You can use no Spark model processing to deploy Kyvos through Query Engine or Kubernetes for Azure and GCP.
AWS: You can use no Spark model processing to deploy Kyvos through Query Engine.
Azure: For Kubernetes, Kyvos processes the semantic model using Azure’s managed service AKS (Azure Kubernetes Service). The Azure cluster is deployed via ARM templates. You can create a cluster without Spark or process the semantic model utilizing Spark Mode within ARM templates.
GCP: For Kubernetes, Kyvos processes 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:
Post deployment for all clouds (AWS, Azure and GCP)
After deploying Kyvos using no-Spark processing model, perform the following post deployment steps.
Add the kyvos.connection.readUsingCustomFS.jobs.internal=NONE property from the Kyvos connections page
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
Set the kyvos.process.datastore.properties property on Hadoop Connection properties and set the value as SET disabled_optimizers = 'join_order';SET memory_limit='40GB';SET threads TO 1;
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.