Star20
127
代码
代码
Issues3690
Pull Requests41
流水线
项目讨论
Wiki
分析
Star20
127

Release Notes

Terms of Use

Copyright © Huawei Technologies Co., Ltd. 2022.

Your replication, use, modification, and distribution of this document are governed by the Creative Commons License Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0). You can visit https://creativecommons.org/licenses/by-sa/4.0/ to view a human-readable summary of (and not a substitute for) CC BY-SA 4.0. For the complete CC BY-SA 4.0, visit https://creativecommons.org/licenses/by-sa/4.0/legalcode.

Certain document contents (such as standard APIs and parameter descriptions) on this website are from the official PostgreSQL website (https://www.postgresql.org/docs/).

Complies with the following protocols: PostgreSQL is Copyright © 1996–2020 by the PostgreSQL Global Development Group. Postgres95 is Copyright © 1994–5 by the Regents of the University of California.

Permission to use, copy, modify, and distribute this software and its documentation for any purpose, without fee, and without a written agreement is hereby granted, provided that the above copyright notice and this paragraph and the following two paragraphs appear in all copies.

IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

THE UNIVERSITY OF CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS-IS" BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.

Trademarks and Permissions

openGauss is a trademark of Huawei Technologies Co., Ltd. All other trademarks and registered trademarks mentioned in this document are the property of their respective holders.

Disclaimer

This document is used only as a guide. Unless otherwise specified by applicable laws or agreed by both parties in written form, all statements, information, and recommendations in this document are provided "AS IS" without warranties, guarantees or representations of any kind, including but not limited to non-infringement, timeliness, and specific purposes.

User Notice

openGauss is an open-source, secure, and reliable relational OLTP database with ultimate performance. It is released with the Mulan PSL v2 protocol, allowing users to copy, use, modify, and distribute the source code.

The version number of openGauss is in X.Y.0-RCx format, where X.0.0 indicates a long-term support (LTS) release, X.Y.0-RCx represents a preview release, and X.Y.0 denotes a patch release. LTS releases are typically made every two years and are intended for large-scale deployment; preview releases are provided for beta testing; and patch releases may be issued as needed for critical bug fixes.

  • LTS releases are made every 2 years, with community support for 3 years.
  • Preview releases are made every 6 months, with community support for 6 months.

Versions

openGauss 5.0.0 is the third LTS version of openGauss, and its lifecycle is three years. This document applies only to the lite edition.

5.0.0 is compatible with the earlier versions. Main functions are as follows:

  • Inherited functions:

    • SQL standard syntax, UPSERT, data type, XML type, table, temporary table, global temporary table, foreign table, view, materialized view, index, foreign key, generalized inverted index (GIN), sequence, function, trigger, ROWNUM, MEDIAN aggregate function, JSONB data type, GB18030 character set, UPSERT subquery, and row-store execution to vectorized execution.

    • Stored procedure, commit/rollback in stored procedure, omission of parameter parentheses () from the stored procedure or function calling, stored procedure debugging, and autonomous transaction.

    • Security features such as authentication, permission management, network communication security, database audit, SM algorithm, and built-in role and permission management.

    • HA functions such as primary/standby two-node cluster, cascaded standby node, logical replication, ultimate RTO, standby node scale-out, and Paxos-based distributed consensus framework (DCF).

    • Range partitioning, global partitioned indexes, list partitioning, hash partitioning, and interval partitioning (automatic partitioning based on range partitioning).

    • Full physical backup, logical backup, standby node backup, incremental backup and restoration, and point-in-time recovery (PITR).

    • NUMA-aware high-performance optimization, parallel query, Global SysCache, and automatic eviction of unique SQL statements.

    • Storage features such as delayed standby node replay, logical replication on standby nodes, Xlog archiving on standby nodes, parallel logical decoding, hash indexes, and row-store table compression.

    • Load balancing and read/write isolation on the JDBC client, CMake script compilation, container-based deployment, IPv6 protocol, and postgis plug-in.

    • Toolchain: development tool DataStudio

    • Middleware: ShardingSphere, Kubernetes, and openLookeng.

    • Basic functions: standard SQL syntax, data types, tables (including temporary tables, global temporary tables, and foreign tables), views, materialized views, foreign keys, indexes (including B-tree indexes, GIN indexes, and hash indexes), sequences, functions, triggers, MEDIAN aggregate function, ROWNUM, UPSERT, JSONB data type, and GB18030 character set.

