My Journey With Spark On Kubernetes... In Python (1/3)

• volcano

  2 3,744 9.1 Go

  A Cloud Native Batch System (Project under CNCF)

  

For our experiments, we will use Volcano which is a batch scheduler for Kubernetes, well-suited for scheduling Spark applications pods with a better efficiency than the default kube-scheduler. The main reason is that Volcano allows "group scheduling" or "gang scheduling": while the default scheduler of Kubernetes schedules containers one by one, Volcano ensures that a gang of related containers (here, the Spark driver and its executors) can be scheduled at the same time. If for any reason it is not possible to deploy all the containers in a gang, Volcano will not schedule that gang. This article explains in more detail the reasons for using Volcano.

• helm

  5 19,316 9.2 Go

  Discontinued The Kubernetes Package Manager [Moved to: https://github.com/helm/helm] (by kubernetes)

  

In this section, you use Helm to deploy the Kubernetes Operator for Apache Spark from the incubator Chart repository. Helm is a package manager you can use to configure and deploy Kubernetes apps.

• InfluxDB

  www.influxdata.com sponsored

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• spark-operator

  8 2,603 6.2 Go

  Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes.

  

In this section, you use Helm to deploy the Kubernetes Operator for Apache Spark from the incubator Chart repository. Helm is a package manager you can use to configure and deploy Kubernetes apps.

• charts

  28 15,373 2.1 Go

  Discontinued ⚠️(OBSOLETE) Curated applications for Kubernetes (by helm)

  

In this section, you use Helm to deploy the Kubernetes Operator for Apache Spark from the incubator Chart repository. Helm is a package manager you can use to configure and deploy Kubernetes apps.

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