2つの別々のクエリの結果をまとめるためにMySQLでUNIONを使用しています。これらの2つのクエリは、多くの同じテーブルを使用します。クエリを最適化するためにこれを利用する方法はありますか？
SELECT 2 AS RELEVANCE_SCORE_TYPE,
VIEWER_ID,
QUESTION_ID,
sum(ANSWER_SCORE) AS RELEVANCE_SCORE
FROM(SELECT cr.COMMUNICATIONS_ID AS ANSWER_ID,
cr.CONSUMER_ID as VIEWER_ID,
nc.PARENT_COMMUNICATIONS_ID AS QUESTION_ID,
case when cr.CONSUMER_ID= nc.SENDER_CONSUMER_ID then 3*((24/(((UNIX_TIMESTAMP(NOW())-UNIX_TIMESTAMP(cal.LAST_MOD_TIME)+3600)/3600))*(ces.EXPERT_SCORE * cirm.CONSUMER_RATING) + (12.5 * scs.SIMILARITY)* (1 - EXP(-0.5 * (cal.TIPS_AMOUNT / ATV.AVG_TIPS)) + .15)))
else ((24/(((UNIX_TIMESTAMP(NOW())-UNIX_TIMESTAMP(cal.LAST_MOD_TIME)+3600)/3600))*(ces.EXPERT_SCORE * cirm.CONSUMER_RATING) + (12.5 * scs.SIMILARITY)* (1 - EXP(-0.5 * (cal.TIPS_AMOUNT / ATV.AVG_TIPS)) + .15)))
end as ANSWER_SCORE
FROM (SELECT 238 AS CONSUMER_ID,
ACTION_LOG_ID,
COMMUNICATIONS_ID
FROM consumer_action_log
WHERE COMM_TYPE_ID=4) AS cr
JOIN network_communications AS nc
ON cr.COMMUNICATIONS_ID=nc.COMMUNICATIONS_ID
JOIN consumer_action_log AS cal
ON cr.ACTION_LOG_ID=cal.ACTION_LOG_ID
JOIN communication_interest_mapping AS cim
ON nc.PARENT_COMMUNICATIONS_ID=cim.COMMUNICATION_ID
JOIN consumer_interest_rating_mapping AS cirm
ON cr.CONSUMER_ID=cirm.CONSUMER_ID
AND cim.CONSUMER_INTEREST_EXPERT_ID=cirm.CONSUMER_INTEREST_ID
JOIN consumer_expert_score AS ces
ON nc.SENDER_CONSUMER_ID=ces.CONSUMER_ID
AND cim.CONSUMER_INTEREST_EXPERT_ID=ces.CONSUMER_EXPERT_ID
JOIN survey_customer_similarity AS scs
ON cr.CONSUMER_ID=scs.CONSUMER_ID_2
AND cal.SENDER_CONSUMER_ID=scs.CONSUMER_ID_1
OR cr.CONSUMER_ID=scs.CONSUMER_ID_1
AND cal.SENDER_CONSUMER_ID=scs.CONSUMER_ID_2
CROSS JOIN
(
SELECT AVG(cal.TIPS_AMOUNT) AS AVG_TIPS
FROM CONSUMER_ACTION_LOG AS cal
JOIN (SELECT 234 AS CONSUMER_ID,
ACTION_LOG_ID,
COMMUNICATIONS_ID
FROM consumer_action_log
WHERE COMM_TYPE_ID=4) AS cr
ON cal.SENDER_CONSUMER_ID=cr.consumer_id
) ATV) AS ASM
GROUP BY ANSWER_ID
UNION
SELECT 1 AS RELEVANCE_SCORE_TYPE,
qcr.CONSUMER_ID AS Viewer_ID,
qcr.COMMUNICATIONS_ID,
case when reply.replies IS NOT NULL AND qcr.CONSUMER_ID <> qcr.SENDER_CONSUMER_ID then
24/((UNIX_TIMESTAMP(NOW())-UNIX_TIMESTAMP(qcr.LAST_MOD_TIME)+3600)/3600)*(ces.EXPERT_SCORE+2.5*scs.SIMILARITY)*(EXP(-reply.replies))
when reply.replies IS NULL AND qcr.CONSUMER_ID <> qcr.SENDER_CONSUMER_ID then
24/((UNIX_TIMESTAMP(NOW())-UNIX_TIMESTAMP(qcr.LAST_MOD_TIME)+3600)/3600)*(ces.EXPERT_SCORE+2.5*scs.SIMILARITY)*(EXP(0))
