What's new in Apache ShardingSphere 5.3.0?

The latest release of Apache ShardingSphere includes improvements to features, performance, testing, documentation, examples, and more.

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After 1.5 months in development, Apache ShardingSphere 5.3.0 has been released. Our community merged 687 PRs from contributors around the world.

The new release has been improved in terms of features, performance, testing, documentation, examples, etc.

The 5.3.0 release brings the following highlights:

Support fuzzy query for CipherColumn.
Support Datasource-level heterogeneous database.
Support checkpoint resume for data consistency check.
Automatically start a distributed transaction while executing DML statements across multiple shards.

Additionally, release 5.3.0 also brings the following adjustments:

Remove the Spring configuration.
Systematically refactor the DistSQL syntax.
Refactor the configuration format of ShardingSphere-Proxy.

4 highlights of the Apache ShardingSphere release

1. Support fuzzy query for CipherColumn

In previous versions, ShardingSphere's Encrypt feature didn't support using the LIKE operator in SQL.

For a while, users strongly requested adding the LIKE operator to the Encrypt feature. Usually, encrypted fields are mainly of the string type, and it is a common practice for the string to execute LIKE.

To minimize friction in accessing the Encrypt feature, our community has initiated a discussion about the implementation of encrypted LIKE.

Since then, we've received a lot of feedback.

Some community members even contributed their original encryption algorithm implementation supporting fuzzy queries after fully investigating conventional solutions.

The relevant issue can be found here.
For the algorithm design, please refer to the attachment within the issue.

The [single-character abstract algorithm] contributed by the community members is implemented as CHAR_DIGEST_LIKE in the ShardingSphere encryption algorithm SPI.

2. Support datasource-level heterogeneous database

ShardingSphere supports a database gateway, but its heterogeneous capability is limited to the logical database in previous versions. This means that all the data sources under a logical database must be of the same database type.

This new release supports datasource-level heterogeneous databases at the kernel level. This means the datasources under a logical database can be different database types, allowing you to use various databases to store data.

Combined with ShardingSphere's SQL dialect conversion capability, this new feature significantly enhances ShardingSphere's heterogeneous data gateway capability.

3. Data migration: support checkpoint resume for data consistency check

Data consistency checks happen at the later stage of data migration.

Previously, the data consistency check was triggered and stopped by DistSQL (Distributed SQL). If a large amount of data was migrated and the data consistency check was stopped for any reason, the check would've had to be started again—which is sub-optimal and affects user experience.

ShardingSphere 5.3.0 now supports checkpoint storage, which means data consistency checks can be resumed from the checkpoint.

For example, if data is being verified during data migration and the user stops the verification for some reason, with the verification progress (finished_percentage) being 5%, then:

mysql> STOP MIGRATION CHECK 'j0101395cd93b2cfc189f29958b8a0342e882';
Query OK, 0 rows affected (0.12 sec)

mysql> SHOW MIGRATION CHECK STATUS 'j0101395cd93b2cfc189f29958b8a0342e882';
+--------+--------+---------------------+-------------------+-------------------------+-------------------------+------------------+---------------+
| tables | result | finished_percentage | remaining_seconds | check_begin_time        | check_end_time          | duration_seconds | error_message |
+--------+--------+---------------------+-------------------+-------------------------+-------------------------+------------------+---------------+
| sbtest | false  | 5                   | 324               | 2022-11-10 19:27:15.919 | 2022-11-10 19:27:35.358 | 19               |               |
+--------+--------+---------------------+-------------------+-------------------------+-------------------------+------------------+---------------+
1 row in set (0.02 sec)

In this case, the user restarts the data verification. But the work does not have to restart from the beginning. The verification progress (finished_percentage) remains at 5%.

mysql> START MIGRATION CHECK 'j0101395cd93b2cfc189f29958b8a0342e882';
Query OK, 0 rows affected (0.35 sec)

mysql> SHOW MIGRATION CHECK STATUS 'j0101395cd93b2cfc189f29958b8a0342e882';
+--------+--------+---------------------+-------------------+-------------------------+----------------+------------------+---------------+
| tables | result | finished_percentage | remaining_seconds | check_begin_time        | check_end_time | duration_seconds | error_message |
+--------+--------+---------------------+-------------------+-------------------------+----------------+------------------+---------------+
| sbtest | false  | 5                   | 20                | 2022-11-10 19:28:49.422 |                | 1                |               |
+--------+--------+---------------------+-------------------+-------------------------+----------------+------------------+---------------+
1 row in set (0.02 sec)

Limitation: this new feature is unavailable with the CRC32_MATCH algorithm because the algorithm calculates all data at once.