    • Enhanced SQL engine: range partitioning, global partitioned index, list partitioning, hash partitioning, automatic extended partitioning based on range partitioning, row-store execution to vectorized execution, autonomous transaction, parallel query, Global SysCache, IPv6 protocol, and PostGIS extensions.

    • Enhanced storage engine: delayed standby node replay, logical replication on standby nodes, parallel logical decoding, gray upgrade, rolling upgrade, hash index, unique primary key constraint for column-store tables, publication and subscription, and NUMA-aware high-performance optimization.

    • Stored procedure, commit/rollback in a stored procedure, omission of parameter parentheses () from the stored procedure or function calling, and stored procedure debugging.

    • Security functions: authentication, permission management, network communication security, database audit, Chinese national cryptographic algorithm, built-in role and permission management, and ANY permission management.

    • High availability: primary/standby two-node cluster, cascaded standby node, logical replication, ultimate RTO, standby node scale-out, and Paxos-based distributed consensus framework (DCF),

    • Backup and restoration: Full physical backup, logical backup, standby node backup, incremental backup and restoration, and point-in-time recovery (PITR).

    • O&M capabilities: database running metrics in WDRs, diagnosis view for slow SQL statements on the standby node, and automatic eviction of unique SQL statements.

    • JDBC client load is balanced and read and write are isolated.

    • Toolchain: development tool DataStudio, MySQL full migration tool, incremental migration tool, reverse migration tool, and data check tool.

    • Middleware: ShardingSphere and openLookeng.

    • Peripheral ecosystem: dblink, supporting openEuler, CentOS, and FusionOS.

    • Others: CMake script compilation, container-based deployment, and Kubernetes.

  • New functions:

    • High performance: The performance of basic operators is improved. (For details, see the feature description.)
    • High security: user-level audit.
    • Enterprise-level feature: event trigger.
    • Application development interface: Embedded C preprocessor
    • Application development interface: enhanced JDBC capabilities.
    • Middleware: ShardingSphere supports read/write isolation in multiple modes and cross-database query.
    • Middleware: 32-node networking performance of openGauss+ShardingSphere > 21 million tpmC
    • Toolchain: full-lifecycle data production tool DataKit
    • Toolchain: MySQL migration tool gs_rep_portal
    • Toolchain: MySQL incremental and reverse migration tool gs_replicate
    • Toolchain: gs_datacheck based on the Merkle tree
    • Compatibilities: Compatible with most common MySQL syntax, including data types, operators, system functions, DDL, DML, DCL, and PL/SQL, implementing application migration without modification.

  • Fixed defects:

    • I6NVAB: An error is reported during rollback and forcible rollback after gray upgrade from 3.0.3 to 5.0.0.
    • I6NK8U: When a publication/subscription name is changed to an existing name, the error message "ERROR: unsupported object class xxx" is displayed.
    • I6NK9V: The pg_os_threads view frequently allocates memory. As a result, the access efficiency is low.
    • I6LRP5: After a session exits or a dblink is deleted, the connection can still be queried in the remotely connected database.
    • I6JEG9: After a column is added to an column-store table and the transaction is rolled back, the system breaks down or an error is reported when the transaction is redone.
    • I6N2QD: When ESCAPE is used in SIMILAR TO, if the escape character is Chinese, an error is reported. If the LIKE escape character is Chinese, the operation is successful.
    • I6MOCS: In the B-compatible database, if the partition key of a level-2 partitioned table is the year function, an unknown error is reported when pg_get_tabledef is used after the ADD PARTITION operation is performed.
    • I6LMTU: In B-compatible mode, objects in backquotes are not supported.
    • I6K2BZ: Chameleon migration fails due to double quotation marks.
    • I6KIWQ: During Debezium+kafka incremental migration, the timestamp after the migration is incorrect.
    • I6I640: When the data check tool is used to check data in 150,000 tables, the check process is suspended.

Features

  • Standard SQL support

    Supports SQL-92, SQL-99, SQL:2003, and SQL:2011 standards, GBK and UTF-8 character sets, SQL standard functions and analytic functions, and stored procedures.

  • Database storage management

    Supports tablespaces where different tables can be stored in different locations.

  • Primary/standby deployment

    Supports the ACID properties, single-node fault recovery, primary/standby data synchronization, and primary/standby switchover.

