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

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

To deploy Kyvos through Kubernetes (K8s) 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 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

To deploy Kyvos through Query Engine

• Azure:

• GCP:

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

After deploying Kyvos using no-Spark processing model, perform the following post deployment steps.

1. Add the kyvos.connection.readUsingCustomFS.jobs.internal=NONE property from the Kyvos connections page

2. Modify the values of the following properties in the advance properties of semantic model job:

   • kyvos.process.compute.type=KYVOS_COMPUTE

   • kyvos.build.aggregate.type=TABULAR

3. Set the kyvos.process.datastore.propertiesproperty on Hadoop Connection properties and set the value as SET disabled_optimizers = 'join_order';SET memory_limit='40GB';SET threads TO 1;

4. Restart Kyvos services.

Changing Kyvos compute cluster mode

To change the Kyvos compute cluster mode, modify the value of the KYVOS_PROCESS_COMPUTE_SUBTYPE property through Kyvos Manager on the Kyvos Properties page.