What's New
The tables below describe the functions released in each MapReduce Service version and corresponding documentation updates. New features will be successively launched in each region.
October, 2023
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
IAM user synchronization supports specified users |
When synchronizing IAM users in an MRS cluster, you can specify a user or user group to synchronize IAM users. |
Commercial use |
May, 2023
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
MRS 3.2.0-LTS.1 |
|
Commercial use |
March, 2023
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
MRS 3.1.5 |
|
Commercial use |
List of MRS Component Versions |
January, 2023
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
Added the function of viewing alarm details. |
You can use this function to quickly view alarm details. |
Commercial use |
|
|
2 |
The effective date can be configured when a scaling policy is configured for an MRS cluster. |
You can set the effective date of a resource plan as required. |
Commercial use |
July, 2022
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
Added the API for obtaining the file list of a specified directory. |
The list of files in a specified directory can be obtained through an API in an MRS cluster. |
Commercial use |
May, 2022
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
Supported MRS clusters of the LTS version. |
LTS:
|
Commercial use |
March, 2022
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
Scaled up the specifications of multiple Master nodes. |
Added the conditions for scaling up the specifications of multiple Master nodes. |
Commercial use |
February, 2022
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
Suppored unsubscription from nodes in yearly/monthly clusters. |
You can reduce the number of specific nodes to scale in a cluster so that MRS delivers better storage and computing capabilities at lower O&M costs based on service requirements. |
Commercial use |
Unsubscribing from a Specified Node in a Yearly/Monthly Cluster |
September, 2021
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
Supported custom node names. |
During MRS cluster creation, you can customize prefixes for the hostnames of ECSs or BMSs in the cluster. |
Commercial use |
July, 2021
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
Upgraded ClickHouse to 21.3.4.25 and supported data redistribution. |
After new ClickHouse nodes are added, you can balance data in the ClickHouse cluster through data migration. |
Commercial use |
|
|
2 |
Added Hudi in MRS. |
Hudi is the file organization layer of the data lake. It manages Parquet files, provides the data lake capability, and supports multiple compute engines. It also provides insert, update, and deletion (IUD) interfaces and streaming primitives for inserting, updating, and incremental pulling on HDFS datasets. |
Commercial use |
March, 2021
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
Brought MRS 2.1.0 offline. |
Purchase MRS 3.1.0. |
Commercial use |
|
|
2 |
Brought MRS 1.8.10 offline. |
Purchase MRS 1.9.2. |
Commercial use |
|
|
3 |
Supported scale-in of specified nodes. |
If a node is faulty and is no longer needed, you can use this function to remove the faulty node. When the node is removed, the role instance of the component will not be decommissioned. Before deleting the node, ensure that the data on the node has been backed up. |
Commercial use |
November, 2020
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
Supported ClickHouse clusters. |
MRS 3.x allows you to create ClickHouse clusters and provides capabilities such as smooth scale-out, HA, Kunpeng, flexible configuration, simple O&M, and security and reliability. |
Commercial use |
|
|
2 |
Upgraded new big data components. |
MRS 3.x provides the latest capabilities of open-source components and enhances functions, performance, and reliability based on the community versions. |
Commercial use |
September, 2020
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
Supported multiple heterogeneous VM specifications. |
MRS clusters support hybrid deployment of x86 and Arm servers, and hybrid deployment of Elastic Cloud Servers (ECSs) and Bare Metal Servers (BMSs). |
Commercial use |
|
|
2 |
Added the V2 API for creating a cluster. |
The API of V2 is more powerful and easy to use. If you need to create a cluster, you are advised to use V2 API. |
Commercial use |
August, 2020
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
Added automatic synchronization between IAM accounts and cluster users. |
IAM user synchronization is to synchronize IAM users bound with MRS policies to the MRS system and create accounts sharing same names with the IAM users but different passwords. Then, you can use an IAM username (the password needs to be reset by user admin of Manager) to log in to Manager for cluster management. |
Commercial use |
June, 2020
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
Supported user-defined cluster topologies. |
MRS allows you to customize the deployment mode of cluster process instances on cluster nodes. |
Commercial use |
March, 2020
|
No. |
Feature |
Description |
Phase |
Related Documents |
|---|---|---|---|---|
|
1 |
Added Presto HA in MRS. |
MRS supports the installation of multiple Presto instances for a large-scale cluster by default. That is, multiple Worker instances, such as Worker1, Worker2, and Worker3, are installed on a Core/Task node. Multiple Worker instances interact with a Coordinator to execute computing tasks, greatly improving node resource utilization and computing efficiency. |
Commercial use |
|
|
2 |
Added Tez in MRS. |
Tez is Apache's latest open source computing framework that supports Directed Acyclic Graph (DAG) jobs. It can convert multiple dependent jobs into one job, greatly improving the performance of DAG jobs. If projects like Hive and Pig use Tez instead of MapReduce as the backbone of data processing, response time will be significantly reduced. Tez is built on Yarn and can run MapReduce jobs without any modification. |
Commercial use |
|
|
3 |
Added Alluxio in MRS. |
Alluxio is data orchestration technology for analytics and artificial intelligence (AI) for the cloud. In the MRS big data ecosystem, Alluxio lies between computing and storage. It provides a data abstraction layer for computing frameworks including Apache Spark, Presto, MapReduce, and Apache Hive, so that upper-layer computing applications can access persistent storage systems including HDFS and OBS through unified client APIs and a global namespace. In this way, computing and storage are separated. |
Commercial use |
|
|
4 |
Added Ranger in MRS. |
Apache Ranger offers a centralized security framework and supports authorization and auditing. It manages fine-grained access control over Hadoop and related components, such as HDFS, Hive, HBase, Kafka, and Storm. You can use the frontend web UI console provided by Ranger to configure policies to control users' access to these components. |
Commercial use |
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