers. 50PK350 probably doesn't show up anywhere other than as related to this one model.
Now, MySQL itself isn't designed to deal with questions like this, but some bolt-on tools above it are. Part of the problem is that querying across all those fields in all positions is expensive. You really want to split it up a certain way and index that. The similarity class of Lucene will grant a high score to words that rarely appear across all data, but do appear as a high percentage of your data. See High level explanation of Similarity Class for Lucene?
You should also look at Comparison of full text search engine - Lucene, Sphinx, Postgresql, MySQL?
Scoring each word against the Lucene similarity class ought to be faster and more reliable. The sum of your scores should give you the most related products. For the TV, I'd expect to see exact matches first, then some others of the same size, then brand, then TVs in general, etc.
Whatever you do, realize that unless you alter the data structures by using another tool on top of the SQL system to create better data structures, your queries will be too slow and expensive. I think Lucene is probably the way to go. Sphinx or other options not mentioned may also be up for consideration.
This is trickier than it seems and there is information missing in your post:
How are people going to use this auto-complete function?
Is it relevant that you can find all names for a product? Because apparently not all stores name their products similarly so a clerk might not be able to find the product (s)he found.
Do you have information about which product names are for the same product?
Is it relevant from which store you're searching? where is this auto-complete used?
Should the auto-complete really only suggest products that match all the words you typed? (it's not so hard, technically, to correct typos)
I think you need a more clear picture of what you (or better yet: the users) want this auto-complete function to do.
An auto-complete function is very much a user-friendly type feature. It aids the user, possibly in a fuzzy way so there is no single right answer. You have to figure out what works best, not what is easiest to do technically.
First figure out what you want, then worry about technology.
One possible solution is to use Damerau-Levenstein distance. It could be used like this
select *
from products p
where DamerauLevenstein(p.name, '*user input here*')<=*X*
You'll have to figure out X that suites your needs best. It should be integer greater than zero. You could have it hard-coded, parameterized or calculated as needed.
The trickiest thing here is DamerauLevenstein. It has to be stored procedure, that implements Damerau-Levenstein algorithm. I don't have MySQL here, so I might write it for you later this day.
Update: MySQL does not support arrays in stored procedures, so there is no way to implement Damerau-Levenstein in MySQL, except using temporary table for each function call. And that will result in terrible performance. So you have two options: loop through the results in PHP with levenstein like Alix Axel suggests, or migrate your database to PostgreSQL, where arrays are supported.
There is also an option to create User-Defined function, but this requires writing this function in C, linking it to MySQL and possibly rebuilding MySQL, so this way you'll just add more headache.
Your approach seems sound. For matching similar products, I would suggest a trigram search. There's a pretty decent explanation of how this works along with the String::Trigram Perl module.
I would suggest using trigram search to get a list of matches, perhaps coupled with some manual review depending on how much data you have to deal with and how frequent you need to add new products. I've found this approach to work quite well in practice.
Maybe you want to find the longest common substring from the 2 strings? Then you need to compute a suffix tree for each of your strings see here http://en.wikipedia.org/wiki/Longest_common_substring_problem.
If you want to check all names against each other you need a cross join in mysql. There are many ways to achieve this:
1. Select a, b From t1, t2
2. Select a, b From t1 Join t2
3. Select a, b From t1 Cross Join t2
Then you can loop through the result. This is the same when I say create a 2d array with n^2-(n-1) elements and each element is connected with each other.
P.S.: Select t1.name, t2.name From products t1, products t2
It sounds like you've gone through all this trouble to explain a complex scenario, then said that you want to ignore the optimal answers and just get us to give you the "handshake" protocol (everything is compared to everything that hasn't been compared to it yet). So... pseudocode:
select * from table order by id
while (result) {
select * from table where id > result_id
}
That will do it.
If your database simply had a UPC code as one of it's fields, and this field was well-maintained, i.e., you could trust that it was entered correctly by the database maintainer and correctly reflected what the item was -- then you wouldn't need to do all of the work you suggest.
An even better idea might be to have a UPC field in your next database -- and constrain it as unique.
Database users attempt to put an-already-existing UPC into the database -- they get an error.
Database maintains its integrity.
And if such a database maintained its integrity -- the necessity of doing what you suggest never arises.
This probably doesn't help much with your current task (apologies) -- but for a future similar database -- you might wish to think about it...
I`d advise you to use some fulltext search engine, like sphinx. It has possibilities to implement any algorithm you want. For example, you may use "quorom" or "any" searches.
It seems that you might always want to return the shortest string?? That's more or a question than anything. But then you might have something like...
SELECT * FROM products LIMIT 1
WHERE product_name like '%LG%'
ORDER BY LENGTH(product_name) ASC
This is a clustering problem, which can be resolved by a data mining method. ( http://en.wikipedia.org/wiki/Cluster_analysis) It requires a lot of memory and computation intensive operations which is not suitable for database engine. Otherwise, separate data mining, text mining, or business analytics software wouldn't have existed.
This question is similar :) to this one:
What is the best way to implement a substring search in SQL?
Trigram can easily find similar rows, and in that question i posted a php+mysql+trigram solution.
You can use LIKE to find similar product names within the table. For example:
SELECT * FROM product WHERE product_name LIKE 'LG%';
Here is another idea (but I'm voting for levenshtein()):
Create a temporary table of all words used in names and their frequencies.
Choose range of results (most popular words are probably words like LCD or LED, most unique words could be good, they might be product actual names).
Suggest for each of result words either:
results with those words
results containing longest substring (like this: http://forums.mysql.com/read.php?10,277997,278020#msg-278020 ) of those words.
Ok, I think I was trying to implement very much similar thing. It can work the same as the google chrome address box. When you type the address it gives you the suggestions. This is what you are trying to achieve as far I am concerned.
I cannot give you exact solution to that but some advice.
You need to implement the dropdown box where someone starts to enter the product they are looking for
Then you need to get the current value of the dropdown and then run query like guy posted above. Can be "SELECT * FROM product WHERE product_name LIKE 'LG%';"
Save results of the query
Refresh the page
Add the results of the query to the dropdown
Note:
You need to save the query results somewhere like the text file with the HTML code i.e. "option" LG TS 600"/option" (add <> brackets to option of course). This values will be used for populating your option box after the page refresh. You need to set up the users session for the user to get the same results for the same user, otherwise if more users would use the search at the same time it could clash. So, with the search id and session id you can match them then. You can save it in the file or the table. Table would be more convenient. It is actually in my sense the whole subsystem for that what are you looking for.
I hope it helps.
I'm running a sql query to get basic details from a number of tables. Sorted by the last update date field. Its terribly tricky and I'm thinking if there is an alternate to using the UNION clause instead...I'm working in PHP MYSQL.
Actually I have a few tables containing news, articles, photos, events etc and need to collect all of them in one query to show a simple - whats newly added on the website kind of thing.
Maybe do it in PHP rather than MySQL - if you want the latest n items, then fetch the latest n of each of your news items, articles, photos and events, and sort in PHP (you'll need the last n of each obviously, and you'll then trim the dataset in PHP). This is probably easier than combining those with UNION given they're likely to have lots of data items which are different.
I'm not aware of an alternative to UNION that does what you want, and hopefully those fetches won't be too expensive. It would definitely be wise to profile this though.
If you use Join in your query you can select datas from differents tables who are related with foreign keys.
You can look of this from another angle: do you need absolutely updated information? (the moment someone enters new information it should appear)
If not, you can have a table holding the results of the query in the format you need (serving as cache), and update this table every 5 minutes or so. Then your query problem becomes trivial, as you can have the updates run as several updates in the background.