I'm in the planning phase of developing a very tag heavy website. Everything will essentially be associated with tags and the entire site would be based on searching these tags.
Now, I've been thinking a lot about going the nosql route here, since from what I read and understand, it makes the most sense for something like this.
Would it be best to go with this database system? Would it makes sense to go with the relational database system? Should I think incorporating something like SOLR?
What would the ideal setup be?
UPDATE:
Ideally they would be user generated, but we all know how that would turn out with giving users that much power. So, let’s change up the requirements and say that users WILL NOT have the power to create tags.
Searching on tags based on text matches is something that would probably be useful and needed. If the tag is “garage sale”, the search for “sale” should also pick this up, at a lower relevance for sure.
I can’t imagine the usage being so much that scaling would be an issue.
Thanks
I would spend a bit of time thinking about these tags. For example, are these tags going to be user generated or will you provide a few tags and let users select which ones they want?
Will you need to search on tags based on text matches? For example if a tag is "garage sale" do you want to search for "sale" to also pick this up? Maybe at a lower relevance?
Also, what kind of usage are you looking at? One good thing about Solr is that it's super easy to scale and synchronize data, it is easy to deploy multiple nodes, shard collections and replicate data to other nodes, something that traditional databases struggle with.
Another thing to keep in mind is that most of the time, Solr is not the official "repository of record", most of the time the data gets fed to it from a DB somewhere, but all reading activities are done from Solr.
See this answer for a SQL solution. Offhand I can't think of any advantage to using most NoSQL databases (i.e. key-value, columnar, or document) as the SQL solution will be more compact and ought to give good performance; a graph database may be appropriate if you're doing a lot of navigational type queries on your tags, but it doesn't sound like that's the case.
Use of Solr (or ElasticSearch or whatever) is orthogonal to your primary database; it may be appropriate to incorporate a search tool if users are typing inexact tags for search, but I recommend integrating a stemming library or something along those lines before turning to a full blown search tool.
Related
I am using asp.net core and Razor - and as it is a help system I would like to implement some kind of search facility to bring back a list of results hyperlinked based on the search terms.
I would like the search to iterate essentially over the content contained within the and tags and then link this to the appropriate page/view.
What is the best way to do this?
I'm not even sure how you get a handle on the actual content of your own cshtml pages and then go from there.
This question is far too broad. However, I can provide you some pointers.
First, you need to determine what you're actually wanting to surface and where that data lives. Your question says "static web pages", but then you mention .cshtml. Traditionally, when it comes to creating your own search, you're going to have access to some particular dataset (tables in a database, for example). It's much simpler to search across the more structured data than the end result of it being dumped in various and sundry places over a web page.
Search engines like Google only index in this way because they typically don't have access to the raw data (although some amount of "access" can be granted via things like JSON-LD and other forms of Schema.org markup). In other words, they actually read from the web page out of necessity, because that's what they have to work with. It's certainly not the approach you would take if you have access to the data directly.
If for some reason you need to actually spider an index your own site's HTML content, then you'll essentially have to do what the big boys do: create a bot, run it on a schedule, crawl your site, link by link, downloading each document, and then parse and process it. The end result would be to create a set of structured data that you can actually query against, which is why all this is pretty much just wasted effort if you already have that data.
Once you have the data, however you got there, you simply query it. In the most basic of forms, you could store it in a table in a database and literally issue SQL queries against it. Your search keywords/parameters are essentially the WHERE of the SELECT statement, so you'd have to figure out a way to map the keywords/parameters you're receiving to an acceptable WHERE clause that achieves that.
More traditionally, you'd use an actual search engine: essentially a document database that is designed and optimized for search, and generally provides a more search-appropriate API to query against. There's lots of options in this space from roll your own to hosted SaaS solutions, and anywhere in between. Of course the cost meter goes down the more work you have to do and goes up the more out of the box it is.
One popular open-source and largely free option is Elasticsearch. It uses Lucene indexes, which it stitches to together in a clustered environment to provide failover and scale. Deployment is a beast, to say the least, though it's gotten considerably better with things like containerization and orchestration. You can stand up an Elasticsearch cluster in something like Kubernetes with relative ease, though you still will probably need to do a bit of config. Elasticsearch does also have hosted options, but you know, cost.
