REQUEST TO HAVE DATA STRUCTURE AND ALGORITHMS COURSE ON LARACASTS

@tykus I agree.

@vincent15000 10 hours ago you didn't know what the term data structure meant, but you agree that they're not needed?

@tykus I'm surprised by this take. I know this is web programming forum about a framework that boots and exits on every request, but still. You never think about problems in terms of data structures?

I think it's important to understand the basics. I'm not saying you have to remember how to write quicksort from scratch, but it helps to be able to make some quantitative estimates about performance rather than just guessing. Otherwise, any non-trivial problem becomes trial and error, which IMO isn't taking the job seriously. You can't always push everything live to see if it can handle production loads and then roll back when the database becomes unresponsive or the queued job times out.

It might not matter for CRUD form apps with 100 users, but not every program is like that.

@ekpono In my opinion, you absolutely should learn about those things, and not only for job interviews. But just know that you'll mostly use them without actually implementing them yourself, at least in web programming.

@JussiMannisto just saying I never had a need to use or implement a linked lists, or bubblesort, or whatever in a real world application. Doesn't follow that one doesn't understand Big-O ¯\_(ツ)_/¯.

YMMV.

@JussiMannisto You are right, I am always surprised why developers hold the opinion that learning the basics of programming should not be an important skill set. If you are going to stay 8 hours everyday on your job, the least you can do is be good at the basics

@tykus Fair enough. I guess I read too much into your comment, thinking you were recommending against learning about these things.

@jlrdw

There are also packages to install for things like linked list, etc.

Why would anyone install a package for linked lists? This reminds me of the is-even package on npm. But also, the Standard PHP Library already has linked lists.

But for general database management it's not needed. You are probably better off following laravel conventions, setting up proper indexes, following MVC, etc.

Database indexes are B+trees, with nodes connected via doubly-linked lists. If someone doesn't understand basic data structures, they can't know how indexes work. How would they know what a "proper index" is if they have no idea how they work under the hood?

@JussiMannisto I've see many users use https://github.com/lazychaser/laravel-nestedset and similar in laravel.

And you don't have to understand the in depth studies required to for example index an id and name column in SQL. The background work has been done for you.

Your comment kind of implies anyone using Mysql has an in depth knowledge of the code used to achieve such indexing.

I have myself used b-tree programs in progeny in dogs to check for such things as the amount of inbreeding.

I have also in python programmed flat pattern development for duct fittings, like:

• transitions
• rectangular to round
• offsets of various types
• etc

But I never got good enough to do advanced nesting.

But for the average laravel user, the things mentioned above by OP is not needed.

But there are other learning materials out there.

Edit:

And yes I have in the past read the parts of the Mysql manual covering how indexes basically work. I have even forgotten much of what I read, again not generally needed. But the mysql manual doesn't teach their programming that makes it work. Which I think is what the OP is after.

Like the laravel manual shows how to upload a file, but not what is happening behind the scenes. Which symfony goes through a routine and ends up using the php move for the upload.

But the average laravel user may not even know that neither. All they know is what the laravel docs tell them to do for an upload.

Yes some, perhaps you, me, and others also study the framework code, and the symfony code to see what is happening behind the scenes. But again to use laravel for the average user, not needed.

@jlrdw

Your comment kind of implies anyone using Mysql has an in depth knowledge of the code used to achieve such indexing.

I didn't mean to imply that. But it's also not exactly arcane knowledge.

I was thinking of a thread from not too long ago, where someone had performance issues on their large database. I think they even used the phrase properly indexed to describe the table, which I took to mean that every column had a separate index. Their query ran fast when they had a where-condition on one column, but slowed down when additional conditions were added. They didn't understand why that would be. After all, they were just adding more filters and every column was indexed, so they thought the query should've been faster.

The right move there was to dedicate one afternoon to reading about indexes: how they're structured and how they're used. That would've cleared things up, but I don't know if they did that.

I agree that going deep into databases isn't necessary for day 1, and you can build apps without knowing too much. But it may become important to learn at some point, and then it helps if you have the necessary tools to understand the material. That means knowing data structures.

@JussiMannisto I might have used the term "Properly index", but in my world that doesn't mean all columns, because that will give other performance issues in the database. I think Aaron Francis put it best.

"Use as many indexes as you need, but as few as you can get away with."

Knowing how to analyze queries and take the appropiate action is in my opinion worth way more that knowing how to do a bubble sort.

