Sharding Algorithm

Additionally, considering the complexity of business scenarios, the built-in algorithm also provides a way to customize the sharding algorithm. Users can complete complex sharding logic by writing java code.

Modulo Sharding Algorithm

Type: MOD

Attributes:

Hash Modulo Sharding Algorithm

Type: HASH_MOD

Attributes:

Name	DataType	Description
sharding-count	int	Sharding count

Volume Based Range Sharding Algorithm

Type: VOLUME_RANGE

Attributes:

Name	DataType	Description
range-lower	long	Range lower bound, throw exception if lower than bound
range-upper	long	Range upper bound, throw exception if upper than bound
sharding-volume	long	Sharding volume

Boundary Based Range Sharding Algorithm

Type: BOUNDARY_RANGE

Attributes:

Name	DataType	Description
sharding-ranges	String	Range of sharding border, multiple boundaries separated by commas

Auto Interval Sharding Algorithm

Type: AUTO_INTERVAL

Apache ShardingSphere built-in standard sharding algorithm are:

Inline Sharding Algorithm

With Groovy expressions, provides single-key support for the sharding operation of = and IN in SQL. Simple sharding algorithms can be used through a simple configuration to avoid laborious Java code developments. For example, t_user_$->{u_id % 8} means table t_user is divided into 8 tables according to u_id, with table names from t_user_0 to t_user_7. Please refer to Inline Expression for more details.

Type: INLINE

Attributes:

Name	DataType	Description	Default Value
algorithm-expression	String	Inline expression sharding algorithm	-
allow-range-query-with-inline-sharding (?)	boolean	Whether range query is allowed. Note: range query will ignore sharding strategy and conduct full routing	false

Interval Sharding Algorithm

This algorithm actively ignores the time zone information of datetime-pattern. This means that when datetime-lower, datetime-upper and the incoming shard key contain time zone information, time zone conversion will not occur due to time zone inconsistencies. When the incoming sharding key is java.time.Instant, there is a special case, which will carry the time zone information of the system and convert it into the string format of , and then proceed to the next sharding.

Type: INTERVAL

Attributes:

Name	DataType	Description	Default Value
datetime-pattern	String	Timestamp pattern of sharding value, must can be transformed to Java LocalDateTime. For example: yyyy-MM-dd HH:mm:ss, yyyy-MM-dd or HH:mm:ss etc. But Gy-MM etc. related to `java.time.chrono.JapaneseDate` are not supported	-
datetime-lower	String	Datetime sharding lower boundary, pattern is defined `datetime-pattern`	-
datetime-upper (?)	String	Datetime sharding upper boundary, pattern is defined `datetime-pattern`	Now
sharding-suffix-pattern	String	Suffix pattern of sharding data sources or tables, must can be transformed to Java LocalDateTime, must be consistent with `datetime-interval-unit`. For example: yyyyMM	-
datetime-interval-amount (?)	int	Interval of sharding value, after which the next shard will be entered	1
datetime-interval-unit (?)	String	Unit of sharding value interval, must can be transformed to Java ChronoUnit’s Enum value. For example: MONTHS	DAYS

Fixed interval sharding algorithm provided by CosId

A fixed time range sharding algorithm implemented by the tool class based on me.ahoo.cosid:cosid-core. When the sharding key is a JSR-310 containing class or a time-related class, it will be converted to java.time.LocalDateTime before the next sharding. See the discussion at .

Type：COSID_INTERVAL

Attributes：

Name	DataType	Description
zone-id	String	Time zone, which must follow the contained value of `java.time.ZoneId`. For example: Asia/Shanghai
logic-name-prefix	String	Prefix pattern of sharding data sources or tables
datetime-lower	String	Datetime sharding lower boundary, pattern is consistent with the timestamp format of `yyyy-MM-dd HH:mm:ss`
datetime-upper	String	Datetime sharding upper boundary, pattern is consistent with the timestamp format of `yyyy-MM-dd HH:mm:ss`
sharding-suffix-pattern	String	Suffix pattern of sharding data sources or tables, must can be transformed to Java LocalDateTime, must be consistent with . For example: yyyyMM
datetime-interval-unit	String	Unit of sharding value interval, must can be transformed to Java ChronoUnit’s Enum value. For example: MONTHS
datetime-interval-amount	int	Interval of sharding value, after which the next shard will be entered

Snowflake key-based fixed interval sharding algorithm provided by CosId

Type：COSID_INTERVAL_SNOWFLAKE

Attributes：

Modulo sharding algorithm provided by CosId

Modulo sharding algorithm implemented by the tool class based on me.ahoo.cosid:cosid-core. See the discussion at https://github.com/apache/shardingsphere/issues/14047 .

Type: COSID_MOD

Attributes:

Name	DataType	Description
mod	int	Sharding count
logic-name-prefix	String	Prefix pattern of sharding data sources or tables

Complex Inline Sharding Algorithm

Please refer to for more details.

Type: COMPLEX_INLINE

Name	DataType	Description	Default Value
sharding-columns (?)	String	sharing column names	-
algorithm-expression	String	Inline expression sharding algorithm	-
allow-range-query-with-inline-sharding (?)	boolean	Whether range query is allowed. Note: range query will ignore sharding strategy and conduct full routing	false

Hint Inline Sharding Algorithm

Please refer to Inline Expression for more details.

Type: COMPLEX_INLINE

Name	DataType	Description	Default Value
algorithm-expression	String	Inline expression sharding algorithm	${value}

Realize custom extension by configuring the sharding strategy type and algorithm class name. CLASS_BASED allows additional custom properties to be passed into the algorithm class. The passed properties can be retrieved through the java.util.Properties class instance with the property name . Refer to Git’s org.apache.shardingsphere.example.extension.sharding.algortihm.classbased.fixture.ClassBasedStandardShardingAlgorithmFixture.

Attributes：

When using data sharding, configure the corresponding data sharding algorithm under the shardingAlgorithms attribute.