ingraph | declarative infrastructure graph DSL for AWS | Infrastructure Automation library

I would like to pass dynamic arrays to functions and receive user input. Currently I'm using the following code:

I have a structure with arrays of structures inside in C, and I need a copy of that in the GPU. For that I am writing a function that makes some cudaMalloc and cudaMemcpys of the variables in the struct from host to device.

A simple version (the real one has various structs and variables/arrays inside) of the struct is:

If I want to delete age from the JSON in first output. Is there a way to do that in one step, in other words, not invoking jq 2 times?

I develop a Scala project in IntelliJ IDEA (GitHub repository). The project is built with Gradle 4.3 and uses ScalaTest plus its latest Gradle plugin for testing (id 'com.github.maiflai.scalatest' version '0.19'). The version of the Scala plug-in is 2017.3.11.1

The project has two levels of hierarchy: the parent project at the root level and the subprojects as the children. The tests use input files that are located in the root level (e.g. the ./compiler/ dir's project uses files from the ./queries/ dir). Tests refer to the files with relative paths: for example, if the compiler uses query files, it refers to them as ../queries/query-file.ext.

With this setup, tests work fine from the command line when running ./gradlew test. However, when I run a new test form IntelliJ, the working directory is always set to the root level, which breaks the tests. (Of course, this can be fixed manually, but this has to be done for each test executed). Note that I imported the project to IntelliJ IDEA using the "Create separate module per source set" setting (because of issue SCL-12718, which is not yet fixed in stable - and I am unsure whether this will fix the problem).

Is there a way to fix or work around this? Updating the ScalaTest Gradle configuration to use the directory of the current subproject or reconfiguring IntelliJ to use the directory of the parent project would both work for me.

I use Spark Catalyst for representing the query plans for an openCypher query engine, ingraph. During the query planning process, I would like to convert from a certain logical plan (Plan1) to another logical plan (Plan2). (I try to keep the question simple, so I omitted some details here. The project is fully open-source, so if required, I am happy to provide more information on why this is necessary.)

The best approach I could find is to use transformDown recursively. Here is a small example that converts from Plan1Nodes to Plan2Nodes by replacing each OpA1 instance with OpA2 and each OpB1 instance with OpB2.