I am trying to design a database with search-ability at its core. My knowledge of database design and SQL is all self-taught and still fairly beginner-level, so my questions may possibly have easy answers.
Suppose I have a single table containing a large number of records. For example, suppose that each record contains details of a different computer application (name, developer, version number, etc). A list of keywords are associated with each record, such as a list of programming languages used to write the applications.
I wish to be able to enter one or more keywords (each separated by a space) into a search box, and I wish to have all associated records returned. How should I design the database to store the keywords, and what SQL query would I need to apply to the search text? (The search should be uppercase/lowercase independent.)
My next challenge would then be to order search results by relevance, and to allow entire key-phrases as well as keywords to be associated with each record. For example, if I type "Visual Basic" into the search field, I want the first results to have exactly the key-phrase "Visual Basic" associated with them. The next results should all have both keywords "Visual" and "Basic" associated with them, and the remaining results should have only one of these keywords. Again, please could anyone advise on how to implement this?
The final challenge I believe would be much harder: how much 'intelligent interpretation' can I design my database and SQL code to handle? For example, if I search for "CSS", can I get the records with the key-phrase "Cascading Style Sheets" to appear? Can I also get SQL to identify and search for similar words, such as plurals of search phrases or, for example, "programmer" or "programming" when "program" is input? Thanks!
Learn relational algebra, normalization rules, and SQL.
Start with entity relationships. Sounds like you could have an APPLICATION table as parent for a FEATURE child table, with a one-to-many relationship between the two. You'll query them by JOINing one to the other:
SELECT A.NAME, F.NAME
FROM APPLICATION AS A
JOIN FEATURE AS F
ON F.APP_ID = A.ID
Your challenges would not suggest SQL and relations to me. I would think more in terms of a parser, an indexer and search engine like Lucene, and a NoSQL document database like MongoDB.
I've come to the conclusion, after a LOT of research, that #duffymo's answer is hinting in the right direction. For the benefit of other n00bs like me, here's the conclusion I've drawn:
Many open source search engine server apps are out there to install for free. Lucene was the first I had ever heard of them, but others do exist and I think my favourite at the moment is Sphinx. As far as I can tell, the 'indexer' that #duffymo mentions is built into it. I have learnt that the indexer is the program that will examine my database for keywords and will automatically keep a record of which results should be returned for different input queries. I have also now learnt that the terminology for the behaviour I was looking for (and which Sphinx has) is 'stemming'. I'm still not sure what role a parser plays in all this...
A more basic approach would be to use SQL itself. Whilst I was already aware of the most basic of these (ie. using the LIKE keyword with 'wildcards'), I also discovered something a little more powerful: natural language / full-text search. For anyone not interested in installing a server app, I recommend you look this up.
Also, I see no reason why I would need to use NoSQL instead of SQL (as #duffymo has suggested), and so I'm going to stick with SQL for the moment (at least until I come across some good entry-level books to learn NoSQL from). Furthermore, I have very little intention to learn relational algebra until I know why I should and how it would be useful. The message here is that other beginners shouldn't be off-put by these things, as I don't think Sphinx requires any knowledge of them.
while I like #duffymo's answer, I will also suggest you research SPARQL and the wordnet project for your semantic equivalence questions.
If you choose Oracle, you can use the spatial option triple store to implement the SPARQL endpoint and do some very nice seaching like your css = Cascading Style Sheet example.
I started a new application and now I am looking at two paths and don't know which is good way to continue.
I am building something like eCommerce site. I have a categories and subcategories.
The problem is that there are different type of products on site and each has different properties. And site must be filterable by those product properties.
This is my initial database design:
Products{ProductId, Name, ProductCategoryId}
ProductCategories{ProductCategoryId, Name, ParentId}
CategoryProperties{CategoryPropertyId, ProductCategoryId, Name}
ProductPropertyValues{ProductId, CategoryPropertyId, Value}
Now after some analysis I see that this design is actually EAV model and I read that people usually don't recommend this design.
