workload | A library to run heavy task operations | File Utils library
kandi X-RAY | workload Summary
kandi X-RAY | workload Summary
A library to run heavy task operations.
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Top functions reviewed by kandi - BETA
- Computes the workload
- Compute the given workload
- Determines if the work should be executed
- Runs the job
- Proceeds the current distribution size
- Computes if this task should be re - scheduled
- Checks if the work should be rescheduled
- Adds the given workload to the supplier
- Executes action and checks if the given value supplier succeeds
- Creates a new workload thread
- Reschedule the task
- Performs test
- Test whether number of ticks should be incremented
- Test whether an AtomicLong is positive
- Run the work thread
workload Key Features
workload Examples and Code Snippets
Lines of Code : 42License : Permissive (MIT)
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org.apache.maven.plugins
maven-shade-plugin
3.2.4
package
shade
true
false
plugins {
id "com.github.johnrengelman.shadow" version "7.0.0"
}
repositories {
maven {
url "https://jitpack.io"
}
}
dependencies {
implementation("com.github.portlek:workload:${version}")
}
def non_max_suppression_padded(boxes,
scores,
max_output_size,
iou_threshold=0.5,
score_threshold=float('-inf'),
def combined_non_max_suppression(boxes,
scores,
max_output_size_per_class,
max_total_size,
iou_threshold=0.5,
def get_local_ip(self):
"""Return the local ip address of the Google Cloud VM the workload is running on."""
return _request_compute_metadata('instance/network-interfaces/0/ip') Community Discussions
Trending Discussions on workload
QUESTION
I have an EKS node group with 2 nodes for compute workloads. I use a taint on these nodes and tolerations in the deployment. I have a deployment with 2 replicas I want these two pods to be spread on these two nodes like one pod on each node.
I tried using:
...ANSWER
Answered 2021-Jun-13 at 12:51You can use DeamonSet instead of Deployment. A DaemonSet ensures that all (or some) Nodes run a copy of a Pod. As nodes are added to the cluster, Pods are added to them. As nodes are removed from the cluster, those Pods are garbage collected. Deleting a DaemonSet will clean up the Pods it created.
See documentation for Deamonset
QUESTION
I am trying to dynamically generate the following html table, as seen on the screenshot
I was able to manually create the table using dummy data, but my problem is that I am trying to combine multiple data sources in order to achieve this HTML table structure.
SEE STACKBLITZ for the full example.
The Data looks like this (focus on the activities field):
...ANSWER
Answered 2021-Jun-13 at 13:28Oh, if you can change your data structure please do.
QUESTION
I have deployed Azure Migrate appliance but it seems it can only connect to vCenter server and not a standalone ESXi host. The same seems to be the case with Azure Vmware Solutions by Cloud Simple. Are there any other simple ways of migrating workloads to Azure ?
...ANSWER
Answered 2021-Jun-15 at 07:37Azure at this time only supports Azure Migrate through a VCSA and not a standalone ESXi host.
QUESTION
As our forge viewer app sometimes needs to load large model, we are trying partial loading as mentioned here-
Now we are facing a strange problem. When we load a big element(single dbid) and try to rotate or zoom to the item, viewer displaying the item in a very strange way. It's like some parts of the item is cut down. Like this-
But the item should look like this -
It's not a problem for some other items of the same model. Could you please tell me what's going on here?
...ANSWER
Answered 2021-Jun-14 at 18:38I can see some heavy quantization artifacts...
This Looks like a 'large offset issue' bug.
Try shifting the model's global offset to the origin, like this article explains: Model aggregating in viewer - coordinate issue
QUESTION
I am getting {"code": "Too many requests", "message": "Request is denied due to throttling."} from ADX when I run some batch ADF pipelines. I have came across this document on workload group. I have a cluster where we did not configured work load groups. Now i assume all the queries will be managed by default workload group. I found that MaxConcurrentRequests property is 20. I have following doubts.
