Databricks
by Databricks, Inc.
Run notebooks, trigger jobs, execute SQL queries, and manage clusters on the Databricks Lakehouse platform
Sådan bruger agenter Databricks
- ✓Agent triggers a Databricks ETL notebook to process new data files and reports the outcome
- ✓Agent runs SQL queries against Delta Lake tables to retrieve business metrics for a report
- ✓Agent monitors job run status and retries failed jobs or sends alerts after consecutive failures
- ✓Agent starts a cluster, runs a data transformation job, and terminates the cluster to optimize costs
- ✓Agent queries aggregated analytics data from Databricks to answer natural language questions about business performance
Agenthandlinger
Input: notebookPath, clusterId, parameters, timeoutSeconds
Returnerer: runId, state, result, runPageUrl, durationMs
Input: jobId, notebookParams, pythonParams, jarParams
Returnerer: runId, numberInJob
Input: runId
Returnerer: state, result, startTime, endTime, runPageUrl
Input: sql, warehouseId, catalog, schema, rowLimit
Returnerer: rows, columns, rowCount, statementId
Input: limit, nameFilter
Returnerer: jobs, total
Returnerer: clusters
Input: clusterId
Returnerer: success
Input: jobId, limit, activeOnly
Returnerer: runs, hasMore
Eksempel på workflows
Scheduled ETL pipeline
Trigger a Databricks notebook to process daily data and wait for successful completion
Ad-hoc data query
Run SQL against Delta Lake tables in Unity Catalog to answer data questions on demand
Om Databricks
- Leverandør
- Databricks, Inc.
- Pris Tjek altid detaljer med udbyderen
- Betalt — Usage-based pricing on DBUs (Databricks Units). Community edition available. AWS/Azure/GCP pricing varies.
- Godkendelse
- Bearer-token
- Hastighedsgrænse Tjek altid detaljer med udbyderen
- 200 anmodninger / minut
- Kompatible noder
- AgentResource
- Hjemmeside
- https://www.databricks.com
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