[pg15.2]一个亿级聊天记录表的调优

下面的 sql 查询非常慢。。。

select count(distinct "public"."tb_groupchat"."chat_id"), count("public"."tb_groupchat"."id"), count(distinct "public"."tb_groupchat"."sender_id") from "public"."tb_groupchat" where ("public"."tb_groupchat"."timestamp" >= $1 and "public"."tb_groupchat"."timestamp" < $2) 

表结构：

 "id" serial8 PRIMARY KEY NOT NULL, "chat_id" int8 NOT NULL, "sender_id" int8 NOT NULL, "timestamp" int8 NOT NULL 

explain 的结果

[ { "Plan": { "Node Type": "Aggregate", "Strategy": "Plain", "Partial Mode": "Simple", "Parallel Aware": false, "Async Capable": false, "Startup Cost": 181904.15, "Total Cost": 181904.16, "Plan Rows": 1, "Plan Width": 24, "Output": ["count(DISTINCT chat_id)", "count(id)", "count(DISTINCT sender_id)"], "Plans": [ { "Node Type": "Index Scan", "Parent Relationship": "Outer", "Parallel Aware": false, "Async Capable": false, "Scan Direction": "Forward", "Index Name": "idx_timestamp", "Relation Name": "tb_groupchat", "Schema": "public", "Alias": "tb_groupchat", "Startup Cost": 0.43, "Total Cost": 172205.39, "Plan Rows": 1293168, "Plan Width": 24, "Output": ["id", "chat_id", "sender_id", "content", "\"timestamp\""], "Index Cond": "((tb_groupchat.\"timestamp\" >= '1684944000000'::bigint) AND (tb_groupchat.\"timestamp\" < '1685030400000'::bigint))" } ] }, "Query Identifier": 6892608323288585066, "JIT": { "Functions": 5, "Options": { "Inlining": false, "Optimization": false, "Expressions": true, "Deforming": true } } } ] 

不知道各位同学有没有啥高招。。。