הערה
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הגישה לדף זה מחייבת הרשאה. באפשרותך לנסות לשנות מדריכי כתובות.
This page introduces the core concepts you need to use Databricks SQL effectively.
Interfaces and tools
| Interface | Description |
|---|---|
| SQL editor | A browser-based interface for writing and running SQL queries. Includes integrated AI assistance, code comments, and version history. |
| AI/BI | A business intelligence solution that includes dashboards and Genie spaces for self-service data analysis and conversational data exploration. |
| Notebooks | Interactive documents that combine SQL with Python, Scala, or R. Attach a notebook to a SQL warehouse to run SQL alongside other languages. |
| Metric views | A semantic layer for defining reusable business metrics with consistent calculations across queries and dashboards. |
| Alerts | Automated monitors that evaluate query results against a condition and deliver notifications when the condition is met. |
| Jobs | Scheduled execution of SQL queries for automated data processing and reporting workflows. |
| ETL | Define and refresh streaming tables and materialized views in Databricks SQL for incremental ETL pipelines. |
| REST API | A programmatic interface for automating and managing Databricks SQL objects. |
Queries and computation
| Concept | Description |
|---|---|
| Query | A SQL statement that retrieves or transforms data. Queries in Databricks SQL are saved, versioned, and reusable. |
| SQL warehouse | The compute resource that executes SQL queries. All Databricks SQL interfaces run queries on a SQL warehouse. |
| Query history | A record of executed queries including execution time, resource usage, and performance characteristics. |
| Query profile | A detailed view of a query's execution plan. Use it to identify bottlenecks and optimization opportunities. |
| Visualization | A graphical representation of query results, such as a bar chart, line chart, or table. |
Data management
| Concept | Description |
|---|---|
| Dashboard | A collection of visualizations and commentary built from one or more queries. Dashboards are shareable and support interactive filtering. |
| Metric view | A named, reusable definition of a business metric backed by a SQL expression. Enforces consistent calculations across teams and tools. |
| Streaming table | A table that ingests data incrementally from a streaming source, managed by a Databricks SQL pipeline. |
| Materialized view | A precomputed view whose results are stored and refreshed automatically by a Databricks SQL pipeline. |
Authentication and authorization
| Concept | Description |
|---|---|
| User and group | A user is a unique individual with access to the Azure Databricks workspace. A group is a collection of users managed together for access control purposes. |
| Personal access token | A credential used to authenticate to the REST API and to connect third-party tools to SQL warehouses. |
| Access control list | A set of permissions attached to an object that controls which principals can perform which actions on it. |
| Unity Catalog | The governance layer for Azure Databricks. Provides centralized access control, auditing, lineage, and data discovery across workspaces. |