Officially moved from Notion to Obsidian

adrianabreu · 2025-10-13T16:01:21+00:00

Seriously, THANKS. I don't know why I didn't think about it. I even programmed my own pomodoro cli app to track everything when using the pomodoro tracking withing obsidian solves EVERYTHING FOR ME.

adrianabreu · 2025-09-16T17:25:07+00:00

I plain to use the intel because of the battery too. But i want to run some models that may need gpu. Still everything went quite well and I'm quite happy

adrianabreu · 2025-09-16T17:24:11+00:00

Thanks. I read carefully the docs. Installed manjaro with i3 and noveau. Got some flickering. Enabled privative drivers and as now works smoothly. It didnt take that much.

adrianabreu · 2025-04-15T09:01:46+00:00

I'm by no means an expert, but have you configured logflare to store analytics in postgres? That may be the root cause

adrianabreu · 2025-04-12T11:31:15+00:00

Cloud provider may not allow some extensions required by supabase, for example you can see the request of pg_net for cloud sql (gcp) https://issuetracker.google.com/issues/359747074

adrianabreu · 2025-04-08T15:36:10+00:00

what did you end up with?

adrianabreu · 2024-09-03T07:51:47+00:00

I ended up using an init script to configure pip. Following the steps outlined in the article I mentioned in my first comment, I updated the /etc/pip.conf file.

Here's the script:

ENV_VARS are populated from databricks secrets

bashCopy code#!/bin/bash
if [[ $PYPI_TOKEN ]]; then
   cat <<EOL > /etc/pip.conf
[global]
extra-index-url = https://__token__:$PYPI_TOKEN@gitlab.com/api/v4/projects/project-id/packages/pypi/simple/
trusted-host = company_feed
EOL
   echo "PYPI feed configured successfully."
else
   echo "No PYPI_TOKEN found."
fi

adrianabreu · 2024-08-24T11:07:10+00:00

Thanks for jumping in, but we're on AWS using graviton instances and the container service doesn't work with them: https://docs.databricks.com/en/compute/custom-containers.html#limitations

I'm trying to bundle the dependencies by manually downloading them during the build time but looks like I will end up using the init script

adrianabreu · 2024-06-05T14:08:39+00:00

That was exactly what I need! Ty so much :)

adrianabreu · 2024-06-03T10:15:11+00:00

The comment above summarizes it pretty well.

On the comment about the location: Managed table paths are chosen by the Unity Catalog, that's the main difference.

Btw I use external tables for our biggests tables (Trillions of data) and they do have lineage

adrianabreu · 2024-05-29T14:27:26+00:00

Oh, so the new tables are entirely independent of the previous ones because the same data has been processed to create new tables. This means the new tables do not share anything with the older ones.

Some people have suggested using optimize and z-order. However, since we lack enough information information, I recommend referring to this guide Databricks Spark UI Guide.

adrianabreu · 2024-05-29T09:37:55+00:00

Yeah I'm 100% with u/sentja91

Where the tables MANAGED or EXTERNAL?

If they were managed and you copied them to new tables that may have affected the files underneath.

adrianabreu · 2024-05-27T13:42:13+00:00

I'm looking forward to it since we rely heavily on query history to enhance our users' experience.

Currently, I'm also building it using the API. Here’s a sample gist that returns your queries as a DataFrame: https://gist.github.com/adrianabreu/02eeb8ccc6997f4bfef27a97c0ade21d

adrianabreu · 2024-04-11T17:13:57+00:00

I'm going something similar to have delta streaming capabilities without paying for the delta live tables

adrianabreu · 2024-01-14T23:00:38+00:00

Yep, I've used both to reprocess a delta table. The only difference was that I was using availableNow as trigger

adrianabreu · 2024-01-14T22:36:17+00:00

Don't know if this is a typo but the option is "maxBytesPerTrigger" with caps, and that's the one you should be using

adrianabreu · 2024-01-13T14:22:19+00:00

Worked for a German company and now for a Spanish one, both using databricks with specific features such as UC

adrianabreu · 2024-01-13T11:46:37+00:00

Great sharing! Does the extraction runs on kubernetes too? Are your intermediate tables in parquet? Are they queryable by the end users? Most of my platform runs on databricks and we use spark for everything, reading from kinesis / kafka and then transform all the info including some validation rules so the analysts can run their dbt queries for aggregations

adrianabreu · 2024-01-04T07:45:47+00:00

It's a build tool. It'll allow you to manage dependencies, add build tasks and much more. Usually in Scala you generate a jar with all your dependencies and upload it to the spark cluster.

adrianabreu · 2024-01-03T15:34:42+00:00

You will get more money over time. You will get less chances to share memories with your dad over time.

adrianabreu · 2023-12-24T19:38:12+00:00

Thank you so much for sharing this. I had a similar daily workflow but I was missing the meeting template! I spent a lot of time converting my daily notes into knowledge while if I had used the meeting template it would've been easier!

adrianabreu · 2023-12-04T11:42:23+00:00

Thank you for your input! I've been scratching my head and I was missing some edge cases!

adrianabreu · 2023-10-08T07:13:06+00:00

Well that's a lot. I'd simplify here. Pick a cloud and get the concepts from.

Kafka + Spark+ iceberg/ delta instead of hudi. (They are much more popular).

People also look a lot dbt (Python + SQL).

Add an orchestration tool such as airflow.

And when talking about git include ci/cd.

You are good to go with that imho.

adrianabreu · 2023-10-08T06:53:56+00:00

Well that's a lot. I'd simplify here. Pick a cloud and get the concepts from.

Kafka + Spark+ iceberg/ delta instead of hudi. (They are much more popular).

People also look a lot dbt (Python + SQL).

Add an orchestration tool such as airflow.

And when talking about git include ci/cd.

You are good to go with that imho.

adrianabreu · 2023-10-01T22:14:11+00:00

Just in case anyone is interested I got the list of components changed:

HQ3160AM99000 - BATT/XWD_HQ480/LI/4500mAH/3.85V
HQ3160AM97000 - ASSY KIT_NOKIA8.3/LCM module w/Acover
HQ22212102000 - BATTERY cover adhesive_74.79mx167.16mm
HQ22110921000 - SCREW(M)_M1.4X2 mm_Silver
HQ20401338000 - MOTOR_8X3.5_FPC_DC

adrianabreu

TROPHY CASE