tencent cloud

Elastic MapReduce

  • Release Notes and Announcements
  • Product Introduction
  • Purchase Guide
    • EMR on CVM Billing Instructions
    • EMR on TKE Billing Instructions
    • EMR Serverless HBase Billing Instructions
    • EMR Serverless TCBase Billing Overview
  • Getting Started
  • EMR on CVM Operation Guide
    • Planning Cluster
    • Administrative rights
    • Configuring Cluster
    • Managing Cluster
    • Managing Service
    • Monitoring and Alarms
    • TCInsight
  • EMR on TKE Operation Guide
  • EMR Serverless HBase Operation Guide
  • EMR Serverless TCBase Operation Guide
  • EMR Development Guide
    • Hadoop Development Guide
    • Spark Development Guide
    • Hbase Development Guide
    • Phoenix on Hbase Development Guide
    • Hive Development Guide
    • Presto Development Guide
    • Sqoop Development Guide
    • Hue Development Guide
    • Oozie Development Guide
    • Flume Development Guide
    • Kerberos Development Guide
    • Knox Development Guide
    • Alluxio Development Guide
    • Kylin Development Guide
    • Livy Development Guide
    • Kyuubi Development Guide
    • Zeppelin Development Guide
    • Hudi Development Guide
    • Superset Development Guide
    • Impala Development Guide
    • Druid Development Guide
    • TensorFlow Development Guide
    • Kudu Development Guide
    • Ranger Development Guide
    • Kafka Development Guide
    • StarRocks Development Guide
    • Flink Development Guide
    • JupyterLab Development Guide
    • MLflow Development Guide
  • Practical Tutorial
    • Practice of EMR on CVM Ops
    • Data Migration
    • Practical Tutorial on Custom Scaling
  • API Documentation
    • History
    • Introduction
    • API Category
    • Making API Requests
    • Cluster Resource Management APIs
    • Cluster Services APIs
    • User Management APIs
    • Information Query APIs
    • Scaling APIs
    • Configuration APIs
    • Other APIs
    • Cluster Lifecycle APIs
    • Serverless HBase APIs
    • YARN Resource Scheduling APIs
    • Data Types
    • Error Codes
  • FAQs
    • EMR on CVM
  • Service Level Agreement
  • Contact Us

Version Overview

Download
포커스 모드
폰트 크기
마지막 업데이트 시간: 2023-12-27 09:50:17

Product Release Overview

EMR consists of open-source applications in a series of big data ecosystems. It offers six cluster types for you to deploy as needed.

Product Release Number Format

1. EMR version numbers are in the format of EMR va.b.c as detailed below:
The meanings of a for different clusters are as follows:
For Hadoop clusters, a indicates the Hadoop versions supported by the current version. When a is 1 or 2, Hadoop v2.x is supported; when a is 3, Hadoop v3.x is supported.
For Druid clusters, a indicates the Druid versions supported by the current version. When a is 1, Druid v0.17.x is supported.
For ClickHouse clusters, a indicates the ClickHouse versions supported by the current version. When a is 1, ClickHouse v19.x and v20.x are supported.
For Kafka clusters, a indicates the Kafka versions supported by the current version. When a is 1, Kafka v1.x is supported.
For Doris clusters, a indicates the Doris versions supported by the current version. When a is 1, Doris v0.13x is supported.
For StarRocks clusters, a indicates the StarRocks versions supported by the current version. When a is 1, StarRocks v2.x is supported.
b indicates that the version has new components or supports component version upgrade. c indicates feature optimization.
Caution
The components and their versions bundled with each EMR version are fixed. Currently, neither selecting multiple versions of a component nor changing a component version in one EMR version is supported. For example, Hadoop v2.8.5 and Spark v3.2.1 are built into EMR v2.7.0.
Once a version of EMR is selected for cluster creation, the EMR and component version used by the cluster will not be automatically upgraded. For example, if EMR v2.7.0 is selected, then Hadoop will always be v2.8.5, and Spark will always be v3.2.1. Even if EMR is upgraded to v2.8.0, Hadoop is upgraded to a higher version, and Spark is upgraded to v3.3.0 afterward, the previously created cluster will not be affected, and only new clusters will use the new versions.
When you upgrade the cluster through data migration, for example, from EMR v2.6.0 to EMR v2.7.0, in order to avoid issues such as version incompatibility or environment changes, be sure to test the tasks to be migrated and ensure that they can work properly in the new software environment.
EMR v2.4.0 comes with Kona (based on OpenJDK8). We have developed and improved Kona based on the characteristics of cloud scenarios.

도움말 및 지원

문제 해결에 도움이 되었나요?

피드백