postgresql?json取值慢的原因分析
目录
- 一、缘起
- 二、对比
- 2.1 输出类型对比
- 2.2 性能对比
- 三、优化
- 四、待调查
- 4.1 同类型转换是否影响性能
- 4.2 如何分析函数的耗时
- 五、附
- 5.1 json、jsonb区别
- 5.2 postgresql查看字段类型函数
- 5.3 性能分析指令
- 5.4 示例中的建表语句
- 5.5 示例中的压测脚本
一、缘起
慢sql分析，总行数80w+，通过监控分析慢SQL， 某个查询耗时超1s。
比较特殊的是：其中有个字段info是jsonb类型，写法：info::json->'length' as length
同样的查询条件查这个字段和不查这个字段相差3.3倍
那看来就是json取值拖垮了查询的性能。
取jsonb中的字段有多种取法(如下)， 那他们有什么区别呢，对性能有啥影响呢？
- info::json->'length'
- info::jsonb->'length'
- info::json->>'length'
- info::jsonb->>'length'
- info->'length'
- info->'length'
- info->>'length'
- info->>'length'
二、对比
2.1 输出类型对比
查询不同写法的类型：
select info::json->'length' AS "info::json->", pg_typeof(info::json->'length' ) , info::jsonb->'length' AS "info::jsonb->" , pg_typeof(info::jsonb->'length' ), info::json->>'length' AS "info::json->>" , pg_typeof(info::json->>'length' ), info::jsonb->>'length' AS "info::jsonb->>" , pg_typeof(info::jsonb->>'length'), info->'length' AS "info->" , pg_typeof(info->'length' ), info->'length' AS "info->" , pg_typeof(info->'length' ), info->>'length' AS "info->>" , pg_typeof(info->>'length' ), info->>'length' AS "info->>" , pg_typeof(info->>'length' ) from t_test_json limit 1;
结果
info::json-> | pg_typeof | info::jsonb-> | pg_typeof | info::json->> | pg_typeof | info::jsonb->> | pg_typeof | info-> | pg_typeof | info-> | pg_typeof | info->> | pg_typeof | info->> | pg_typeof
--------------+-----------+---------------+-----------+---------------+-----------+----------------+-----------+--------+-----------+--------+-----------+---------+-----------+---------+-----------
123.9 | json | 123.9 | jsonb | 123.9 | text | 123.9 | text | 123.9 | jsonb | 123.9 | jsonb | 123.9 | text | 123.9 | textttui
分析小结
- ->> 输出类型为text
- ->输出到底为何得看调用它的数据类型，比如：info类型是jsonb, 那么info->'length'为jsonb类型
- ::json、::jsonb起到类型转换的作用。
- info本来就是jsonb类型，info::jsonb算无效转换，是否对性能有影响，待会验证
2.2 性能对比
jihite=> EXPLAIN ANALYSE
jihite-> select
jihite-> info::json->'length' AS "info::json->", pg_typeof(info::json->'length' )
jihite-> from t_test_json limit 1;
QUERY PLAN
---------------------------------------------------------------------------------------------------------------
Limit (cost=0.00..0.04 rows=1 width=36) (actual time=0.028..0.028 rows=1 loops=1)
-> Seq Scan on t_test_json (cost=0.00..30.62 rows=750 width=36) (actual time=0.027..0.027 rows=1 loops=1)
Planning time: 0.056 ms
Execution time: 0.047 ms
(4 rows)
jihite=> EXPLAIN ANALYSE
jihite-> select
jihite-> info::jsonb->'length' AS "info::jsonb->" , pg_typeof(info::jsonb->'length' )
jihite-> from t_test_json limit 1
jihite-> ;
QUERY PLAN
---------------------------------------------------------------------------------------------------------------
Limit (cost=0.00..0.03 rows=1 width=36) (actual time=0.017..0.017 rows=1 loops=1)
-> Seq Scan on t_test_json (cost=0.00..23.12 rows=750 width=36) (actual time=0.015..0.015 rows=1 loops=1)
Planning time: 0.053 ms
Execution time: 0.031 ms
(4 rows)
jihite=> EXPLAIN ANALYSE
jihite-> select
jihite-> info::jsonb->'length' AS "info::jsonb->" , pg_typeof(info::jsonb->'length' )
jihite-> from t_test_json limit 1;
QUERY PLAN
---------------------------------------------------------------------------------------------------------------
Limit (cost=0.00..0.03 rows=1 width=36) (actual time=0.010..0.010 rows=1 loops=1)
-> Seq Scan on t_test_json (cost=0.00..23.12 rows=750 width=36) (actual time=0.009..0.009 rows=1 loops=1)
Planning time: 0.037 ms
Execution time: 0.022 ms
(4 rows)
jihite=>
jihite=> EXPLAIN ANALYSE
jihite-> select
jihite-> info::json->>'length' AS "info::json->>" , pg_typeof(info::json->>'length' )
jihite-> from t_test_json limit 1;
QUERY PLAN
---------------------------------------------------------------------------------------------------------------
Limit (cost=0.00..0.04 rows=1 width=36) (actual time=0.026..0.027 rows=1 loops=1)
-> Seq Scan on t_test_json (cost=0.00..30.62 rows=750 width=36) (actual time=0.025..0.025 rows=1 loops=1)
Planning time: 0.056 ms
Execution time: 0.046 ms
(4 rows)
jihite=>
jihite=> EXPLAIN ANALYSE
jihite-> select
jihite-> info::jsonb->>'length' AS "info::jsonb->>" , pg_typeof(info::jsonb->>'length')
jihite-> from t_test_json limit 1;
QUERY PLAN
---------------------------------------------------------------------------------------------------------------
Limit (cost=0.00..0.03 rows=1 width=36) (actual time=0.012..0.012 rows=1 loops=1)
-> Seq Scan on t_test_json (cost=0.00..23.12 rows=750 width=36) (actual time=0.011..0.011 rows=1 loops=1)
Planning time: 0.053 ms
Execution time: 0.029 ms
(4 rows)
jihite=>
jihite=> EXPLAIN ANALYSE
jihite-> select
jihite-> info->'length' AS "info->" , pg_typeof(info->'length' )
jihite-> from t_test_json limit 1;