  • Application programming interface (API)

    Supports standard JDBC 4.0 and ODBC 3.5 features, and Python and Go connection drivers.

  • Management tools

    Provides the installation and deployment tools, instance start and stop tools, backup and restoration tools, and upgrade tool, supports the full-lifecycle data production tool DataKit, MySQL full/incremental/reverse migration tools, and data check tool.

  • Security management

    Supports SSL network connections, user permission management, password management, security auditing, fine-grained ANY permission control, and other functions, to ensure data security at the management, application, system, and network layers.

New Features

This section describes openGauss 5.0.0. Compared with openGauss 3.1.0, it has the following new features:

  • High performance: The performance of basic operators is improved.

The performance of the scan operators and aggregate operators is optimized, improving the end-to-end performance by 37% in the TPC-H 100 GB data scenario. - Parser optimization: The method of searching for keywords in the parser is optimized. - Expression and operator optimization: The expression framework is flattened and the operator performance is optimized. - Inner Unique optimization. - Predicate optimization: New pushdown predicates are obtained through predicate equivalence inference. - Scan operator optimization: The index scanning and full table scanning operators are optimized. - Aggregate operator optimization: The performance of the aggregate operators is optimized.

  • High security: user-level audit.

    • User-level audit is supported. The GUC parameter full_audit_users is added to set the list of audited users. Audit logs are recorded for all SQL statements executed by users in the list. Administrators' operations can be fully audited to audit administrators' access to user data.
    • The audit operation can be configured based on client information. The GUC parameter no_audit_client is added to configure the list of clients that do not need to be audited. Audit logs are not recorded for specified client apps and IP addresses.
    • Audit logs are recorded for high-risk system function calls. The list of system functions that support audit recording must be specified in documents.

  • Enterprise-level feature: event trigger.

    • DDL operations in the current database and their target objects are captured and processed.
    • The following DDL events can be captured: ddl_command_start, ddl_command_end, sql_drop, and table_rewrite.

  • Application development interface: enhanced JDBC capabilities.

    • Quick load balancing can be triggered when the cluster status changes.
    • The heartbeat thread can be enabled to periodically maintain the heartbeat of the primary node. When the primary node is faulty, the old connection is quickly killed and the new connection is connected to the new primary node.

  • Middleware: ShardingSphere supports read/write isolation in multiple modes and cross-database query.

    • The read/write isolation of statements in a transaction is supported.
    • The computing capability of the aggregate operator is supported to implement associated query across sharded tables in the database.

  • Middleware: 32-node networking performance of openGauss+ShardingSphere > 21 million tpmC

    • ShardingSphere uses asynchronous JDBC at the backend to reduce connection consumption. openGauss uses the resource pooling architecture to improve the single-sharding capability. When 32 Kunpeng 920 (128 cores) nodes are used for networking (1 x shardingsphere-proxy ,11 x shardingsphere-jdbc, 20 x openGauss), the perfect sharding performance is greater than 21 million tpmc.

  • Toolchain: full-lifecycle data production tool DataKit

    • DataKit is positioned as a full-lifecycle data productivity tool of openGauss. It supports full-lifecycle data management, covering openGauss deployment, migration, development, and O&M.
    • DataKit is a tool kit of openGauss. It uses the browser/server (B/S) software architecture and provides basic software and hardware resource management capabilities such as servers and database instances.
    • In addition, on-demand deployment of function extensions is supported. Currently, the community provides function extensions such as installation and deployment, data migration, data development, and intelligent O&M.
    • The DataKit is also a tool development platform that allows users to implement their own functions based on extension interfaces and specifications. Function extensions can be dynamically loaded to and run on the DataKit or dynamically uninstalled from the DataKit. Extensions can invoke open interfaces of the platform and other extensions to obtain corresponding data and functions, implementing quick construction of featured functions.

  • Toolchain: MySQL migration tool gs_rep_portal

    • gs_rep_portal can connect to Debezium+kafka and gs_mysync to integrate full migration, incremental migration, and data check capabilities, implementing full migration, incremental migration, reverse migration, and data check.
    • Users are allowed to create parallel migration task flows and customize migration plans. Each migration step is automatically executed based on the preset execution sequence.
    • The migration progress (including the total amount, remaining amount and time, and replication delay) and statements that fail to be migrated can be displayed.

  • Toolchain: MySQL full migration tool gs_mysync

    • The gs_mysync (original Chameleon) full migration tool supports progress display and enhanced debugging. The full migration performance is greater than 300 MB/s, that is, 1 TB/h.

