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Select and Configure Compute in a Workspace

MS DocsCompute types in Azure DatabricksJob compute, serverless, SQL warehouses, classic clusters, shared compute›MS DocsAzure Databricks serverless computeServerless SQL and jobs: benefits, limitations, when to use›MS LearnGet started with Azure DatabricksWorkspace overview, compute options, notebook intro›

MS DocsConfigure clusters in Azure DatabricksCPU/memory, node count, autoscaling, termination, pooling›MS DocsInstance pools in Azure DatabricksPre-warmed VMs for faster cluster startup, cost optimization›MS DocsCluster autoscalingMin/max workers, optimized autoscaling vs standard autoscaling›

MS DocsPhoton acceleration in Azure DatabricksVectorized query engine: supported operations, limitations, cost›MS DocsDatabricks Runtime versionsChoose DBR vs ML runtime, LTS vs non-LTS releases›MS DocsLibraries on Azure DatabricksInstall libraries on clusters: PyPI, Maven, JAR, wheel files›

MS DocsCluster access control in Azure DatabricksCan Restart, Can Manage, CAN_ATTACH_TO permissions per cluster›MS DocsWorkspace access control in Azure DatabricksWorkspace-level permissions, Unity Catalog compute access›

Create and Organize Objects in Unity Catalog

MS DocsUnity Catalog overviewThree-level namespace: catalog.schema.table, securable objects›MS DocsUnity Catalog best practicesNaming conventions, isolation strategies, multi-env patterns›MS DocsCreate catalogs in Unity CatalogCatalog creation, workspace binding, storage credentials›

MS DocsCreate tables in Unity CatalogCREATE TABLE, CREATE OR REPLACE, managed vs external tables›MS DocsMaterialized views in Databricks SQLMaterialized views: refresh, staleness, query optimization›MS DocsVolumes in Unity CatalogManaged and external volumes for file storage in Unity Catalog›

MS DocsLakehouse Federation (foreign catalog)Connect to external sources via federated catalog: Snowflake, MySQL, Hive›MS DocsDDL statements for Unity Catalog tablesALTER TABLE, COMMENT ON, DESCRIBE EXTENDED for managed/external›MS DocsConfigure AI/BI Genie for data discoveryGenie instructions, verified answers, column descriptions›

Secure Unity Catalog Objects

MS DocsManage privileges in Unity CatalogGRANT, REVOKE, SHOW GRANTS on catalog, schema, table, view, volume›MS DocsUnity Catalog privilege modelPrivilege inheritance, metastore admin, catalog owner, schema owner›

MS DocsRow filters and column masks in Unity CatalogCREATE ROW FILTER, column masks: syntax, function-based RLS›MS DocsColumn-level security in Unity CatalogMASK function, sensitive column protection, audit trail›

MS DocsAccess Azure Key Vault secrets from Azure DatabricksSecret scopes, Key Vault-backed scopes, dbutils.secrets.get()›MS DocsService principals in Azure DatabricksCreate SP, assign workspace roles, use for job authentication›MS DocsManaged identities for Azure DatabricksSystem/user-assigned managed identities for ADLS, Key Vault access›

Govern Unity Catalog Objects

MS DocsData lineage in Unity CatalogColumn-level lineage tracking in Catalog Explorer: owner, history, deps›MS DocsTags in Unity Catalog (ABAC)Tag-based ABAC: catalog, schema, table, column tagging and policies›MS DocsComments and descriptions in Unity CatalogCOMMENT ON TABLE, COLUMN, CATALOG: data discovery best practices›

MS DocsRow filters and column masks in Unity CatalogFunction-based filters, row filter policies, masking policy assignment›MS DocsData retention policies in Delta LakeVACUUM, time travel, log retention, data deletion patterns›

MS DocsAudit logging in Azure DatabricksEnable diagnostic logging, send to Log Analytics, audit events catalog›MS DocsDelta Sharing overviewProvider/recipient model, share catalog, open protocol sharing›MS DocsDelta Sharing security best practicesCredential rotation, recipient tokens, Databricks-to-Databricks sharing›

Design and Implement Data Modeling in Unity Catalog

MS DocsLakeflow Connect in Azure DatabricksManaged ingestion connectors: Salesforce, JDBC, cloud storage sources›MS DocsMedallion architecture in Azure DatabricksBronze/Silver/Gold: batch vs streaming, tool selection per layer›MS LearnIngest data with Azure Databricks and Azure Data FactoryADF pipelines triggering Databricks notebooks, parameterized ingestion›

MS DocsDelta Lake in Azure DatabricksDelta format: ACID transactions, time travel, schema enforcement›MS DocsLiquid clustering in Delta LakeReplaces partitioning/Z-ordering: flexible, auto-optimizing clustering›MS DocsOptimize file sizes and Z-orderingOPTIMIZE command, ZORDER BY, file compaction, deletion vectors›

MS DocsSlowly changing dimensions with Delta LakeSCD Type 1 (overwrite), Type 2 (history rows) patterns with MERGE›MS DocsManaged and external tables in Unity CatalogLifecycle differences, storage location, DROP behavior›MS DocsDelta table history and time travelDESCRIBE HISTORY, VERSION AS OF, TIMESTAMP AS OF for audit/recovery›