QUERY PLAN
---------------------------------------------------------------------------------------------------------------
Limit (cost=0.00..0.03 rows=1 width=36) (actual time=0.014..0.014 rows=1 loops=1)
-> Seq Scan on t_test_json (cost=0.00..23.12 rows=750 width=36) (actual time=0.013..0.013 rows=1 loops=1)
Planning time: 0.052 ms
Execution time: 0.030 ms
(4 rows)
jihite=>
jihite=> EXPLAIN ANALYSE
jihite-> select
jihite-> info->'length' AS "info->" , pg_typeof(info->'length' )
jihite-> from t_test_json limit 1;
QUERY PLAN
---------------------------------------------------------------------------------------------------------------
Limit (cost=0.00..0.03 rows=1 width=36) (actual time=0.013..0.013 rows=1 loops=1)
-> Seq Scan on t_test_json (cost=0.00..23.12 rows=750 width=36) (actual time=0.012..0.012 rows=1 loops=1)
Planning time: 0.051 ms
Execution time: 0.029 ms
(4 rows)
jihite=>
jihite=> EXPLAIN ANALYSE
jihite-> select
jihite-> info->>'length' AS "info->>" , pg_typeof(info->>'length' )
jihite-> from t_test_json limit 1;
QUERY PLAN
---------------------------------------------------------------------------------------------------------------
Limit (cost=0.00..0.03 rows=1 width=36) (actual time=0.012..0.013 rows=1 loops=1)
-> Seq Scan on t_test_json (cost=0.00..23.12 rows=750 width=36) (actual time=0.011..0.011 rows=1 loops=1)
Planning time: 0.053 ms
Execution time: 0.030 ms
(4 rows)
jihite=>
jihite=> EXPLAIN ANALYSE
jihite-> select
jihite-> info->>'length' AS "info->>" , pg_typeof(info->>'length' )
jihite-> from t_test_json limit 1;
QUERY PLAN
---------------------------------------------------------------------------------------------------------------
Limit (cost=0.00..0.03 rows=1 width=36) (actual time=0.012..0.013 rows=1 loops=1)
-> Seq Scan on t_test_json (cost=0.00..23.12 rows=750 width=36) (actual time=0.011..0.011 rows=1 loops=1)
Planning time: 0.053 ms
Execution time: 0.029 ms
(4 rows)从执行耗时(Execution time)分析小结
执行了类型转换 jsonb->json，转换性能（0.46ms）显然低出不转换（0.3ms）
三、优化
把查询字段：info::json->'length' 改为info->>'length',减少类型转换导致性能的损耗。
四、待调查
4.1 同类型转换是否影响性能
字段本身是jsonb， 进行强转::jsonb 是否对性能造成影响，还是在执行预编译时就已被优化
从大量数据的压测看，转换会对性能有影响，但是不大
4.2 如何分析函数的耗时
在explain analyze时，主要分析了索引对性能的影响，那函数的具体影响如何查看呢？
五、附
5.1 json、jsonb区别
- jsonb 性能优于json
- jsonb 支持索引
- 【最大差异：效率】jsonb 写入时会处理写入数据，写入相对较慢，json会保留原始数据（包括无用的空格）
推荐把JSON 数据存储为jsonb
5.2 postgresql查看字段类型函数
pg_typeof()
5.3 性能分析指令
如果您有一条执行很慢的 SQL 语句，您想知道发生了什么以及如何优化它。
EXPLAIN ANALYSE 能够获取数据库执行 sql 语句，所经历的过程，以及耗费的时间，可以协助优化性能。
关键参数：
Execution time: *** ms 表明了实际的SQL 执行时间，其中不包括查询计划的生成时间
5.4 示例中的建表语句
# 建表语句
create table t_test_json
(
id bigserial not null PRIMARY KEY,
task character varying not null,
info jsonb not null,
create_time timestamp not null default current_timestamp
);# 压测数据
insert into t_test_json(task, info) values('1', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('2', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('3', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('4', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('5', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('6', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('7', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('8', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('9', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('10', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('11', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('12', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('13', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('14', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('15', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('16', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('17', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('18', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('19', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');
insert into t_test_json(task, info) values('20', '{"length": 123.9, "avatar": "avatar_url", "tags": ["python", "golang", "db"]}');5.5 示例中的压测脚本
import time
import psycopg
dbname, user, pwd, ip, port = '', '', '', '', '5432'
connection = "dbname=%s user=%s password=%s host=%s port=%s" % (dbname, user, pwd, ip, port)
db = psycopg.connect(connection)
cur = db.cursor()
ss = 0
lens = 20
for i in range(lens):
s = time.time()
sql = ''' select
id,
info::json->'length' as length
from
t_test_json
order by id
offset %s limit 1000 ''' % (i * 1000)
#print("sql:", sql)
cur.execute(sql)
rev = cur.fetchall()
e = time.time()
print("scan:", i, e - s)
ss += (e - s)
print('avg', ss / lens)到此这篇关于postgresql json取值慢的原因分析的文章就介绍到这了,更多相关postgresql json取值内容请搜索电脑手机教程网以前的文章或继续浏览下面的相关文章希望大家以后多多支持电脑手机教程网！
