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I'm trying to design an application in which a user can make multiple operations like add, delete.. Work stations or Applications from database. How do I design it?
To deal this, I've found two solutions that I couldn't be able to choose the best:
1st solution, 2nd solution.
Is this right?
Any brilliant suggestion, please?
Thanks a lot!
To think this out a bit, a user can have one or more operations i.e. a one to many relationship with the operation.
An operation can delete one or more Workstations or Applications, again a one to many relationships.
Therefore, I think your 1st solution captures it nicely.
I think solution 1 is better. Solution 2 requires that you insert 2 records in the 2 many-to-many associative tables, for each single operation. This is more complex, and probably unnecessarily so.
In solution 1 the Operation table becomes the only associative table. 1 operation, 1 insert. You may have to have to make some of the referencing keys nullable, depending on your requirements, but this is manageable. Simpler and sufficient for the needs you expressed.
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I am currently enrolled in the course by IBM on Coursera. I have written down two queries one with a sub query method and one with a case statement with correlated query.Answer of both looks same initially but is different in the values of other columns. Is the problem in my query?
I believe the issue is that multiple values of local_name have the same value of lang_num. That means that the sorting has ties.
The order by clause in SQL is not stable. This has a technical meaning that running order by twice on the same data produces the same results -- even when keys have the same value. The reason is simple: SQL tables represent unordered sets, so there is no default ordering for rows that have the same key values.
The solution is easy. Just make sure that the order by keys uniquely identify each row:
order by lang_num, local_name
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I Want to update a table column after checking multiple conditions on multiple tables
I think set from is more feasible at often and is faster than subquerying.See this understandable example.
UPDATE t_name AS t
SET T.attr1 = r.attr2
FROM any_list AS r
WHERE t.anylist_id = t.id
Joins are executed by the RDBMS with an execution pattern such that to optimize data loading and processing, unlike the sub-query where it will run all the queries and load all their data to do the processing.
More on subqueries can be found here
The subquery will generally only be executed far enough to determine whether at least one row is returned, not all the way to completion like in joins. It is unwise to write a subquery that has any side effects (such as calling sequence functions); whether the side effects occur or not may be difficult to predict.
I don't know how well they perform, but I see at least the following two possibilities:
A subquery
UPDATE SET FROM - syntax (can be found in PostgreSQL documentation, too)
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Good sirs.
I've just started planning a new project, and it seems that I should stick with a relational database, (even though I want to play with mongo). Tell me if I'm mistaken!
There will be box models, each of which can contain hundreds to thousands of items.
At any time, the user can move an item to another box.
for example, using some Railsy pseudocode...
item = Item(5676)
item.box // returns 24
item.update(box:25)
item.box // returns 25
This sounds like a simple SQL join table to me, but an expensive array manipulation operation for mongodb.
Or is removing an object out of one (huge) array and inserting it in another (huge) array not a big problem for mongo?
Thanks for any wisdom. I've only just started with mongo.
If you want to use big arrays, stay away from MongoDB. I tell from personal experience. There are two big problems with arrays. If they start to grow, document grows and it needs to be moved on disk. That is very, very slow operation. Plus if you need to scan array to get to 10000 element, that will be very slow as it needs to check 9999 before that.
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I appreciate there are one or two similar questions on SO but we are a few years on and I know EF's speed and general performance has been enhanced so those may be out of date.
I am writing a new webservice to replace an old one. Replicating the existing functionality it needs to do just a handful of database operations. These are:
Call existing stored procedures to get data (2)
Send SQL to the database to be executed (should be stored procedures I know) (5)
Update records (2)
Insert records (1)
So 10 operations in total. The database is HUGE but I am only dealing with 3 tables directly (stored procedures do some complex JOINs).
When getting the data I build an array of objects (e.g. Employees) which then get returned by the web service.
From my experience with Entity Framework, and because I'm not doing anything clever with the data, I believe EF is not the right tool for my purpose and SqlDataReader is better (I imagine it is going to be lighter and faster).
Entity Framework focuses mostly on developer productivity - easy to use, easy to get things done.
EF does add some abstraction layers on top of "raw" ADO.NET. It's not designed for large-scale, bulk operations, and it will be slower than "raw" ADO.NET.
Using a SqlDataReader will be faster - but it's also a lot more (developer's) work, too.
Pick whichever is more important to you - getting things done quickly and easily (as a developer), or getting top speed by doing it "the hard way".
There's really no good "one single answer" to this "question" ... pick the right tool / the right approach for the job at hand and use it.
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I'm starting out to design a site that has some requirements that I've never really dealt with. Specifically, the data objects will have similar, but not exact, attributes. Yes, I could probably figure out most of the possible attributes and then just not populate the ones that don't make sense, and therefore keep a traditional "Relational" table and column design, but I'm thinking this might be a really good time to learn NoSQL.
In addition, the user will have 1, and only 1, textbox to search, and I will need to search all data objects and their attributes to find that string.
Ideally, I'd like to have the search return in order of "importance", meaning that if a match for the user's entered string is found in a "name" attribute, it would be returned as a higher confidence match than if the string was matched on a sub-attribute.
Anyone have any experience in this sort of situation? What have you tried that worked or didn't work? Am I wrong in thinking that this project is very well suited to a NoSQL type of database?
Stick with a traditional relational database such as MySQL or Postgresql. I would suggest sorting by relevance in your application code after obtaining the matching results. The size of your result set should impact your design choices, but if you will have less than 1-2k results then just keep it simple and don't worry too much about optimization.
NoSQL is just a dumb key value store, a persistent dictionary that can be shared across multiple application instances. It can solve scalability issues, but introduces new ones since you now just have a dumb data store. Relational databases have had years of performance tuning and do a great job.
I find NoSQL to be much more suited to storing state data, like a users preferences or cache. If you are analyzing the relationship between data then you need a relational database.