Does it mean that this is the maximum concurrent requests my cluster can handle?
If I create a rest API which provides data from ADX will it support only 20 requests at a given time?
How to find the maximum concurrent requests an ADX cluster can handle?
ANSWER
Answered 2021-Jun-14 at 14:37for understanding the reason your command is throttled, the key element in the error message is this: Capacity: 6, Origin: 'CapacityPolicy/Ingestion'.
this means - the number of concurrent ingestion operations your cluster can run is 6. this is calculated based on the cluster's ingestion capacity, which is part of the cluster's capacity policy.
it is impacted by the total number of cores/nodes the cluster has. Generally, you could:
- scale up/out in order to reach greater capacity, and/or
- reduce the parallelism of your ingestion commands, so that only up to 6 are being run concurrently, and/or
- add logic to the client application to retry on such throttling errors, after some backoff.
additional reference: Control commands throttling
QUESTION
I originally posted this question as an issue on the GitHub project for the AWS Load Balancer Controller here: https://github.com/kubernetes-sigs/aws-load-balancer-controller/issues/2069.
I'm seeing some odd behavior that I can't trace or explain when trying to get the loadBalacnerDnsName from an ALB created by the controller. I'm using v2.2.0 of the AWS Load Balancer Controller in a CDK project. The ingress that I deploy triggers the provisioning of an ALB, and that ALB can connect to my K8s workloads running in EKS.
Here's my problem: I'm trying to automate the creation of a Route53 A Record that points to the loadBalancerDnsName of the load balancer, but the loadBalancerDnsName that I get in my CDK script is not the same as the loadBalancerDnsName that shows up in the AWS console once my stack has finished deploying. The value in the console is correct and I can get a response from that URL. My CDK script outputs the value of the DnsName as a CfnOutput value, but that URL does not point to anything.
In CDK, I have tried to use KubernetesObjectValue to get the DNS name from the load balancer. This isn't working (see this related issue: https://github.com/aws/aws-cdk/issues/14933), so I'm trying to lookup the Load Balancer with CDK's .fromLookup and using a tag that I added through my ingress annotation:
ANSWER
Answered 2021-Jun-13 at 20:23I think that the answer is to use external-dns.
ExternalDNS allows you to control DNS records dynamically via Kubernetes resources in a DNS provider-agnostic way.
QUESTION
So over the past few weeks I have been testing out FirebaseAuth both for the web and Android and the experience has been mostly bad. I have tried to add as much information as I can to give you enough context.
My Goal
My EndGoal is to make a package to simplify FirebaseAuth in Flutter Basically, the StreamBuilder runs on the authStateChanges stream from FirebaseAuth, It gives a user immediately after signIn or when I reload the whole page (Flutter Web) but doesnt return a user during hot reload eventhough I know the user has been authenticated. It works again when i reload the webpage. This does not exist in Android and it works as expected. Its very frustrating, and i could use some help from anyone!
Flutter Doctor
...ANSWER
Answered 2021-Jun-03 at 12:01I just Found a Solution to this problem! Basically the FireFlutter Team had fixed a production level bug and inturn that exposed a flaw of the Dart SDK. As this was only a Development only bug (bug only during Hot Restart), it was not given importance.
In my Research I have found that the last version combination that supports StreamBuilder and Hot Restart is
firebase_auth: 0.20.1; firebase_core 0.7.0
firebase_auth: 1.1.0; firebase_core: 1.0.3
These are the only versions that It works properly on. Every subsequent version has the new upgrade that has exposed the bug.
The Solution is very Simple! Works for the latest version (1.2.0) of the firebase_auth and firebase_core plugins too!
Firstly Import Sharedpreferences
QUESTION
I am running a TPC-DS benchmark for Spark 3.0.1 in local mode and using sparkMeasure to get workload statistics. I have 16 total cores and SparkContext is available as
Spark context available as 'sc' (master = local[*], app id = local-1623251009819)
Q1. For local[*], driver and executors are created in a single JVM with 16 threads. Considering Spark's configuration which of the following will be true?
