Let's say I am building a simple dictionary where users type a word and see a definition.
In an oversimplification, are there any problems with setting up my dictionary as a MySQL table, and each user request for a word will call a PHP script to find the word, and display its definition?
What's the optimal way to build this to minimize user lag time/not overheat the server? How does dictionary.com do it? My resources are limited, so I can't afford a dedicated server
As this question is tagged as architecture, so trying to provide a basic architecture overview in this case.
Problem statement consists of following points.
Online application - So single service/application will provide services to multiple users.
Text search - Most of the time queries are not complete word which could be find in database.
Frequent database queries - As the number of user grows this might become problem.
So, you might think of following solutions.
Google the text searching tools/library. You will find lots of them. To have some relevant search results. Or you can use how wordweb does.
To avoid frequent database queries you can cached last 1000 results or some configurable number of results in some file such as Lucene Search does.
DISCLAIMER
Above architecture will hold good if there are simultaneously multiple users. Or if this is even needed. Otherwise this might be more than effort required.
Best way to develop an architecture is to make system adaptable to change. So start with basic work and keep adapting to changes.
Related
I'm going to add simple live search to website (tips while entering text in input box).
Main task:
39k plain text lines for search into (~500 length of each line, 4Mb total size)
1k online users can simultaneously typing something in inputbox
In some cases 2k-3k resuts can match user request
I'm worried about the following questions:
Database VS textfile?
Are there any general rules or best practices related to my task aimed for decreasing db/server memory load? (caching/indexing/etc)
Do Sphinx/Solr are appropriate for such task?
Any links/advice will be extremely helpful.
Thanks
P.S. May be this is the best solution? PHP to search within txt file and echo the whole line
Put your data in a database (SQLite should do just fine, but you can also use a more heavy-duty RDBMS like MySQL or Postgres), and put an index on the column or columns that will be searched.
Only do the absolute minimum, which means that you should not use a framework, an ORM, etc. They will just slow down your code.
Create a PHP file, grab the search text and do a SELECT query using a native PHP driver, such as SQLite, MySQLi, PDO or similar.
Also, think about how the search box will work. You can prevent many requests if you e.g. put a minimum character limit (it does not make sense to search only for one or two characters), put a short delay between sending requests (so that you do not send requests that are never used), and so on.
Whether or not to use an extension such as Solr depends on your circumstances. If you have a lot of data, and a lot of requests, then maybe you should look into it. But if the problem can be solved using a simple solution then you should probably try it out before making it more complicated.
I have implemented 'live search' many times, always using AJAX with querying the database (MySQL) and haven't had/observed any speed or large load issues yet.
Anyway I saw an implementations using Solr but cannot suggest whether it was quicker or consumed less resources.
It completely depends on the HW the server will run on, IMO. As I wrote somewhere, I had seen a server with very slow filesystem so implementing live search while reading and parsing from txt files (or using Solr) could be slower than when querying the database. On the other hand You can host on poor shared webhosting with slow DB connection (that gets even slower with more concurrent connections) so this won't be the best solution.
My suggestion: use MySQL with AJAX (look at this jquery plugin or this article), set proper INDEXes on the searched columns and if this is found slow You still can move to a txt file.
In the past, i have used Zend search Lucene with great success.
It is a general purpose text search engine written entirely in PHP 5. It manages the indexing of your sources and is quite fast (in my experience). It supports many query types, search fields, search ranking.
I am currently working on an existing website that lists products, there are currently a little over 500 products.
The website has a text file for every product and I want to make a search option, thinking of reading all the text files and create an xml document with the values once a day that can be searched.
The client indicated that they wanted to add products and is used to add them using the text files. There might be over 5000 products in the future so I think it's best to do this with mysql. This means importing the current products and create a crud page for products.
Does anyone have experience with a PHP website that does not use MySQL? Is it possible to keep adding text files and just index them once a day even if it would mean having over 5000 products?
5000 seems like an amount that's still managable to index with a daily cron job. As long as you don't plan on searching them real-time, it should work. It's not ideal, but it would work.
Yes, it is very much possible, NOT plausible that you use files for these type of transactions.