When it comes to database driven applications, most, if not all performance issues comes down to how the database is structured and the queries are written.

Unfortunately tha knowledge on how to use the database in the way it is intended , is something that too many don't really care about.

Sidenote: I'm not the author of the thread being referred to by @jussimannisto

@Tray2 The author said they had all columns indexed, and I'm guessing they meant an index on each column used in a query condition. So not necessarily bad, but clearly not sufficient in their case. They used multiple conditions, each targeting a separate index. With the correct composite indexes and some refactoring, I think the queries could've been turned into simple range scans.

Knowing how to analyze queries and take the appropiate action is in my opinion worth way more that knowing how to do a bubble sort.

Yes. But algorithms are often taught alongside complexity analysis, which helps with both code and databases. At least it provides some foundation for thinking about it, even if it usually boils down to something simple, like million operations = ok, million^2 operations = not ok.

When it comes to database driven applications, most, if not all performance issues comes down to how the database is structured and the queries are written.

Plus caching.

@jlrdw You're still using the data structures, even if someone else wrote them. It's still useful to know what's going on. Let's take these two lines of code:

isset($cache[$id]);
in_array($id, $cache);

Knowing PHP arrays immediately tells you which cache implementation is faster, and why it's so much faster.

I don't agree that you need that advanced math for basic algorithms and data structures. It's mostly just powers and logarithms.

@jlrdw now you are seeing my point, you don't need advanced math skills to learn this course, right? now imagine if Laracasts is teaching the course, I reckon it would be much more better than w3schools

@ekpono If you want to learn this that's fine.

But as already mentioned not actually needed for database management.

I've been at this since the latter 1980's starting out in dbase 3. I can understand the need to know how to setup the correct indexes in a database.

And yes I have had courses such as matrices and determinants.

But again when it comes to sorting (ORDER BY), the work is already accomplised by the programmers that maintain MySql.

It sounds more like you want to program things like Mysql than use it. So by all means learn this stuff.

Even when I programmed in java, servlets and and beans, for truck dispatch, A/R, A/P, payroll, etc I never needed such things. And many were multi pick and drop loads, thus child tables.

But I agree to know how and when and what to use an index on, much of which is common sense.

Just curious, why a course here when these courses exist already?

Like another user has said in past post, let the database to it's job.

Edit:

I just don't believe things like this is needed for laravel:

Quote

class Graph:
    def __init__(self, size):
        self.adj_matrix = [[0] * size for _ in range(size)]
        self.size = size
        self.vertex_data = [''] * size  

    def add_edge(self, u, v):
        if 0 <= u < self.size and 0 <= v < self.size:
            self.adj_matrix[u][v] = 1
            self.adj_matrix[v][u] = 1

    def add_vertex_data(self, vertex, data):
        if 0 <= vertex < self.size:
            self.vertex_data[vertex] = data

    def print_graph(self):
        print("Adjacency Matrix:")
        for row in self.adj_matrix:
            print(' '.join(map(str, row)))
        print("\nVertex Data:")
        for vertex, data in enumerate(self.vertex_data):
            print(f"Vertex {vertex}: {data}")
            
    def dfs_util(self, v, visited):
        visited[v] = True
        print(self.vertex_data[v], end=' ')

        for i in range(self.size):
            if self.adj_matrix[v][i] == 1 and not visited[i]:
                self.dfs_util(i, visited)

    def dfs(self, start_vertex_data):
        visited = [False] * self.size
        start_vertex = self.vertex_data.index(start_vertex_data)
        self.dfs_util(start_vertex, visited)

g = Graph(7)

g.add_vertex_data(0, 'A')
g.add_vertex_data(1, 'B')
g.add_vertex_data(2, 'C')
g.add_vertex_data(3, 'D')
g.add_vertex_data(4, 'E')
g.add_vertex_data(5, 'F')
g.add_vertex_data(6, 'G')

g.add_edge(3, 0)  # D - A
g.add_edge(0, 2)  # A - C
g.add_edge(0, 3)  # A - D
g.add_edge(0, 4)  # A - E
g.add_edge(4, 2)  # E - C
g.add_edge(2, 5)  # C - F
g.add_edge(2, 1)  # C - B
g.add_edge(2, 6)  # C - G
g.add_edge(1, 5)  # B - F

g.print_graph()

print("\nDepth First Search starting from vertex D:")
g.dfs('D')

Unquote

Which is from that course. But of course learn what you feel you need to.