Managed Service for Apache Spark on GKE allows you to execute Big Data applications using the
Managed Service for Apache Spark jobs
API on GKE clusters.
Use the Google Cloud console, Google Cloud CLI or the Managed Service for Apache Spark API
(HTTP request or Cloud Client Libraries) to create a Managed Service for Apache Spark on GKE virtual cluster
,
then submit a Spark, PySpark, SparkR, or Spark-SQL job to the Managed Service for Apache Spark
service.
Managed Service for Apache Spark on GKE supports Spark 3.5 versions .
How Managed Service for Apache Spark on GKE works
Managed Service for Apache Spark on GKE deploys Managed Service for Apache Spark virtualclusters on a GKE cluster. Unlike Managed Service for Apache Spark on Compute Engine clusters , Managed Service for Apache Spark on GKE virtual clusters do not include separate master and worker VMs. Instead, when you create a Managed Service for Apache Spark on GKE virtual cluster, Managed Service for Apache Spark on GKE creates node pools within a GKE cluster. Managed Service for Apache Spark on GKE jobs are run as pods on these node pools. The node pools and scheduling of pods on the node pools are managed by GKE.
