There are so many exciting new features in MySQL 5.6 that I almost don't know where to start. To mention a few, MySQL's multi-core scalability has been significantly improved to meet modern hardware, InnoDB has better index statistics, much better performance, and online ALTER, replication has multi-threaded slaves and …

In a previous post, I had demonstrated how subquery materialization, introduced in MySQL 5.6.5, improves the performance of certain queries, like query Q16 of DBT3. Such improvement was easily explained:

• Subquery materialization has a high start up cost (it needs to create and fill the temporary table).
• But afterwards it has fast lookups (temporary table has a hash index, no duplicates, and is in memory).
• In other words, compared to EXISTS, the first evaluation of the IN predicate is slow (high start up cost) and all following evaluations are fast (just a hash lookup).
• In the DBT 3 setup, one outer table (named "part") has 200,000 rows, so there are 200,000 evaluations of …

In a previous post, I analyzed how a query of the famous DBT3 benchmark was
optimized by MySQL. It was this query, named "Q16" in the DBT3 jargon:

select
 p_brand,
 p_type,
 p_size,
 count(distinct ps_suppkey) as supplier_cnt
from
 partsupp,
 part
where
 p_partkey = ps_partkey
 and p_brand <> 'Brand#23'
 and p_type not like 'LARGE PLATED%'
 and p_size in (43, 1, 25, 5, 35, 12, 42, 40)
 and ps_suppkey not in (
  select
   s_suppkey
  from
   supplier
  where
   s_comment like '%Customer%Complaints%'
 )
group by
 p_brand,
 p_type,
 p_size
order by
 supplier_cnt desc,
 p_brand,
 p_type,
 p_size;

Here is a brief recap of conclusions I had drawn:

• for this query, MySQL tranforms the IN condition to EXISTS and then
  evaluates it with the "unique_subquery" technique, which does an …