partitionProcessor

逻辑优化partitionProcessor会计算出Datasource的possibleAccessPath prune时候，会参照datasource 的allconds

var optRuleList = []logicalOptRule{
	&partitionProcessor{},
}
// partitionProcessor rewrites the ast for table partition.
//
// create table t (id int) partition by range (id)
//   (partition p1 values less than (10),
//    partition p2 values less than (20),
//    partition p3 values less than (30))
//
// select * from t is equal to
// select * from (union all
//      select * from p1 where id < 10
//      select * from p2 where id < 20
//      select * from p3 where id < 30)
//
// partitionProcessor is here because it's easier to prune partition after predicate push down.

首先处理分区，然后会根据hints: IndexHints, indexMergeHints, preferStoreType 以及 Table自己的Index(在getPossibleAccessPath中会遍历TableInfo.Indices), 组合列举出所有的accessPath. 最后会去掉违反IsolationRead的path.

pruneRangePartition

REATE TABLE employees (
    id INT NOT NULL,
    fname VARCHAR(30),
    lname VARCHAR(30),
    hired DATE NOT NULL DEFAULT '1970-01-01',
    separated DATE NOT NULL DEFAULT '9999-12-31',
    job_code INT NOT NULL,
    store_id INT NOT NULL
)

PARTITION BY RANGE (store_id) (
    PARTITION p0 VALUES LESS THAN (6),
    PARTITION p1 VALUES LESS THAN (11),
    PARTITION p2 VALUES LESS THAN (16),
    PARTITION p3 VALUES LESS THAN (21)
);

The optimizer can prune partitions through WHERE conditions in the following two scenarios:

partition_column = constant partition_column IN (constant1, constant2, ..., constantN)

pruneHashPartition

CREATE TABLE employees (
    id INT NOT NULL,
    fname VARCHAR(30),
    lname VARCHAR(30),
    hired DATE NOT NULL DEFAULT '1970-01-01',
    separated DATE NOT NULL DEFAULT '9999-12-31',
    job_code INT,
    store_id INT
)

PARTITION BY HASH(store_id)
PARTITIONS 4;

pruneListPartition

CREATE TABLE employees (
    id INT NOT NULL,
    fname VARCHAR(30),
    lname VARCHAR(30),
    hired DATE NOT NULL DEFAULT '1970-01-01',
    separated DATE NOT NULL DEFAULT '9999-12-31',
    job_code INT,
    store_id INT
)
PARTITION BY LIST(store_id) (
    PARTITION pNorth VALUES IN (3,5,6,9,17),
    PARTITION pEast VALUES IN (1,2,10,11,19,20),
    PARTITION pWest VALUES IN (4,12,13,14,18),
    PARTITION pCentral VALUES IN (7,8,15,16)
);

makeUnionAllChildren

对于每个Partition对应的Datasource, 生成所有可能的AccessPath

possibleAccessPaths

参考

揭秘 TiDB 新优化器：Cascades Planner 原理解析

Trash

分区剪枝

func (s *partitionProcessor) prune(ds *DataSource) (LogicalPlan, error) {
	pi := ds.tableInfo.GetPartitionInfo()
	if pi == nil {
		return ds, nil
	}
	// Try to locate partition directly for hash partition.
	if pi.Type == model.PartitionTypeHash {
		return s.processHashPartition(ds, pi)
	}
	if pi.Type == model.PartitionTypeRange {
		return s.processRangePartition(ds, pi)
	}

	// We haven't implement partition by list and so on.
	return s.makeUnionAllChildren(ds, pi, fullRange(len(pi.Definitions)))
}

TiDB中分区主要有Range和Hash两种,一下文字摘自book.tidb.io

Range分区

Range 分区是指将数据行按分区表达式计算的值都落在给定的范围内。在 Range 分区中，你必须为每个分区指定值的范围，并且不能有重叠，通过使用 VALUES LESS THAN 操作进行定义。目前只支持单列的 Range 分区表。

Hash分区

Hash 分区主要用于保证数据均匀地分散到一定数量的分区里面。在 Hash 分区中，你只需要指定分区的数量。使用 Hash 分区时，需要在 CREATE TABLE 后面添加 PARTITION BY HASH (expr) PARTITIONS num ，其中：expr 是一个返回整数的表达式，它可以是一个列名，但这一列的类型必须整数类型；num 是一个正整数，表示将表划分为多少个分区。

prune parition 调用图

每个partition 会生成一个新的DataSource, 然后用LogicalPartitionUnionAll最为父节点，把这些Datasource Union起来。

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