PolarDB：分區串連

概述

分區串連用於兩個分區表之間Join最佳化。當分區表之間使用分區鍵進行Join時，可以通過分區串連減少分區之間無效的串連，提升串連查詢的效能。

使用說明

可通過如下語句開啟分區串連功能：

set enable_partitionwise_join to on;

樣本

下文通過兩個簡單易理解的樣本來詳細介紹分區串連。

樣本中包含兩個表measurement和sales，具體如下：

CREATE TABLE measurement(
    city_id         int not null,
    logdate         date not null,
    peaktemp        int,
    unitsales       int
) PARTITION BY RANGE (logdate);
CREATE TABLE measurement_y2023q1 PARTITION OF measurement
    FOR VALUES FROM ('2023-01-01') TO ('2023-04-01');
CREATE TABLE measurement_y2023q2 PARTITION OF measurement
    FOR VALUES FROM ('2023-04-01') TO ('2023-07-01');
CREATE TABLE measurement_y2023q3 PARTITION OF measurement
    FOR VALUES FROM ('2023-07-01') TO ('2023-10-01');
CREATE TABLE measurement_y2023q4 PARTITION OF measurement
    FOR VALUES FROM ('2023-10-01') TO ('2024-04-01');
    
CREATE TABLE sales (
    dept_no     integer,
    part_no     varchar(2),
    country     varchar(20),
    date        date,
    amount      decimal
) PARTITION BY RANGE (date);
CREATE TABLE sales_y2023q1 PARTITION OF sales
    FOR VALUES FROM ('2023-01-01') TO ('2023-04-01');
CREATE TABLE sales_y2023q2 PARTITION OF sales
    FOR VALUES FROM ('2023-04-01') TO ('2023-07-01');
CREATE TABLE sales_y2023q3 PARTITION OF sales
    FOR VALUES FROM ('2023-07-01') TO ('2023-10-01');
CREATE TABLE sales_y2023q4 PARTITION OF sales
    FOR VALUES FROM ('2023-10-01') TO ('2024-04-01');

從以上建表語句可以看到：

• 表measurement有四個分區，即measurement_y2023q1,measurement_y2023q2, measurement_y2023q3, measurement_y2023q4，分別對應了2023年的四個季度。

• 表sales也有四個分區，即sales_y2023q1,sales_y2023q2, sales_y2023q3, sales_y2023q4，分別對應了2023年的四個季度。

此時，執行表measurement和表sales的串連查詢SQL語句，並查看其查詢計劃：

explain select a.* from sales a join measurement b on a.date = b.logdate where b.unitsales > 10;

當未開啟分區串連功能時，表measurement 和表sales 全串連，查詢計劃如下：

                                            QUERY PLAN                                            
--------------------------------------------------------------------------------------------------
 Aggregate  (cost=871.75..871.76 rows=1 width=8)
   ->  Merge Join  (cost=448.58..812.79 rows=23587 width=32)
         Merge Cond: (a.date = b.logdate)
         ->  Sort  (cost=185.83..191.03 rows=2080 width=40)
               Sort Key: a.date
               ->  Append  (cost=0.00..71.20 rows=2080 width=40)
                     ->  Seq Scan on sales_y2023q1 a  (cost=0.00..15.20 rows=520 width=40)
                     ->  Seq Scan on sales_y2023q2 a_1  (cost=0.00..15.20 rows=520 width=40)
                     ->  Seq Scan on sales_y2023q3 a_2  (cost=0.00..15.20 rows=520 width=40)
                     ->  Seq Scan on sales_y2023q4 a_3  (cost=0.00..15.20 rows=520 width=40)
         ->  Sort  (cost=262.75..268.42 rows=2268 width=8)
               Sort Key: b.logdate
               ->  Append  (cost=0.00..136.34 rows=2268 width=8)
                     ->  Seq Scan on measurement_y2023q1 b  (cost=0.00..31.25 rows=567 width=8)
                           Filter: (unitsales > 10)
                     ->  Seq Scan on measurement_y2023q2 b_1  (cost=0.00..31.25 rows=567 width=8)
                           Filter: (unitsales > 10)
                     ->  Seq Scan on measurement_y2023q3 b_2  (cost=0.00..31.25 rows=567 width=8)
                           Filter: (unitsales > 10)
                     ->  Seq Scan on measurement_y2023q4 b_3  (cost=0.00..31.25 rows=567 width=8)
                           Filter: (unitsales > 10)
(21 rows)

可以看到，該查詢計劃是使用表measurement的所有資料和表sales的所有資料進行全串連。但此時是存在無效串連的，比如sales_y2023q1和measurement_y2023q3他們之間的Join一定是空的，因為串連條件是分區鍵相等，而sales_y2023q1和measurement_y2023q3的分區鍵是不相等的。只有比如當sales_y2023q1和measurement_y2023q1串連後分區鍵相等才會有結果。

此時如果開啟分區串連功能：

set enable_partitionwise_join to on;

然後再執行同樣的表measurement和表sales的串連查詢SQL語句，其查詢計劃如下：

explain select a.* from sales a join measurement b on a.date = b.logdate where b.unitsales > 10;
                                       QUERY PLAN                                       
----------------------------------------------------------------------------------------
 Append  (cost=21.70..453.33 rows=5896 width=128)
   ->  Hash Join  (cost=21.70..105.96 rows=1474 width=128)
         Hash Cond: (b.logdate = a.date)
         ->  Seq Scan on measurement_y2023q1 b  (cost=0.00..31.25 rows=567 width=8)
               Filter: (unitsales > 10)
         ->  Hash  (cost=15.20..15.20 rows=520 width=128)
               ->  Seq Scan on sales_y2023q1 a  (cost=0.00..15.20 rows=520 width=128)
   ->  Hash Join  (cost=21.70..105.96 rows=1474 width=128)
         Hash Cond: (b_1.logdate = a_1.date)
         ->  Seq Scan on measurement_y2023q2 b_1  (cost=0.00..31.25 rows=567 width=8)
               Filter: (unitsales > 10)
         ->  Hash  (cost=15.20..15.20 rows=520 width=128)
               ->  Seq Scan on sales_y2023q2 a_1  (cost=0.00..15.20 rows=520 width=128)
   ->  Hash Join  (cost=21.70..105.96 rows=1474 width=128)
         Hash Cond: (b_2.logdate = a_2.date)
         ->  Seq Scan on measurement_y2023q3 b_2  (cost=0.00..31.25 rows=567 width=8)
               Filter: (unitsales > 10)
         ->  Hash  (cost=15.20..15.20 rows=520 width=128)
               ->  Seq Scan on sales_y2023q3 a_2  (cost=0.00..15.20 rows=520 width=128)
   ->  Hash Join  (cost=21.70..105.96 rows=1474 width=128)
         Hash Cond: (b_3.logdate = a_3.date)
         ->  Seq Scan on measurement_y2023q4 b_3  (cost=0.00..31.25 rows=567 width=8)
               Filter: (unitsales > 10)
         ->  Hash  (cost=15.20..15.20 rows=520 width=128)
               ->  Seq Scan on sales_y2023q4 a_3  (cost=0.00..15.20 rows=520 width=128)
(25 rows)

可以看到，當開啟分區串連後，分布串連最佳化的效果很明顯：sales_y2023q2只需要和measurement_y2023q2串連，sales_y2023q3只需要和measurement_y2023q3串連，sales_y2023q4只需要和measurement_y2023q4串連。分區之間無效的串連被大大減少，從而顯著提升串連查詢的效能。