*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: p
   partitions: NULL
         type: index_merge
possible_keys: key1,key6,key8,key5,key7,key2,key4,key3
          key: key7,key5
      key_len: 254,17
          ref: NULL
         rows: 63220
     filtered: 10.00
        Extra: Using intersect(key7,key5); Using where

## 查看Trace信息：
{   ## range扫描的代价 
    "index": "key5",
    "index_dives_for_eq_ranges": true,
    "rowid_ordered": true,
    "using_mrr": false,
    "index_only": false,
    "in_memory": 0.0892,
    "rows": 83730,  
    "cost": 92104,	## key5 range扫描代价
    "chosen": true,
    "cause": "cost"
  },

  { ## range扫描的代价 
    "index": "key7",
    "index_dives_for_eq_ranges": true,
    "rowid_ordered": true,
    "using_mrr": false,
    "index_only": false,
    "in_memory": 0.0161,
    "rows": 188308,  
    "cost": 207140,		## key7 range扫描代价
    "chosen": false,
    "cause": "cost"
  },


"analyzing_roworder_intersect": {
  ### Index Merge的代价估算
  "intersecting_indexes": [
    {
      "index": "key7",
      "index_scan_cost": 5814.5,
      "cumulated_index_scan_cost": 5814.5,
      "disk_sweep_cost": 166598,
      "cumulated_total_cost": 172412,  ## ror scan cost
      "usable": true,
      "matching_rows_now": 188308,
      "isect_covering_with_this_index": false,
      "chosen": true
    },
    {
      "index": "key5",
      "index_scan_cost": 239.13,
      "cumulated_index_scan_cost": 6053.7,
      "disk_sweep_cost": 59370,
      "cumulated_total_cost": 65423,  ## ror intersect代价
      "usable": true,
      "matching_rows_now": 64048,
      "isect_covering_with_this_index": false,
      "chosen": true
    }
  ],
  "clustered_pk": {
    "clustered_pk_added_to_intersect": false,
    "cause": "no_clustered_pk_index"
  },
  "rows": 64047,
  "cost": 65423,
  "covering": false,
  "chosen": true
}

SELECT * FROM tbl_name WHERE key1 = 10 OR key2 = 20;

SELECT * FROM tbl_name
  WHERE (key1 = 10 OR key2 = 20) AND non_key = 30;

SELECT * FROM t1, t2
  WHERE (t1.key1 IN (1,2) OR t1.key2 LIKE 'value%')
  AND t2.key1 = t1.some_col;

SELECT * FROM t1, t2
  WHERE t1.key1 = 1
  AND (t2.key1 = t1.some_col OR t2.key2 = t1.some_col2);

page_read_cost = mem_read_cost(table_pages_in_mem) + io_read_cost(table_pages_on_disk)
index_page_read_cost = mem_read_cost(index_pages_in_mem) + io_read_cost(index_pages_on_disk)

# 检索最优的ROR-intersection
find_min_ror_intersection_scan()
{
  R= select all ROR scans;  ## Sort indexes in an order that is likely to be a
                            ## good index merge intersection order.

  S= first(R); -- set of scans that will be used for ROR-intersection
  R= R-first(S);
  min_cost= cost(S);
  min_scan= make_scan(S);
  while (R is not empty)
  {
    firstR= R - first(R);
    if (!(selectivity(S + firstR) < selectivity(S)))
      continue;

    S= S + first(R);
    if (cost(S) < min_cost)
    {
      min_cost= cost(S);
      min_scan= make_scan(S);
    }
  }
  return min_scan;
}

# 假设有如下的多个索引的条件：
cond=k_11=c_11 AND k_12=c_12 AND ...  // key_parts of first key
     k_21=c_21 AND k_22=c_22 AND ...  // key_parts of second key
      ...
     k_n1=c_n1 AND k_n3=c_n3 AND ...  // key_parts of n key

# 其中k_ij 和 k_pq 可能是相同的列

selectivity_mult = prefix_scan_records(..., j) /  prefix_scan_records(..., b)   
                    * prefix_scan_records(..., y) / prefix_scan_records(..., c)
                    * ...

info->out_rows *= selectivity_mult     ## 计算合并后的输出行数
info->index_records += quick_rows[ror_scan->keynr]; ## 扫描行数累计
info->index_scan_cost += ror_scan->index_read_cost;  ## index-only的扫描代价累计
bitmap_union(&info->covered_fields, &ror_scan->covered_fields); ##合并covered_fields

info->total_cost = info->index_scan_cost; 
if 非覆盖索引：
  sweep_cost = get_sweep_read_cost ## sweep就是计算回表的IO代价
  info->total_cost += sweep_cost;  ## 

## ROR-Union的代价计算：
## 计算流程：(a = 1 and b = 2) or (c = 3 and d = 3)
Loop 'OR' range 条件tree：
  - cur_child = get_key_scans_params  ## 获取当前range条件best range scan方式 
    ## 如果没有找到best range，则设置imerge_too_expensive = true
  - imerge_cost += (*cur_child)->cost_est;  ## 累加对应range scan的代价
  - non_cpk_scan_records += (*cur_child)->records;

sweep_cost = get_sweep_read_cost  ## 计算回表代价，回表行数就是non_cpk_scan_records
imerge_cost += sweep_cost

dup_removal_cost = Unique::get_use_cost  ##计算
imerge_cost.add_cpu(dup_removal_cost);

# imerge_cost 为总代价

## ROR-Union的代价公式：

## 计算流程：(a = 1 and b = 2) or (c = 3 and d = 3)
Loop cur_child in range_scans:  ## range_scans已经在计算sort-union时填充好了，这里无需再调用get_key_scans_params
  - cur_roru_plan = get_best_ror_intersect ## 复用ror-intersection来计算(a = 1 and b = 2) 单独某部分range条件的代价
  - roru_index_cost += (*cur_roru_plan)->index_scan_cost;
  - roru_total_records += (*cur_roru_plan)->records;
  - roru_intersect_part *=
        (*cur_roru_plan)->records / param->table->file->stats.records;  # 计算去重率

# 估算去重后的行数
roru_total_records -=
      (ha_rows)(roru_intersect_part * param->table->file->stats.records);

sweep_cost = get_sweep_read_cost  ## 回表行数roru_total_records

# Calculate cost:
roru_total_cost += roru_index_cost ## index only scan cost
roru_total_cost += sweep_cost   # 回表代价
roru_total_cost.add_cpu(cost_model->key_compare_cost(
        rows2double(roru_total_records) * std::log2(n_child_scans)));  ## queue_use_cost(rowid_len, n)