skills/azure-databricks/SKILL.md
Expert knowledge for Azure Databricks development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when working with Unity Catalog, Lakeflow pipelines, Lakebase/Postgres, AI/Model Serving, or SQL warehouses, and other Azure Databricks related development tasks. Not for Azure Synapse Analytics (use azure-synapse-analytics), Azure HDInsight (use azure-hdinsight), Azure Machine Learning (use azure-machine-learning), Azure Data Factory (use azure-data-factory).
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This skill provides expert guidance for Azure Databricks. Covers troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g.,
L35-L120), useread_filewith the specified lines. For categories with file links (e.g.,[security.md](security.md)), useread_fileon the linked reference file
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mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.| Category | Location | Description | |----------|----------|-------------| | Troubleshooting | L37-L158 | Diagnosing and fixing Databricks issues across compute, Spark, SQL, connectors, Lakeflow, AI/Model Serving, VS Code/CLI, and Unity Catalog, with error-specific guides and debugging workflows. | | Best Practices | L159-L356 | Best practices for Databricks compute, governance, Delta/Lakehouse design, streaming, Lakeflow, RAG/GenAI, ML/serving, BI, cost, security, and performance tuning across Azure Databricks. | | Decision Making | L357-L464 | Guides for architectural and migration decisions in Azure Databricks: choosing tiers, compute, SQL warehouses, pipelines, ML/LLM options, Unity Catalog, federation, and cost-optimized configurations. | | Architecture & Design Patterns | architecture-patterns.md | Architectural blueprints and design patterns for Databricks: data/AI pipelines, agents, dashboards, networking, security, HA/DR, storage, streaming, and model deployment. | | Limits & Quotas | limits-quotas.md | Quotas, limits, and constraints for Databricks compute, AI/GenAI, Lakeflow connectors, SQL features, Lakebase/Postgres, dashboards, tokens, and resource usage, plus related scaling and governance. | | Security | security.md | Identity, access control, encryption, networking, compliance, and secrets guidance for securing Azure Databricks, Unity Catalog, Lakeflow, Lakebase, AI/BI, and external integrations. | | Configuration | configuration.md | Configuring and managing Azure Databricks and Unity Catalog: accounts, compute, networking, security, AI/ML, Lakeflow, connectors, SQL behavior, telemetry, and cost/usage monitoring. | | Integrations & Coding Patterns | integrations.md | Patterns and APIs for integrating Databricks with agents, AI/ML, streaming, external data systems, BI tools, SDKs, Terraform, Lakehouse Federation, and advanced SQL/PySpark functions. | | Deployment | deployment.md | Deploying and operating Azure Databricks workspaces, apps, agents, ML/LLM services, Lakeflow/Lakebase pipelines, and CI/CD/IaC automation across tools like CLI, PowerShell, GitHub, Azure DevOps, and Terraform. |
| Topic | URL | |-------|-----| | Troubleshoot Databricks Agent Evaluation issues | https://learn.microsoft.com/en-us/azure/databricks/agents/agent-evaluation/troubleshooting | | Debug custom AI agents on Databricks Apps and Model Serving | https://learn.microsoft.com/en-us/azure/databricks/agents/agent-framework/debug-agent | | Troubleshoot Azure Databricks compute startup issues | https://learn.microsoft.com/en-us/azure/databricks/compute/troubleshooting/ | | Troubleshoot Azure Databricks classic compute termination errors | https://learn.microsoft.com/en-us/azure/databricks/compute/troubleshooting/cluster-error-codes | | Debug Spark applications using Databricks Spark UI | https://learn.microsoft.com/en-us/azure/databricks/compute/troubleshooting/debugging-spark-ui | | Troubleshoot Unity Catalog file events for external locations | https://learn.microsoft.com/en-us/azure/databricks/connect/unity-catalog/cloud-storage/file-events-faq | | Troubleshoot common Databricks CLI issues | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/troubleshooting | | Diagnose and fix Databricks Connect Python issues | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/python/troubleshooting | | Diagnose and fix Databricks Connect Scala issues | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/scala/troubleshooting | | Troubleshoot common Databricks Terraform provider errors | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/terraform/troubleshoot | | Resolve common issues with Databricks VS Code extension | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/vscode-ext/faqs | | Troubleshoot Databricks VS Code extension errors | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/vscode-ext/troubleshooting | | Resolve ARITHMETIC_OVERFLOW errors in Databricks | https://learn.microsoft.com/en-us/azure/databricks/error-messages/arithmetic-overflow-error-class | | Handle CAST_INVALID_INPUT errors in Databricks | https://learn.microsoft.com/en-us/azure/databricks/error-messages/cast-invalid-input-error-class | | Diagnose DC_GA4_RAW_DATA_ERROR in GA4 connector | https://learn.microsoft.com/en-us/azure/databricks/error-messages/dc-ga4-raw-data-error-error-class | | Understand DC_SFDC_API_ERROR in Databricks connectors | https://learn.microsoft.com/en-us/azure/databricks/error-messages/dc-sfdc-api-error-error-class | | Diagnose DC_SQLSERVER_ERROR in SQL Server connector | https://learn.microsoft.com/en-us/azure/databricks/error-messages/dc-sqlserver-error-error-class | | Understand DELTA_ICEBERG_COMPAT_V1_VIOLATION errors | https://learn.microsoft.com/en-us/azure/databricks/error-messages/delta-iceberg-compat-v1-violation-error-class | | Resolve DIVIDE_BY_ZERO error in Azure Databricks SQL | https://learn.microsoft.com/en-us/azure/databricks/error-messages/divide-by-zero-error-class | | Handle Azure Databricks error conditions programmatically | https://learn.microsoft.com/en-us/azure/databricks/error-messages/error-classes | | Fix EWKB_PARSE_ERROR geometry parsing issues | https://learn.microsoft.com/en-us/azure/databricks/error-messages/ewkb-parse-error-error-class | | Fix EWKT_PARSE_ERROR geometry parsing issues | https://learn.microsoft.com/en-us/azure/databricks/error-messages/ewkt-parse-error-error-class | | Resolve GEOJSON_PARSE_ERROR in Databricks | https://learn.microsoft.com/en-us/azure/databricks/error-messages/geojson-parse-error-error-class | | Address GROUP_BY_AGGREGATE errors in Databricks SQL | https://learn.microsoft.com/en-us/azure/databricks/error-messages/group-by-aggregate-error-class | | Handle H3_INVALID_CELL_ID errors in Databricks | https://learn.microsoft.com/en-us/azure/databricks/error-messages/h3-invalid-cell-id-error-class | | Interpret and resolve H3_INVALID_GRID_DISTANCE_VALUE in Databricks | https://learn.microsoft.com/en-us/azure/databricks/error-messages/h3-invalid-grid-distance-value-error-class | | Handle H3_INVALID_RESOLUTION_VALUE errors in Databricks | https://learn.microsoft.com/en-us/azure/databricks/error-messages/h3-invalid-resolution-value-error-class | | Resolve H3_NOT_ENABLED errors and tier requirements | https://learn.microsoft.com/en-us/azure/databricks/error-messages/h3-not-enabled-error-class | | Fix INSUFFICIENT_TABLE_PROPERTY errors in Databricks | https://learn.microsoft.com/en-us/azure/databricks/error-messages/insufficient-table-property-error-class | | Troubleshoot INVALID_ARRAY_INDEX errors in Databricks SQL | https://learn.microsoft.com/en-us/azure/databricks/error-messages/invalid-array-index-error-class | | Troubleshoot INVALID_ARRAY_INDEX_IN_ELEMENT_AT in Databricks | https://learn.microsoft.com/en-us/azure/databricks/error-messages/invalid-array-index-in-element-at-error-class | | Resolve MISSING_AGGREGATION errors in Databricks queries | https://learn.microsoft.com/en-us/azure/databricks/error-messages/missing-aggregation-error-class | | Diagnose ROW_COLUMN_ACCESS errors for filters and masks | https://learn.microsoft.com/en-us/azure/databricks/error-messages/row-column-access-error-class | | Interpret Azure Databricks SQLSTATE error codes | https://learn.microsoft.com/en-us/azure/databricks/error-messages/sqlstates | | Fix TABLE_OR_VIEW_NOT_FOUND errors in Databricks | https://learn.microsoft.com/en-us/azure/databricks/error-messages/table-or-view-not-found-error-class | | Resolve UNRESOLVED_ROUTINE function resolution errors | https://learn.microsoft.com/en-us/azure/databricks/error-messages/unresolved-routine-error-class | | Understand UNSUPPORTED_TABLE_OPERATION errors in Databricks | https://learn.microsoft.com/en-us/azure/databricks/error-messages/unsupported-table-operation-error-class | | Understand UNSUPPORTED_VIEW_OPERATION errors in Databricks | https://learn.microsoft.com/en-us/azure/databricks/error-messages/unsupported-view-operation-error-class | | Troubleshoot WKB_PARSE_ERROR for geometry parsing | https://learn.microsoft.com/en-us/azure/databricks/error-messages/wkb-parse-error-error-class | | Troubleshoot WKT_PARSE_ERROR for geometry parsing | https://learn.microsoft.com/en-us/azure/databricks/error-messages/wkt-parse-error-error-class | | Troubleshoot common Genie Agent issues | https://learn.microsoft.com/en-us/azure/databricks/genie-agents/troubleshooting | | Monitor and troubleshoot Auto Loader ingestion pipelines | https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/auto-loader/observability | | Troubleshoot common Aha! connector errors in Lakeflow | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/aha-troubleshoot | | Troubleshoot Databricks Anthropic connector issues | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/anthropic-troubleshoot | | Resolve common Confluence connector ingestion issues | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/confluence-faq | | Troubleshoot authentication and rate limit errors for Confluence | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/confluence-troubleshoot | | Troubleshoot Dynamics 365 ingestion with Lakeflow Connect | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/d365-troubleshoot | | Resolve common Databricks Lakeflow managed connector issues | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/faq | | Troubleshoot Google Ads connector ingestion issues | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-ads-troubleshoot | | Troubleshoot Google Analytics raw data ingestion issues | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-analytics-troubleshoot | | Resolve common Databricks Google Drive connector issues | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-drive-faq | | Troubleshoot Databricks Google Drive ingestion failures | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-drive-troubleshoot | | Diagnose and fix HubSpot connector ingestion issues | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/hubspot-troubleshoot | | Resolve common Azure Databricks Jira connector issues | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/jira-faq | | Troubleshoot Jira Lakeflow ingestion errors | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/jira-troubleshoot | | Troubleshoot Databricks managed Kafka ingestion | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/kafka-troubleshoot | | Diagnose and fix Databricks Meta Ads ingestion issues | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/meta-ads-troubleshoot | | Troubleshoot Databricks Monday.com connector errors | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/monday-com-troubleshoot | | Diagnose and fix MySQL Lakeflow Connect ingestion | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/mysql-troubleshoot | | Troubleshoot Netskope Logs connector errors | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/netskope-logs-troubleshoot | | Troubleshoot common Outlook connector ingestion errors | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/outlook-troubleshoot | | Pendo connector FAQs for Databricks ingestion | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/pendo-faq | | Troubleshoot Databricks Pendo connector errors and failures | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/pendo-troubleshoot | | Troubleshoot PostgreSQL Lakeflow Connect ingestion issues | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/postgresql-troubleshoot | | Troubleshoot query-based connector cursor and errors | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/query-based-troubleshoot | | Troubleshoot Databricks RabbitMQ ingestion errors | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/rabbitmq-troubleshoot | | Troubleshoot Databricks Salesforce ingestion issues | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/salesforce-troubleshoot | | Diagnose and fix Databricks ServiceNow connector issues | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/servicenow-troubleshoot | | Troubleshoot Salesforce Marketing Cloud connector issues | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sfmc-troubleshoot | | Troubleshoot Microsoft SharePoint connector issues | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sharepoint-troubleshoot | | Troubleshoot Databricks Slack logs connector errors | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/slack-access-integration-logs-troubleshoot | | Troubleshoot Databricks Smartsheet connector errors | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/smartsheet-troubleshoot | | Answer common SQL Server Lakeflow Connect connector questions | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sql-server-faq | | Resolve SQL Server Lakeflow Connect ingestion problems | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sql-server-troubleshoot | | Use SQL Server utility script for Databricks ingestion | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sql-server-utility-reference | | Resolve common Square connector errors in Databricks | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/square-troubleshoot | | Troubleshoot common Strac connector errors in Databricks | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/strac-troubleshoot | | Troubleshoot TikTok Ads connector in Lakeflow | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/tiktok-ads-troubleshoot | | Diagnose and fix UNITY_CATALOG_INITIALIZATION_FAILED in Lakeflow | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/uc-initialization-troubleshoot | | Diagnose and fix common Veeva Vault connector errors | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/veeva-vault-troubleshoot | | Diagnose and fix Wiz Audit Logs connector errors | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/wiz-audit-logs-troubleshoot | | Troubleshoot Workday HCM connector in Lakeflow | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/workday-hcm-troubleshoot | | Diagnose and fix Databricks Workday connector issues | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/workday-reports-troubleshoot | | Diagnose and fix Zendesk Support connector errors | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/zendesk-support-troubleshoot | | Troubleshoot Databricks Zip connector errors | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/zip-troubleshoot | | Troubleshoot Zoho Books connector errors in Databricks | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/zoho-books-troubleshoot | | Troubleshoot common Zoom Logs connector errors | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/zoom-logs-troubleshoot | | Diagnose Zerobus Ingest API errors and handling | https://learn.microsoft.com/en-us/azure/databricks/ingestion/zerobus-errors | | Inspect logs for Databricks init script execution | https://learn.microsoft.com/en-us/azure/databricks/init-scripts/logs | | Test and validate Databricks