Inline Expression #

Motivation #

Configuration simplicity and unity are two main problems that inline expression intends to solve.

In complex sharding rules, with more data nodes, a large number of configuration repetitions make configurations difficult to maintain. Inline expressions can simplify data node configuration work.

Java code is not helpful in the unified management of common configurations. By writing sharding algorithms with inline expressions, users can store rules together, making them easier to be browsed and stored.

Syntax Explanation #

The use of inline expressions is really direct. Users only need to configure ${ expression } or $->{ expression } to identify them. ShardingSphere currently supports the configurations of data nodes and sharding algorithms. Inline expressions use Groovy syntax, which can support all kinds of operations, including inline expressions. For example:

${begin..end} means range

${[unit1, unit2, unit_x]} means enumeration

If there are many continuous ${ expression } or $->{ expression } expressions, according to each sub-expression result, the ultimate result of the whole expression will be in cartesian combination.

For example, the following inline expression:

${['online', 'offline']}_table${1..3}

Will be parsed as:

online_table1, online_table2, online_table3, offline_table1, offline_table2, offline_table3

Configuration #

Data Node #

For evenly distributed data nodes, if the data structure is as follow:

db0
  ├── t_order0
  └── t_order1
db1
  ├── t_order0
  └── t_order1

It can be simplified by inline expression as:

db${0..1}.t_order${0..1}

db$->{0..1}.t_order$->{0..1}

For self-defined data nodes, if the data structure is:

db0
  ├── t_order0
  └── t_order1
db1
  ├── t_order2
  ├── t_order3
  └── t_order4

It can be simplified by inline expression as:

db0.t_order${0..1},db1.t_order${2..4}

db0.t_order$->{0..1},db1.t_order$->{2..4}

For data nodes with prefixes, inline expression can also be used to configure them flexibly, if the data structure is:

db0
  ├── t_order_00
  ├── t_order_01
  ├── t_order_02
  ├── t_order_03
  ├── t_order_04
  ├── t_order_05
  ├── t_order_06
  ├── t_order_07
  ├── t_order_08
  ├── t_order_09
  ├── t_order_10
  ├── t_order_11
  ├── t_order_12
  ├── t_order_13
  ├── t_order_14
  ├── t_order_15
  ├── t_order_16
  ├── t_order_17
  ├── t_order_18
  ├── t_order_19
  └── t_order_20
db1
  ├── t_order_00
  ├── t_order_01
  ├── t_order_02
  ├── t_order_03
  ├── t_order_04
  ├── t_order_05
  ├── t_order_06
  ├── t_order_07
  ├── t_order_08
  ├── t_order_09
  ├── t_order_10
  ├── t_order_11
  ├── t_order_12
  ├── t_order_13
  ├── t_order_14
  ├── t_order_15
  ├── t_order_16
  ├── t_order_17
  ├── t_order_18
  ├── t_order_19
  └── t_order_20

Users can configure separately, data nodes with prefixes first, those without prefixes later, and automatically combine them with the cartesian product feature of inline expressions. The example above can be simplified by inline expression as:

db${0..1}.t_order_0${0..9}, db${0..1}.t_order_${10..20}

db$->{0..1}.t_order_0$->{0..9}, db$->{0..1}.t_order_$->{10..20}

Sharding Algorithm #

For single sharding SQL that uses = and IN, inline expression can replace codes in configuration.

Inline expression is a piece of Groovy code in essence, which can return the corresponding real data source or table name according to the computation method of sharding keys.

For example, sharding keys with the last number 0 are routed to the data source with the suffix of 0, those with the last number 1 are routed to the data source with the suffix of 1, the rest goes on in the same way. The inline expression used to indicate sharding algorithm is:

ds${id % 10}

ds$->{id % 10}