  • Toolchain: MySQL incremental and reverse migration tool gs_replicate

    • Incremental migration and reverse migration are incorporated into Debezium+kafka and integrated into gs_replicate. The incremental migration performance is greater than 30,000 TPS.

  • Toolchain: gs_datacheck based on the Merkle tree

    • The data check performance reaches 70 MB/s.
    • The row-level, column-level, and table-level data checks are supported.
    • Data exported from a full migration can be directly read and checked.

  • Compatibilities: Compatible with most common MySQL syntax, including data types, operators, system functions, DDL, DML, DCL, and PL/SQL, implementing application migration without modification.

    Version 5.0.0 supports the following syntax points: (Only some typical syntax points are listed. For details, see section "MySQL Compatibility" in the Data Migration Guide.)

    • Data types:

      (1) XML type (2) Binary data types and operators (3) Converting the output of the Boolea type to tinyint (4) Signed and unsigned tinyint types

    • System functions: ADDDATE(), ADDTIME(), CONVERT_TZ(), CURDATE(), DATE_ADD(), DATE_FORMAT(), DATE_SUB(), DATEDIFF(), DAY(), DAYNAME(), EXTRACT(), FROM_DAYS(), FROM_UNIXTIME(), GET_FORMAT(), LAST_DAY, LOCALTIME(), LOCALTIME, LOCALTIMESTAMP, LOCALTIMESTAMP(), MAKEDATE(), MAKETIME(), MONTH(), MONTHNAME(), NOW(), JSON_ARRAY(), JSON_OBJECT(), JSON_QUOTE(), JSON_CONTAINS(), JSON_CONTAINS_PATH(), JSON_EXTRACT(), JSON_UNQUOTE(), JSON_KEYS(), JSON_SEARCH(), JSON_APPEND(), JSON_ARRAY_APPEND(), JSON_ARRAY_INSERT(), JSON_INSERT(), JSON_MERGE(), JSON_MERGE_PATCH(), DATABASE(), ROW_COUNT() and ANY_VALUE()

    • DDLs:

      (1) The default character set and collation can be set and modified at the schema, table, and column levels. The character set of a table can be converted. (2) Columns can be added before the first column of a table or after a specified column. (3) The syntax for modifying column names and column definitions is compatible. (4) The ALTER TABLE tablename ADD CONSTRAINT UNIQUE INDEX|KEY syntax is supported. (5) The CREATE/ALTER/DROP DATABASE can be converted to the CREATE/ALTER/DROP SCHEMA when the character set is specified. (6) Indexes can be hidden and index visibility can be set. (7) Compatibility with uncommon options in table creation statements is supported, such as checksum and max_rows; (8) Columns can be specified when a table is created in CREATE TABLE SELECT mode. (9) Columns are case sensitive. (10) The dual tables are supported. (11) The authid can be used as the column name.

    • DMLs:

      (1) Column aliases can be specified when INSERT is used. (2) The SELECT INTO syntax is compatible. OUTFILE, DUMPFILE, and variables are added after SELECT INTO. (3) The LOAD DATA statement can be used to import table data. (4) The union query can be associated with columns of different types. (5) DISTINCT supports ORDER BY with expressions. (6) Foreign keys can be associated with non-unique indexes. (7) The SELECT statement supports the FORCE keyword to forcibly use the index. (8) The SELECT statement supports user-defined variables. (9) Views can be inserted, deleted, and updated. (10) In an INSERT statement, the right value of an expression following SET can contain the column name. (11) Multiple partitions can be specified to query data. (12) The default function can be used for SQL statements.

    • DCLs:

      (1) The syntax tree of SET TRANSACTION can be used to set the session level, global isolation level, and read/write permission. (2) The event scheduler can be used to periodically execute specified statements at intervals, create, modify, and delete events, and support SHOW EVENTS. (3) LOCK TABLE and UNLOCK TABLE are supported. (4) SHOW STATUS, SHOW TABLE STATUS, SHOW PRIVILEGES, SHOW WARNING, and SHOW ERRORS are supported. (5) The IF NOT EXISTS option is supported when a user is created. (6) Users can be specified in the 'user'@'host' format.

