with Databricks and Filter?
Retrieve the output and metadata of a single task run. See the documentation
Run a job now and return the id of the triggered run. See the documentation
The Databricks API allows you to interact programmatically with Databricks services, enabling you to manage clusters, jobs, notebooks, and other resources within Databricks environments. Through Pipedream, you can leverage these APIs to create powerful automations and integrate with other apps for enhanced data processing, transformation, and analytics workflows. This unlocks possibilities like automating cluster management, dynamically running jobs based on external triggers, and orchestrating complex data pipelines with ease.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
databricks: {
type: "app",
app: "databricks",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://${this.databricks.$auth.domain}.cloud.databricks.com/api/2.0/clusters/list`,
headers: {
Authorization: `Bearer ${this.databricks.$auth.access_token}`,
},
})
},
})
The Filter API in Pipedream allows for real-time data processing within workflows. It's designed to evaluate data against predefined conditions, enabling workflows to branch or perform specific actions based on those conditions. This API is instrumental in creating efficient, targeted automations that respond dynamically to diverse datasets. Using the Filter API, you can refine streams of data, ensuring that subsequent steps in your Pipedream workflow only execute when the data meets your specified criteria. This cuts down on unnecessary processing and facilitates the creation of more intelligent, context-aware systems.
export default defineComponent({
async run({ steps, $ }) {
let condition = false
if (condition == false) {
$.flow.exit("Ending workflow early because the condition is false")
} else {
$.export("$summary", "Continuing workflow, since condition for ending was not met.")
}
},
})