t-digest VS TablaM

> I get a lot of benefit from this information but somehow it feels shallow.

I take a longer view to this. For example, a few years ago I read about an algorithm to calculate percentiles in real time. [0]

It literally just came up at work today. I haven't used that information but maybe two times since I read it, but it was super relevant today and saved my team potential weeks of development.

So maybe it's not so shallow.

But to your actual question, I have a similar problem. The best I can say is that deadlines help. I usually put down the HN and Youtube when I have a deadline coming up. And not just at work. I make sure my hobbies have deadlines too.

I tell people when I think something will be done, so they start bugging me about it when it doesn't get done, so that I have a "deadline". Also one of my hobbies is pixel light shows for holidays, which come with excellent natural deadlines -- it has to be done by the holiday or it's useless.

So either find an "accountability buddy" who will hold you to your self imposed deadlines, or find a hobby that has natural deadlines, like certain calendar dates, or annual conventions or contests that you need to be done by.

[0] https://github.com/tdunning/t-digest

I am enamored by data structures in the sketch/summary/probabilistic family: t-digest[1], q-digest[2], count-min sketch[3], matrix-sketch[4], graph-sketch[5][6], Misra-Gries sketch[7], top-k/spacesaving sketch[8], &c.

What I like about them is that they give me a set of engineering tradeoffs that I typically don't have access to: accuracy-speed[9] or accuracy-space. There have been too many times that I've had to say, "I wish I could do this, but it would take too much time/space to compute." Most of these problems still work even if the accuracy is not 100%. And furthermore, many (if not all of these) can tune accuracy to by parameter adjustment anyways. They tend to have favorable combinatorial properties ie: they form monoids or semigroups under merge operations. In short, a property of data structures that gave me the ability to solve problems I couldn't before.

I hope they are as useful or intriguing to you as they are to me.

1. https://github.com/tdunning/t-digest

2. https://pdsa.readthedocs.io/en/latest/rank/qdigest.html

3. https://florian.github.io/count-min-sketch/

4. https://www.cs.yale.edu/homes/el327/papers/simpleMatrixSketc...

5. https://www.juanlopes.net/poly18/poly18-juan-lopes.pdf

6. https://courses.engr.illinois.edu/cs498abd/fa2020/slides/20-...

7. https://people.csail.mit.edu/rrw/6.045-2017/encalgs-mg.pdf

8. https://www.sciencedirect.com/science/article/abs/pii/S00200...

9. It may better be described as error-speed and error-space, but I've avoided the term error because the term for programming audiences typically evokes the idea of logic errors and what I mean is statistical error.

Ah, I misunderstood what you meant. If you are reporting static buckets I get how that is better than what folks typically do but how do you know the buckets a priori? Others back their histograms with things like https://github.com/tdunning/t-digest. It is pretty powerful as the buckets are dynamic based on the data and histograms can be added together.

Yes, but if you need to estimate median on the fly (e.g., over a stream of data) or in parallel there are better ways.

There are some newer data structures that take this to the next level such as T-Digest[1], which remains extremely accurate even when determining percentiles at the very tail end (like 99.999%)

[1]: https://arxiv.org/pdf/1902.04023.pdf / https://github.com/tdunning/t-digest

[2] https://github.com/tdunning/t-digest

T-Digest

This is pretty cool. The title would be a bit more descriptive if it were “Fast Rolling Quantile Filters for Python”, since the high-pass/low-pass filter functionality seems to be the focus.

The README mentions it uses binary heaps - if you’re willing to accept some (bounded) approximation, then it should be possible to reduce memory usage and somewhat reduce runtime by using a sketching data structure like Dunning’s t-digest: https://github.com/tdunning/t-digest/blob/main/docs/t-digest....

There is an open source Python implementation, although I haven’t used it and can’t vouch for its quality: https://github.com/CamDavidsonPilon/tdigest

> Very curious if anyone knows how to pull this off.

I work in this space (small/mid-size).

The good news is that there are several "obvious" ways to pull this off because an ERP is the culmination of everything a company needs and does. So almost anything you can imagine on the software is part of it.

The bad news, and the reason everyone wants a solution, is that is truly a big space, and then you need E.V.E.R.Y.T.H.I.N.G.

---

My take is to start from the bottom, and build a much better version of Access/FoxPro (https://tablam.org).

Any medium/big ERP end being a specialized computing platform that needs:

- A programming language

- A database engine

- An orchestration engine

- ELT engine

- Auth

- UI/Report builders

And to be clear: NONE of the "programming language", "database engine", etc are a good fit today.

NONE.

This is the big thing, This is the reason (from a tech POW only) that most attempts fail.

This is the secret of why Cobol rule(d): Is all of this! but is too old! (also, this is why SQL still is best: Is almost this).

---

So, to pull this off, you need a team that knows what is "missing" from our current tools, makes a well-integrated package, and adds a "user-friendly" interface in a way that is palatable for the kind of user that uses excel (powerfully).

