Databricks
Big data clusterdatabricks
Managed lakehouse platform running Spark compute clusters and jobs.
- Provider
- default
- Kind
- Big data cluster
- Category
- Compute
- Official docs
- https://docs.databricks.com/aws/en/compute/configure
| property | type | values | required | kind default | this component |
|---|---|---|---|---|---|
| accessMode | enum | auto | standard | dedicated | no | auto | inherited |
| autoscaling | boolean | — | no | false | ▸ false |
| computeType | enum | all-purpose | job | serverless | no | — | inherited |
| engine | enum | spark | hadoop | presto | flink | hpc | ray | dask | kubernetes-batch | no | — | ▸ spark |
| managed | boolean | — | no | false | ▸ true |
| mosaicAi | boolean | — | no | false | inherited |
| photon | boolean | — | no | true | inherited |
| runtimeVersion | string | — | no | — | inherited |
| singleNode | boolean | — | no | false | inherited |
| spotInstances | boolean | — | no | false | ▸ false |
| workerNodes | integer | — | no | — | inherited |
| zoneRedundant | boolean | — | no | — | inherited |
Every rule whose selector covers this component's kind or its category. Whether a rule fires depends on the design: its properties, its edges and its groups.
stateful-node-without-zone-redundancy
A stateful compute node pinned to exactly one availability zone disappears with that zone, and its state goes with it. Nodes inside a cell are exempt, because there the cell is deliberately single-zone and redundancy comes from the other cells.
- — all of these hold:
- — the node's `stateless` is false
- — the node sits inside exactly 1 availability-zone group
- — this does not hold:
- — the node sits inside at least one cell group
nodes:
- { id: "databricks", component: "databricks" }Elastic High Performance Computingalibaba-e-hpcE-MapReducealibaba-e-mapreduceAWS Clean Roomsaws-clean-roomsAmazon EMRaws-emrAmazon EMR Serverlessaws-emr-serverlessAWS Parallel Computing Serviceaws-pcsAmazon SageMaker HyperPodaws-sagemaker-hyperpodAzure CycleCloudazure-cyclecloudAzure Databricksazure-databricksAzure HDInsightazure-hdinsightArmadaarmadaGeneric big data clusterbig-data-clusterDaskdaskApache Hadoop YARNhadoop-yarnRayraySlurmslurmApache Spark clusterspark-clusterVolcanovolcanoCluster Directorgoogle-cluster-directorDataprocgoogle-dataprocManaged Service for Apache Spark (serverless)google-dataproc-serverlessIBM Analytics Engineibm-analytics-engineOCI AI Data Platformoci-ai-data-platformOCI Big Data Serviceoci-big-data-serviceOCI Data Flowoci-data-flow
# yaml-language-server: $schema=../../schema/component.schema.json # Databricks: managed lakehouse platform whose classic compute is a Spark cluster of driver and workers. # Defaults from "Compute" and "Configure compute": access mode Auto, multi-node, autoscaling and # spot instances off until enabled, Photon on from Databricks Runtime 9.1 LTS. mosaicAi says the workspace # uses Mosaic AI (Model Serving, Agent Framework, Vector Search, AutoML), Databricks' AI layer; off until stated. schemaVersion: "1" type: "component" id: "databricks" kind: "big-data-cluster" provider: "default" docs: "https://docs.databricks.com/aws/en/compute/configure" defaults: engine: "spark" autoscaling: false spotInstances: false managed: true properties: computeType: type: "enum" values: ["all-purpose", "job", "serverless"] accessMode: type: "enum" values: ["auto", "standard", "dedicated"] default: "auto" photon: type: "boolean" default: true singleNode: type: "boolean" default: false mosaicAi: type: "boolean" default: false