Related
So I'm thinking to write some small piece of software, which to run/execute ML experiments on a cluster or arbitrary abstracted executor and then save them such that I can view them in real time efficiently. The executor software will have access for writing to the database and will push metrics live. Now, I have not worked too much with databases, thus I'm not sure what is the correct approach for this. Here is a description of what the system should store:
Each experiment will consist of a single piece of code/archive of code such that it can be executed on the remote machine. For now we will assume allow dependencies and etc are installed there. The code will accept command line arguments. The experiment also will consists of a YAML scheme defining the command line arguments. In the code byitself will specify what will be logged in (e.g. I will provide a library in the language for registering channels). Now in terms of logging, you can log numerical values, arrays, text, etc so quite a few types. Each channel will be allowed a single specification (e.g. 2 columns, first int iteration, second float error). The code will also provide special copy of parameters at the end of the experiments.
When one submit an experiments, it will need to provide its unique group name + parameters for execution. This will launch the experiment and log everything.
Implementing this for me is easiest to do with a flat file system. Each project will have a unique name. Each new experiment gets a unique id and folder inside the project. I can store the code there. Each channel gets a file, which for simplicity can be an csv delimeter, with a special schema file describing what type of values are stored there so I can load them there. The final parameters can also be copied in the folder.
However, because of the variety of ways I can do this, and the fact that this might require a separate "table" for each experiment, I have no idea if this is possible in any database systems? Additionally, maybe I'm overseeing something very obvious or maybe not, if you had any experience with this any suggestions/advices are most welcome. The main goal is at the end to be able to serve this to a web interface. Maybe noSQL could accommodate this maybe not (I don't know exactly how those work)?
The data for ML primarily would be unstructured data. That kind of data will not naturally fit into a RDBMS. Essentially a document database like mongodb is far better suited....for such cases.
I'm a student and starting to relearn again the basics of programming.
The problem I stated above starts when I have read some Facebook posts that most of the programmers use arrays in their application and arrays are useful. And I started to realize that I never use arrays in my program.
I read some books but they only show the syntax of array and didn't discuss on when to apply them in creating real world applications. I tried to research this on the Internet but I cannot find any. Do you guys have circumstance when you use arrays. Can you please share it to me so I can have an idea.
Also, to clear my doubts can you please explain to me why arrays are good to store information because database can also store information. When is the right time for me to use database and arrays?
I hope to get a clear answer because I have one remaining semester before the internship and I want to clear my head on this. I do not include any specific programming language because I know most of the programming language have arrays.
I hope to get an answer that can I can easily understand.
When is the right time for me to use database and arrays?
I can see how databases and arrays may seem like competing solutions to the same problem, but you're comparing apples and oranges. Arrays are a way to represent structured data in memory. Databases are a tool to store data on disk until you need to retrieve it.
The question you pose is kind of like asking: "When is the right time to use an integer to hold a value, vs a piece of paper?" One of them is a structural representation in memory; the other is a storage tool.
Do you guys have circumstance when you use arrays
In most applications, databases and arrays work together. Applications often retrieve data from a database, and hold it in an array for easy processing. Here is a simple example:
Google allows you to receive an alert when something of interest is mentioned on the news. Let's call it the event. Many people can be interested in the event, so Google needs to keep a list of people to alert. How? Probably in a database.
When the event occurs, what does Google do? Well it needs to:
Retrieve the list of interested users from the DB and place it in an array
Loop through the array and send a notification to each user.
In this example, arrays work really well because users form a collection of similarly shaped data structures that needs to be put through a similar process. That's exactly what arrays are for!
Some other common uses of arrays
A bank wants to send invoice and payment due reminders at the end of the day. So it retrieves the users with past due payments from the DB, and loops through the users' array sending notifications.
An IT admin panel wants to check whether all critical websites in a list are still online. So it loops through the array of domains, pings each one and records the results in a log
An educational program wants to perform statistical functions on student test results. So it puts the results in an array to easily perform operations such as average, sum, standardDev...
Arrays are also awesome at keeping things in a predictable order. You can be certain that as you loop forward through an array, you encounter values in the order you put them in. If you're trying to simulate a checkout line at the store, the customers in a queue are a perfect candidate to represent in an array because:
They are similarly shaped data: each customer has a name, cart contents, wait time, and position in line
They will be put through a similar process: each customer needs methods for enter queue, request checkout, approve payment, reject payment, exit queue
Their order should be consistent: When your program executes next(), you should expect that the next customer in line will be the one at the register, not some customer from the back of the line.