Is not that impossible. FoxPro was the best example of this kind of integrated solution.

P.D: This is my life's dream, to make this truth!

SEEKING VOLUNTEERS: TablaM relational language (https://tablam.org)

TablaM is an in-progress programming language to provide a more ergonomic experience for building data-oriented applications.

This means that where most languages are focused on low-level details or engineering at large, TablaM is tailored with some small & big design decisions to make it enjoyable to write applications for e-commerce, finance, ERPs, and similar.

Cool things:

- TablaM marry the array + relational models. It means we should get very little need for manual loops and all the ops are vectorized.

Yeah, I worked on https://tablam.org and https://spacetimedb.com.

It becomes pretty clear that `order` is a significant property to make useful (and performant!) programs. "Duplicates" is also required to make usefull programs.

One nonobvious reason for this: You wanna report that a `customer` has a duplicated key `1`. If you CAN'T model `[(customer.id = 1), (customer.id = 1)]` then you can't report errors! And `erroneous` data is VITAL to make useful programs because then the only possibility is "perfect" data, and that is not possible!

Another reason is that we want to `count` duplicates, to see `duplicates`, and other NON-obvious at first: "What is a duplicate?". Get fun with floats, Unicode, combining case and non-case sensitive input... and is obvious that for useful programs IS REQUIRED to support bags in an extended version of the relational model.

And yet...

IS very important to remember about `set semantics` and try to adhere to it when makes sense. Your query planner will like it. You "valid" constraints like it. And `unique index` like it. And so on...

Finally, for app development, I will "suggest" everyone use my lang https://tablam.org!

This is moe interesting than it looks, probably because the best part (IMHO) is about the type system, that is what enables the other ideas.

> In Julia, types are first-class and every value has a type

This is what I do from the start in https://tablam.org and only later found that is not common! Is so intuitive this way and simpler to check, by a lot. In fact, I waste so much time adapting type inference algorithms that are hard to translate because for some reason graphs are imposed on trees, types are second-class and live at a distance (and erased) and all is a mess this way.

The relational model already makes this so simple: `project / rename / extend` relational operators cover you.

From this other facilities become possible. Note how in `SQL` you don't have functions as first-class per se, but now try to imagine that a function is a table and suddenly, is much better!

My relational lang (https://tablam.org) that I wish to be a Excel + Access replacement is still half-backed.

I move it slowly in my personal computer but not much in public. Maybe adding another person will help me on that!

> what is a good alternative to Access (or Fox, I add)

Nothing.

Access is(was) in fact a worse alternative to Fox:

- Much worse DB engine, and that is saying a lot (FoxPro db can and get corrupted. A typical functionality that was added to any fox codebase was a utility to fix it)

- MUCH MUCH worse programming language (VB) that is neither good as-is, much less as a data-programing language.

Fox/dbase is the only data-oriented language that was relatively popular and fit for the use-case.

This is by a mile the main point: Is a desert looking for languages that are made for business app/data oriented programing (and much harder looking for something not weird).

The main options: Fox/dBase/Informix(? not remember), kdb+, Cobol, SQL(when extended as store procedure lang with loops and that)

--

This point is big. Having a good form builder (that is already rare) is not enough to be a real contender for this space. You need a language where making queries is truly nice.

In short, you need a language that is `LINQ/Relational` as first-class end-to-end.

- If this lang needs an ORM: FAIL.

- If this lang needs to compose strings to make a query: FAIL.

- If exist "impedance mismatch" between data manipulation/queries and the rest of the lang: FAIL.

- It should also support super-advanced types like date, decimal, currency and ideally dimensional units. Ideally algebraic types as today.

- It should have a version of Rust `serve, Into/From` for easy conversion between data + formats.

- It should look "normal" like python/swift with `LINQ` queries.

This is the lang I trying to build: https://tablam.org

> I asked was about querying data without ever using a SQL language, like tapping directly into the data.

I agree (making https://tablam.org to try a fix & working on https://github.com/clockworklabs/SpacetimeDB in the SQL conformance).

Before I think SQL was bad. *Now I'm certain*. SQL is absurdly massive for things that could have collapse all the features 10x or more.

However, working in an RDBM now I also understand why is not desirable to make "raw" calls to the DB: The engine MUST mediate all the calls to make things works (from query optimization, execution, iteration, lock management, transaction management, etc).

Is incredible how much sophistication is in a simple `SELECT * FROM table`.

What I wish is to build a `Wasm-like` IR so that is what anybody target, and `SQL` is not the mediator.

In my case each lang I have learned (+12) I start coding a mini-ORM. I have done the same so many times, and that is a good way to learn from me. Also, I have to learn Rust building https://tablam.org.

It sounds puzzling, I start learning Rust with https://tablam.org and probably was making my life harder trying to do "advanced" stuff when not have any idea of what I was doing.