when reply.replies IS NULL AND qcr.CONSUMER_ID = qcr.SENDER_CONSUMER_ID then
24/((UNIX_TIMESTAMP(NOW())-UNIX_TIMESTAMP(qcr.LAST_MOD_TIME)+3600)/3600)*(7.5)*(1-EXP(0))
when reply.replies IS NOT NULL AND qcr.CONSUMER_ID = qcr.SENDER_CONSUMER_ID then
24/((UNIX_TIMESTAMP(NOW())-UNIX_TIMESTAMP(qcr.LAST_MOD_TIME)+3600)/3600)*(7.5)*(1-EXP(-reply.replies))
else null
end as QUESTION_SCORE
FROM (SELECT 238 AS CONSUMER_ID,
SENDER_CONSUMER_ID,
COMMUNICATIONS_ID,
LAST_MOD_TIME
FROM network_communications
WHERE NETWORK_COMM_TYPE_ID=1) AS qcr
JOIN communication_interest_mapping AS cim
ON qcr.COMMUNICATIONS_ID=cim.COMMUNICATION_ID
JOIN consumer_expert_score AS ces
ON ces.CONSUMER_ID=qcr.CONSUMER_ID
AND cim.CONSUMER_INTEREST_EXPERT_ID=ces.CONSUMER_EXPERT_ID
JOIN survey_customer_similarity AS scs
ON qcr.CONSUMER_ID=scs.CONSUMER_ID_2
AND qcr.SENDER_CONSUMER_ID=scs.CONSUMER_ID_1
OR qcr.CONSUMER_ID=scs.CONSUMER_ID_1
AND qcr.SENDER_CONSUMER_ID=scs.CONSUMER_ID_2
LEFT JOIN (SELECT COUNT(*) AS replies,
PARENT_COMMUNICATIONS_ID
FROM network_communications AS nc1
WHERE NETWORK_COMM_TYPE_ID=2
GROUP BY PARENT_COMMUNICATIONS_ID) AS reply
ON qcr.COMMUNICATIONS_ID=reply.PARENT_COMMUNICATIONS_ID
ORDER BY RELEVANCE_SCORE DESC;
FROM (SELECT 234 AS CONSUMER_ID,
ACTION_LOG_ID,
COMMUNICATIONS_ID
FROM consumer_action_log
WHERE COMM_TYPE_ID=4) AS cr
JOIN network_communications AS nc
ON cr.COMMUNICATIONS_ID=nc.COMMUNICATIONS_ID
JOIN consumer_action_log AS cal
ON cr.ACTION_LOG_ID=cal.ACTION_LOG_ID
JOIN communication_interest_mapping AS cim
ON nc.PARENT_COMMUNICATIONS_ID=cim.COMMUNICATION_ID
JOIN consumer_interest_rating_mapping AS cirm
ON cr.CONSUMER_ID=cirm.CONSUMER_ID
AND cim.CONSUMER_INTEREST_EXPERT_ID=cirm.CONSUMER_INTEREST_ID
JOIN consumer_expert_score AS ces
ON nc.SENDER_CONSUMER_ID=ces.CONSUMER_ID
AND cim.CONSUMER_INTEREST_EXPERT_ID=ces.CONSUMER_EXPERT_ID
JOIN survey_customer_similarity AS scs
ON cr.CONSUMER_ID=scs.CONSUMER_ID_2
AND cal.SENDER_CONSUMER_ID=scs.CONSUMER_ID_1
OR cr.CONSUMER_ID=scs.CONSUMER_ID_1
AND cal.SENDER_CONSUMER_ID=scs.CONSUMER_ID_2
CROSS JOIN
(
SELECT AVG(cal.TIPS_AMOUNT) AS AVG_TIPS
FROM CONSUMER_ACTION_LOG AS cal
JOIN (SELECT 234 AS CONSUMER_ID,
ACTION_LOG_ID,
COMMUNICATIONS_ID
FROM consumer_action_log
WHERE COMM_TYPE_ID=4) AS cr
ON cal.SENDER_CONSUMER_ID=cr.consumer_id
) ATV) AS ASM
GROUP BY ANSWER_ID
ORDER BY ANSWER_SCORE_SUMMED DESC;
長いので、全部読む義務を感じないでください。要点は、ユニオンの両側のクエリが多くの同じテーブルを利用するということです。