Trying to store the checkout queue in a database doesn't make sense because we want to actively work with the queue while we run our simulation, so we need data in memory. The database can hold a historical record of all customers and their checkout outcomes, perhaps for another program to retrieve and use in another way (maybe build customized statistical reports)
There are two different points. Let's me try to explain the simple way:
Array: container objects to keep a fixed number of values. The array is stored in your memory. So it depends on your requirements but when you need a fixed and fast one, just use array.
Database: when you have a relational data or you would like to store it in somewhere and not really worry about the size of the objects. You can store 10, 100, 1000 records to you DB. It's also flexible and you can select/query/update the data flexible. Simple way to use is: have a relational data, large amount and would like to flexible it, use database.
Hope this help.
There are a number of ways to store data when you have multiple instances of the same type of data. (For example, say you want to keep information on all the people in your city. There would be some sort of object to hold the information on each person, and you might want to have a data structure that holds the information on every person.)
Java has two main ways to store multiple instances of data in memory: arrays and Collections.
Databases are something different. The difference between a database and an array or collection, as I see it, are:
databases are persistent, i.e. the data will stay around after your program has finished running;
databases can be shared between programs, often programs running in all different parts of the world;
databases can be extremely large, much, much larger than could fit in your computer's memory.
Arrays and collections, however, are intended only for use by one program as it runs. Your program may want to keep track of some information in order to do its calculations. But the data will be in your computer's memory, and therefore other programs on other computers won't be able to access it. And when your program is done running, the data is gone. However, since the data is in memory, it's much faster to use it than data in a database, which is stored on some sort of external device. (This is really an overgeneralization, and doesn't consider things like virtual memory and caching. But it's good enough for someone learning the basics.)
The Java run time gives you three basic kinds of collections: sets, lists, and maps. A set is an unordered collection of unique elements; you use that when the data doesn't belong in any particular order, and the main operations you want are to see if something is in the set, or return all the data in the set without caring about the order. A list is ordered, though; the data has a particular order, and provides operations like "get the Nth element" for some number N, and adding to the ends of the list or inserting in a particular place in the list. A map is unordered like a set, but it also attaches keys to the data, so that you can look for data by giving the key. (Again, this is an overgeneralization. Some sets do have order, like SortedSet. And I haven't even gotten into queues, trees, multisets, etc., some of which are in third-party libraries.)
Java provides a List type for ordered lists, but there are several ways to implement it. One is ArrayList. Like all lists, it provides the capability to get the Nth item in the list. But an ArrayList provides this capability faster; under the hood, it's able to go directly to the Nth item. Some other list implementations don't do that--they have to go through the first, second, etc., items, until they get to the Nth.
An array is similar to an ArrayList, but it has a different syntax. For an array x, you can get the Nth element by referring to x[n], while for an ArrayList you'd say x.get(n). As far as functionality goes, the biggest difference is that for an array, you have to know how big it is before you create it, while an ArrayList can grow. So you'd want to use an ArrayList if you don't know beforehand how big your list will be. If you do know, then an array is a little more efficient, I think. Although you can probably get by mostly with just ArrayList, arrays are still fundamental structures in every computer language. The implementation of ArrayList depends on arrays under the hood, for instance.
Think of an array as a book, and database as library. You can't share the book with others at the same time, but you can share a library. You can't put the entire library in one book, but you can checkout 1 book at a time.
I am doing an information retrieval project in c++. What are the advantages of using a database to store terms, as opposed to storing it in a data structure such as a vector? More generally when is it a good idea to use a database rather than a data structure?
(Shawn): Whenever you want to keep the data beyond the length of the instance of the program. (persistence across time)
(Michael Kjörling): Whenever you want many instances of your program, either in the same computer or in many computers, like in a network or the Net, access and manipulate (share) the same data. (persistence across network space)
Whenever you have very big amount of data that do not fit into memory.
Whenever you have very complex data structures and you prefer to not rewrite code to manipulate them, e.g search, update them, when the db programmers have already written such code and probably much faster than the code you (or I)'ll write.
Whenever you want to keep the data beyond the length of the instance of the program?
In addition to Shawn pointing out persistence: whenever you want multiple instances of the program to be able to easily share data?
In-memory data structures are great, but they are not a replacement for persistence.
It really depends on the scope. For example if you're going to have multiple applications accessing the data then a database is better because you won't have to worry about file locks, etc. Also, you'd use a database when you need to do things like joining other data, sorting, etc... unless you like to implement Quicksort.
Hi I'm using CakePHP and I'm wondering if it's advisable to store things that don't change a lot in the database lik the list of cities?
If your application already needs a database, why would you keep data anywhere else?
If the list doesn't change (per installation) and it's reasonably small and frequently used, then it might be worth reading it once on initialization and caching the result to improve performance and reduce the load on the database.
