I have created a spreadsheet userform that allows users to input information, do surface level data verification, and other things. The problem that I run into is because part of it involves adding all items involved in their submission (the input this is used for could be related to one or more items, sometimes in the higher 30's) I had to create an array and have the array write to the new sheet. This is terribly slow.
I've been learning about classes and thinking that they may be able to provide a sufficient alternative to an array since each item has the exact same information needed. (QTY, UOM, Type, etc) I was thinking of doing 2 classes, one where I have the member class for the item and another where it's the collection and it composes the members objects.
My question is if the performance of doing this would be better than using an array. Are arrays generally the better way of handling collections of data that need to be inputted and outputted to a sheet?
Related
I am currently studying a material that introduces the fundamental concepts required to understand REACT and there is a section of the material where there was an example on converting an array into an object.
My question under what circumstance may I need to convert an array into an object.
A common use case is normalizing data structures which is kind of splitting and simplifying large and complex objects. This is often done in databases and makes it easier to update and maintain the data.
If you want to dive deeper, I recommend you to read this redux example. You don't need to know redux to understand the idea.
Otherwise you can google it, I am not an expert in the subject and for me it's difficult to summarize it.
Regards.
Dani
When to Use Objects
Objects are used to represent a “thing” in your code. That could be a person, a car, a building, a book, a character in a game — basically anything that is made up or can be defined by a set of characteristics. In objects, these characteristics are called properties that consist of a key and a value.
When to Use Arrays
We use arrays whenever we want to create and store a list of multiple items in a single variable. Arrays are especially useful when creating ordered collections where items in the collection can be accessed by their numerical position in the list. Just as object properties can store values of any primitive data type (as well as an array or another object), so too can arrays consist of strings, numbers, booleans, objects, or even other arrays.
I hope that clarifies the circumstance that lead to using each one.
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 looking for a good solution to represent a 2-D array in a database. With a few catches of course. For instance, the array could grow in terms of columns and rows (which could be inserted at any point). Also important is that people (users) can manipulate specific cells in this array (and hopefully without having to update the entire array). Also there may be multiple arrays to store.
I have thought about using a json but that would require always writing the entire json to database when an update is made on a a specific cell which would not be idea especially when multiple people could manipulate the array at once.
The typical data structure would be three columns:
row
column
value
Of course, you might have other columns if you have a separate array for each user (say a userid or arrayid column). Or, you might have multiple values for each cell.
I run a report daily which lists various files based on a particular identifier which indicates what is within the file. In the hopes of expediting my workflow, I'd like to set these files in a simple report by identifier, along with how frequently each identifier occurred, and organize this list from most to least frequent. Below is what I'm working with:
This is a VBA based terminal emulator with limited object library references, so Excel isn't an option
There's usually anywhere from 0-200 separate identifiers on any report, and they don't always appear on each. Since there are thousands of possible identifiers that could appear, I'd rather just have the macro list what it finds than look for them specifically.
I use a bit of code utilizing ADOdb streaming to write similar reports to a .txt file, which I would like to use here. I'm sure I can make that happen after the data is sorted, but felt it worth mentioning in case the nature of how the filtered/organized list would be utilized would affect how it is addressed.
I'm a novice, self-taught programmer with a particular fear of arrays (and I know this is going to come down to arrays...). So I don't necessarily know what commands and options are available to me in coding. (ie, a lot of what I've read involved possibly using dictionaries or collections, but I'm unsure I even have these available, let alone how to use them.)
I'd rather avoid creating multiple arrays, and creating multiple For loops if possible. It seems like a two dimensional dynamic array SortList(category, frequency) would be the route to go, but I can't find a way to filter unique values into it, while counting any of the values it has already found, and then sorting it afterwards.
I found a REALLY nifty bit of code on one site that can filter unique values without using a loop... (credit to where it's due: http://www.jpsoftwaretech.com/finding-values-in-an-array-without-looping/), but it seems it can only work for one dimensional arrays:
Function IsInArray(arr As Variant, valueToFind As Variant) As Boolean
IsInArray = (UBound(Filter(arr, valueToFind)) > -1)
End Function
Does anyone have any suggestions on how I should try and tackle this dilemma?