4. Automatically start a distributed transaction while executing DML statements across multiple shards

Previously, even with XA and other distributed transactions configured, ShardingSphere could not guarantee the atomicity of DML statements that are routed to multiple shards—if users didn't manually enable the transaction.

Take the following SQL as an example:

insert into account(id, balance, transaction_id) values
(1, 1, 1),(2, 2, 2),(3, 3, 3),(4, 4, 4),
(5, 5, 5),(6, 6, 6),(7, 7, 7),(8, 8, 8);

When this SQL is sharded according to id mod 2, the ShardingSphere kernel layer will automatically split it into the following two SQLs and route them to different shards for execution:

insert into account(id, balance, transaction_id) values
(1, 1, 1),(3, 3, 3),(5, 5, 5),(7, 7, 7);

insert into account(id, balance, transaction_id) values
(2, 2, 2),(4, 4, 4),(6, 6, 6),(8, 8, 8);

If the user does not manually start the transaction, and one of the sharded SQL fails to execute, the atomicity cannot be guaranteed because the successful operation cannot be rolled back.

ShardingSphere 5.3.0 is optimized in terms of distributed transactions. If distributed transactions are configured in ShardingSphere, they can be automatically started when DML statements are routed to multiple shards. This way, we can ensure atomicity when executing DML statements.

3 improvements made in Apache ShardingSphere

1. Remove Spring configuration

In earlier versions, ShardingSphere-JDBC provided services in the format of DataSource. If you wanted to introduce ShardingSphere-JDBC without modifying the code in the Spring/Spring Boot project, you needed to use modules such as Spring/Spring Boot Starter provided by ShardingSphere.

Although ShardingSphere supports multiple configuration formats, it also has the following problems:

When API changes, many config files need to be adjusted, which is a heavy workload.
The community has to maintain multiple config files.
The lifecycle management of Spring bean is susceptible to other dependencies of the project, such as PostProcessor failure.
Spring Boot Starter and Spring NameSpace are affected by Spring, and their configuration styles are different from YAML.
Spring Boot Starter and Spring NameSpace are affected by the version of Spring. When users access them, the configuration may not be identified, and dependency conflicts may occur. For example, Spring Boot versions 1.x and 2.x have different configuration styles.

ShardingSphere 5.1.2 first supported the introduction of ShardingSphere-JDBC in the form of JDBC Driver. That means applications only need to configure the Driver provided by ShardingSphere at the JDBC URL before accessing ShardingSphere-JDBC.

Removing the Spring configuration simplifies and unifies the configuration mode of ShardingSphere. This adjustment not only simplifies the configuration of ShardingSphere when using different configuration modes but also reduces maintenance work for the ShardingSphere community.

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2. Systematically refactor the DistSQL syntax

One of the characteristics of Apache ShardingSphere is its flexible rule configuration and resource control capability.

DistSQL is ShardingSphere's SQL-like operating language. It's used the same way as standard SQL and is designed to provide incremental SQL operation capability.

ShardingSphere 5.3.0 systematically refactors DistSQL. The community redesigned the syntax, semantics, and operating procedure of DistSQL. The new version is more consistent with ShardingSphere's design philosophy and focuses on a better user experience.

Please refer to the latest ShardingSphere documentation for details. A DistSQL roadmap will be available soon, and you're welcome to leave your feedback.

3. Refactor the configuration format of ShardingSphere-Proxy

In this update, ShardingSphere-Proxy has adjusted the configuration format and reduced the config files required for startup.

server.yaml before refactoring:

rules:
  - !AUTHORITY
    users:
      - root@%:root
      - sharding@:sharding
    provider:
      type: ALL_PERMITTED
  - !TRANSACTION
    defaultType: XA
    providerType: Atomikos
  - !SQL_PARSER
    sqlCommentParseEnabled: true
    sqlStatementCache:
      initialCapacity: 2000
      maximumSize: 65535
    parseTreeCache:
      initialCapacity: 128
      maximumSize: 1024

server.yaml after refactoring:

authority:
  users:
    - user: root@%
      password: root
    - user: sharding
      password: sharding
  privilege:
    type: ALL_PERMITTED

transaction:
  defaultType: XA
  providerType: Atomikos
sqlParser:
  sqlCommentParseEnabled: true
  sqlStatementCache:
    initialCapacity: 2000
    maximumSize: 65535
  parseTreeCache:
    initialCapacity: 128
    maximumSize: 1024

In ShardingSphere 5.3.0, server.yaml is no longer required to start Proxy. If no config file is provided by default, Proxy provides the default account root/root.

