aggregates | An experiment of different aggregate implementations

I have a hyper table for exchange candle data set up using TimescaleDB.

• TimescaleDB official image timescale/timescaledb:latest-pg12 set up and running with Docker with the exact version string starting PostgreSQL 12.6 on x86_64-pc-linux-musl, compiled by gcc (Alpine 10.2.1_pre1) 10.2.1 20201203, 64-bit

• Python 3 client

• The table has 5 continuous aggregate views set up like here and around 15 colums

Running the following query is slow (count query generated with SQLAlchemy):

I have two dataframes: df1 and df2. I want to use aggregates to obtain the mean and std between the s_values in both dataframes and put those results in a new dataframe called new_df

in df1 =

When reading about CQRS it is often mentioned that the write model should not depend on any read model (assuming there is one write model and up to N read models). This makes a lot of sense, especially since read models usually only become eventually consistent with the write model. Also, we should be able to change or replace read models without breaking the write model.

However, read models might contain valuable information that is aggregated across many entities of the write model. These aggregations might even contain non-trivial business rules. One can easily imagine a business policy that evaluates a piece of information that a read model possesses, and in reaction to that changes one or many entities via the write model. But where should this policy be located/implemented? Isn't this critical business logic that tightly couples information coming from one particular read model with the write model?

When I want to implement said policy without coupling the write model to the read model, I can imagine the following strategy: Include a materialized view in the write model that gets updated synchronously whenever a relevant part of the involved entities changes (when using DDD, this could be done via domain events). However, this denormalizes the write model, and is effectively a special read model embedded in the write model itself.

I can imagine that DDD purists would say that such a policy should not exist, because it represents a business invariant/rule that encompasses multiple entities (a.k.a. aggregates). I could probably agree in theory, but in practice, I often encounter such requirements anyway.

Finally, my question is simply: How do you deal with requirements that change data in reaction to certain conditions whose evaluation requires a read model?

I am trying to use the .describe() method on df1 to obtain aggregates. The current index is year. I want to obtain these stats based on each statistics over the 3 year period in the index. I tried using stats_df = df1.groupby('statistics').descirbe().unstack(1)) but I don't get the result that I am looking for.

in df1 =

im trying to get only those products for whom no order exists, so each product has an order id, these audit tables were linked to orders, but those orders are now deleted, i need to locate those products with no orders.

I know when doing aggregates if the joining collection has no records its not returning anything as "docs", but how can i get it to return me docs == empty or null only..

I have two concatenated charts built on the same DF. The left one shows a density transform of one data column, the right one shows a scatter plot of aggregates of other data columns.

I would like to do an interval selection on the left side and filter transform the right side accordingly. No matter what I select, however, the right side loses all data points.

Can anyone see what I am doing wrong here?

I have data of devices and its latitudes, longitudes all stored as varchar in PostgreSQL. When my device isn't able to latch on to the GPS - the lat, long is stored in the table as '-1.0', '-1.0'. Here is how the table looks like:

I'm trying to calculate on per day basis, the GPS availability percentage. Which is, the ratio the number of times device had GPS (the lat, long was not -1.0, -1.0) to the total number of GPS pings sent throughout the day.

I made some effort on this:

If want to know on daily basis, how many times each device had GPS (lat, long were not -1.0, -1.0). This is the query:

I have data like so:

I'm trying to create an alternating About Us section where one member has their photo to the left and description on the right. The next member would have their description on the left and then their image to the right.

I tried using another template for the setup, but it doesn't line up quite well. The images that are aligned on the left are fine, but the text of the descriptions are a bit too close. The images that are aligned to the right don't go all the way to the end of the border. They float in the right-side area, but they don't take up the full width of the section.

Additionally, I'm trying to get it to format nicely on mobile where everything is centered (centered image with their descriptions following after). Right now, the descriptions look a bit squished in the center with big margins taking up space. Also, the images aligned to the right won't center correctly.

I don't think this is the best way to go about it, but any advice or guidance is appreciated!