6000万个条目，选择某个月份的条目.如何优化数据库? [英] 60 million entries, select entries from a certain month. How to optimize database?
问题描述
我有一个包含 6000 万个条目的数据库.
I have a database with 60 million entries.
每个条目都包含:
- 身份证
- 数据源ID
- 一些数据
- 日期时间
我需要选择某个月份的条目.每个月包含大约 200 万个条目.
I need to select entries from certain month. Each month contains approximately 2 million entries.
select *
from Entries
where time between "2010-04-01 00:00:00" and "2010-05-01 00:00:00"
(查询大约需要 1.5 分钟)
(query takes approximately 1.5 minutes)
我还想从给定的 DataSourceID 中选择某个月份的数据.(大约需要 20 秒)
I'd also like to select data from certain month from a given DataSourceID. (takes approximately 20 seconds)
大约有 50-100 个不同的 DataSourceID.
There are about 50-100 different DataSourceIDs.
有没有办法让它更快?我有哪些选择?如何优化这个数据库/查询?
Is there a way to make this faster? What are my options? How to optimize this database/query?
大约有.每秒 60-100 次插入！
There's approx. 60-100 inserts PER second!
推荐答案
利用 innodb 聚集主键索引.
Take advantage of innodb clustered primary key indexes.
http://dev.mysql.com/doc/refman/5.0/en/innodb-index-types.html
这将非常高效:
create table datasources
(
year_id smallint unsigned not null,
month_id tinyint unsigned not null,
datasource_id tinyint unsigned not null,
id int unsigned not null, -- needed for uniqueness
data int unsigned not null default 0,
primary key (year_id, month_id, datasource_id, id)
)
engine=innodb;
select * from datasources where year_id = 2011 and month_id between 1 and 3;
select * from datasources where year_id = 2011 and month_id = 4 and datasouce_id = 100;
-- etc..
编辑 2
忘记了我正在使用 3 个月的数据运行第一个测试脚本.这是一个月的结果:0.34 和 0.69 秒.
Forgot i was running the first test script with 3 months of data. Here's the results for a single month : 0.34 and 0.69 seconds.
select d.* from datasources d where d.year_id = 2010 and d.month_id = 3 and datasource_id = 100 order by d.id desc limit 10;
+---------+----------+---------------+---------+-------+
| year_id | month_id | datasource_id | id | data |
+---------+----------+---------------+---------+-------+
| 2010 | 3 | 100 | 3290330 | 38434 |
| 2010 | 3 | 100 | 3290329 | 9988 |
| 2010 | 3 | 100 | 3290328 | 25680 |
| 2010 | 3 | 100 | 3290327 | 17627 |
| 2010 | 3 | 100 | 3290326 | 64508 |
| 2010 | 3 | 100 | 3290325 | 14257 |
| 2010 | 3 | 100 | 3290324 | 45950 |
| 2010 | 3 | 100 | 3290323 | 49986 |
| 2010 | 3 | 100 | 3290322 | 2459 |
| 2010 | 3 | 100 | 3290321 | 52971 |
+---------+----------+---------------+---------+-------+
10 rows in set (0.34 sec)
select d.* from datasources d where d.year_id = 2010 and d.month_id = 3 order by d.id desc limit 10;
+---------+----------+---------------+---------+-------+
| year_id | month_id | datasource_id | id | data |
+---------+----------+---------------+---------+-------+
| 2010 | 3 | 116 | 3450346 | 42455 |
| 2010 | 3 | 116 | 3450345 | 64039 |
| 2010 | 3 | 116 | 3450344 | 27046 |
| 2010 | 3 | 116 | 3450343 | 23730 |
| 2010 | 3 | 116 | 3450342 | 52380 |
| 2010 | 3 | 116 | 3450341 | 35700 |
| 2010 | 3 | 116 | 3450340 | 20195 |
| 2010 | 3 | 116 | 3450339 | 21758 |
| 2010 | 3 | 116 | 3450338 | 51378 |
| 2010 | 3 | 116 | 3450337 | 34687 |
+---------+----------+---------------+---------+-------+
10 rows in set (0.69 sec)
编辑 1
决定用大约测试上述模式.6000 万行分布在 3 年内.每个查询都是冷运行的，即每个查询都单独运行，然后重新启动 mysql，清除任何缓冲区，并且没有查询缓存.
Decided to test the above schema with approx. 60 million rows spread over 3 years. Each query is run cold i.e. each run separately after which mysql is restarted clearing any buffers and with no query caching.
完整的测试脚本可以在这里找到:http://pastie.org/1723506 或以下...
The full test script can be found here : http://pastie.org/1723506 or below...
