MySQL中存儲時間通常會用datetime類型，但現(xiàn)在很多系統(tǒng)也用int存儲unix時間戳，它們有什么區(qū)別？本人總結(jié)如下：

int

（1）4個字節(jié)存儲，INT的長度是4個字節(jié)，存儲空間上比datatime少，int索引存儲空間也相對較小，排序和查詢效率相對較高一點(diǎn)點(diǎn)

（2）可讀性極差，無法直觀的看到數(shù)據(jù)

TIMESTAMP

（1）4個字節(jié)儲存

（2）值以UTC格式保存

（3）時區(qū)轉(zhuǎn)化 ，存儲時對當(dāng)前的時區(qū)進(jìn)行轉(zhuǎn)換，檢索時再轉(zhuǎn)換回當(dāng)前的時區(qū)。

（4）TIMESTAMP值不能早于1970或晚于2037

datetime

（1）8個字節(jié)儲存

（2）與時區(qū)無關(guān)

（3）以'YYYY-MM-DD HH:MM:SS'格式檢索和顯示DATETIME值。支持的范圍為'1000-01-01 00:00:00'到'9999-12-31 23:59:59'

隨著Mysql性能越來越來高，個人覺得關(guān)于時間的存儲方式，具體怎么存儲看個人習(xí)慣和項目需求吧

分享兩篇關(guān)于int vs timestamp vs datetime性能測試的文章

Myisam:MySQL DATETIME vs TIMESTAMP vs INT 測試儀

CREATE TABLE `test_datetime` (
`id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`datetime` FIELDTYPE NOT NULL,
PRIMARY KEY (`id`)
) ENGINE=MyISAM;

機(jī)型配置

• kip-locking
• key_buffer = 128M
• max_allowed_packet = 1M
• table_cache = 512
• sort_buffer_size = 2M
• read_buffer_size = 2M
• read_rnd_buffer_size = 8M
• myisam_sort_buffer_size = 8M
• thread_cache_size = 8
• query_cache_type = 0
• query_cache_size = 0
• thread_concurrency = 4

測試

DATETIME   14111 14010        14369     130000000
TIMESTAMP  13888        13887        14122     90000000
INT        13270        12970        13496     90000000

執(zhí)行mysql

mysql> select * from test_datetime into outfile ‘/tmp/test_datetime.sql';
Query OK, 10000000 rows affected (6.19 sec)

mysql> select * from test_timestamp into outfile ‘/tmp/test_timestamp.sql';
Query OK, 10000000 rows affected (8.75 sec)

mysql> select * from test_int into outfile ‘/tmp/test_int.sql';
Query OK, 10000000 rows affected (4.29 sec)

alter table test_datetime rename test_int;
alter table test_int add column datetimeint INT NOT NULL;
update test_int set datetimeint = UNIX_TIMESTAMP(datetime);
alter table test_int drop column datetime;
alter table test_int change column datetimeint datetime int not null;
select * from test_int into outfile ‘/tmp/test_int2.sql';
drop table test_int;

So now I have exactly the same timestamps from the DATETIME test, and it will be possible to reuse the originals for TIMESTAMP tests as well.

mysql> load data infile ‘/export/home/ntavares/test_datetime.sql' into table test_datetime;
Query OK, 10000000 rows affected (41.52 sec)
Records: 10000000 Deleted: 0 Skipped: 0 Warnings: 0

mysql> load data infile ‘/export/home/ntavares/test_datetime.sql' into table test_timest
Query OK, 10000000 rows affected, 44 warnings (48.32 sec)
Records: 10000000 Deleted: 0 Skipped: 0 Warnings: 44

mysql> load data infile ‘/export/home/ntavares/test_int2.sql' into table test_int;
Query OK, 10000000 rows affected (37.73 sec)
Records: 10000000 Deleted: 0 Skipped: 0 Warnings: 0

As expected, since INT is simply stored as is while the others have to be recalculated. Notice how TIMESTAMP still performs worse, even though uses half of DATETIME storage size.

Let's check the performance of full table scan:

mysql> SELECT SQL_NO_CACHE count(id) FROM test_datetime WHERE datetime > ‘1970-01-01 01:30:00′ AND datetime  ‘1970-01-01 01:35:00′;
+———–+
| count(id) |
+———–+
|  211991 |
+———–+
1 row in set (3.93 sec)

mysql> SELECT SQL_NO_CACHE count(id) FROM test_timestamp WHERE datetime > ‘1970-01-01 01:30:00′ AND datetime  ‘1970-01-01 01:35:00′;
+———–+
| count(id) |
+———–+
|  211991 |
+———–+
1 row in set (9.87 sec)

mysql> SELECT SQL_NO_CACHE count(id) FROM test_int WHERE datetime > UNIX_TIMESTAMP('1970-01-01 01:30:00′) AND datetime  UNIX_TIMESTAMP('1970-01-01 01:35:00′);
+———–+
| count(id) |
+———–+
|  211991 |
+———–+
1 row in set (15.12 sec)

Then again, TIMESTAMP performs worse and the recalculations seemed to impact, so the next good thing to test seemed to be without those recalculations: find the equivalents of those UNIX_TIMESTAMP() values, and use them instead:

mysql> select UNIX_TIMESTAMP('1970-01-01 01:30:00′) AS lower, UNIX_TIMESTAMP('1970-01-01 01:35:00′) AS bigger;
+——-+——–+
| lower | bigger |
+——-+——–+
| 1800 |  2100 |
+——-+——–+
1 row in set (0.00 sec)

mysql> SELECT SQL_NO_CACHE count(id) FROM test_int WHERE datetime > 1800 AND datetime  2100;
+———–+
| count(id) |
+———–+
|  211991 |
+———–+
1 row in set (1.94 sec)

Innodb:MySQL DATETIME vs TIMESTAMP vs INT performance and benchmarking with InnoDB

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