postgresql json取值为何这么慢？

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一、缘起

慢sql分析，总行数80w+。

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

        task.id,

        act.payload::json->'prod_type' as prod_type

        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)