8/14 - Suppose this is also important to note: these are not individual files one can access in a folder somewhere; the data I'm working with is presented simply as a list. It might be better to state what I'm doing is having these identifiers read as strings. It's the strings I want to count, sort, and organize... it seems like something that can be done with beginner's programming techniques, I just can't seem to find a way to do it without extraneous arrays or unnecessary nested loops and if/then conditions. Thoughts?
If you are familiar with ADO/DAO you could try querying the files ensuring the field in question is in GROUP BY and outputting the result of a COUNT() of the identifier.
Alternatively you could use a combination of collections and arrays.
GSeg illustrates quite well how you could utilise a collection of arrays here.
Collection of Arrays
By using a collection you can add an identifier as a Key and its count as the second array element.
As you cant duplicate keys in collections, if you use the identifier as a key it will give you a unique list. When you try and add a duplicate key you therefre just need to trap the error and increase the count for that key. The count would be the second element in the array for that collections key.
Hope this makes sense. Good luck.
Suppose I have a list of R objects which are themselves lists. Each list has a defined structure: data, model which fits data and some attributes for identifying data. One example would be time series of certain economic indicators in particular countries. So my list object has the following elements:
data - the historical time series for economic indicator
country - the name of the country, USA for example
name - the indicator name, GDP for example
model - ARIMA orders found out by auto.arima in suitable format, this again may be a list.
This is just an example. As I said suppose I have a number of such objects combined into a list. I would like to save it into some suitable format. The obvious solution is simply to use save, but this does not scale very well for large number of objects. For example if I only wanted to inspect a subset of objects, I would need to load all of the objects into memory.
If my data is a data.frame I could save it to database. If I wanted to work with particular subset of data I would use SELECT and rely on database to deliver the required subset. SQLite served me well in this regard. Is it possible to replicate this for my described list object with some fancy database like MongoDB? Or should I simply think about how to convert my list to several related tables?
My motivation for this is to be able to easily generate various reports on the fitted models. I can write a bunch of functions which produce some report on a given object and then just use lapply on my list of objects. Ideally I would like to parallelise this process, but this is a another problem.
I think I explained the basics of this somewhere once before---the gist of it is that
R has complete serialization and deserialization support built in, so you can in fact take any existing R object and turn it into either a binary or textual serialization. My digest package use that to turn the serialization into hash using different functions
R has all the db connectivity you need.
Now, what a suitable format and db schema is ... will depend on your specifics. But there is (as usual) nothing in R stopping you :)
This question has been inactive for a long time. Since I had a similar concern recently, I want to add the pieces of information that I've found out. I recognise these three demands in the question:
to have the data stored in a suitable structure
scalability in terms of size and access time
the possibility to efficiently read only subsets of the data
Beside the option to use a relational database, one can also use the HDF5 file format which is designed to store a large amount of possible large objects. The choice depends on the type of data and the intended way to access it.
Relational databases should be favoured if:
the atomic data items are small-sized
the different data items possess the same structure
there is no anticipation in which subsets the data will be read out
convenient transfer of the data from one computer to another is not an issue or the computers where the data is needed have access to the database.
The HDF5 format should be preferred if:
the atomic data items are themselves large objects (e.g. matrices)
the data items are heterogenous, it is not possible to combine them into a table like representation
most of the time the data is read out in groups which are known in advance
moving the data from one computer to another should not require much effort
Furthermore, one can distinguish between relational and hierarchial relationships, where the latter is contained in the former. Within a HDF5 file, the information chunks can be arranged in a hierarchial way, e.g.:
/Germany/GDP/model/...
/Germany/GNP/data
/Austria/GNP/model/...
/Austria/GDP/data
The rhdf5 package for handling HDF5 files is available on Bioconductor. General information on the HDF5 format is available here.
Not sure if it is the same, but I had some good experience with time series objects with:
str()
Maybe you can look into that.