Tuesday, October 06, 2020

Parallel execution of Outer/Semi joins in NDB Cluster

In MySQL Cluster 8.0.20 we added one more query type that can be pushed

down to NDB data nodes. These queries are outer join queries and semi-join

queries using the FirstMatch strategy.

These queries can be pushed if conditions can be pushed on those parts of

the query that involve the outer join using a concept in the MySQL Server

called join nests.

Pushed queries means that the join execution is pushed down to the NDB

data nodes. This means that the rows to process for the second table in

the join is sent directly from the LDM threads to the join processor

that will start the select on the second table. The join can contain

up to 32 tables. Many filters can be pushed as well. It is also possible

to push parts of a join query. We are actively working on supporting

more and more query variants for push down to NDB data nodes.

The main benefits of pushing the queries down to data nodes is that it

enables the queries to be parallelised since both accesses to the data

owning parts (LDM threads) and the join processors (tc threads) can be

executed in parallel on multiple nodes and multiple threads in each

node. This means that queries can return the results much quicker.

Some queries can become more than 50 times faster using this approach

compared to when queries are executed entirely in the MySQL Server.

In our development of these new pushdown join features we measure the

result of executing queries in TPC-H. In TPC-H there is one outer join

query that looks like this:



        count(*) as custdist





                        count(o_orderkey) as c_count


                        customer left outer join orders on

                                c_custkey = o_custkey

                                and o_comment not like '%special%requests%'

                group by


        ) as c_orders

group by


order by

        custdist desc,

        c_count desc;

This query benefits greatly from both the push of outer joins, it also

benefits greatly from the new CPU spinning and it benefits from using the

shared memory transporter between the data node and the MySQL Server.

Combined together these 3 things together improve latency of this query

(Q13) in TPC-H by a factor of 10x when compared to executing it in

MySQL Cluster 7.6.

Another query that benefits greatly from these changes is Q4 in TPC-H.



        count(*) as order_count




        o_orderdate >=  '1993-07-01'

        and o_orderdate < date_add( '1993-07-01', interval '3' month)

        and exists (






                        l_orderkey = o_orderkey

                        and l_commitdate < l_receiptdate


group by


order by


This query executes more than 50 times faster in MySQL Cluster 8.0.20

compared to in MySQL Cluster 7.6 and this benefit comes strictly from

changing the execution algorithm.

No comments: