I had a similar problem with several lookup tables joining to a large table with all id fields indexed. To monitor the effect of the joins on query time execution, I ran my query several times (limiting to first 100 rows), adding a Join to an additional table each time. After joining 12 tables, there was no significant change in query execution time. By the time I had joined the 13th table the execution time jumped to a 1 second; 14th table 4 seconds, 15th table 20 s, 16th 90 seconds.
Keijro's suggestion to use a correlated subqueries instead of joins e.g.
SELECT t1_id,
(select t2_name from t2 where t1_id = t2_id),
(select t3_name from t3 where t1_id = t3_id),
(select t4_name from t4 where t1_id = t4_id),
(select t5_name from t5 where t1_id = t5_id),
(select t6_name from t6 where t1_id = t6_id),
(select t7_name from t7 where t1_id = t7_id),
(select t8_name from t8 where t1_id = t8_id),
(select t9_name from t9 where t1_id = t9_id) FROM t1
improved query performance dramatically. In fact the subqueries did not seem to lengthen the time to execute the query (the query was almost instanteous).
I am a little suprised as I thought correlated subqueries perform worse than joins.
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