我有一个索引：CREATE INDEX index_c_profiles_on_city_state_name_domain ON
c_profiles ((data->>'state'), (data->>'city'), name, domain);
和另一个索引：CREATE INDEX index_c_profiles_on_state ON
c_profiles (state)，我创建了一个名为'state'的新列，其中data->>'state'的值是从jsonb列中手动复制的每一行
我尝试使用以下查询来使用第一个索引：SELECT mm.name, mm.domain, mm.data ->> 'city' as city, mm.data ->> 'state' as state
FROM c_profiles as mm
WHERE ((mm.data ->> 'state') = 'CA')，并且花了8秒钟来完成
[
{
"Execution Time": 8023.687,
"Planning Time": 0.5,
"Plan": {
"Exact Heap Blocks": 16743,
"Node Type": "Bitmap Heap Scan",
"Actual Total Time": 8014.769,
"Shared Hit Blocks": 2523,
"Schema": "public",
"Plans": [
{
"Node Type": "Bitmap Index Scan",
"Actual Total Time": 94.311,
"Shared Hit Blocks": 3,
"Shared Read Blocks": 350,
"Temp Written Blocks": 0,
"Local Dirtied Blocks": 0,
"Local Hit Blocks": 0,
"Plan Width": 0,
"Actual Loops": 1,
"Actual Startup Time": 94.311,
"Temp Read Blocks": 0,
"Local Read Blocks": 0,
"Index Name": "index_c_profiles_on_city_state_name_domain",
"Startup Cost": 0,
"Shared Dirtied Blocks": 0,
"Shared Written Blocks": 0,
"Local Written Blocks": 0,
"Plan Rows": 21870,
"Index Cond": "((mm.data ->> 'state'::text) = 'CA'::text)",
"Actual Rows": 21729,
"Parent Relationship": "Outer",
"Total Cost": 1604.45
}
],
"Shared Read Blocks": 17472,
"Relation Name": "c_profiles",
"Local Hit Blocks": 0,
"Local Dirtied Blocks": 0,
"Temp Written Blocks": 0,
"Plan Width": 980,
"Actual Loops": 1,
"Rows Removed by Index Recheck": 0,
"Lossy Heap Blocks": 0,
"Alias": "mm",
"Recheck Cond": "((mm.data ->> 'state'::text) = 'CA'::text)",
"Temp Read Blocks": 0,
"Output": [
"(data ->> 'city'::text)",
"(data ->> 'state'::text)"
],
"Actual Startup Time": 99.44,
"Local Read Blocks": 0,
"Startup Cost": 1609.91,
"Shared Dirtied Blocks": 360,
"Shared Written Blocks": 0,
"Local Written Blocks": 0,
"Plan Rows": 21870,
"Actual Rows": 21537,
"Total Cost": 42388.85
},
"Triggers": []
}
]
然后，我尝试使用该查询使用第二个索引：SELECT state
FROM mattermark_profiles as mm
WHERE state = 'CA'，并且花费了20毫秒的时间
[
{
"Execution Time": 20.19,
"Planning Time": 0.5,
"Plan": {
"Node Type": "Index Only Scan",
"Actual Total Time": 16.206,
"Shared Hit Blocks": 633,
"Schema": "public",
"Scan Direction": "Forward",
"Shared Read Blocks": 59,
"Relation Name": "c_profiles",
"Local Hit Blocks": 0,
"Heap Fetches": 776,
"Local Dirtied Blocks": 0,
"Temp Written Blocks": 0,
"Plan Width": 3,
"Actual Loops": 1,
"Rows Removed by Index Recheck": 0,
"Actual Startup Time": 0.08,
"Alias": "mm",
"Temp Read Blocks": 0,
"Output": [
"state"
],
"Local Read Blocks": 0,
"Index Name": "index_c_profiles_on_state",
"Startup Cost": 0.42,
"Shared Dirtied Blocks": 53,
"Shared Written Blocks": 0,
"Local Written Blocks": 0,
"Plan Rows": 21870,
"Index Cond": "(mm.state = 'CA'::text)",
"Actual Rows": 21524,
"Total Cost": 639.12
},
"Triggers": []
}
]
由于两个输出都是相同的行，为什么JSON索引的性能如此差？由于数据和行数是相同的，因此似乎必须有一种方法可以通过JSON索引获得相似的结果，但是我不清楚如何实现。任何帮助将不胜感激！