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Semi-join Materialization is a special kind of subquery materialization that's used for Semi-join subqueries. It actually includes two strategies:

  • Materialization/lookup
  • Materialization/scan

The idea

Let us again look at the query that finds countries in Europe that have big cities:

select * from Country 
where Country.code IN (select City.Country 
                       from City 
                       where City.Population > 7*1000*1000)
      and Country.continent='Europe'

The subquery is uncorrelated, that is, we can run it independently of the upper query. The idea of semi-join materialization is to do just that, and fill a temporary table with possible values of City.country field of big cities, and then do a join with countries in Europe:

sj-materialization1

The join can be done in two directions:

  1. From Materialized table to countries in Europe
  2. From Countries in Europe to materialized table

The first way involves doing a full scan on the materialized table, so we call it "Materialization-scan".

If you run a join from Countries to materialized table, the cheapest way to find a match in materialized table is to make a lookup on its primary key (it has one: we used it to remove duplicates). Because of that, we call the strategy "Materialization-lookup".

Semi-join materialization in action

Materialization-Scan

If we chose to look for cities with population greater than 7 million, the optimizer will use Materialization-Scan and the EXPLAIN will show this:

MariaDB [world]> explain select * from Country where Country.code IN (select City.Country from City where  City.Population > 7*1000*1000);
+----+--------------+-------------+--------+--------------------+------------+---------+--------------------+------+-----------------------+
| id | select_type  | table       | type   | possible_keys      | key        | key_len | ref                | rows | Extra                 |
+----+--------------+-------------+--------+--------------------+------------+---------+--------------------+------+-----------------------+
|  1 | PRIMARY      | <subquery2> | ALL    | distinct_key       | NULL       | NULL    | NULL               |   15 |                       |
|  1 | PRIMARY      | Country     | eq_ref | PRIMARY            | PRIMARY    | 3       | world.City.Country |    1 |                       |
|  2 | MATERIALIZED | City        | range  | Population,Country | Population | 4       | NULL               |   15 | Using index condition |
+----+--------------+-------------+--------+--------------------+------------+---------+--------------------+------+-----------------------+
3 rows in set (0.01 sec)

Here, you can see:

  • There are still two SELECTs (look for columns with id=1 and id=2)
  • The second select (with id=2) has select_type=MATERIALIZED. This means it will be executed and its results will be stored in a temporary table with a unique key over all columns. The unique key is there to prevent the table from containing any duplicate records.
  • The first select got table named <subquery2>. This is the table that we've got as a result of materialization of the select with id=2.

The optimizer chose to do a full scan over the materialized table, so this is an example of use of Materialization-Scan strategy.

As for execution costs, we're going to read 15 rows from table City, write 15 rows to materialized table, read them back (the optimizer assumes there won't be any duplicates), and then do 15 eq_ref accesses to table Country. In total, we'll do 45 reads and 15 writes.

If you run the EXPLAIN in MySQL, you'll get this:

MySQL [world]> explain select * from Country where Country.code IN (select City.Country from City where  City.Population > 7*1000*1000) and Country.continent='Europe';
+----+--------------------+---------+-------+--------------------+------------+---------+------+------+------------------------------------+
| id | select_type        | table   | type  | possible_keys      | key        | key_len | ref  | rows | Extra                              |
+----+--------------------+---------+-------+--------------------+------------+---------+------+------+------------------------------------+
|  1 | PRIMARY            | Country | ALL   | NULL               | NULL       | NULL    | NULL |  239 | Using where                        |
|  2 | DEPENDENT SUBQUERY | City    | range | Population,Country | Population | 4       | NULL |   15 | Using index condition; Using where |
+----+--------------------+---------+-------+--------------------+------------+---------+------+------+------------------------------------+

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