正如你所看到的，即使在我简陋的桌面上，它也是一个非常高性能的架构:)
As you can see it's a pretty performant schema even on my humble desktop :)
select count(*) from datasources;
+----------+
| count(*) |
+----------+
| 60306030 |
+----------+
select count(*) from datasources where year_id = 2010;
+----------+
| count(*) |
+----------+
| 16691669 |
+----------+
select
year_id, month_id, count(*) as counter
from
datasources
where
year_id = 2010
group by
year_id, month_id;
+---------+----------+---------+
| year_id | month_id | counter |
+---------+----------+---------+
| 2010 | 1 | 1080108 |
| 2010 | 2 | 1210121 |
| 2010 | 3 | 1160116 |
| 2010 | 4 | 1300130 |
| 2010 | 5 | 1860186 |
| 2010 | 6 | 1220122 |
| 2010 | 7 | 1250125 |
| 2010 | 8 | 1460146 |
| 2010 | 9 | 1730173 |
| 2010 | 10 | 1490149 |
| 2010 | 11 | 1570157 |
| 2010 | 12 | 1360136 |
+---------+----------+---------+
12 rows in set (5.92 sec)
select
count(*) as counter
from
datasources d
where
d.year_id = 2010 and d.month_id between 1 and 3 and datasource_id = 100;
+---------+
| counter |
+---------+
| 30003 |
+---------+
1 row in set (1.04 sec)
explain
select
d.*
from
datasources d
where
d.year_id = 2010 and d.month_id between 1 and 3 and datasource_id = 100
order by
d.id desc limit 10;
+----+-------------+-------+-------+---------------+---------+---------+------+---------+-----------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref |rows | Extra |
+----+-------------+-------+-------+---------------+---------+---------+------+---------+-----------------------------+
| 1 | SIMPLE | d | range | PRIMARY | PRIMARY | 4 | NULL |4451372 | Using where; Using filesort |
+----+-------------+-------+-------+---------------+---------+---------+------+---------+-----------------------------+
1 row in set (0.00 sec)
select
d.*
from
datasources d
where
d.year_id = 2010 and d.month_id between 1 and 3 and datasource_id = 100
order by
d.id desc limit 10;
+---------+----------+---------------+---------+-------+
| year_id | month_id | datasource_id | id | data |
+---------+----------+---------------+---------+-------+
| 2010 | 3 | 100 | 3290330 | 38434 |
| 2010 | 3 | 100 | 3290329 | 9988 |
| 2010 | 3 | 100 | 3290328 | 25680 |
| 2010 | 3 | 100 | 3290327 | 17627 |
| 2010 | 3 | 100 | 3290326 | 64508 |
| 2010 | 3 | 100 | 3290325 | 14257 |
| 2010 | 3 | 100 | 3290324 | 45950 |
| 2010 | 3 | 100 | 3290323 | 49986 |
| 2010 | 3 | 100 | 3290322 | 2459 |
| 2010 | 3 | 100 | 3290321 | 52971 |
+---------+----------+---------------+---------+-------+
10 rows in set (0.98 sec)
select
count(*) as counter
from
datasources d
where
d.year_id = 2010 and d.month_id between 1 and 3;
+---------+
| counter |
+---------+
| 3450345 |
+---------+
1 row in set (1.64 sec)
explain
select
d.*
from
datasources d
where
d.year_id = 2010 and d.month_id between 1 and 3
order by
d.id desc limit 10;
+----+-------------+-------+-------+---------------+---------+---------+------+---------+-----------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref |rows | Extra |
+----+-------------+-------+-------+---------------+---------+---------+------+---------+-----------------------------+
| 1 | SIMPLE | d | range | PRIMARY | PRIMARY | 3 | NULL |6566916 | Using where; Using filesort |
+----+-------------+-------+-------+---------------+---------+---------+------+---------+-----------------------------+
1 row in set (0.00 sec)
select
d.*
from
datasources d
where
d.year_id = 2010 and d.month_id between 1 and 3
order by
d.id desc limit 10;
+---------+----------+---------------+---------+-------+
| year_id | month_id | datasource_id | id | data |
+---------+----------+---------------+---------+-------+
| 2010 | 3 | 116 | 3450346 | 42455 |
| 2010 | 3 | 116 | 3450345 | 64039 |
| 2010 | 3 | 116 | 3450344 | 27046 |
| 2010 | 3 | 116 | 3450343 | 23730 |
| 2010 | 3 | 116 | 3450342 | 52380 |
| 2010 | 3 | 116 | 3450341 | 35700 |
| 2010 | 3 | 116 | 3450340 | 20195 |
| 2010 | 3 | 116 | 3450339 | 21758 |
| 2010 | 3 | 116 | 3450338 | 51378 |
| 2010 | 3 | 116 | 3450337 | 34687 |
+---------+----------+---------------+---------+-------+
10 rows in set (1.98 sec)
希望这有帮助:)
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