Ingest Data into Unity Catalog

MS DocsLakeflow Connect – batch and streamingManaged ingestion: configure connections, targets, incremental load›MS DocsCOPY INTO for batch ingestionIdempotent file ingestion from cloud storage: CSV, JSON, Parquet, Delta›MS DocsCREATE TABLE AS SELECT (CTAS) and CREATE OR REPLACE TABLEDDL ingestion patterns in Unity Catalog: materialize data at rest›

MS DocsChange data capture with Delta LakeMERGE INTO for CDC: source/target reconciliation, SCD Type 2›MS DocsSpark Structured Streaming in Azure DatabricksreadStream/writeStream, triggers, checkpointing, output modes›MS DocsStream Azure Event Hubs data into DatabricksKafka connector for Event Hubs: connection strings, consumer groups›

MS DocsAuto Loader in Azure DatabrickscloudFiles source: automatic schema inference, incremental file ingestion›MS DocsLakeflow Spark Declarative Pipelines (formerly DLT, now Lakeflow SDP) overviewDeclarative ETL: Bronze/Silver/Gold as live tables + streaming tables›MS DocsCreate a Lakeflow Spark Declarative PipelinePipeline creation, table declarations, expectations, cluster config›

Cleanse, Transform, and Load Data into Unity Catalog

MS DocsData profiling in DatabricksSummary statistics, column distributions, quality metrics›MS LearnTransform data with Azure DatabricksPySpark: filter, groupBy, join, handle nulls, deduplicate›MS DocsPySpark DataFrame operationsselect, filter, groupBy, agg, join, union, pivot, unpivot›

MS DocsDelta Lake MERGE operationsMERGE INTO: upsert, SCD Type 2, conditional actions›MS DocsSQL transformation patterns in DatabricksCTE, window functions, PIVOT, UNPIVOT, EXCEPT, INTERSECT›

Implement and Manage Data Quality Constraints

MS DocsSchema enforcement in Delta LakeAutomatic schema enforcement on write, incompatible schema errors›MS DocsSchema evolution in Delta LakemergeSchema, overwriteSchema, ADD COLUMN, ALTER COLUMN›MS DocsPipeline expectations in Lakeflow Spark Declarative PipelinesEXPECT, EXPECT OR DROP, EXPECT OR FAIL: data quality rules›

Design and Implement Data Pipelines

MS DocsLakeflow Spark Declarative Pipelines overviewDeclarative vs imperative: when to choose Lakeflow Spark Declarative Pipelines over notebooks›MS DocsNotebook workflows in Azure Databricksdbutils.notebook.run(), precedence constraints, modular pipelines›MS DocsDesign task logic for Lakeflow JobsJob tasks: Notebook, Python script, Lakeflow Spark Declarative Pipelines pipeline, SQL query, dbt›

MS DocsError handling in Databricks notebookstry/except patterns, notebook exit values, downstream conditional logic›MS DocsRepair and rerun failed jobs in Lakeflow JobsRepair run: reuse successful task results, partial re-execution›

Implement Lakeflow Jobs

MS DocsLakeflow Jobs: create and configureTask types, dependencies, parameters, timeout, retries, concurrency›MS DocsJob triggers in Azure DatabricksScheduled, file arrival, continuous, API-triggered job runs›MS DocsConfigure alerts and notifications for jobsEmail, Slack, PagerDuty, webhook alerts on start/success/failure›MS DocsConfigure automatic restarts for jobs and pipelinesMax retries, retry on timeout, Lakeflow Spark Declarative Pipelines pipeline restart policies›

Implement Development Lifecycle Processes

MS DocsGit integration for Databricks ReposConnect to GitHub/Azure DevOps, branching, PR workflow, conflict resolution›MS DocsGit folders (Repos) best practicesFeature branches, merge strategies, CI/CD trigger patterns›MS DocsTesting strategies in DatabricksUnit tests with pytest, integration tests, end-to-end UAT in staging›

MS DocsDatabricks Asset Bundles (DAB) overviewBundle structure: databricks.yml, resources, targets, variables›MS DocsConfigure and package a Databricks Asset Bundledatabricks bundle init, bundle validate, bundle deploy›MS DocsAzure Databricks CLIInstall CLI, authenticate, deploy bundles and run jobs from terminal›MS DocsDatabricks REST APIsJobs API, Clusters API, SCIM API for automation and CI/CD›

Monitor, Troubleshoot, and Optimize Workloads

MS DocsMonitor cluster and job performanceCluster metrics, job run history, Spark UI diagnostics, cost tracking›MS DocsSpark UI in Azure DatabricksDAG visualization, stages, tasks, executor metrics for bottlenecks›MS DocsQuery profile in Databricks SQLQuery plan, operator-level timing, push-down analysis›

MS DocsOptimize Apache Spark performanceAQE, broadcast joins, skew hints, shuffle partition tuning›MS DocsCaching in Azure DatabricksSpark cache vs Delta cache (SSD): when to use each›ApacheSpark Structured Streaming Programming GuideWatermarking, output modes, checkpointing for stateful streaming›

MS DocsOPTIMIZE and VACUUM commands in Delta LakeFile compaction, stale file removal, Z-ordering for performance›MS DocsLog streaming to Azure Monitor via Log AnalyticsDiagnostic settings, log categories, Kusto queries on Databricks logs›MS DocsConfigure Azure Monitor alerts for DatabricksMetric alerts, log alerts, action groups for Databricks workloads›

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