horcle_buzz horcle_buzz - 6 months ago 12
SQL Question

Optimization of query using covering indices

I have the following query with a subquery and self join:

SELECT bucket.patient_sid AS sid
FROM
(SELECT clinical_data.patient_sid,
clinical_data.lft,
clinical_data.rgt
FROM clinical_data INNER JOIN
(SELECT clinical_data.patient_sid,
clinical_data.lft,
clinical_data.rgt,
clinical_data.attribute_id
FROM clinical_data
WHERE clinical_data.attribute_id = '33' AND clinical_data.string_value = '2160-0') AS attribute
ON clinical_data.patient_sid = attribute.patient_sid
AND clinical_data.lft >= attribute.lft
AND clinical_data.rgt <= attribute.rgt
WHERE clinical_data.attribute_id = '36') AS bucket;


I have the following indices defined on this:

KEY `idx_bucket` (`attribute_id`,`string_value`)
KEY `idx_self_join` (`attribute_id`,`patient_sid`,`lft`,`rgt`)


When I look at the query using EXPLAIN, the subquery using the covering index idx_bucket is definitely optimized, but the self join and where clause are not. Furthermore, why does it report that only
patient_sid
and
attribute_id
are used for
used_key_parts
while an
attachment_condition
is shown for
lft
,
rgt
(what does this mean?). Both
lft
and 'rgt` are just defined as integers with no special properties, so why aren't they being used in my covering index?

Even more strange is when I define

KEY `idx_self_join` (`patient_sid`,`lft`,`rgt`,`attribute_id`)


only
patient_sid
is registered in
used_key_parts.
Furthermore
filtered
drops to
1.60%
from
11.00%
!

{
"query_block": {
"select_id": 1,
"cost_info": {
"query_cost": "645186.71"
},
"nested_loop": [
{
"table": {
"table_name": "clinical_data",
"access_type": "ref",
"possible_keys": [
"fk_attribute_idx",
"idx_value_string",
"idx_value_double",
"idx_bucket",
"idx_self_join_idx"
],
"key": "idx_bucket",
"used_key_parts": [
"attribute_id",
"string_value"
],
"key_length": "308",
"ref": [
"const",
"const"
],
"rows_examined_per_scan": 126402,
"rows_produced_per_join": 126402,
"filtered": "100.00",
"cost_info": {
"read_cost": "126402.00",
"eval_cost": "25280.40",
"prefix_cost": "151682.40",
"data_read_per_join": "46M"
},
"used_columns": [
"patient_sid",
"string_value",
"attribute_id",
"lft",
"rgt"
],
"attached_condition": "(`ns_large2`.`clinical_data`.`patient_sid` is not null)"
}
},
{
"table": {
"table_name": "clinical_data",
"access_type": "ref",
"possible_keys": [
"fk_attribute_idx",
"idx_value_string",
"idx_value_double",
"idx_bucket",
"idx_self_join_idx"
],
"key": "idx_self_join_idx",
"used_key_parts": [
"attribute_id",
"patient_sid"
],
"key_length": "10",
"ref": [
"const",
"ns_large2.clinical_data.patient_sid"
],
"rows_examined_per_scan": 14,
"rows_produced_per_join": 201169,
"filtered": "11.11",
"using_index": true,
"cost_info": {
"read_cost": "131327.39",
"eval_cost": "40233.83",
"prefix_cost": "645186.71",
"data_read_per_join": "73M"
},
"used_columns": [
"patient_sid",
"attribute_id",
"lft",
"rgt"
],
"attached_condition": "((`ns_large2`.`clinical_data`.`lft` >= `ns_large2`.`clinical_data`.`lft`) and (`ns_large2`.`clinical_data`.`rgt` <= `ns_large2`.`clinical_data`.`rgt`))"
}
}
]
}
}

Answer

Here's your basic JOIN:

SELECT

FROM clinical_data cd1

JOIN clinical_data cd2
    ON cd1.patient_sid = cd2.patient_sid
    AND cd2.attribute_id = '33'

WHERE cd1.attribute_id = '36'