    • PLs/SQLs:

      (1) The WHILE loops with labels are supported. (2) The CASE WHEN condition control syntax is supported. (3) The IF_THEN control syntax is supported. (4) The cursor-related syntax is supported. (5) The stored procedure processes the condition. (6) The DROP TRIGGER supports cascading deletion without specifying the table name. (7) The DO statement is supported. (8) The stored procedure supports REPEAT. (9) The CREATE PROCEDURE SELECT syntax is supported. (10) The stored procedure supports RETURN. (11) The as $$begin and end; $$language plpgsql are not added to the beginning and end of CREATE FUNCTION. (12) A slash (/) is not added at the end of CREATE TRIGGER. (13) DECLARE HANDLER, CONTINUE HANDLER, and EXIT HANDLERS are supported.

    • Other syntax compatibility:

      (1) Users are allowed to customize variables to save the result of the SELECT statement. (2) Seven character sequences are supported: utf8_general_ci, utf8_bin, utf8_unicode_ci, utf8mb4_general_ci, utf8mb4_bin, and utf8mb4_unicode_ci and binary. (3) The utf8mb4 character set is supported. (4) The operator behavior is the same as that of MySQL. (5) Character strings can be enclosed in double quotation marks.

Important Notes

  • For details about technical specifications, see section "Technical Specifications" in Technical White Paper.
  • Currently, openGauss supports a maximum of eight standby nodes. The lite edition does not have CM management. If one primary node and multiple standby nodes are used and the primary node is faulty, promote a standby node with more logs to primary, preventing other standby nodes from being rebuilt.
  • For the lite edition, you are advised to deploy one primary node and two standby nodes to ensure database reliability and availability.
  • The lite edition does not support two-city three-DC deployment.

Known Issues

  • openGauss Lite cannot monitor storage space, file permission, and slow disks. When the storage space is full or the file permission is abnormal, the database exits and the corresponding information is recorded in logs. On a slow disk, the response to database operations is slower than usual.
  • openGauss Lite has only database kernel capabilities and does not support primary/standby monitoring or switchovers. If the primary and standby nodes are disconnected and their logs do not match, the HA cluster needs to be rebuilt.
  • By default, the OM starts the primary and standby databases based on the initial primary/standby relationship. If an application performs a primary/standby switchover on the databases, the application needs to notify the OM of the new primary/standby relationship to prevent the HA cluster from being rebuilt due to incorrect primary/standby relationship.
  • The read-only mode of the standby node and cascaded standby node is incompatible with the ultimate RTO feature. If the ultimate RTO feature is enabled, disable the read-only mode of the standby node and cascaded standby node.

Common Vulnerabilities and Exposures (CVEs)

This is the tenth release of openGauss. The disclosed CVEs have been fixed.

Resolved Issues

This is the tenth release of openGauss. The disclosed CVEs have been fixed.

Source Code

openGauss contains the following 16 code repositories.

Contribution

Participating in Contribution

As an openGauss user, you can contribute to the openGauss community in multiple ways. For details about how to contribute to the community, see Contribution. Here, some methods are listed for reference.

Special Interest Groups (SIGs)

openGauss brings together people of common interest to form different SIGs. For details about existing SIGs, see the SIG list.

You are welcome to join an existing SIG or create a SIG. For details about how to create a SIG, see Special Interest Group (SIG).

Mail List and Issues

You are welcome to actively help users solve problems raised in the mail list and issues (including code repository issues). In addition, you can commit an issue. All these will help the openGauss community develop better.

Documents

You can contribute to the community by committing code. We also welcome your feedback on problems and difficulties, or suggestions on improving the usability and integrity of documents, for example, problems encountered when obtaining software or documents and difficulties encountered when using the system. You are welcome to pay attention to and help us improve the documentation module of the openGauss community.

Acknowledgement

We sincerely thank all the members who participated in and assisted in the openGauss project, including Huawei, ENMOTECH, VASTDATA, China Unicom, GBASE, Greater Bay Area National Center of Technology Innovation (GBA NCTI), iSoftStone, Beijing SuperMap Software Co., Ltd., China Minsheng Banking, SHENTONGDATA, School of Computer Science and Engineering of UESTC, School of Information Engineering of Ningxia University, School of Software Engineering of SCUT, School of Computer Science and Engineering of Sun Yat-sen University, School of Information Engineering of Minzu University of China, Xi'an Rita Network Technology Co., Ltd., SphereEx, and SANGFOR. It is your hard work to make the version released successfully and provide the possibility for the better development of openGauss.