ShardingSphere is completely committed to becoming cloud-native. Thanks to DistSQL, ShardingSphere-Proxy's config files can be further simplified, which is more friendly to container deployment.

Release Notes

API Changes

DistSQL: refactor syntax API; please refer to the user manual
Proxy: change the configuration style of the global rule, remove the exclamation mark
Proxy: allow zero-configuration startup, enable the default account root/root when there is no Authority configuration
Proxy: remove the default logback.xml and use API initialization
JDBC: remove the Spring configuration and use Driver + YAML configuration instead

Enhancements

DistSQL: new syntax REFRESH DATABASE METADATA, refresh logic database metadata
Kernel: support DistSQL REFRESH DATABASE METADATA to load configuration from the governance center and rebuild MetaDataContext
Support PostgreSQL/openGauss setting transaction isolation level
Scaling: increase inventory task progress update frequency
Scaling: DATA_MATCH consistency check support checkpoint resume
Scaling: support drop consistency check job via DistSQL
Scaling: rename column from sharding_total_count to job_item_count in job list DistSQL response
Scaling: add a sharding column in incremental task SQL to avoid broadcast routing
Scaling: sharding column could be updated when generating SQL
Scaling: improve column value reader for DATA_MATCH consistency check
DistSQL: encrypt DistSQL syntax optimization, support like query algorithm
DistSQL: add properties value check when REGISTER STORAGE UNIT
DistSQL: remove useless algorithms at the same time when DROP RULE
DistSQL: EXPORT DATABASE CONFIGURATION supports broadcast tables
DistSQL: REGISTER STORAGE UNIT supports heterogeneous data sources
Encrypt: support Encrypt LIKE feature
Automatically start distributed transactions when executing DML statements across multiple shards
Kernel: support client \d for PostgreSQL and openGauss
Kernel: support select group by, order by statement when a column contains null values
Kernel: support parse RETURNING clause of PostgreSQL/openGauss Insert
Kernel: SQL HINT performance improvement
Kernel: support mysql case when then statement parse
Kernel: support data source level heterogeneous database gateway
(Experimental) Sharding: add sharding cache plugin
Proxy: support more PostgreSQL datetime formats
Proxy: support MySQL COM_RESET_CONNECTION
Scaling: improve MySQLBinlogEventType.valueOf to support unknown event type
Kernel: support case when for federation

Bug Fix

Scaling: fix barrier node created at job deletion
Scaling: fix part of columns value might be ignored in DATA_MATCH consistency check
Scaling: fix jdbc url parameters are not updated in consistency check
Scaling: fix tables sharding algorithm type INLINE is case-sensitive
Scaling: fix incremental task on MySQL require mysql system database permission
Proxy: fix the NPE when executing select SQL without storage node
Proxy: support DATABASE_PERMITTED permission verification in unicast scenarios
Kernel: fix the wrong value of worker-id in show compute nodes
Kernel: fix route error when the number of readable data sources and weight configurations of the Weight algorithm are not equal
Kernel: fix multiple groups of readwrite-splitting refer to the same load balancer name, and the load balancer fails problem
Kernel: fix can not disable and enable compute node problem
JDBC: fix data source is closed in ShardingSphereDriver cluster mode when startup problem
Kernel: fix wrong rewrite result when part of logical table name of the binding table is consistent with the actual table name, and some are inconsistent
Kernel: fix startup exception when use SpringBoot without configuring rules
Encrypt: fix null pointer exception when Encrypt value is null
Kernel: fix oracle parsing does not support varchar2 specified type
Kernel: fix serial flag judgment error within the transaction
Kernel: fix cursor fetch error caused by wasNull change
Kernel: fix alter transaction rule error when refresh metadata
Encrypt: fix EncryptRule cast to TransparentRule exception that occurs when the call procedure statement is executed in the Encrypt scenario
Encrypt: fix exception which caused by ExpressionProjection in shorthand projection
Proxy: fix PostgreSQL Proxy int2 negative value decoding incorrect
Proxy: PostgreSQL/openGauss support describe insert returning clause
Proxy: fix gsql 3.0 may be stuck when connecting Proxy
Proxy: fix parameters are missed when checking SQL in Proxy backend
Proxy: enable MySQL Proxy to encode large packets
Kernel: fix oracle parse comment without whitespace error
DistSQL: fix show create table for encrypt table

Refactor

Scaling: reverse table name and column name when generating SQL if it's SQL keyword
Scaling: improve incremental task failure handling
Kernel: governance center node adjustment, unified hump to underscore