mysql query taking 46 seconds - needs to be more efficient - mysql

Question

I have arrived at a query that gives me what I want but it is not efficient and takes over 45 seconds to execute. How can I modify to make this quicker?
SELECT *
FROM (SELECT DISTINCT email,
title,
first_name,
last_name,
'chauntry' AS source,
post_code AS postcode
FROM chauntry
WHERE mailing_indicator = 1) AS x
LEFT JOIN (SELECT email,
Avg(amount_paid) AS avg_paid,
Count(*) AS no_times_booked,
Count(DISTINCT( Month(added) )) AS unique_months
FROM chauntry
WHERE added >= Now() - INTERVAL 1 year
GROUP BY email) AS y
ON x.email = y.email
here are the data fields
here are the column headings I am after

Answer 1

DRapp, appreciate the detailed feedback - spot on about the date being an oversight.
Are we talking about something like the below to speed up my query? I cant find much info about creating a covering index and the source of the below one was questionable.
ALTER TABLE `chauntry`
ADD INDEX(`mailing_indicator`, `email`);
ALTER TABLE `chauntry`
ADD INDEX covering_index (`added`, `email`, `amount_paid`);

Answer 2

You use SELECT DISTINCT in the first subquery, and GROUP BY in the second subquery.
Which has the same effect.
Subqueries in a from clause are often redundant, they produce derived tables which aren't indexed. When you run explain over the query you'll see 4 tabels in the execution plan. This can be rewritten to a query without subqueries:
SELECT x.email,
x.title,
x.first_name,
x.last_name,
'chauntry' AS source,
post_code AS postcode,
Avg(y.amount_paid) AS avg_paid,
Count(y.email) AS no_times_booked,
Count(DISTINCT( Month(y.added) )) AS unique_months
FROM
chauntry x
LEFT JOIN
chaunrty y
ON x.email = y.email AND y.added >= CURRENT_DATE - INTERVAL 1 YEAR
GROUP BY x.email
However your model isn't properly normalized, you should have two tables, one with the account data, and one with the payments

Answer 3

To help your performance, you really need indexes. Since you are in essence running two different queries, I would have the following indexes on your CHAUNTRY table
First... by having the mailing_indicator first, you are jumping directly to those, then getting email too which is a basis for the join after. You could actually extend the index to include title, first, last, post_code to be a covering index, but that might be overkill.
( mailing_indicator, email )
Your LEFT JOIN query, it appears you want the count, avg, etc regardless of the mailing_indicator status. To help optimize this, I would have an index on
( added, email, amount_paid )
This WOULD be a covering index so the engine does not need to go to the raw data pages to query the data, but gets them directly from the index.
One additional note about your count of distinct months. You MIGHT be missing a count entry. Consider the middle of the month, such as now Jan 28.
if you have entries for Jan 29, 2014 and Jan 27, 2015, they will fall into the same distinct month count basis as 1 and not 2 representing two different months as they span month AND year. You might want to change that to
DATE_FORMAT(added, '%M %Y') as unique_months_yrs
Syntax to create index
CREATE [UNIQUE|FULLTEXT|SPATIAL] INDEX index_name
[index_type]
ON tbl_name (index_col_name,...)
[index_type]
Create index Chauntry_MailInd_EMail on Chauntry ( mailing_indicator, email );
Create index Chauntry_Add_Email_Paid on Chauntry ( added, email, amount_paid );