ODBC driver connections | https://learn.microsoft.com/en-us/azure/databricks/integrations/odbc/testing | | Diagnose and improve Lakeflow Jobs performance | https://learn.microsoft.com/en-us/azure/databricks/jobs/diagnose-job-performance | | Troubleshoot and repair Azure Databricks job failures | https://learn.microsoft.com/en-us/azure/databricks/jobs/repair-job-failures | | Manage and debug Foundation Model Fine-tuning runs | https://learn.microsoft.com/en-us/azure/databricks/large-language-models/foundation-model-training/view-manage-runs | | Monitor and troubleshoot Databricks materialized views | https://learn.microsoft.com/en-us/azure/databricks/ldp/dbsql/materialized-monitor | | Monitor and troubleshoot Lakeflow pipelines | https://learn.microsoft.com/en-us/azure/databricks/ldp/observability | | Recover Lakeflow pipelines from checkpoint failures | https://learn.microsoft.com/en-us/azure/databricks/ldp/recover-streaming | | Migrate and troubleshoot Databricks AI Runtime GPU workloads | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/guides | | Troubleshoot Databricks Feature Store errors and limits | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/troubleshooting-and-limitations | | Debug common Databricks Model Serving endpoint issues | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/model-serving-debug | | Diagnose Databricks model serving with Genie Code | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/model-serving-genie-code | | Debug Databricks Model Serving timeout issues | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/model-serving-timeouts | | Resolve common OpenSharing data access errors | https://learn.microsoft.com/en-us/azure/databricks/opensharing/troubleshooting | | Troubleshoot failing Spark jobs and executors in Databricks | https://learn.microsoft.com/en-us/azure/databricks/optimizations/spark-ui-guide/failing-spark-jobs | | Use Databricks Spark jobs timeline for debugging | https://learn.microsoft.com/en-us/azure/databricks/optimizations/spark-ui-guide/jobs-timeline | | Diagnose long-running Spark stages in Databricks | https://learn.microsoft.com/en-us/azure/databricks/optimizations/spark-ui-guide/long-spark-stage | | Debug slow low-I/O Spark stages in Databricks | https://learn.microsoft.com/en-us/azure/databricks/optimizations/spark-ui-guide/slow-spark-stage-low-io | | Identify expensive reads in Spark DAG on Databricks | https://learn.microsoft.com/en-us/azure/databricks/optimizations/spark-ui-guide/spark-dag-expensive-read | | Diagnose gaps between Spark jobs in Databricks | https://learn.microsoft.com/en-us/azure/databricks/optimizations/spark-ui-guide/spark-job-gaps | | Diagnose and fix Spark memory issues on Databricks | https://learn.microsoft.com/en-us/azure/databricks/optimizations/spark-ui-guide/spark-memory-issues | | Troubleshoot Azure Databricks Partner Connect issues | https://learn.microsoft.com/en-us/azure/databricks/partner-connect/troubleshoot | | Retrieve exceptions from terminated StreamingQuery | https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/exception | | Debug streaming queries with explain plans | https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/explain | | Troubleshoot Databricks Git folder sync errors | https://learn.microsoft.com/en-us/azure/databricks/repos/errors-troubleshooting | | Detect and repair Delta table metadata and file issues | https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/delta-fsck | | Act on Databricks SQL query performance insights | https://learn.microsoft.com/en-us/azure/databricks/sql/user/queries/performance-insights | | Use Databricks SQL query history for troubleshooting | https://learn.microsoft.com/en-us/azure/databricks/sql/user/queries/query-history | | Troubleshoot Databricks SQL queries with profiles | https://learn.microsoft.com/en-us/azure/databricks/sql/user/queries/query-profile | | Inspect and debug Structured Streaming state on Databricks | https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/read-state |
| Topic | URL | |-------|-----| | Use default Databricks policy families to enforce compute best practices | https://learn.microsoft.com/en-us/azure/databricks/admin/clusters/policy-families | | Apply identity best practices in Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/admin/users-groups/best-practices | | Apply best practices to Azure Databricks serverless workspaces | https://learn.microsoft.com/en-us/azure/databricks/admin/workspace/serverless-workspaces-best-practices | | Apply Databricks best practices for MLflow 2 evaluation sets | https://learn.microsoft.com/en-us/azure/databricks/agents/agent-evaluation/evaluation-set | | Load test Databricks Apps agents for QPS limits | https://learn.microsoft.com/en-us/azure/databricks/agents/agent-framework/load-test-agent-app | | Measure RAG performance with retrieval and response metrics | https://learn.microsoft.com/en-us/azure/databricks/agents/tutorials/ai-cookbook/evaluate-assess-performance | | Define RAG application quality with evaluation sets | https://learn.microsoft.com/en-us/azure/databricks/agents/tutorials/ai-cookbook/evaluate-define-quality | | Evaluate and monitor RAG applications for quality, cost, latency | https://learn.microsoft.com/en-us/azure/databricks/agents/tutorials/ai-cookbook/fundamentals-evaluation-monitoring-rag | | Design and optimize RAG inference chains on Databricks | https://learn.microsoft.com/en-us/azure/databricks/agents/tutorials/ai-cookbook/fundamentals-inference-chain-rag | | Build and tune unstructured data pipelines for RAG | https://learn.microsoft.com/en-us/azure/databricks/agents/tutorials/ai-cookbook/quality-data-pipeline-rag | | Improve RAG application quality via key tuning knobs | https://learn.microsoft.com/en-us/azure/databricks/agents/tutorials/ai-cookbook/quality-overview | | Optimize RAG chain components for better responses | https://learn.microsoft.com/en-us/azure/databricks/agents/tutorials/ai-cookbook/quality-rag-chain | | Optimize Databricks AI Search performance and scaling | https://learn.microsoft.com/en-us/azure/databricks/ai-search/best-practices | | Load test Databricks AI Search endpoints for sizing | https://learn.microsoft.com/en-us/azure/databricks/ai-search/endpoint-load-test | | Apply Databricks AI Search filter expressions effectively | https://learn.microsoft.com/en-us/azure/databricks/ai-search/filtering-guide | | Apply Databricks AI Search retrieval best practices | https://learn.microsoft.com/en-us/azure/databricks/ai-search/retrieval-quality | | Evaluate Databricks AI Search retrieval strategies | https://learn.microsoft.com/en-us/azure/databricks/ai-search/retrieval-quality-eval | | Detect and clean up unused Databricks AI Search endpoints | https://learn.microsoft.com/en-us/azure/databricks/ai-search/unused-endpoints | | Migrate Databricks library installs from init scripts | https://learn.microsoft.com/en-us/azure/databricks/archive/compute/libraries-init-scripts | | Apply compute policy best practices in Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/archive/compute/policies-best-practices | | Use DBIO for transactional writes to cloud storage in Databricks | https://learn.microsoft.com/en-us/azure/databricks/archive/legacy/dbio-commit | | Optimize skewed joins in Databricks using skew hints | https://learn.microsoft.com/en-us/azure/databricks/archive/legacy/skew-join | | Migrate from Databricks Deep Learning Pipelines | https://learn.microsoft.com/en-us/azure/databricks/archive/spark-3.x-migration/deep-learning-pipelines | | Apply Azure Databricks administration best practices | https://learn.microsoft.com/en-us/azure/databricks/cheat-sheet/administration | | Optimize BI performance with Databricks SQL warehouses | https://learn.microsoft.com/en-us/azure/databricks/cheat-sheet/bi-serving | | Optimize BI performance with Databricks data preparation | https://learn.microsoft.com/en-us/azure/databricks/cheat-sheet/bi-serving-data-prep | | Configure Databricks SQL warehouses for optimal BI serving | https://learn.microsoft.com/en-us/azure/databricks/cheat-sheet/bi-serving-sql-serving | | Apply Azure Databricks compute creation best practices | https://learn.microsoft.com/en-us/azure/databricks/cheat-sheet/compute | | Implement Azure Databricks production job scheduling best practices | https://learn.microsoft.com/en-us/azure/databricks/cheat-sheet/jobs | | Apply Power BI performance best practices with Databricks | https://learn.microsoft.com/en-us/azure/databricks/cheat-sheet/power-bi | | Apply classic compute configuration best practices in Databricks | https://learn.microsoft.com/en-us/azure/databricks/compute/cluster-config-best-practices | | Use flexible node types for reliable Databricks compute | https://learn.microsoft.com/en-us/azure/databricks/compute/flexible-node-types | | Apply best practices for Databricks pools | https://learn.microsoft.com/en-us/azure/databricks/compute/pool-best-practices | | Use serverless compute effectively on Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/compute/serverless/best-practices | | Tune Databricks SQL warehouses for BI workloads | https://learn.microsoft.com/en-us/azure/databricks/compute/sql-warehouse/bi-workload-settings | | Control large interactive queries with Query Watchdog | https://learn.microsoft.com/en-us/azure/databricks/compute/troubleshooting/query-watchdog | | Optimize Azure Databricks dashboard caching and datasets | https://learn.microsoft.com/en-us/azure/databricks/dashboards/caching | | Apply Azure Databricks data engineering best practices | https://learn.microsoft.com/en-us/azure/databricks/data-engineering/best-practices | | Implement observability for Databricks jobs and pipelines | https://learn.microsoft.com/en-us/azure/databricks/data-engineering/observability-best-practices | | Handle schema evolution in Azure Databricks pipelines | https://learn.microsoft.com/en-us/azure/databricks/data-engineering/schema-evolution | | Best practices for Unity Catalog ABAC policies | https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/abac/best-practices | | Implement common ABAC row filtering and masking patterns | https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/abac/common-patterns | | Optimize performance of ABAC row and column policies | https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/abac/performance | | Understand ABAC policy evaluation behavior | https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/abac/policy-evaluation | | Apply Unity Catalog governance best practices in Databricks | https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/best-practices | | Manage Unity Catalog object storage lifecycle and recovery | https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/object-storage-lifecycle | | Work with legacy Hive metastore objects in Databricks | https://learn.microsoft.com/en-us/azure/databricks/database-objects/hive-metastore | | Follow DBFS root storage recommendations in Databricks | https://learn.microsoft.com/en-us/azure/databricks/dbfs/dbfs-root | | Apply DBFS and Unity Catalog usage best practices | https://learn.microsoft.com/en-us/azure/databricks/dbfs/unity-catalog | | Apply Delta Lake best practices on Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/delta/best-practices | | Handle Delta Lake limitations and risks on Amazon S3 | https://learn.microsoft.com/en-us/azure/databricks/delta/s3-limitations | | Use selective overwrite options in Delta Lake | https://learn.microsoft.com/en-us/azure/databricks/delta/selective-overwrite | | Apply MLOps Stack best practices with bundles | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/mlops-stacks | | Apply CI/CD workflow best practices on Databricks | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/ci-cd/flows | | Apply security and performance best practices for Databricks apps | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/best-practices | | Test Databricks Connect for Python code with pytest | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/python/testing | | Handle async queries and interruptions in Databricks Connect | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/queries | | Apply Databricks developer and CI/CD best practices | https://learn.microsoft.com/en-us/azure/databricks/developers/best-practices | | Explore Unity Catalog volumes and storage files in Databricks | https://learn.microsoft.com/en-us/azure/databricks/discover/files | | Choose between Databricks volumes and workspace files | https://learn.microsoft.com/en-us/azure/databricks/files/files-recommendations | | Curate effective Genie Agents for accuracy | https://learn.microsoft.com/en-us/azure/databricks/genie-agents/best-practices | | Apply prompt and context best practices in Genie Code | https://learn.microsoft.com/en-us/azure/databricks/genie-code/tips | | Apply Auto Loader best practices for reliable ingestion | https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/auto-loader/best-practices | | Optimize Databricks Auto Loader directory listing mode | https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/auto-loader/directory-listing-mode | | Configure Databricks Auto Loader for production workloads | https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/auto-loader/production | | Configure Auto Loader automatic type widening | https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/auto-loader/type-widening | | Apply common COPY INTO data loading patterns | https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/copy-into/examples | | Incrementally clone Parquet and Iceberg tables to Delta | https://learn.microsoft.com/en-us/azure/databricks/ingestion/data-migration/clone-parquet | | Use the Anthropic connector effectively in Lakeflow | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/anthropic-faq | | Apply Lakeflow Connect patterns for managed ingestion | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/common-patterns | | Query system.billing.usage to monitor Lakeflow costs | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/monitor-costs | | Apply Netskope Logs connector usage recommendations | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/netskope-logs-faq | | Maintain Databricks Lakeflow managed ingestion pipelines | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/pipeline-maintenance | | Maintain and operate PostgreSQL ingestion pipelines | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/postgresql-maintenance | | RabbitMQ connector behavioral FAQs and guidance | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/rabbitmq-faq | | Filter rows during Lakeflow Connect ingestion | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/row-filtering | | Optimize incremental ingestion of Salesforce formula fields | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/salesforce-formula-fields | | SharePoint connector FAQs and behavioral guidance | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sharepoint-faq | | Optimize Databricks smart closure for CDC pipelines | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/smart-closure | | Use Wiz Audit Logs connector effectively and safely | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/wiz-audit-logs-faq | | Apply Workday Reports connector FAQs and guidance | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/workday-reports-faq | | Query OpenTelemetry data ingested into Databricks Delta | https://learn.microsoft.com/en-us/azure/databricks/ingestion/opentelemetry/queries | | Use and configure init scripts on Azure Databricks clusters | https://learn.microsoft.com/en-us/azure/databricks/init-scripts/ | | Reference external files safely in Databricks init scripts | https://learn.microsoft.com/en-us/azure/databricks/init-scripts/referencing-files | | Implement recurring and backfill SQL jobs in Lakeflow | https://learn.microsoft.com/en-us/azure/databricks/jobs/how-to/create-recurring-job | | Drive Databricks For each jobs with control tables | https://learn.microsoft.com/en-us/azure/databricks/jobs/how-to/foreach-sql-lookup-tutorial | | Apply classic compute best practices for Databricks jobs | https://learn.microsoft.com/en-us/azure/databricks/jobs/run-classic-jobs | | Apply Databricks cost optimization best practices | https://learn.microsoft.com/en-us/azure/databricks/lakehouse-architecture/cost-optimization/best-practices | | Apply Databricks data and AI governance best practices | https://learn.microsoft.com/en-us/azure/databricks/lakehouse-architecture/data-governance/best-practices | | Design compute and workspace configuration for Databricks | https://learn.microsoft.com/en-us/azure/databricks/lakehouse-architecture/deployment-guide/compute | | Design observability and monitoring for Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/lakehouse-architecture/deployment-guide/observability | | Implement interoperability and usability best practices in Databricks | https://learn.microsoft.com/en-us/azure/databricks/lakehouse-architecture/interoperability-and-usability/best-practices | | Apply operational excellence best practices for Databricks | https://learn.microsoft.com/en-us/azure/databricks/lakehouse-architecture/operational-excellence/best-practices | | Optimize Databricks performance with efficiency best practices | https://learn.microsoft.com/en-us/azure/databricks/lakehouse-architecture/performance-efficiency/best-practices | | Use Databricks reliability best practices for resilient systems | https://learn.microsoft.com/en-us/azure/databricks/lakehouse-architecture/reliability/best-practices | | Implement Databricks security, compliance, and privacy best practices | https://learn.microsoft.com/en-us/azure/databricks/lakehouse-architecture/security-compliance-and-privacy/best-practices | | Classify documents with large label taxonomies in Databricks | https://learn.microsoft.com/en-us/azure/databricks/large-language-models/classify-documents-labels-tutorial | | Optimize Lakeflow clusters with enhanced and vertical autoscaling | https://learn.microsoft.com/en-us/azure/databricks/ldp/auto-scaling | | Best practices for designing Lakeflow pipelines | https://learn.microsoft.com/en-us/azure/databricks/ldp/best-practices | | Use REPLACE WHERE flows for targeted recomputes | https://learn.microsoft.com/en-us/azure/databricks/ldp/dbsql/flows-replace-where | | Handle compatibility issues with pipeline environment versions | https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/environment-version-compatibility | | Apply data quality expectations in pipelines | https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-expectations | | Apply advanced expectation patterns in Lakeflow | https://learn.microsoft.com/en-us/azure/databricks/ldp/expectation-patterns | | Reduce high initialization times in Lakeflow pipelines | https://learn.microsoft.com/en-us/azure/databricks/ldp/fix-high-init | | Infer and evolve JSON schemas with from_json in pipelines | https://learn.microsoft.com/en-us/azure/databricks/ldp/from-json-schema-evolution | | Run full refreshes on Lakeflow streaming tables safely | https://learn.microsoft.com/en-us/azure/databricks/ldp/full-refresh-st | | Optimize stateful streaming with watermarks in pipelines | https://learn.microsoft.com/en-us/azure/databricks/ldp/stateful-processing | | Implement CDC ETL pipelines with Lakeflow and Auto Loader | https://learn.microsoft.com/en-us/azure/databricks/ldp/tutorial-pipelines | | Build geospatial Lakeflow pipelines with native spatial types | https://learn.microsoft.com/en-us/azure/databricks/ldp/tutorial-spatial-pipelines | | Restart the Python process to refresh Databricks libraries | https://learn.microsoft.com/en-us/azure/databricks/libraries/restart-python-process | | Apply Hyperopt best practices on Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl-hyperparam-tuning/hyperopt-best-practices | | Implement point-in-time correct feature joins | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/time-series | | Benchmark Databricks LLM endpoints for performance | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/foundation-model-apis/prov-throughput-run-benchmark | | Apply Databricks batch model inference patterns | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-inference/ | | Validate models before Databricks serving deployment | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/model-serving-pre-deployment-validation | | Monitor Databricks model quality and endpoint health | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/monitor-diagnose-endpoints | | Optimize Databricks Model Serving endpoints for production | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/production-optimization | | Plan and execute load testing for Databricks serving endpoints | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/what-is-load-test | | Tune and autoscale Ray clusters on Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ray/scale-ray | | Apply deep learning best practices on Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/train-model/dl-best-practices | | Adapt Apache Spark workloads for Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/migration/spark | | Apply MLflow 3 best practices for GenAI observability | https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/ | | Align MLflow judges with human feedback | https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/align-judges | | Evaluate and compare MLflow prompt versions for GenAI | https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/prompt-version-mgmt/prompt-registry/evaluate-prompts | | Apply MLflow Tracing for GenAI observability | https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/ | | Use manual MLflow tracing for production GenAI apps | https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/app-instrumentation/manual-tracing/ | | Collect and log user feedback on GenAI traces with MLflow | https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/collect-user-feedback/ | | Analyze GenAI trace data using MLflow Trace SDK | https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/observe-with-traces/analyze-traces | | Implement PII redaction for OTel traces in Databricks | https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/redact-pii-otel-traces | | Apply software engineering practices to Databricks notebooks | https://learn.microsoft.com/en-us/azure/databricks/notebooks/best-practices | | Run Databricks notebooks safely and efficiently | https://learn.microsoft.com/en-us/azure/databricks/notebooks/run-notebook | | Apply unit testing patterns in Databricks notebooks | https://learn.microsoft.com/en-us/azure/databricks/notebooks/test-notebooks | | Optimize OpenSharing egress costs for data providers | https://learn.microsoft.com/en-us/azure/databricks/opensharing/manage-egress | | Apply performance optimization recommendations on Databricks | https://learn.microsoft.com/en-us/azure/databricks/optimizations/ | | Use adaptive query execution on Databricks | https://learn.microsoft.com/en-us/azure/databricks/optimizations/aqe | | Migrate away from deprecated Bloom filter indexes | https://learn.microsoft.com/en-us/azure/databricks/optimizations/bloom-filters | | Optimize Spark SQL queries with Databricks CBO | https://learn.microsoft.com/en-us/azure/databricks/optimizations/cbo | | Improve read performance with Databricks disk cache | https://learn.microsoft.com/en-us/azure/databricks/optimizations/disk-cache | | Improve Delta query performance with dynamic file pruning | https://learn.microsoft.com/en-us/azure/databricks/optimizations/dynamic-file-pruning | | Choose and configure Databricks Delta isolation levels | https://learn.microsoft.com/en-us/azure/databricks/optimizations/isolation/isolation-levels | | Use row-level concurrency for Delta tables on Databricks | https://learn.microsoft.com/en-us/azure/databricks/optimizations/isolation/row-level-concurrency | | Optimize Delta MERGE performance with low shuffle merge | https://learn.microsoft.com/en-us/azure/databricks/optimizations/low-shuffle-merge | | Use predictive I/O optimizations on Databricks | https://learn.microsoft.com/en-us/azure/databricks/optimizations/predictive-io | | Optimize Azure Databricks range join performance | https://learn.microsoft.com/en-us/azure/databricks/optimizations/range-join | | Diagnose Databricks Spark cost and performance in UI | https://learn.microsoft.com/en-us/azure/databricks/optimizations/spark-ui-guide/ | | Diagnose high I/O Spark stages using Databricks UI | https://learn.microsoft.com/en-us/azure/databricks/optimizations/spark-ui-guide/long-spark-stage-io | | Debug skew and spill in Databricks Spark stages | https://learn.microsoft.com/en-us/azure/databricks/optimizations/spark-ui-guide/long-spark-stage-page | | Handle Databricks spot instance losses effectively | https://learn.microsoft.com/en-us/azure/databricks/optimizations/spark-ui-guide/losing-spot-instances | | Resolve long Spark stages with a single task | https://learn.microsoft.com/en-us/azure/databricks/optimizations/spark-ui-guide/one-spark-task | | Optimize many small Spark jobs on Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/optimizations/spark-ui-guide/small-spark-jobs | | Mitigate overloaded Spark driver on Databricks | https://learn.microsoft.com/en-us/azure/databricks/optimizations/spark-ui-guide/spark-driver-overloaded | | Detect unnecessary data rewriting in Databricks Spark writes | https://learn.microsoft.com/en-us/azure/databricks/optimizations/spark-ui-guide/spark-rewriting-data | | Best practices for setting up Databricks Partner Connect | https://learn.microsoft.com/en-us/azure/databricks/partner-connect/best-practice | | Handle to_utc_timestamp semantics in Spark Databricks | https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/to_utc_timestamp | | Apply networking recommendations for Lakehouse Federation | https://learn.microsoft.com/en-us/azure/databricks/query-federation/networking | | Optimize performance of Lakehouse Federation queries | https://learn.microsoft.com/en-us/azure/databricks/query-federation/performance-recommendations | | Transform complex and nested data types in Databricks | https://learn.microsoft.com/en-us/azure/databricks/semi-structured/complex-types | | Use higher-order functions on arrays in Databricks SQL | https://learn.microsoft.com/en-us/azure/databricks/semi-structured/higher-order-functions | | Compare VARIANT and JSON string storage semantics | https://learn.microsoft.com/en-us/azure/databricks/semi-structured/variant-json-diff | | Convert Parquet tables to Delta Lake in Databricks | https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/delta-convert-to-delta | | Optimize Delta Lake table layout with Databricks OPTIMIZE | https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/delta-optimize | | Vacuum unused files from Delta and Spark tables | https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/delta-vacuum | | Apply partitioning and liquid clustering best practices in Databricks | https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-partition | | Use ANALYZE TABLE statistics for Databricks optimization | https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-analyze-compute-statistics | | Use Databricks SQL query hints for performance | https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-hints | | Use OFFSET and LIMIT safely for pagination in Databricks SQL | https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-offset | | Benchmark Databricks SQL warehouses with the TPC-DS dataset | https://learn.microsoft.com/en-us/azure/databricks/sql/tpcds-eval | | Author effective SQL patterns for Databricks alerts | https://learn.microsoft.com/en-us/azure/databricks/sql/user/alerts/query-patterns | | Optimize Databricks SQL queries with RELY constraints | https://learn.microsoft.com/en-us/azure/databricks/sql/user/queries/query-optimization-constraints | | Operate multiple Databricks streaming queries per cluster | https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/multiple-streams | | Run Databricks Structured Streaming in production | https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/production | | Optimize and monitor Databricks real-time streaming performance | https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/real-time/performance | | Optimize stateful Structured Streaming on Databricks | https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/stateful-streaming | | Optimize stateless Structured Streaming queries on Databricks | https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/stateless-streaming | | Monitor Structured Streaming queries on Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/stream-monitoring | | Tune Databricks Structured Streaming trigger intervals | https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/triggers | | Apply watermarks for stateful streaming on Databricks | https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/watermarks | | Use automatic upgrades for Unity Catalog tables | https://learn.microsoft.com/en-us/azure/databricks/tables/automatic-upgrades | | Optimize Databricks tables using liquid clustering | https://learn.microsoft.com/en-us/azure/databricks/tables/clustering | | Leverage data skipping on Databricks tables | https://learn.microsoft.com/en-us/azure/databricks/tables/data-skipping | | Optimize external table partition discovery in Unity Catalog | https://learn.microsoft.com/en-us/azure/databricks/tables/external-partition-discovery | | Optimize VARIANT queries with variant shredding | https://learn.microsoft.com/en-us/azure/databricks/tables/features/variant-shredding | | Use table history and time travel safely | https://learn.microsoft.com/en-us/azure/databricks/tables/history | | Optimize Delta and Iceberg table file layout | https://learn.microsoft.com/en-us/azure/databricks/tables/operations/optimize | | Use VACUUM to remove unused Delta files | https://learn.microsoft.com/en-us/azure/databricks/tables/operations/vacuum | | Interpret table size versus storage usage | https://learn.microsoft.com/en-us/azure/databricks/tables/size | | Tune Delta and Iceberg data file sizes | https://learn.microsoft.com/en-us/azure/databricks/tables/tune-file-size | | Design Delta Lake data models for Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/transform/data-modeling | | Apply join patterns for batch and streaming | https://learn.microsoft.com/en-us/azure/databricks/transform/join | | Optimize join performance in Azure Databricks workloads | https://learn.microsoft.com/en-us/azure/databricks/transform/optimize-joins | | Clean and validate data in Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/transform/validate | | Apply advanced modeling techniques in metric views | https://learn.microsoft.com/en-us/azure/databricks/uc-semantics/metric-views/advanced-techniques | | Use level of detail expressions in metric views | https://learn.microsoft.com/en-us/azure/databricks/uc-semantics/metric-views/level-of-detail | | Download internet data into Azure Databricks volumes | https://learn.microsoft.com/en-us/azure/databricks/volumes/download-internet-files |