It seems that dynamic sql queries are required for everything.
That's one way and I am looking at it right now.
Another way that I see is probably named a LOT WORK WAY but if it's better I want to go there.
To make table
Product{ProductId, CategoryId, Name, ManufacturerId}
and to make table inheritance in database wich means to make tables like
Cpus{ProductId ....}
HardDisks{ProductId ....}
MotherBoards{ProductId ....}
erc. for each product (1 to 1 relation).
I understand that this will be a very large database and very large application domain but is it better, easier and performance better than the option one with EAV design.
EAV is rarely a win. In your case I can see the appeal of EAV given that different categories will have different attributes and this will be hard to manage otherwise. However, suppose someone wants to search for "all hard drives with more than 3 platters, using a SATA interface, spinning at 10k rpm?" Your query in EAV will be painful. If you ever want to support a query like that, EAV is out.
There are other approaches however. You could consider an XML field with extended data or, if you are on PostgreSQL 9.2, a JSON field (XML is easier to search though). This would give you a significantly larger range of possible searches without the headaches of EAV. The tradeoff would be that schema enforcement would be harder.
This questions seems to discuss the issue in greater detail.
Apart from performance, extensibility and complexity discussed there, also take into account:
SQL databases such as SQL Server have full-text search features; so if you have a single field describing the product - full text search will index it and will be able to provide advanced semantic searches
take a look at no-sql systems that are all the rage right now; scalability should be quite good with them and they provide support for non-structured data such as the one you have. Hadoop and Casandra are good starting points.
You could very well work with the EAV model.
We do something similar with a Logistics application. It is built on .net though.
Apart from the tables, your application code has to handle the objects correctly.
See if you can add generic table for each object. It works for us.
I was searching the net for something like a wiki database, just like wikipedia but instead stores structured content, editable by users. What I was looking for was an online database accessible by everyone where people can design the schema and data with proper versioning of both schema and data. I couldn't find any such site. I am not sure if it is my search skills or if there really is no wiki database as of now. Does anyone out there know anything like this?
I think there is a great potential for something like this. A possible example will be a website with a GUI for querying a MySQL DB where any website visitor can create DB objects and populate data.
UPDATE: I had registered the domain wikidatabase.org to get started on a tool but I didn't find enough time yet. If anyone is interested in spending some time and coding on this, please let me know at wikidatabase.org
It's not quite what you're looking for, but Semantic Mediawiki adds database-like features to MediaWiki:
http://semantic-mediawiki.org/wiki/Semantic_MediaWiki
It's still fundamentally a Wiki, but you can add semantic tags to pages ([[foo::bar]] [[baz::1000]]) and then do database-type queries across them: SELECT baz FROM pages WHERE foo=bar would be {{#ask: [[foo::bar]] | ?baz}}. There is even an embryonic SPARQL implementation for pseudo-SQL queries.
OK this question is old, but Google led me here, so for anyone else out there looking for a wiki for structured data: Take a look at Foswiki.
This might be like what you're looking for: dbpedia.org. They're working on extracting data from Wikipedia, and encoding it in a structured format using RDF, so that it can be queried using SPARQL.
Linkeddata.org has a big list of RDF data sets.
Do you mean something like http://www.freebase.com?
You should check out https://www.wikidata.org/wiki/Wikidata:Main_Page which is a bit different but still may be of interest.
Something that might come close to your requirements is Google Docs.
What's offered is document editing roughly similar to MS Word, and spreadsheets roughly similar to Excel. I'm thinking of the latter, of course.
In Google Docs, You can create spreadsheets for free; being spreadsheets, they naturally have a row-and-column structure similar to a database, and which you can define flexibly. You can also share these sheets with other people. This seems to be a by-invite-only process rather than open-to-all, but there may be other possibilities I'm not aware of, or that level of sharing might be enough for you in any case.
mindtouch should be able to do it. It's rather easy to get data in / out. (for example: it's trivial to aggregate all the IP's for servers into one table).
I pretty much use it as a DB in the wiki itself (pages have tables, key/value..inheritance, templates, etc...) but you can also interface with the API, write dekiscript, grab the XML...
