databricks-zerobus-ingest
Skill2 starsChanged 3 months agoNo licenceView on GitHub
Build Zerobus Ingest clients for near real-time data ingestion into Databricks Delta tables via gRPC. Use when creating producers that write directly to Unity Catalog tables without a message bus, working with the Zerobus Ingest SDK in Python/Java/Go/TypeScript/Rust, generating Protobuf schemas from UC tables, or implementing stream-based ingestion with ACK handling and retry logic.
- Installs packages
We split this skill into the rules it gives an agent
7 rules. 0 are common, 4 are distinctive, and 3 are very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Other versions3 projects use a version of this.
Word for word · 0
None found.
Edited · 1
- RobsonRogerio/LakehouseDatabricks★ 056% same
Wrote their own version · 2
- databricks/databricks-agent-skills★ 379same name
- databricks/devhub★ 29same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository35 other files it gives its agents.
- agent-evaluationSkill
- analyzing-mlflow-sessionSkill
- analyzing-mlflow-traceSkill
- databricks-agent-bricksSkill
- databricks-aibi-dashboardsSkill
- databricks-ai-functionsSkill
- databricks-apps-pythonSkill
- databricks-appsSkill
- databricks-bundlesSkill
- databricks-configSkill
- databricks-dbsqlSkill
- databricks-docsSkill
- databricks-genieSkill
- databricks-icebergSkill
- databricks-jobsSkill
- databricks-lakebase-autoscaleSkill
- databricks-lakebase-provisionedSkill
- databricks-lakebaseSkill
- databricks-metric-viewsSkill
- databricks-mlflow-evaluationSkill
- databricks-model-servingSkill
- databricks-python-sdkSkill
- databricks-coreSkill
- databricks-spark-declarative-pipelinesSkill
- databricks-spark-structured-streamingSkill
- databricks-synthetic-data-genSkill
- databricks-unity-catalogSkill
- databricks-unstructured-pdf-generationSkill
- databricks-vector-searchSkill
- instrumenting-with-mlflow-tracingSkill
- mlflow-onboardingSkill
- querying-mlflow-metricsSkill
- retrieving-mlflow-tracesSkill
- searching-mlflow-docsSkill
- spark-python-data-sourceSkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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