| Topic | URL | |-------|-----| | Manage and change Azure Databricks subscription tier | https://learn.microsoft.com/en-us/azure/databricks/admin/account-settings/account | | Plan migration from Standard to Premium Databricks tier | https://learn.microsoft.com/en-us/azure/databricks/admin/account-settings/standard-tier | | Decide when to enable Mission Critical add-on for Databricks | https://learn.microsoft.com/en-us/azure/databricks/admin/mission-critical | | Decide when and how to use serverless Databricks workspaces | https://learn.microsoft.com/en-us/azure/databricks/admin/workspace/serverless-workspaces | | Decide and migrate agents from Model Serving to Apps | https://learn.microsoft.com/en-us/azure/databricks/agents/agent-framework/migrate-agent-to-apps | | Choose BI tools that integrate with Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/ai-bi/tools | | Optimize Databricks AI Search costs and usage | https://learn.microsoft.com/en-us/azure/databricks/ai-search/cost-management | | Decide and migrate from dbx to Databricks bundles | https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/dbx/dbx-migrate | | Migrate optimized LLM endpoints to provisioned throughput | https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/migrate-provisioned-throughput | | Decide when to use Databricks Light runtime | https://learn.microsoft.com/en-us/azure/databricks/archive/runtime/light | | Plan migration of Databricks workloads to Spark 3.x | https://learn.microsoft.com/en-us/azure/databricks/archive/spark-3.x-migration/ | | Choose and manage the default Unity Catalog catalog | https://learn.microsoft.com/en-us/azure/databricks/catalogs/default | | Choose appropriate Azure Databricks compute types | https://learn.microsoft.com/en-us/azure/databricks/compute/choose-compute | | Decide when and how to use GPU Databricks compute | https://learn.microsoft.com/en-us/azure/databricks/compute/gpu | | Plan migration from classic to serverless Databricks compute | https://learn.microsoft.com/en-us/azure/databricks/compute/serverless/migration | | Choose serverless streaming configurations in Databricks | https://learn.microsoft.com/en-us/azure/databricks/compute/serverless/streaming | | Choose and manage Azure Databricks SQL warehouse sizing and scaling | https://learn.microsoft.com/en-us/azure/databricks/compute/sql-warehouse/warehouse-behavior | | Choose appropriate Azure Databricks SQL warehouse type | https://learn.microsoft.com/en-us/azure/databricks/compute/sql-warehouse/warehouse-types | | Choose Databricks connection options for external data | https://learn.microsoft.com/en-us/azure/databricks/connect/ | | Select batch vs streaming semantics in Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/data-engineering/batch-vs-streaming | | Choose procedural vs declarative data processing in Databricks | https://learn.microsoft.com/en-us/azure/databricks/data-engineering/procedural-vs-declarative | | Choose tables, views, materialized and streaming tables | https://learn.microsoft.com/en-us/azure/databricks/data-engineering/tables-views | | Process CDC, snapshots, and SCD in Lakeflow pipelines | https://learn.microsoft.com/en-us/azure/databricks/data-engineering/what-is-cdc | | Choose between ABAC and table-level filters | https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/abac/abac-vs-rls-cm | | Update Databricks jobs when migrating to Unity Catalog | https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/jobs-update | | Decide between managed and external Unity Catalog assets | https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/managed-versus-external | | Plan and execute Unity Catalog workspace upgrade | https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/upgrade/ | | Prepare and migrate to Unity Catalog–only Databricks workspaces | https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/upgrade/uc-only-migration | | Choose local development tools for Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/ | | Migrate from legacy to new Databricks CLI | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/migrate | | Migrate from older to new Databricks Connect for Python | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/python/migrate | | Migrate Scala projects to Databricks Connect 13.3+ | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/scala/migrate | | Decide between CDKTF and Databricks Terraform provider | https://learn.microsoft.com/en-us/azure/databricks/dev-tools/terraform/cdktf | | Use Compatibility Mode for external table reads | https://learn.microsoft.com/en-us/azure/databricks/external-access/compatibility-mode | | Choose between Azure Databricks free options | https://learn.microsoft.com/en-us/azure/databricks/getting-started/free-trial-vs-free-edition | | Choose Auto Loader file detection mode in Databricks | https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/auto-loader/file-detection-modes | | Choose and manage Lakeflow community connectors | https://learn.microsoft.com/en-us/azure/databricks/ingestion/community-connectors | | Plan migration of existing data to Delta Lake on Databricks | https://learn.microsoft.com/en-us/azure/databricks/ingestion/data-migration/ | | Understand Aha! connector plans and table coverage | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/aha-faq | | Plan and configure MySQL ingestion with Lakeflow Connect | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/mysql | | Understand Slack logs connector requirements and support | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/slack-access-integration-logs-faq | | Understand Zip connector capabilities and FAQs | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/zip-faq | | Understand Zoom Logs connector requirements and capabilities | https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/zoom-logs-faq | | Choose and start with Databricks ODBC and JDBC drivers | https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc-odbc-bi | | Migrate from Simba Spark ODBC to Databricks ODBC | https://learn.microsoft.com/en-us/azure/databricks/integrations/odbc/migration | | Migrate from Spark Submit tasks to JAR and notebook tasks | https://learn.microsoft.com/en-us/azure/databricks/jobs/tasks/spark-submit | | Choose the right development language on Databricks | https://learn.microsoft.com/en-us/azure/databricks/languages/overview | | Plan migration from deprecated Foundation Model Fine-tuning | https://learn.microsoft.com/en-us/azure/databricks/large-language-models/foundation-model-training/ | | Clone Hive metastore pipelines to Unity Catalog via REST API | https://learn.microsoft.com/en-us/azure/databricks/ldp/clone-hms-to-uc | | Use materialized views in Lakeflow pipelines | https://learn.microsoft.com/en-us/azure/databricks/ldp/concepts/materialized-views | | Compare Lakeflow pipelines with Spark Declarative Pipelines | https://learn.microsoft.com/en-us/azure/databricks/ldp/concepts/spark-declarative-pipelines | | Choose between standalone and Lakeflow pipelines | https://learn.microsoft.com/en-us/azure/databricks/ldp/concepts/standalone-pipelines | | Decide when to use Lakeflow streaming tables | https://learn.microsoft.com/en-us/azure/databricks/ldp/concepts/streaming-tables | | Map Delta Live Tables features to Lakeflow pipelines | https://learn.microsoft.com/en-us/azure/databricks/ldp/concepts/where-is-dlt | | Choose between standalone tables and Lakeflow pipelines | https://learn.microsoft.com/en-us/azure/databricks/ldp/dbsql/dbsql-for-ldp | | Choose SQL or Python for Lakeflow pipelines | https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/sql-vs-python | | Use incremental refresh for materialized views vs streaming tables | https://learn.microsoft.com/en-us/azure/databricks/ldp/incremental-refresh | | Migrate from legacy LIVE schema in Lakeflow | https://learn.microsoft.com/en-us/azure/databricks/ldp/live-schema | | Choose triggered vs continuous mode for Lakeflow pipelines | https://learn.microsoft.com/en-us/azure/databricks/ldp/pipeline-mode | | Optimize Databricks Feature Store usage costs | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/cost-management | | Migrate legacy online tables to Databricks Feature Store | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/migrate-from-online-tables | | Select and use Databricks Online Feature Stores | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/online-feature-store | | Upgrade workspace feature tables to Unity Catalog | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/uc/upgrade-feature-table-to-uc | | Plan capacity using model units for throughput | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/foundation-model-apis/model-units | | Migrate Databricks ML workflows to Unity Catalog | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/manage-model-lifecycle/migrate-to-uc | | Upgrade ML workflows to Unity Catalog models | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/manage-model-lifecycle/upgrade-workflows | | Choose supported foundation models on Databricks | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/foundation-model-overview | | Migrate from legacy MLflow Model Serving to Databricks Model Serving | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/migrate-model-serving | | Choose between Spark and Ray on Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ray/spark-ray-overview | | Decide when to use distributed training on Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/train-model/distributed-training/ | | Choose and train deep-learning recommenders on Databricks | https://learn.microsoft.com/en-us/azure/databricks/machine-learning/train-recommender-models | | Plan migration of data applications to Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/migration/ | | Assess and migrate ETL pipelines to Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/migration/etl | | Plan migration from Parquet data lake to Delta Lake | https://learn.microsoft.com/en-us/azure/databricks/migration/parquet-to-delta-lake | | Decide how to migrate data warehouses to Databricks lakehouse | https://learn.microsoft.com/en-us/azure/databricks/migration/warehouse-to-lakehouse | | Migrate from MLflow 2 Agent Evaluation to MLflow 3 | https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/agent-eval-migration | | Quick reference for migrating to MLflow 3 | https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/agent-eval-migration-reference | | Choose between open source and managed MLflow on Databricks | https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/overview/oss-managed-diff | | Decide and migrate MLflow traces to Unity Catalog | https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/migrate-traces-to-uc | | Migrate legacy Unity Catalog trace tables to prefix format | https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/migrate-uc-trace-table-prefix | | Choose Lakebase backup and restore methods | https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/backup-methods | | Migrate Databricks Asset Bundles to Autoscaling Lakebase | https://learn.microsoft.com/en-us/azure/databricks/oltp/update-to-autoscaling-dabs | | Plan and understand Lakebase upgrade to Autoscaling | https://learn.microsoft.com/en-us/azure/databricks/oltp/upgrade-to-autoscaling | | Choose pandas options and patterns on Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/pandas/ | | Choose Microsoft Fabric integration for Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/partners/bi/fabric | | Select Databricks options for external query federation | https://learn.microsoft.com/en-us/azure/databricks/query-federation/ | | Choose and configure Databricks-to-Databricks federation | https://learn.microsoft.com/en-us/azure/databricks/query-federation/databricks | | Migrate Databricks HTTP connections to serverless routing | https://learn.microsoft.com/en-us/azure/databricks/query-federation/http-migration | | Migrate legacy Databricks query federation to Lakehouse Federation | https://learn.microsoft.com/en-us/azure/databricks/query-federation/migrate | | Plan and execute Databricks Runtime 11.x migration | https://learn.microsoft.com/en-us/azure/databricks/release-notes/runtime/11.x-migration | | Migrate workloads to Databricks Runtime 12.x safely | https://learn.microsoft.com/en-us/azure/databricks/release-notes/runtime/12.x-migration | | Plan and execute Databricks Runtime 13.x migration | https://learn.microsoft.com/en-us/azure/databricks/release-notes/runtime/13.x-migration | | Migrate workloads to Databricks Runtime 14.x safely | https://learn.microsoft.com/en-us/azure/databricks/release-notes/runtime/14.x-migration | | Assess Databricks Runtime support lifecycle and upgrades | https://learn.microsoft.com/en-us/azure/databricks/release-notes/runtime/databricks-runtime-ver | | Choose Azure Databricks serverless SKUs and DBU rates | https://learn.microsoft.com/en-us/azure/databricks/resources/pricing | | Plan and manage Databricks serverless networking costs | https://learn.microsoft.com/en-us/azure/databricks/security/network/serverless-network-security/cost-management | | Choose and use Azure Databricks workspace export options | https://learn.microsoft.com/en-us/azure/databricks/security/privacy/export-workspace-data | | Choose between Spark Connect and Spark Classic | https://learn.microsoft.com/en-us/azure/databricks/spark/connect-vs-classic | | Choose between SparkR and sparklyr on Azure Databricks | https://learn.microsoft.com/en-us/azure/databricks/sparkr/sparkr-vs-sparklyr | | Choose and size SQL warehouses for alerts | https://learn.microsoft.com/en-us/azure/databricks/sql/user/alerts/compute | | Choose Structured Streaming output modes on Databricks | https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/output-mode | | Decide when to use real-time mode in Databricks | https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/real-time/concepts | | Connect metric views to external BI tools with trade-offs | https://learn.microsoft.com/en-us/azure/databricks/uc-semantics/metric-views/bi-tools | | Choose aggregated vs unaggregated metric view materializations | https://learn.microsoft.com/en-us/azure/databricks/uc-semantics/metric-views/choose-materialization-type |
tools
Expert knowledge for Microsoft Foundry (aka Azure AI Foundry) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Foundry agents with IQ retrieval, Entra RBAC, Azure OpenAI, M365/Teams publishing, or MCP tools, and other Microsoft Foundry related development tasks. Not for Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Local (use microsoft-foundry-local), Microsoft Foundry Tools (use microsoft-foundry-tools).
tools
Expert knowledge for Microsoft Foundry Local (aka Azure AI Foundry Local) development including best practices, configuration, and integrations & coding patterns. Use when compiling HF models with Olive, managing local models via CLI, or building chat, embeddings, or transcription apps, and other Microsoft Foundry Local related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Tools (use microsoft-foundry-tools), Azure Local (use azure-local).
tools
Expert knowledge for Microsoft Foundry Classic (aka Azure AI Foundry classic) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring Foundry agents, routing Azure OpenAI models, integrating tools/RAG, securing endpoints, or deploying hubs, and other Microsoft Foundry Classic related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Local (use microsoft-foundry-local), Microsoft Foundry Tools (use microsoft-foundry-tools).
development
Expert knowledge for Azure Web PubSub development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using WebSockets/MQTT, Socket.IO, Functions bindings, geo-replication, or Premium autoscale in Web PubSub, and other Azure Web PubSub related development tasks. Not for Azure SignalR Service (use azure-signalr-service), Azure Event Hubs (use azure-event-hubs), Azure Service Bus (use azure-service-bus), Azure Relay (use azure-relay).