It is also better to use XML instead of normal TXTs for the job. 5000 products with what kind of data associated to them might create problems in future.
PS
Why not MySQL?
Mysql was made because file based databases are slow and inaccurate.
Just use mysql. If you want to keep your old txt based database, just build an easy script that will import each file one by one and create corresponding tables in your sql database.
Good luck.
It's possible, however if this is a anything more than simply an online catalog, then managing transaction integrity is horrendously difficult - and that you're even asking the question implies that you are not in a good position to implement the kind of controls required. And as you've already discovered, it doesn't make for easy searching (BTW: mysql's fulltext indexing is a very blunt instrument - it's not a huge amount of effort to implement an effective search engine yourself - or there are excellent ones available off-the-shelf, e.g. mnogosearch)
(as a conicdental point, why XML? It makes managing the data much more complicated than it needs to be)
and create a crud page for products
Why? If the client wants to maintain the data via file uploads and you already need to port the data, then just use the same interface - where the data is stored is not relevant just now.
If there are issues with hosting+mysql, then using SQLite gives most of the benefits (although it wion't scale as well).
I'm working with a Postgres database that I have no control over the administration of. I'm building a calendar that deals with seeing if resources (physical items) were online or offline on a specific day. Unfortunately, if they're offline I can only confirm this by finding the resource name in a text field.
I've been using
select * from log WHERE log_text LIKE 'Resource Kit 06%'
The problem is that when we're building a calendar using LIKE 180+ times (at least 6 resources per day) is slow as can be. Does anybody know of a way to speed this up (keep in mind I can't modify the database). Also, if there's nothing I can do on the database end, is there anything I can do on the php end?
I think, that some form of cache will be required for this. As you cannot change anything in database, your only chance is to pull data from it and store it in some more accessible and faster form. This is highly dependent on frequency of data inserted into table. If there are more inserts than selects, it will not probably help much. Other way there is slight chance of improved performance.
Maybe you can consider using Lucene search engine, which is capable of fulltext indexing. There is implementation from Zend and even Apache has some http service. I haven't opportunity to test it however.
If you don't use something that robust, you can write your own caching mechanism in php. It will not be as fast as postgres, but probably faster than not indexed LIKE queries. If your queries need to be more sofisticated (conditions, grouping, ordering...), you can use SQLite database, which is file based and doesn't need extra service running on server.
Another way could be using triggers in database, which could on insert data store required information to some other table in more indexed manner. But without rights to administer database, it is probably dead end.
Please be more specific with your question, if you want more specific information.
I've been working on a new site of mine for a couple of days now which will be retrieving almost all of its most used content from a MySql database. Seeming as the Database and website is still under development the tables are really small at the moment and speed is of no concern yet.
But you know what they say, a little bit of hard work now saves you a headache later on.
Now I'm only 17, the only database I've ever been taught was through Microsoft Access, and we were practically given the database completed - we learned up to 3NF, but that was about it.
I remember reading once when I was looking to pull data (randomly) out of a database how large databases were taking several seconds/minutes to complete a single query, so this just got me thinking. In a fraction of a second I can submit a search to google, google processes the query and returns the result, and then my browser renders it - all done in the blink of an eye. And google has billions of records to search through. And they're also doing this for millions of users simultaneously.
I'm thinking, how do they do it? I know that they have huge data centers, but still.
I realize that it probably comes down to the design of the database, how it's been optimized, and obviously the configuration. And I guess that's my question really. Could someone please tell me how to design high performance databases for millions/billions of rows (yes, I'm being optimistic), and possibly point me towards some good reading material to help me learn further?
Also, all my queries are done via PHP, if that's at all relevant to any answers.
The blog http://highscalability.com/ has some good articles and pointers to how companies handle large problems.
Specifically related to MySQL, you can Google for craigslist.org's use of MySQL.
http://www.slideshare.net/jzawodn/mysql-and-search-at-craigslist
First the good news... MySQL scales well (depending on the hardware) to at least hundreds of millions of rows.
Once you get to a certain point, a single database server will have trouble managing the load. That's when you get into the realm of partitioning or sharding... spreading the load across multiple database servers using any one of a number of different schemes (e.g. putting unrelated tables on different servers, spreading a single table across multiple servers e.g. by using the ID or date range as a partitioning key).
