ShardingSphere built-in algorithms provide a variety of sharding algorithms, which can be divided into automatic sharding algorithms, standard sharding algorithms, composite sharding algorithms, and hint sharding algorithms, and can meet the needs of most business scenarios of users.
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.
Type: MOD
Attributes:
| Name | DataType | Description |
|---|---|---|
| sharding-count | int | Sharding count |
Type: HASH_MOD
Attributes:
| Name | DataType | Description |
|---|---|---|
| sharding-count | int | Sharding count |
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 |
Type: BOUNDARY_RANGE
Attributes:
| Name | DataType | Description |
|---|---|---|
| sharding-ranges | String | Range of sharding border, multiple boundaries separated by commas |
Type: AUTO_INTERVAL
Attributes:
| Name | DataType | Description |
|---|---|---|
| datetime-lower | String | Shard datetime begin boundary, pattern: yyyy-MM-dd HH:mm:ss |
| datetime-upper | String | Shard datetime end boundary, pattern: yyyy-MM-dd HH:mm:ss |
| sharding-seconds | long | Max seconds for the data in one shard, allows sharding key timestamp format seconds with time precision, but time precision after seconds is automatically erased |
Apache ShardingSphere built-in standard sharding algorithm are:
With Groovy expressions, InlineShardingStrategy 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 |
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 datetime-pattern, 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 |
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 https://github.com/apache/shardingsphere/issues/14047.
Type：COSID_INTERVAL
Attributes：
| Name | DataType | Description | Default Value |
|---|---|---|---|
| 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 datetime-interval-unit. 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 ID sharding algorithm with fixed time range implemented by 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 https://github.com/apache/shardingsphere/issues/14047.
Type：COSID_INTERVAL_SNOWFLAKE
Attributes：
| Name | DataType | Description | Default Value |
|---|---|---|---|
| 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 datetime-interval-unit. 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 |
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 |
Please refer to Inline Expression 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 |
Please refer to Inline Expression for more details.
Type: COMPLEX_INLINE
| Name | DataType | Description | Default Value |
|---|---|---|---|
| algorithm-expression | String | Inline expression sharding algorithm | ${value} |
Realize custom extension by configuring the sharding strategy type and algorithm class name.
CLASS_BASED allows additional custom properties to be passed into the algorithm class. The passed properties can be retrieved through the java.util.Properties class instance with the property name props.
Refer to Git’s org.apache.shardingsphere.example.extension.sharding.algortihm.classbased.fixture.ClassBasedStandardShardingAlgorithmFixture.
Type：CLASS_BASED
Attributes：
| Name | DataType | Description |
|---|---|---|
| strategy | String | Sharding strategy type, support STANDARD, COMPLEX or HINT (case insensitive) |
| algorithmClassName | String | Fully qualified name of sharding algorithm |
rules:
- !SHARDING
tables:
t_order:
actualDataNodes: ds_${0..1}.t_order_${0..1}
tableStrategy:
standard:
shardingColumn: order_id
shardingAlgorithmName: t_order_inline
keyGenerateStrategy:
column: order_id
keyGeneratorName: snowflake
t_order_item:
actualDataNodes: ds_${0..1}.t_order_item_${0..1}
tableStrategy:
standard:
shardingColumn: order_id
shardingAlgorithmName: t_order_item_inline
keyGenerateStrategy:
column: order_item_id
keyGeneratorName: snowflake
t_account:
actualDataNodes: ds_${0..1}.t_account_${0..1}
tableStrategy:
standard:
shardingAlgorithmName: t_account_inline
keyGenerateStrategy:
column: account_id
keyGeneratorName: snowflake
defaultShardingColumn: account_id
bindingTables:
- t_order,t_order_item
broadcastTables:
- t_address
defaultDatabaseStrategy:
standard:
shardingColumn: user_id
shardingAlgorithmName: database_inline
defaultTableStrategy:
none:
shardingAlgorithms:
database_inline:
type: INLINE
props:
algorithm-expression: ds_${user_id % 2}
t_order_inline:
type: INLINE
props:
algorithm-expression: t_order_${order_id % 2}
t_order_item_inline:
type: INLINE
props:
algorithm-expression: t_order_item_${order_id % 2}
t_account_inline:
type: INLINE
props:
algorithm-expression: t_account_${account_id % 2}
keyGenerators:
snowflake:
type: SNOWFLAKE