3

我有以下表结构：

CREATE TABLE mytable (
  id   serial PRIMARY KEY,
  data jsonb
);

以下数据（部分为简洁起见......请注意年份的随机性和销售/费用年份彼此不一致）：

INSERT INTO mytable (data)
VALUES
('{"employee": "Jim Romo", 
 "sales": [{"value": 10, "yr": "2012"}, {"value": 5, "yr": "2013"}, {"value": 40, "yr": "2014"}],
 "expenses": [{"value": 2, "yr": "2007"}, {"value": 1, "yr": "2013"}, {"value": 3, "yr": "2014"}], 
 "product": "tv", "customer": "1", "updated": "20150501"
}'),
('{"employee": "Jim Romo", 
 "sales": [{"value": 10, "yr": "2012"}, {"value": 5, "yr": "2013"}, {"value": 41, "yr": "2014"}],
 "expenses": [{"value": 2, "yr": "2009"}, {"value": 3, "yr": "2013"}, {"value": 3, "yr": "2014"}], 
 "product": "tv", "customer": "2", "updated": "20150312"
}'),
('{"employee": "Jim Romo", 
 "sales": [{"value": 20, "yr": "2012"}, {"value": 25, "yr": "2013"}, {"value": 33, "yr": "2014"}],
 "expenses": [{"value": 8, "yr": "2012"}, {"value": 12, "yr": "2014"}, {"value": 5, "yr": "2009"}], 
 "product": "radio", "customer": "2", "updated": "20150311"
}'),
('{"employee": "Bill Baker", 
 "sales": [{"value": 1, "yr": "2010"}, {"value": 2, "yr": "2009"}, {"value": 3, "yr": "2014"}],
 "expenses": [{"value": 3, "yr": "2011"}, {"value": 1, "yr": "2012"}, {"value": 7, "yr": "2013"}], 
 "product": "tv", "customer": "1", "updated": "20150205"
}'),
('{"employee": "Bill Baker", 
 "sales": [{"value": 10, "yr": "2010"}, {"value": 12, "yr": "2011"}, {"value": 3, "yr": "2014"}],
 "expenses": [{"value": 4, "yr": "2011"}, {"value": 7, "yr": "2009"}, {"value": 4, "yr": "2013"}], 
 "product": "radio", "customer": "1", "updated": "20150204"
}'),
('{"employee": "Jim Romo",
 "sales": [{"value": 22, "yr": "2009"}, {"value": 17, "yr": "2013"}, {"value": 35, "yr": "2014"}],
 "expenses": [{"value": 14, "yr": "2011"}, {"value": 13, "yr": "2014"}, {"value": 8, "yr": "2013"}], 
 "product": "tv", "customer": "3", "updated": "20150118"
}')

对于每个员工，我需要评估最近更新的行，并找到 2014 年电视销售额大于 30 的员工。从那里我需要进一步过滤平均电视费用低于 5 的员工。对于平均值，我只需要取他们所有的电视费用，而不仅仅是最新的一排。

我的预期输出将是 1 行：

employee    | customer | 2014 tv sales   |  2013 avg tv expenses
------------+----------+-----------------+----------------------
Jim Romo    |    1     |   40            |  4

我可以（有点）做1或其他但不能同时做：

一个。获得 2014 年销售额 > 30（但无法获得他们最近的“电视”销售额；（

SELECT * FROM mytable WHERE (SELECT (a->>'value')::float FROM
    (SELECT jsonb_array_elements(data->'sales') as a) as b 
    WHERE a @> json_object(ARRAY['yr', '2014'])::jsonb) > 30

湾。获取 2013 年的平均费用（这需要是平均电视费用）

SELECT avg((a->>'value')::numeric) FROM  
  (SELECT jsonb_array_elements(data->'expenses') as a FROM mytable) as b
  WHERE a @> json_object(ARRAY['yr', '2013'])::jsonb

编辑：这可能是一个非常大的表，因此任何关于性能和索引需求的评论都将不胜感激，因为我对 postgresql 和 jsonb 都是新手。

编辑＃2：我已经尝试了这两个答案，但对于大桌子来说似乎都没有效率；（

4

1 回答 1

1

这是对您的问题的（相当冗长的）答案。查询中的注释应该解释不同的部分。我遵循的基本思想是：1）每个操作保持简单，先尝试产生正确的结果，然后优化；2）尽可能（但不是太多）将json结构转换为更“类似关系”的结构，因为关系具有比postgres中的json数据更强大的运算符。当然，还有空间可以简化查询，甚至生成更高效的版本，但至少这是一个起点。

with mytable1 as   -- transform the table in a more "relational-like" structure (just for clarity)
  (select id, data->>'employee' as employee, data->>'product' as product, 
      (data->>'updated')::integer as updated, (data->>'customer')::integer as customer,
          data->'sales' as sales, data->'expenses' as expenses 
   from mytable),
avg_exp_for_2013_tv as -- find the average expenses for tv in 2013 for each employee
   (select employee, avg(expenses.value) as avg2013_expenses
    from mytable1 , jsonb_to_recordset(expenses) as expenses(yr text, value float)
    where product = 'tv' and expenses.yr = '2013'
    group by employee),
most_recent_updates_employees as  -- find the most recent updates for each employee 
   (select employee, max(updated) as updated
    from mytable1 t1
    group by employee),
most_recent_updated_rows as   -- find the rows with the most recent updates
   (select t1.*
    from mytable1 t1, most_recent_updates_employees m
    where t1.employee = m.employee and t1.updated = m.updated),
employees_with_2014_tv_sales_gt_30 as
   (select employee, customer, sales.value as sales_value
    from most_recent_updated_rows m, jsonb_to_recordset(m.sales) as sales(yr text, value float)
    where yr = '2014' and value > 30)
select e1.employee, e1.customer, e1.sales_value as "2014 tv sales", e2.avg2013_expenses as "2013 avg tv expenses"
from employees_with_2014_tv_sales_gt_30 e1, avg_exp_for_2013_tv e2
where e1.employee = e2.employee and avg2013_expenses < 5
于 2015-06-19T08:52:40.700 回答