Update the minor version of an ApsaraDB for HBase cluster in the ApsaraDB for HBase console - ApsaraDB for HBase

This topic describes how to update the minor version of an ApsaraDB for HBase cluster in the ApsaraDB for HBase console. This topic also describes the feature updates in each minor version.

Important

The update does not interrupt the ApsaraDB for HBase service. The system performs a rolling update on the ApsaraDB for HBase cluster. Before the RegionServer restarts, all regions are moved to other servers to minimize the impact on your workloads. Jitters may occur during the update, but the ApsaraDB for HBase cluster remains available. You can perform minor version updates based on your business requirements.
The amount of time that is required to update the minor version of an ApsaraDB for HBase cluster varies based on the size of the ApsaraDB for HBase cluster and the number of regions in the ApsaraDB for HBase cluster. A larger cluster requires more time to update the minor version. In most cases, ApsaraDB for HBase takes less than 10 minutes to update a cluster that contains two core nodes and 100 regions. ApsaraDB for HBase may take more than 1 hour to update a cluster that contains a large number of core nodes and more than 1,000 regions.

Procedure

Log on to the ApsaraDB for HBase console.
In the top navigation bar, select the region where the cluster that you want to manage is deployed.
On the Clusters page, find the cluster and click the ID of the cluster.
In the left-side navigation pane, click Database Connection.
In the upper-right corner, click Upgrade Minor Version.