- 1 worker instance, 1 executor having 16 cores/threads
- 1 worker instance, 16 executors each having 1 core
For a particular query, sparkMeasure reports shuffle data as follows
shuffleRecordsRead => 183364403
shuffleTotalBlocksFetched => 52582
shuffleTotalBlocksFetched => 52582
shuffleLocalBlocksFetched => 52582
shuffleRemoteBlocksFetched => 0
shuffleTotalBytesRead => 1570948723 (1498.0 MB)
shuffleLocalBytesRead => 1570948723 (1498.0 MB)
shuffleRemoteBytesRead => 0 (0 Bytes)
shuffleRemoteBytesReadToDisk => 0 (0 Bytes)
shuffleBytesWritten => 1570948723 (1498.0 MB)
shuffleRecordsWritten => 183364480
Q2. Regardless of the query specifics, why is there data shuffling when everything is inside a single JVM?
...ANSWER
Answered 2021-Jun-11 at 05:56- executor is a jvm process when you use
local[*]you run Spark locally with as many worker threads as logical cores on your machine so : 1 executor and as many worker threads as logical cores. when you configureSPARK_WORKER_INSTANCES=5inspark-env.shand execute these commandsstart-master.shandstart-slave.sh spark://local:7077to bring up a standalone spark cluster in your local machine you have one master and 5 workers, if you want to send your application to this cluster you must configure application likeSparkSession.builder().appName("app").master("spark://localhost:7077")in this case you can't specify[*]or[2]for example. but when you specify master to belocal[*]a jvm process is created and master and all workers will be in that jvm process and after your application finished that jvm instance will be destroyed.local[*]andspark://localhost:7077are two separate things. - workers do their job using tasks and each task actually is a thread
i.e.
task = thread. workers have memory and they assign a memory partition to each task in order to they do their job such as reading a part of a dataset into its own memory partition or do a transformation on read data. when a task such as join needs other partitions, shuffle occurs regardless weather the job is ran in cluster or local. if you were in cluster there is a possibility that two tasks were in different machines so Network transmission will be added to other stuffs such as writing the result and then reading by another task. in local if task B needs the data in the partition of the task A, task A should write it down and then task B will read it to do its job
QUESTION
The Kubernetes StatefulSet RollingUpdate strategy deletes and recreates each Pod in order. I am interested in updating a StatefulSet by recreating a pod and then deleting the old Pod (note the reversal), one-by-one.
This is interesting to me because:
- There is no reduction in the number of Ready Pods. I understand this is how a normal Deployment update works too (i.e. a Pod is only deleted after the new Pod replacing it is Ready).
- More importantly, it allows me to perform application-specific live migration during my StatefulSet upgrade. I would like to "migrate" data from
(old) pod-ito(new) pod-ibefore(old) pod-iis terminated (I would implement this in(new) pod-ireadiness logic).
Is such an update strategy possible?
...ANSWER
Answered 2021-Jun-10 at 23:04No, because pods have specific names based on their ordinal (-0, -1, etc) and there can only be one pod at a time with a given name. Deployments and DaemonSets can burst for updates because their names are randomized so it doesn't matter what order you do things in.
QUESTION
I am implementing a Kubernetes based solution where I am autoscaling a deployment based on a dynamic metric. I am running this deployment with autoscaling capabilities against a workload for 15 minutes. During this time, pods of this deployment are created and deleted dynamically as a result of the deployment autoscaling decisions.
I am interested in saving (for later inspection) of the logs of each of the dynamically created (and potentially deleted) pods occuring in the course of the autoscaling experiment.
If the deployment has a label like app=myapp , can I run the below command to store all the logs of my deployment?
...ANSWER
Answered 2021-Jun-10 at 17:40Yes, by default GKE sends logs for all pods to Stackdriver and you can view/query them there.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install workload
You can use workload like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the workload component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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