ignite | Visualize current global twitter activity using Play | Data Visualization library

I've got a normal igx-grid where the rows are all editable. However, the first row should never be editable. How do I handle that? Also, in the code-snippet below, can you tell me what I've done wrong with the last column? I just want a trash can icon to show up there, but the cell is blank.

In ignite, how can I control on which node cache is created? If I need to guarantee one cache is created on all nodes, how can I do that?

Will following codes create cache on all nodes or just some of them?

When the camera opens a blank camera appears for a few seconds and it always gives the same below output and stops.

prediction: [{"className":"nematode, nematode worm, roundworm","probability":0.050750732421875},{"className":"matchstick","probability":0.043731689453125},{"className":"lighter, light, igniter, ignitor","probability":0.021453857421875}]

Any idea how I can make the real time prediction work? without getting a false prediction as above just for one time

Below is the Camera Screen code where the prediction should happen in real time camera feed when user scans a certain surrounding

I download an image by cURL on KOBO Collect server. The download is fine, however it overwrites the exif data in the image. I use Code Igniter 4.

I would like to get the exif data contained in the image before or after the download, with PHP or javascript. This data must be stored in my database (gps etc) My code :

I create a REST API with Rust and Rocket that works with swagger. Now I'm trying to consumes this API with React react-admin to be precise. Everything works OK until I need to call a list where the famous X-Total-Count problem appears, and I am not able to solve it, probably due to lack of experience with Rust.

This is the message "The X-Total-Count header is missing in the HTTP Response. The jsonServer Data Provider expects responses for lists of resources to contain this header with the total number of results to build the pagination. If you are using CORS, did you declare X-Total-Count in the Access-Control-Expose-Headers header"

This is my response header

I try to put Apache Arrow vector in Ignite, this is working fine when I turn off native persistence, but after I turn on native persistence, JVM is crashed every time. I create IntVector first then put it in Ignite:

There is a couple of confusing points in the documentation that make me struggle to understand how exactly distribution across the cluster happens in Orleans. Hence, the questions.

Question #1

Orleans claims to have a built-in distribution capabilities to distribute across multiple servers. To me it sounds that Orleans can act as a load balancer itself and can scale out automatically. Thus, if I deploy Orleans app to several servers, then service discovery and load management should happen automatically, correct?

In this case, why some docs and articles suggest using other tools, like Ocelot or Consul, as a single entry point to Orleans cluster?

Question #2

I would like to use simple but distributed in-memory storage across several servers, like Redis or Apache Ignite, and I would like to know if it's possible to use a simple grain as this kind of a data storage?

Let's say, one grain will store a collection of restaurants and some other grain will keep track of the last 1000 visitors for selected restaurant. Can I activate these 2 grains only once as a singleton collection, add or remove records to each collection, and use these 2 grains as in-memory storage evenly available to all nodes in the cluster? Also, if answer is yes, do I need to add locks to these collections or each grain always exists in a single thread?

I am following the instruction (https://github.com/huggingface/transfer-learning-conv-ai) to install conv-ai from huggingface, but I got stuck on the docker build step: docker build -t convai .

I am using Mac 10.15, python 3.8, increased Docker memory to 4G.

I have tried the following ways to solve the issue:

1. add numpy in requirements.txt
2. add RUN pip3 install --upgrade setuptools in Dockerfile
3. add --upgrade to RUN pip3 install -r /tmp/requirements.txt in Dockerfile
4. add RUN pip3 install numpy before RUN pip3 install -r /tmp/requirements.txt in Dockerfile
5. add RUN apt-get install python3-numpy before RUN pip3 install -r /tmp/requirements.txt in Dockerfile
6. using python 3.6.13 because of this post, but it has exact same error.
7. I am currently working on debugging inside the container by entering right before the RUN pip3 install requirements.txt

Can anyone help me on this? Thank you!!

The error:

I have two questions regarding how to set up Ignite in Kubernetes.

1. Do all nodes need to be in the same namespace? E.G. If I have a thick client and a server node, do both need to be in the same name space to form a cluster?

From my research I think the answer is yes they need to be in the same namespace but I have not found any definitive documentation

1. Do both the client and server nodes need to be running the TcpDiscoveryKubernetesIpFinder or can nodes use a mix of the TcpDiscoveryKubernetesIpFinder and the static IPfinder?

From my resaerch I am fairly confident that all nodes must be running with the TcpDiscoveryKubernetesIpFinder but again I have not found any definitive documentation.