Ready for another post in the EXPLAIN FORMAT=JSON is Cool series! Great! This post will discuss how to see all the information that is contained in optimized queries with

UNION

 using the

union_result

 and

query_specifications

 commands.

When optimizing complicated queries with

UNION

, it is easy to get lost in the regular

EXPLAIN

  output trying to identify which part of the output belongs to each part of the

UNION

.

Let’s consider the following example:

mysql> explain
    ->     select emp_no, last_name, 'low_salary' from employees
    ->     where emp_no in (select emp_no from salaries
    ->         where salary < …

Over several previous blog posts, we’ve already discussed what information the 

EXPLAIN FORMAT=JSON

 output provides for some subqueries. You can review those discussions here, here and here. EXPLAIN FORMAT=JSON shows many details that you can’t get with other commands. Let’s now finish this topic and discuss the output for the rest of the subquery types.

We’ve already discussed using the ORDER BY clause with subqueries. You can also, however, use the 

ORDER BY

 clause with sorting results of one of the columns. Actually, this is most common way to use this clause.

Sometimes such queries require using temporary tables or filesort, and a regular

EXPLAIN

  clause provides this information. But it doesn’t show if this job is needed for

ORDER BY

 or for optimizing another part of the query.

For example, if we take a pretty simple query ( 

select distinct last_name from employees order by last_name asc

) and run

EXPLAIN

  on it, we can see …

In the previous EXPLAIN FORMAT=JSON is Cool! series blog post, we discussed the  

group_by_subqueries

  member (which is child of

grouping_operation

). Let’s now focus on the 

grouping_operation

  and other details of 

GROUP BY

  processing.

grouping_operation

 simply shows the details of what happens when the 

GROUP BY

 clause is run:

mysql> explain …

Another post in the EXPLAIN FORMAT=JSON is Cool! series! In this post, we’ll discuss how the EXPLAIN FORMAT=JSON provides optimization details for 

ORDER BY

 and  

GROUP BY

 operations in conjunction with 

order_by_subqueries

 and  

group_by_subqueries

. 

EXPLAIN FORMAT=JSON

 can print details on how a subquery in

ORDER BY

 is optimized:

mysql> explain format=json select emp_no, concat(first_name, ' ', last_name) f2 from employees order by (select emp_no limit 1)G
*************************** 1. row *************************** …

The previous post in the EXPLAIN FORMAT=JSON is Cool! series showed an example of the query

select dept_name from departments where dept_no in (select dept_no from dept_manager where to_date is not null)

, where the subquery was materialized into a temporary table and then joined with the outer query. This is known as a semi-join optimization. But what happens if we turn off this optimization?

EXPLAIN FORMAT=JSON

 can help us with this investigation …

EXPLAIN FORMAT=JSON

The regular

EXPLAIN

 command already provides some information about subquery optimization. For example, you can find out if the subquery is dependent or not, and (since version 5.6) if it was materialized:

mysql> explain select dept_name from departments where dept_no in (select dept_no from dept_manager where to_date is not null)G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: departments
   partitions: NULL
         type: index
possible_keys: PRIMARY
          key: dept_name
      key_len: 42
          ref: NULL
         rows: 9
     filtered: 100.00
        Extra: Using where; Using index
*************************** 2. row ***************************
           id: 1
  select_type: SIMPLE
        table: …

In the previous post for this ongoing “EXPLAIN FORMAT=JSON is Cool!” series, we discussed covered indexes and how the 

used_columns

  array can help to choose them wisely. There is one more type of multiple-column indexes: composite indexes. Composite indexes are just indexes on multiple columns. Covered indexes are a subgroup of the larger set “composite indexes.” In this post we’ll discuss how “used_key_parts” can help show …

In the “MySQL Query tuning 101” video, Alexander Rubin provides an excellent example of when to use a covered index. On slide 25, he takes the query

select name from City where CountryCode = ’USA’ and District = ’Alaska’ and population > 10000

 and adds the index

cov1(CountryCode, District, population, name)

 on table

City

. With Alex’s query tuning experience, making the right index decision is simple – but what about us mere mortals? If a query is more complicated, or simply uses more than one table, how do we know what to do? Maintaining …

At the end of my talk “Troubleshooting MySQL Performance” at the LinuxPiter conference, a user asked me a question: “What does the EXPLAIN ‘filtered’ field mean, and how do I use it?” I explained that this is the percentage of rows that were actually needed, against the equal or bigger number of resolved rows. While the user was happy with the answer, I’d like to better illustrate this. And I can do it with help of EXPLAIN FORMAT=JSON and its

rows_examined_per_scan, rows_produced_per_join

  statistics.

Let’s take a simple query that searches information about the …