hash-db VS dbt-unit-testing

https://github.com/samsquire/hash-db

I need to combine the ideas in each of these projects into a cohesive solution.

I did some work on trying to implement the YATA algorithm, poorly.

From an SQL database implementation perspective, in my toy Python barebones SQL database that barely supports inner joins (https://github.com/samsquire/hash-db) I tested by testing on postgresql and seeing if my query with two joins produces the same results.

I ought to produce unit tests that prove that tuples from each join operation produces the correct dataset.

For a user perspective, I guess you could write some tooling that loads example data into a database and does an incremental join with each part of the join statement added.

I wrote a toy dynamodb, SQL, Cypher graph and document storage database engine in Python for the learning.

https://github.com/samsquire/hash-db

I am interested in database internals. Btrees come up with regard to designing database systems that are efficient to query on disk. Postgres uses them for its indexes. Radix trees are memory efficient tries which are useful for answering prefix queries. They're also called prefix trees. I use them to get a list of prefixes of a string. Useful for simple intellisense style forms or dynamodb style querying. I've also been studying LSM trees which are used in Leveldb and RocksDB.

I experiment with database technology in my experimental project hash-db https://github.com/samsquire/hash-db The code should be readable.

I need to change my search tree to be self balancing currently it grows to the left or right without balancing. I think I need to use tree rotation depending on which branch has the highest height.

If you use dbt for transformations Dbt Unit Testing (https://github.com/EqualExperts/dbt-unit-testing) is getting some attention (https://www.thoughtworks.com/radar/languages-and-frameworks?blipid=202304042)

dbt-unit-testing

We use this and take an example-based tests approach for any non-trivial tables: https://github.com/EqualExperts/dbt-unit-testing

> How do you test some SQL logic in isolation?

I do this using sql

1. Extracting an 'ephemeral model' to different model file

2. Mock out this model in upstream model in unit tests https://github.com/EqualExperts/dbt-unit-testing

3. Write unit tests for this model.

This is not different than regular software development in a language like java.

I would argue its even better better because unit tests are always in tabular format and pretty easy to understand. Java unit tests on other hand are never read by devs in practice.

I haven't done it yet but there are some popular blogs as well as a DBT package someone created.

> I really don’t understand the communities obsession with unwieldy tools like DBT.

It lets me write test first sql transforms. I never thought TDD sql would be possible. My sql is so much more readable with common logic extracted into ephmeral models. I practice same method to write clear code to write sql, eg: too many mocks = refactor into separate model ( class) .

I think DBT made this possible with refs that can be swapped out with mocks. This is the awesome library I am using https://github.com/EqualExperts/dbt-unit-testing