cluster | Node.JS multi-core server manager with plugins support | Runtime Evironment library
kandi X-RAY | cluster Summary
kandi X-RAY | cluster Summary
Node.JS multi-core server manager with plugins support.
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Lines of Code : 174License : Non-SPDX (Apache License 2.0)
Copydef run(fn,
cluster_spec,
rpc_layer=None,
max_run_time=None,
return_output=False,
timeout=_DEFAULT_TIMEOUT_SEC,
args=None,
kwargs=None):
"""Run `fn` in multiple processes according to `cluster def connect_to_cluster(cluster_spec_or_resolver,
job_name="localhost",
task_index=0,
protocol=None,
make_master_device_default=True,
cl def ReportGenerator(
df: pd.DataFrame, ClusteringVariables: np.ndarray, FillMissingReport=None
) -> pd.DataFrame:
"""
Function generates easy-erading clustering report. It takes 2 arguments as an input:
DataFrame - dataframe wi Community Discussions
Trending Discussions on cluster
QUESTION
I have a two dimensional numpy arrays which describes a list of coordinates where something happens. There are two events on the scene and I would like to calculate where those two are. But I do have difficulties to distinguish those two since there isn't any good pattern from event to event.
Example:
...ANSWER
Answered 2021-Jun-15 at 13:53There are all manner of clustering algorithms and many are implemented in scikit-learn.cluster. They are well documented and the docs have nice examples, but the various algorithms have trade-offs which can take a while to figure out. For example if you have a general idea about how spaced the clusters are (reflected in the epsilon parameter) you can get good results with DBSCAN:
QUESTION
I am trying to run a simple parallel program on a SLURM cluster (4x raspberry Pi 3) but I have no success. I have been reading about it, but I just cannot get it to work. The problem is as follows:
I have a Python program named remove_duplicates_in_scraped_data.py. This program is executed on a single node (node=1xraspberry pi) and inside the program there is a multiprocessing loop section that looks something like:
...ANSWER
Answered 2021-Jun-15 at 06:17Pythons multiprocessing package is limited to shared memory parallelization. It spawns new processes that all have access to the main memory of a single machine.
You cannot simply scale out such a software onto multiple nodes. As the different machines do not have a shared memory that they can access.
To run your program on multiple nodes at once, you should have a look into MPI (Message Passing Interface). There is also a python package for that.
Depending on your task, it may also be suitable to run the program 4 times (so one job per node) and have it work on a subset of the data. It is often the simpler approach, but not always possible.
QUESTION
This probably ins't typical setup, but due to higher decisions we endup having multiple kafka clusters within one app, multiple topics per each, and each might have different serializing strategy. Json/avro. And avro might be with confluent schema registry or using single object encoding.
Well I got it working somehow, by building my own abstractions and registry which analyzes the configuration and creates most of stuff manually, but I feel I needed to repeat stuff like topic names, schema registry url on several places multiple times just to create all needed beans. Ugly as hell.
I'd like to ask, if there is some better way and support for this I just might have overlooked.
I need to create N representations of kafka clusters, configuring it once. Configure topics respective to given kafka cluster, configure confluent schema registry for topics where applicable etc, so that I can create instance of Avro schema file, send it to KafkaTemplate and it will work.
...ANSWER
Answered 2021-Jun-15 at 13:28It depends on the complexity and how much different the configurations are, as to whether this will help, but you can override individual Kafka properties (such as bootstrap servers, deserializers, etc on the @KafkaListener and in each KafkaTemplate.
e.g.
QUESTION
Why kubectl cluster-info is running on control plane and not master node And on the control plane it is running on a specific IP Address https://192.168.49.2:8443 and not not localhost or 127.0.0.1 Running the following command in terminal:
- minikube start --driver=docker
😄 minikube v1.20.0 on Ubuntu 16.04 ✨ Using the docker driver based on user configuration 🎉 minikube 1.21.0 is available! Download it: https://github.com/kubernetes/minikube/releases/tag/v1.21.0 💡 To disable this notice, run: 'minikube config set WantUpdateNotification false'
👍 Starting control plane node minikube in cluster minikube 🚜 Pulling base image ... > gcr.io/k8s-minikube/kicbase...: 358.10 MiB / 358.10 MiB 100.00% 797.51 K ❗ minikube was unable to download gcr.io/k8s-minikube/kicbase:v0.0.22, but successfully downloaded kicbase/stable:v0.0.22 as a fallback image 🔥 Creating docker container (CPUs=2, Memory=2200MB) ... 🐳 Preparing Kubernetes v1.20.2 on Docker 20.10.6 ... ▪ Generating certificates and keys ... ▪ Booting up control plane ... ▪ Configuring RBAC rules ... 🔎 Verifying Kubernetes components... ▪ Using image gcr.io/k8s-minikube/storage-provisioner:v5 🌟 Enabled addons: storage-provisioner, default-storageclass 🏄 Done! kubectl is now configured to use "minikube" cluster and "default" namespace by default
- kubectl cluster-info
Kubernetes control plane is running at https://192.168.49.2:8443 KubeDNS is running at https://192.168.49.2:8443/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy
...To further debug and diagnose cluster problems, use 'kubectl cluster-info dump'.