Features in different versions

Version number	Release date	Category	Description
2.7.6	December 6, 2024	New feature	You can specify MySQL-style time zones. For more information, see Specify a time zone for a LindormTable connection. The full-text search function MATCH is supported. For more information, see MATCH. You can view SQL audit logs in the console. For more information, see SQL audit logging. You can use the Python connector mysql-connector-python to connect to the wide table engine. For more information, see Use mysql-connector-python to develop applications.
2.7.6	December 6, 2024	Optimized feature	The aggregate request execution logic is optimized to improve the aggregate request execution performance. The construction logic of secondary index historical data is optimized to solve occasional failed data construction. The request execution retry logic is optimized to reduce the errors during the move/split process. The IN request execution logic is optimized to improve the request execution efficiency in case of a large number of IN queries. The logic of hotspot self-healing is further optimized to discover and solve the hotspot sharding problem in a more fine-grained manner. The compatibility of the HBase protocol is optimized. The compatibility of MySQL statements is optimized and more statements are supported. Some other features are optimized to improve stability.
2.7.1	July 11, 2024	New feature	Expressions that include the MD5 or SHA256 function can be specified as secondary index keys. For more information, see Secondary index function expression (function_expression). You can execute SQL statements to configure the maximum number of connections to LindormTable. For more information, see Supported configuration items. Lindorm Ganos supports S2 secondary indexes. For more information, see S2 secondary indexes. S2 indexes can be used to query whether geometry objects intersect.
2.7.1	July 11, 2024	Optimized feature	The performance of LindormTable when you query a single data record is improved. Indexes can be created for the historical data in multiple index tables of a table at the same time. The progress information of a secondary index when the index is built for historical data is enriched. The stability of LindormTable and its compatibility with MySQL are improved. More MySQL syntaxes are supported by LindormTable.
2.6.5	March 25, 2024	New feature	The following two parameters can be configured for search indexes: INDEX_SETTINGS that specifies index attributes and mapping that specifies index key attributes. For more information, see Index key definition (index_key_definition) and Index key attributes for search indexes (option_definition). Lindorm Ganos supports S2 secondary indexes. For more information, see S2 secondary indexes. Lindorm Ganos supports H3 functions that can be used to efficiently analyze or query spatio-temporal data based on H3 grids. For more information, see H3 functions.
2.6.5	March 25, 2024	Optimized feature	The compatibility with MySQL syntax is improved and more MySQL syntaxes are supported. The reuse of physical plans is supported by Lindorm SQL to improve query performance. You can build secondary indexes for historical data even if the data is stored by using cold storage. Issues related to the compatibility of Apache HBase clients with Lindorm are fixed. If you want to use an open source Apache HBase client to access Lindorm, we recommend that you upgrade the LindormTable version to this version or later.
2.6.2	November 8, 2023	New feature	The MySQL compatibility feature is supported. For more information, see Use the MySQL protocol to develop applications (recommended).
2.5.6	August 18, 2023	Optimized feature	The compatibility issue with the HBase protocol is fixed. The following issue is fixed: Loads among multiple groups are not balanced. Some stability issues are fixed.
2.5.3	May 24, 2023	New feature	Columns can be queried by using wildcards. For more information, see Wildcard columns.
2.5.3	May 24, 2023	Optimized feature	The following issue is fixed: A short-circuit read or write that is performed by using a SQL statement may time out. Note For better read and write experience, we recommend that you update the engine version of your LindormTable to 2.5.3 or later. The compatibility issue that may occur when you use an Apache HBase client to perform operations on ApsaraDB for HBase by using a batch interface is fixed. The following issue is fixed: A large number of meta requests occur when you use an Apache HBase client.
2.5.2	April 19, 2023	New feature	Existing columns can be deleted from a table by using Lindorm SQL. For more information, see ALTER TABLE.
2.5.2	April 19, 2023	Optimized feature	The user experience of using SQL statements to access an ApsaraDB for HBase table is improved. For more information, see Use SQL statements to access an ApsaraDB for HBase table. The user experience of querying hot data and cold data that are separately stored is improved. Asynchronous audit logs are supported. The compatibility with Apache HBase clients is improved. The number of files that are monitored in a region is increased. The execution efficiency of the AGGREGATE statement is optimized. The CPU consumption caused by the expiration of data with a short time to live (TTL) is reduced.
2.4.3	March 10, 2023	Optimized feature	The user experience of Lindorm SQL is optimized. Some stability issues are fixed.
2.4.2	December 13, 2022	New feature	Open source Apache HBase clients can be used to access LindormTable. Hot and cold data separation can be performed based on custom time columns. If you use Lindorm SQL, we recommend that you use this feature. For more information, see Separately store hot data and cold data based on custom time columns.
2.4.2	December 13, 2022	Optimized feature	The user experience of JSON is optimized. Some stability issues are fixed.