I like this idea. I have heard of some sites that are trying to pull together large datasets for various things for open consumption, but none that would allow a wiki feel.
You could start with something as simple as an installation of phpMyAdmin with a known password that would allow people to log in, create a database, edit data and query from any other site on the web.
It might suffer from more accuracy problems than wikipedia though.
OpenRecord, development of which seems to have halted in 2008, seems to approach this. It is a structured wiki in which pages are views on the data. Unlike RDBMSes it is loosely typed - the system tries to make a best guess about what data you entered, but defaults to text when it cannot guess. Schemas appear to have been implied.
http://openrecord.org
An example of the typing that is given is that of a date. If you enter '2008' in a record, the system interprets this as a date. If you enter 'unknown' however, the system allows that as well.
Perhaps you might be interested in Couch DB:
Apache CouchDB is a document-oriented
database that can be queried and
indexed in a MapReduce fashion using
JavaScript. CouchDB also offers
incremental replication with
bi-directional conflict detection and
resolution.
I'm working on an Open Source PHP / Symfony / PostgreSQL app that does this.
It allows multiple projects, each project can have multiple directories, each directory has a defined field structure. Admins set all this up.
Then members of the public can suggest new records, edit or report existing ones. All this is moderated and versioned.
It's early days yet but it basically works and is already in real world use in several projects.
Future plans already in progress include tools to help keep the data up to date, better searching/querying and field types that allow translations of content between languages.
There is more at http://www.directoki.org/
I'm surprised that nobody has mentioned Wikibase yet, which is the software that powers Wikidata.
I'm trying to implement a search feature for an offline-accessible StackOverflow, and I'm noticing some problems with using MySQLs FULLTEXT indexing.
Specifically, by default FULLTEXT indexing is restricted to words between 4 and 84 characters long. Terms such as "PHP" or "SQL" would not meet the minimum length and searching for those terms would yield no results.
It is possible to modify the variable which controls the minimum length a word needs to be to be indexed (ft_min_word_len), but this is a system-wide change requiring indexes in all databases to be rebuilt. On the off chance others find this app useful, I'd rather keep these sort of variables as vanilla as possible. I found a post on this site the other day stating that changing that value is just a bad idea anyway.
Another issue is with terms like "VB.NET" where, as far as I can tell, the period in the middle of the term separates it into two indexed values - VB and NET. Again, this means searches for "VB.NET" would return nothing.
Finally, since I'm doing a direct dump of the monthly XML-based dumps, all values are converted to HTML Entities and I'm concerned that this might have an impact on my search results.
I found a blog post which tries to address these issues with the following advice:
keep two copies of your data - one with markup, etc. for display, and one modified for searching (remove unwanted words, markup, etc)
pad short terms so they will be indexed, I assume with a pre/suffix.
What I'd like to know is, are these really the best workarounds for these issues? It seems like semi-duplicating a > 1GB table is wasteful, but maybe that's just me.
Also, if anyone could recommend a good site to understand MySQL's FULLTEXT indexing, I'd appreciate it. To keep this question from being too cluttered, please leave the site recommendations in the question comments, or email me directly at the site on my user profile).
Thanks!
Additional Info:
I think I should clarify a couple of things.
I know "MySQL" tends to lead to the assumption of "web application", but that's not what I'm going for here. I could install Apache and PHP and run things that way, but I'm trying to keep this light. I can use my website for playing with PHP, so I don't feel the need to install it on my home machine too. I also hope this could be useful for others as well, and I don't want to force anyone else into installing a bunch of extra utilities. I went with MySQL since it was easy and needing to install some sort of DB was unavoidable.
The specifics of the project were going to be:
Desktop application written in C# (WinForms)
MySQL backend
I'm starting to wonder if I should just say to hell with it, and install everything I'd need to make this an (offline) webapp. As much as we'd all like to think our pet project is going to be used and loved by the community at large, I should know by now that this is likely going end up being only used by a single user.
From what was already said, I understand, that MySQL FullText is not for you ;) But why stick to MySQL? Try Sphinx:
http://www.sphinxsearch.com/
It will solve most of your problems.