ANSWER
Answered 2021-Jun-15 at 12:59The Kubernetes project is making an effort to move away from wording that can be considered offensive, with one concrete recommendation being renaming master to control-plane. In other words control-plane and master mean essentially the same thing, and the goal is to switch the terminology to use control-plane exclusively going forward. (More info in this answer)
The kubectl command is a command line interface that executes on a client (i.e your computer) and interacts with the cluster through the control-plane.
The IP address you are seing through cluster-info is the IP address through which you reach the control-plane
QUESTION
I am trying to install jenkins on my kubernetes cluster under jenkins namespace. When I deploy my pv and pvc, the pv remains available and does not bind to my pvc.
Here is my yamls:
...ANSWER
Answered 2021-Jun-15 at 09:52Based on the storage class spec, I think the problem is the volumeBindingMode being set as WaitForFirstConsumer which means the PV will remain unbound until there is a Pod to consume it.
You can change it Immediate to allow the PV to be bound immediately without requiring to create a Pod.
You can read about the different volume binding modes in detail in the docs.
QUESTION
We are using stream ingestion from Event Hubs to Azure Data Explorer. The Documentation states the following:
The streaming ingestion operation completes in under 10 seconds, and your data is immediately available for query after completion.
I am also aware of the limitations such as
Streaming ingestion performance and capacity scales with increased VM and cluster sizes. The number of concurrent ingestion requests is limited to six per core. For example, for 16 core SKUs, such as D14 and L16, the maximal supported load is 96 concurrent ingestion requests. For two core SKUs, such as D11, the maximal supported load is 12 concurrent ingestion requests.
But we are currently experiencing ingestion latency of 5 minutes (as shown on the Azure Metrics) and see that data is actually available for quering 10 minutes after ingestion.
Our Dev Environment is the cheapest SKU Dev(No SLA)_Standard_D11_v2 but given that we only ingest ~5000 Events per day (per metric "Events Received") in this environment this latency is very high and not usable in the streaming scenario where we need to have the data available < 1 minute for queries.
Is this the latency we have to expect from the Dev Environment or are the any tweaks we can apply in order to achieve lower latency also in those environments? How will latency behave with a production environment loke Standard_D12_v2? Do we have to expect those high numbers there as well or is there a fundamental difference in behavior between Dev/test and Production Environments in this concern?
...ANSWER
Answered 2021-Jun-15 at 08:34Did you follow the two steps needed to enable the streaming ingestion for the specific table, i.e. enabling streaming ingestion on the cluster and on the table?
In general, this is not expected, the Dev/Test cluster should exhibit the same behavior as the production cluster with the expected limitations around the size and scale of the operations, if you test it with a few events and see the same latency it means that something is wrong.
If you did follow these steps, and it still does not work please open a support ticket.
QUESTION
I am currently setting up a Kubernetes cluster but I noticed there are no default storage classes defined.
...ANSWER
Answered 2021-Jun-14 at 18:34You need to create the StorageClass object -
QUESTION
I have a list whose elements are integers and I would like to accumulate these elements if only they share at least one value. With regard to those elements that don't share any values with the rest I would like them to stay as they are. Here is my sample date:
...ANSWER
Answered 2021-Jun-15 at 05:23I suspect there's a set covering solution to be had, but in the interim here's a graph approach:
First, let's convert the integer vectors to an edge list so it can be made into a graph. We can use expand.grid.
QUESTION
What is the right way to put the input box just below the label, not in line with it? I am trying to do this for more than 4 hours but could not able to do it.
The product-related duration label and the input are perfect and which is what I wanted but it happened luckily because the text is large. How can I do the same with others? I tried some other methods like adding empty spaces or ClassName="form-control" and a bunch of others but nothing working properly, it makes the form too big.
The code that I am using -
...ANSWER
Answered 2021-Jun-15 at 04:07If the .form-control style does not work for you, then you could simply add .w-100 to the labels. This should have the same effect as your wider label causing the input to wrap.
QUESTION
I am reading an excel file and the parsing some data which i need to dump to the text file.
I want to create a text file in a certain format and write that into a text file.
I dont know if we can do that as an input like df[df['Storage Site'].str.contains(input('Please Enter SiteName: '))]
ANSWER
Answered 2021-Jun-15 at 04:40I think you are almost close, you Just need to add the variable name's into print statement for your desired output linke below:
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