2.4.1	November 1, 2022	Optimized feature	The user experience of Lindorm Ganos is optimized. The bugs that are related to Lindorm SQL are fixed.
2.4.0	October 9, 2022	New feature	SQL statements can be used to access ApsaraDB for HBase tables. For more information, see Use SQL statements to access an ApsaraDB for HBase table.
2.4.0	October 9, 2022	Optimized feature	The user experience of Lindorm SQL is optimized.
2.3.4	August 30, 2022	Optimized feature	The user experience of Lindorm SQL is optimized.
2.3.3	August 16, 2022	Optimized feature	Hot data can be automatically identified and processed. The ST_DWithin and ST_DWithinSphere functions are supported by Ganos. Some stability issues are fixed.
2.3.2	August 2, 2022	Optimized feature	The syntax of Lindorm SQL statements is optimized. More features of Lindorm Ganos are supported. For more information, see Overview.
2.3.1	June 30, 2022	New feature	Lindorm Ganos is supported. For more information, see Overview.
2.2.21	April 25, 2022	Optimized feature	Direct memory consumption is reduced when data is written. The load balancing policy is optimized. The parameters of the compaction process are optimized and the values of the parameters can be automatically adjusted. The speed at which indexes are created is improved. The read and write performance of SQL statements is optimized.
2.2.20	March 16, 2022	Optimized feature	The performance for writing large-size key-value pairs is optimized. Lindorm SQL can be used to read multiple versions of data and write data based on custom timestamps. Other performance issues are fixed.
2.2.19	February 9, 2022	New feature	Dynamic columns and SQL monitoring are supported for Lindorm SQL.
2.2.19	February 9, 2022	Optimized feature	The following issue is fixed: The metadata update is delayed after the attributes of Lindorm SQL tables are modified. Some stability issues are fixed.
2.2.18	January 5, 2022	Optimized feature	The performance of Lindorm SQL statements is optimized. The issues related to the time zones of the DATE or TIME type in Lindorm SQL statements are fixed. Some stability issues are fixed.
2.2.17	December 17, 2021	Optimized feature	The bugs that are related to Lindorm SQL are fixed. The speed at which the cold storage feature is released in regions is improved. If you use cold storage, we recommend that you upgrade the LindormTable version to a version that is later than V2.2.17.
2.2.16	November 12, 2021	Optimized feature	The syntax of Lindorm SQL statements is improved. If you use Lindorm SQL statements, we recommend that you update the version of your LindormTable to 2.2.16 or later. The logic that is used to flush data to a disk is optimized. This prevents out-of-memory errors when an excessive number of regions exist. Some bugs are fixed.
2.2.15	October 18, 2021	Optimized feature	The performance of using Lindorm SQL statements is optimized to fix the following bugs: Tables fail to be created, and data that requires strong consistency fails to be read from tables. We recommend that you update your cluster to this version or a later version.
2.2.12	September 6, 2021	Optimized feature	Compaction policies are optimized to improve efficiency. The amount of data that is returned for scan operations is optimized.
2.2.11	August 25, 2021	New feature	Lindorm SQL statements are supported. High-performance native secondary indexes are supported.
2.2.10	August 12, 2021	Optimized feature	The issue that request errors occur due to network jitters for cold data is fixed. We recommend that you update your cluster to this version or a later version.
2.2.9	June 9, 2021	New feature	A feature that allows you to dynamically generate the configurations of analyzers is added to SearchIndex, and some bugs are fixed.
2.2.8	March 25, 2021	Optimized feature	The memory usage issue that occurs while data is being compressed by using zstd is optimized.
2.2.7	March 11, 2021	New feature	A feature that allows you to export data from Lindorm in sequence is added. This feature must be used together with Lindorm Tunnel Service (LTS).
2.2.5	January 7, 2021	New feature	A feature that allows you to export incremental data of Lindorm is added. The feature must be used together with LTS.
2.2.1	September 9, 2020	Optimized feature	The SearchIndex feature is optimized and some bugs are fixed.
2.1.30	October 26, 2020	Optimized feature	The algorithm that is used to select flush regions when write hotspots occur is optimized.
2.1.26	October 9, 2020	Optimized feature	The memory overhead of BucketCache is optimized for clusters that use lower specifications.
2.1.25	September 30, 2020	Optimized feature	The volume of redundant data that is retrieved for reverse scans is decreased.
2.1.23	September 22, 2020	Optimized feature	Memory management is optimized for servers that use low memory specifications.
2.1.21	July 20, 2020	Optimized feature	We recommend that you update your cluster to this version or a later version. The write throughput is optimized. The performance of reverse scans is optimized. The rate at which hot data is archived into cold storage is optimized.
2.1.17	March 20, 2020	Optimized feature	The SearchIndex feature is optimized.
2.1.15	February 6, 2020	Optimized feature	The SearchIndex feature is optimized and some bugs are fixed.
2.1.12	December 16, 2019	Optimized feature	The SearchIndex feature is optimized and the bugs that occur during bulk loading are fixed.
2.1.10	November 16, 2019	New feature	The SearchIndex feature is supported.
2.1.10	November 16, 2019	Optimized feature	The hot and cold data separation feature is optimized.
2.1.9	October 8, 2019	New feature	The SearchIndex feature is supported and some bugs are fixed.
2.1.8	September 9, 2019	New feature	The cold storage and hot and cold data separation features are supported. For more information, see Cold storage and Hot and cold data separation.