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Results 1 - 7 of 7 for parallelization (0.12 seconds)
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.teamcity/src/main/kotlin/model/FunctionalTestBucketGenerator.kt
{ largeElement, factor -> List(factor) { SmallSubprojectBucket(largeElement.subProject, parallelization(factor)) } }, { list -> SmallSubprojectBucket(list.map { it.subProject }, parallelization(1)) }, testCoverage.expectedBucketNumber, MAX_PROJECT_NUMBER_IN_BUCKET, )Created: Wed Apr 01 11:36:16 GMT 2026 - Last Modified: Thu Apr 10 15:09:32 GMT 2025 - 7.3K bytes - Click Count (0) -
.teamcity/src/main/kotlin/configurations/FunctionalTest.kt
TeamCityParallelTests( methodJsonNode.get("numberOfBatches").asInt(), ) else -> throw IllegalArgumentException("Unknown parallelization method") } } } } class FunctionalTest( model: CIBuildModel, id: String, name: String, description: String, val testCoverage: TestCoverage,
Created: Wed Apr 01 11:36:16 GMT 2026 - Last Modified: Thu Oct 09 05:26:45 GMT 2025 - 5.3K bytes - Click Count (0) -
CONTRIBUTING.md
> even if you have Gradle or Develocity build caching enabled for the project. > The Gradle Build Tool repository is massive, and it will take ages to build on > a local machine without necessary parallelization and caching. > The full test suites are executed on the CI instance for multiple configurations, > and you can rely on it after doing initial sanity check and targeted local testing. ### Copyright and License
Created: Wed Apr 01 11:36:16 GMT 2026 - Last Modified: Fri Mar 27 18:43:39 GMT 2026 - 19.1K bytes - Click Count (0) -
docs/en/docs/deployment/docker.md
normally have **just one process** (e.g. a Uvicorn process running your FastAPI application). They would all be **identical containers**, running the same thing, but each with its own process, memory, etc. That way you would take advantage of **parallelization** in **different cores** of the CPU, or even in **different machines**. And the distributed container system with the **load balancer** would **distribute the requests** to each one of the containers with your app **in turns**. So,...
Created: Sun Apr 05 07:19:11 GMT 2026 - Last Modified: Thu Mar 05 18:13:19 GMT 2026 - 28.3K bytes - Click Count (1) -
CHANGELOG/CHANGELOG-1.3.md
* Google Compute Engine PD Detach fails if node no longer exists ([29358](https://github.com/kubernetes/kubernetes/issues/29358)) * Mounting (only 'default-token') volume takes a long time when creating a batch of pods (parallelization issue) ([28616](https://github.com/kubernetes/kubernetes/issues/28616)) * Error while tearing down pod, "device or resource busy" on service account secret ([28750](https://github.com/kubernetes/kubernetes/issues/28750))
Created: Fri Apr 03 09:05:14 GMT 2026 - Last Modified: Thu Dec 24 02:28:26 GMT 2020 - 84K bytes - Click Count (0) -
docs/fr/docs/deployment/docker.md
processus** (par ex. un processus Uvicorn exécutant votre application FastAPI). Ils seront tous des **conteneurs identiques**, exécutant la même chose, mais chacun avec son propre processus, sa mémoire, etc. De cette façon, vous profiterez de la **parallélisation** sur **différents cœurs** du CPU, voire sur **différentes machines**. Et le système de conteneurs distribués avec l'**équilibreur de charge** **distribuera les requêtes** à chacun des conteneurs exécutant votre application **à tour...
Created: Sun Apr 05 07:19:11 GMT 2026 - Last Modified: Thu Mar 19 18:37:13 GMT 2026 - 32.3K bytes - Click Count (0) -
docs/es/docs/deployment/docker.md
normalmente tendría **solo un proceso** (e.g., un proceso Uvicorn ejecutando tu aplicación FastAPI). Todos serían **contenedores idénticos**, ejecutando lo mismo, pero cada uno con su propio proceso, memoria, etc. De esa forma, aprovecharías la **paralelización** en **diferentes núcleos** de la CPU, o incluso en **diferentes máquinas**. Y el sistema de contenedores distribuido con el **load balancer** **distribuiría las requests** a cada uno de los contenedores con tu aplicación **en turnos**....
Created: Sun Apr 05 07:19:11 GMT 2026 - Last Modified: Thu Mar 19 18:15:55 GMT 2026 - 30.8K bytes - Click Count (0)