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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點
(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_timestamp;
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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