You can use no Spark model processing to deploy Kyvos through Kubernetes for Azure and GCP.

For AWS, you can use no Spark model processing to deploy Kyvos through Query Engine or Kubernetes for AWS.

To Deploy Kyvos through Kubernetes on:

• Azure:

• GCP: For Kubernetes, Kyvos builds the semantic model using Google Cloud's managed service GKE (Google Kubernetes Engine). The GKE cluster is deployed through Google Deployment Manager scripts. Using the scripts, you can either select a No-Spark-based cluster or process the semantic model using Spark Mode. Currently, to proceed with a no-spark-based deployment mode, you must use a Dataproc cluster (either new or existing).
  For more details about how to deploy Kyvos on GCP using the no-Spark model, see the following section:

  • Prerequisites to deploy Kyvos using Kubernetes

  • Creating Kyvos Resources for GCP using Script

Post deployment for all clouds (AWS, Azure and GCP)

1. Set property in connections: Users must add the following property from the Kyvos connections page:

   kyvos.connection.readUsingCustomFS.jobs.internal=NONE

1. Set properties at Cube level: Users should modify the values of the following properties in the advance properties of Cube build:

   kyvos.process.compute.type=KYVOS_COMPUTE

   kyvos.build.aggregate.type=TABULAR

1. Set below property on Hadoop connection properties and restart kyvos services

Property - kyvos.process.datastore.properties

Value - SET disabled_optimizers = 'join_order';SET memory_limit='40GB';SET threads TO 1;

Note: For changing the Kyvos compute cluster mode, users must modify the value of

KYVOS_PROCESS_COMPUTE_SUBTYPE property on KM Kyvos Properties page