databricks-jobs
Use this skill proactively for ANY Databricks Jobs task - creating, listing, running, updating, or deleting jobs. Triggers include: (1) 'create a job' or 'new…
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Updated 11-05 00:16
Data & analytics
17,418 results
databricks-lakebase-autoscale
Patterns and best practices for using Lakebase Autoscaling (next-gen managed PostgreSQL) with autoscaling, branching, scale-to-zero, and instant restore.
databricks-lakebase-provisioned
Patterns and best practices for using Lakebase Provisioned (Databricks managed PostgreSQL) for OLTP workloads.
databricks-metric-views
Unity Catalog metric views: define, create, query, and manage governed business metrics in YAML. Use when building standardized KPIs, revenue metrics, order…
databricks-mlflow-evaluation
MLflow 3 GenAI agent evaluation. Use when writing mlflow.genai.evaluate() code, creating @scorer functions, using built-in scorers (Guidelines, Correctness,…
databricks-parsing
Parse documents (PDF, DOCX, PPTX, images) using ai_parse_document, or build custom RAG pipelines. Use when the user asks to parse documents or build a custom…
databricks-python-sdk
Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API. Use when working with databricks-sdk, databricks-connect, or…
databricks-spark-declarative-pipelines
Creates, configures, and updates Databricks Lakeflow Spark Declarative Pipelines (SDP/LDP) using serverless compute. Handles streaming tables, materialized…
databricks-spark-structured-streaming
Comprehensive guide to Spark Structured Streaming for production workloads. Use when building streaming pipelines, implementing real-time data processing,…
databricks-synthetic-data-gen
Generate realistic synthetic data using Spark + Faker (strongly recommended). Supports serverless execution, multiple output formats (Parquet/JSON/CSV/Delta),…
databricks-unity-catalog
Unity Catalog system tables and volumes. Use when querying system tables (audit, lineage, billing) or working with volume file operations (upload, download,…
databricks-unstructured-pdf-generation
Generate synthetic PDF documents for RAG and unstructured data use cases. Use when creating test PDFs, demo documents, or evaluation datasets for retrieval…
databricks-vector-search
Patterns for Databricks Vector Search: create endpoints and indexes, query with filters, manage embeddings. Use when building RAG applications, semantic…
databricks-zerobus-ingest
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…
querying-mlflow-metrics
Fetches aggregated trace metrics (token usage, latency, trace counts, quality evaluations) from MLflow tracking servers. Triggers on requests to show metrics,…
retrieving-mlflow-traces
Retrieves MLflow traces using CLI or Python API. Use when the user asks to get a trace by ID, find traces, filter traces by status/tags/metadata/execution…
databricks-demo-generator
Generate comprehensive specification files for building Databricks assets, demos or end 2 end projects. Use when users want to create a new demo, design a demo…
03-deduplication
Delta MERGE deduplication pattern for Gold layer to prevent duplicate source key errors. Use when merging from Silver to Gold tables where Silver may contain…
04-conformed-dimensions
Enterprise integration patterns for Gold layer dimensional models. Covers conformed dimensions, the enterprise data warehouse bus matrix, shrunken/rollup…
04-grain-validation
Pre-merge grain validation patterns for Gold layer fact tables. Use when creating fact table merge scripts to validate that DataFrame grain matches DDL PRIMARY…
05-erd-diagrams
Patterns for creating clean, professional Mermaid ERD diagrams for data modeling documentation. Use when documenting Gold layer data models, creating master…
05-schema-validation
Runtime schema validation patterns for Gold layer merge scripts. Use when creating merge scripts to ensure DataFrame columns match target DDL schemas, validate…
adhoc-exploration-notebooks
Create dual-format ad-hoc exploration notebooks for Databricks workspace (.py) and local Jupyter (.ipynb) with Databricks Connect. Use when building data…
bronze-layer-setup
End-to-end Bronze layer creation for testing and demos. Creates table DDLs, generates fake data with Faker, copies from existing sources, and configures Asset…