SQL does shard, but is not fundamentally designed to shard well. There's a whole category of storage alternatives collectively referred to as NoSQL that are designed to solve that very problem (MongoDB, Cassandra, HBase are a few).
When you use SQL at very large scale, you run into any number of issues such as making data model changes across a DB server farm, trouble keeping up with data backups, etc. That's a very complex topic, and people that solve it well are rare. For a glimpse at the issues, have a look at http://gigaom.com/cloud/facebook-trapped-in-mysql-fate-worse-than-death/
When selecting a database platform for a specific project, benchmark the solution early and often to understand whether or not it will meet the performance requirements that you envision. Having a framework to do that will help you learn about scalability, and will help you decide whether to invest effort in improving the data storage part of your solution, and will help you know where best to invest your time.
No one can tell how to design databases. It comes after much reading and many hour working on them. A good design is product of many many years doing them though. As you've only seen Access you got no knowledge of databases. Search through Amazon.com and you'll get tons of titles. For someone that's starting, anyone will do it.
I mean no disrespect. I've been there and I'm also tutor of some people learning programming/database design. I do know that there's no silver bullet or shortcuts for the work you have ahead.
If you intend to work with high performance database, you should have something in mind. The design of them in per application. A good design depends on learning more and more how the app's users interact with the system, the usage patterns, etc. The things you'll learn from books will give you options, using them will depend heavily on the scenario.
Good luck!
It doesn't all come down to the design of the database, though that is indeed a big part of it. The guys who made Google are geniouses, and if I'm not completely wrong about Google you won't be able to find out exactly how they do what they do. Also, I know that years back they had more than 10,000 computers processing queries, and today they probably have many more. I also suspect them for caching most of the recent/popular keywords. And all the websites have been indexed and analyzed using an unknown algorithm which will make sure the computers don't have to look through all the words on every page.
In fact, Google crawls the entire internet around every 14 days, so when you do a search you do not search the entire internet. Your search gets broken down into keywords and then these keywords are used to narrow the number of relevant pages - and I'm pretty sure all pages have already been analyzed for important and/or relevant keywords before you even thought of visiting google.com.
Have a look at this question.
Have a look into Sphinx server.
http://sphinxsearch.com/
Craigslist uses that for their search engine. Basically, you give it a source and it indexes whatever you want (mysql database/table, text files, etc.). If it works for craigslist, it should work for you.
I'd like to find a way to take a piece of user supplied text and determine what addresses on the map are mentioned within the text. I'd be happy to use a free web service if it exists or use a script which will not consume too many resources.
One way I can imagine doing this is taking a gigantic database of addressing and searching for each of them individually in the text, but this does not seem efficient. Is there a better algorithm or technique one can suggest?
My basic idea is to take the location information and turn it into markers on a Google Map. If it is too difficult or CPU intensive to determine the locations automatically, I could require users to add information in a location field if necessary but I would prefer not to do this as some of the users are going to be quite young students.
This needs to be done in PHP as that is the scripting language available on my school hosted server.
Note this whole set-up will happen within the context of a Drupal node, and I plan on using a filter to collect the necessary location information from the individual node, so this parsing would only happen once (when the new text enters the database).
You could get something like opencalais to tag your text. One of the catigories which it returns is "city" you coud then use another third party module to show the location of the city.
If you did have a gigantic list of locations in a relational database, and you're only concerned about 500 to 1000 words, then you could definitely just pass the SQL command to find matches for the 500-1000 words and it would be quite efficient.
But even if you did have to call a slow API, you could feasibly request for 500 words one by one. If you kept a cache of the matches, then the cache would probably quickly fill up with all the stop words (you know, like "the", "if", "and") and then using the cache, it'd be likely that you would be searching much less than 500 words each time.
I think you might be surprised at how fast the brute force approach would work.
For future reference I would just like to mention the Yahoo API called Placemaker and the service GeoMaker that is built on top of it.
Those tools can be used to parse out locations from a text as requested here. Unfortunately no Drupal module seems to exists right now- but a custom solution seems easy to code.