Databricks Runtime Databricks Runtime

Databricks Runtime 包括 Apache Spark,但还添加了许多可以显著提高大数据分析可用性、性能和安全性的组件与更新:Databricks Runtime includes Apache Spark but also adds a number of components and updates that substantially improve the usability, performance, and security of big data analytics:

  • Delta Lake 是基于 Apache Spark 构建的下一代存储层,可提供 ACID 事务、优化的布局和索引以及针对数据管道生成的执行引擎改进。Delta Lake, a next-generation storage layer built on top of Apache Spark that provides ACID transactions, optimized layouts and indexes, and execution engine improvements for building data pipelines.
  • 已安装的 Java、Scala、Python 和 R 库Installed Java, Scala, Python, and R libraries
  • Ubuntu 及其随附的系统库Ubuntu and its accompanying system libraries
  • 启用了 GPU 的群集的 GPU 库GPU libraries for GPU-enabled clusters
  • 与平台的其他组件(如笔记本、作业和群集管理器)集成的 Databricks 服务Databricks services that integrate with other components of the platform, such as notebooks, jobs, and cluster manager

有关每个运行时版本的内容的信息,请参阅发行说明For information about the contents of each runtime version, see the release notes.

运行时版本控制Runtime versioning

将定期发布 Databricks Runtime 版本:Databricks Runtime versions are released on a regular basis:

  • 主版本的变化通过递增小数点之前的版本号来表示(例如从 3.5 跳转到 4.0)。Major versions are represented by an increment to the version number that precedes the decimal point (the jump from 3.5 to 4.0, for example). 它们在发生重大更改时发布,其中一些可能无法向后兼容。They are released when there are major changes, some of which may not be backwards-compatible.
  • 功能版本的变化通过递增小数点之后的版本号来表示(例如从 3.4 跳转到 3.5)。Feature versions are represented by an increment to the version number that follows the decimal point (the jump from 3.4 to 3.5, for example). 每个主要版本都包含多个功能版。Each major release includes multiple feature releases. 功能版总是向后兼容其主要版本中的先前版本。Feature releases are always backwards compatible with previous releases within their major release.
  • 长期支持版本由 LTS 限定符(例如 3.5 LTS)表示 。Long Term Support versions are represented by an LTS qualifier (for example, 3.5 LTS). 对于每个主要版本,我们都声明一个“规范”功能版本,并为其提供为期两年的支持。For each major release, we declare a “canonical” feature version, for which we provide two full years of support. 有关详细信息,请参阅 Databricks 运行时支持生命周期See Databricks runtime support lifecycle for more information.