pluto | cli tool to help discover deprecated apiVersions | Continuous Deployment library

You could use a hash table and tranpose the results...

You can do :

We don't even need to map:

input:

This one should work for you

Demo

Each Neptune instance that you connect to has a pool of worker threads. That pool will be two times the number of vCPU on the instance. If you send the queries in a single threaded fashion you are only taking advantage of one worker thread. You can substantially increase the throughput rates by dividing the work across multiple tasks in your application. I often use the multithreading library but even using basic Python threads will likely help as these are IO bound tasks and so the threads will likely yield. I have added millions of vertices and edges using Python in this way. Without doing something like this you are not taking full advantage of the available resources on the instance. If you have the work already divided up into batches of 50, you can spread those batches across multiple threads. Matching up the number of client threads/tasks with two times the number of vCPU on the Neptune instance is a good place to start.

Ideally the threads will touch different parts of the graph to avoid concurrently trying to modify the same vertices and edges from concurrent threads.

The issue you have run into is that a has step cannot take an arbitrary traversal but a where step can. You just need to reformulate the has step as a where step. An arbitrary traversal inside a has step is treated as "true" if it returns any result. This is one of those Gremlin things that looks as if it should work but actually does not.

Here is a contrived example that shows the where...by pattern that should be helpful in your case.

The error message "Cannot convert Array{Any,2} to series data for plotting" points to the problem lying with the data you pass as y values, i.e. cols(1:cols) (the x values are shared between the series).

Given that its type is Any, some non-numbers appear to have sneaked in. Look at that matrix and see what non-numbers you find, I believe missing should be okay but if that is all you find use skipmissing() to get rid of them.

Firstly, note that if you use Julia v1.5+ then you don't need to make i a global (example below with current stable version v1.5.4):

This is covered in the Pluto FAQ:

How can I modify a variable in a different cell?

Variables can only be assigned and modified in a single cell. This is what makes reactivity possible

https://github.com/fonsp/Pluto.jl/wiki/%E2%9A%A1-Writing-and-running-code

If you are used to a different workflow from python, consider using jupyter Notebooks via IJulia.