You get all sorts of queries and retrievals out of the box, the same way you access any other of your data. Databases are as cheap as flat files today, but you get a full service.
I see this question has had an answer accepted - I still want to chime in with my $0.02
The way I typically do for arrays of static data (country list, timezone list, immutable sets you would use enum for...) is to use this array datasource.
It allows you to map relationships between db models and array based models and to use the usual find syntax / Containable on the relationships.
http://github.com/jrbasso/array_datasource
If it is pretty much a static list, then you can store it either in the db or a file, but keep it in memory for use. In other words, load it once whether from db or file. What you don't want to do is keep taking a hit loading it. Especially if you use it on most page views. Those little bits of time add up if you have a large number of visitors.
The flip side, of course, is if you find yourself doing this for large lists or lots and lots of little lists. Then you could run into problems of keeping too much in memory.
Bill the Lizard is right about it being important whether or not the list links to other tables. If it does, then you will need it in the db if you need queries that will include it.
There's been a discussion between me and some colleagues that are taking the same class as me (and thus have the same project) about saving data to files and read from those files only when we need that specific data.
For instance, the project is something about managing a social network. I'm not going into specifics because it doesn't matter, but the idea is to use the best data structures to manipulate this data.
Let's say I'm using an Hash Table to save the users profile data. Some of them argue that only some specific information should be saved in the data structures, like and ID that represents an user. Everything else should be put on files. We should access the files to get that data we want when we want.
I don't think this is practical... It could be if we were using some library for a database like SQLite or something, but are not and I don't think we are supposed to. We are only supposed to code everything ourselves and use C functions, like these. Nor do I think we are supposed to do a perfect memory management. The requisites of the project are not for us to code a database, or even a pseudo-database. What this project demands of us, are the best data structures (as long as we know how to justify why we picked those instead of others) to store the type of data and the all data specified for the project.
I should let you know that we had 2 classes before where the knowledge we got there is to be applied on this project. One of those dealt with the basis of C, functions, structures, arrays, strings, file IO, recursion, pointers and simple data structures like binary trees and linked lists, stuff like that. The other one was about more complex data structures, hash tables, AVL trees, heaps, graphs, etc... It also talked about time complexity, big O notation and stuff like that.
For instance, let's say all I have in memory is the IDs of the users and then I need to find all friends of a specific user. I'll have to process the whole file (or files) finding out the friends of that user. It would be much easier if I could have all that data in memory already.
It makes no sense to me that we need to pick (and justify) the data structures that we best see fit for the project and then only use them to lookup for an ID. We will then need to do a second lookup, to get the real data we need, which will take it's time, won't it? Why did we bother with the data structures in the first place if we still need to get to search a bunch of files on the hard drive?
How could it be possible, using standard C functions, coding everything manually and still simulate some kind of database? Is this practical at all?
Am I missing something here?
It sounds like the project might be more about how you design the relationships between your data "entities," and not as much about how you store them. I don't think storing data off in files would be a good solution - file IO will be much slower than accessing things in memory. If you had the need to persist data on the disk, you'd probably want to just use a database, rather than files (I know it's an academic course though, so who knows).
I think you should focus more on how you design your data types, and their relationships, to maximize the speed of lookups, searches, etc. For example, you could store all the users in a linked list, or store them in a tree, or a graph, but each will have its implications on how fast you can find users, etc. Depending on what features you want in your social networking site, there will be different designs that will allow different types of behavior to perform better than it would in other designs.
From what you're saying I doubt that you need to store anything on disk.
One thing that I would ask the teacher is if you're optimizing for time or space complexity (there will be a trade off between these two depending on what you're trying to achieve).
That can certainly be done. The resource forks in Mac System 5-8 files were stored as binary indexed databases (general use of the term, don't think SQL!). (I think the interface was actually written in assembly, but I could do it in c).
The only thing is: it's a pain in the butt. Such files typically need to start with some kind of index or header, and then hold a bunch of records at predictable locations. (OK, sometimes the first index just points at some more indexes. How many layers of indirection do you care to manage?)
If you're going to do it, just remember: binary mode access.
Hmm... what about persistent storage?
If your project requires you to be able to remember friend data between two restarts of the app, then don't you think file storage (or whatever else becomes an issue)?
I'm having a very hard time figuring out what you are trying to ask here.
But there is a general rule that may apply:
If all of your data will fit in memory at once, it is usually best to load all of it into memory at once and keep it there. You write out to a file only to save, to exit, or for backup.
There are lots of exceptions to this rule, but for a class project where this is going to be the only major application running on the machine, you may as well store everything in memory. After all, you have already paid for the memory; you don't want it just sitting there idle.
I may have completely misunderstood the question you are trying to ask...