join | 易学教程

Use table column value for LIMIT when performing join

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问题 I have a situation where I'm performing a join between two tables, and I need a value from one table to be used as a LIMIT factor for a subquery in the join. Assume I have the following [extremely simplified] tables - data: experiment_id | value --------------|-------- 1 | 2.5 1 | 2.6 1 | 4.5 1 | 2.3 1 | 3.5 1 | 2.8 2 | 2.3 2 | 1.2 2 | 1.1 2 | 3.6 2 | 3.8 2 | 4.1 2 | 7.9 2 | 4.2 2 | 1.0 data_clip: experiment_id | clip_index --------------|------------ 1 | 3 2 | 5 I need to sum each experiment

Access SQL FROM IN and JOINS

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问题 I've been successfully using SELECT [field] FROM [Table] IN 'Network Location'; this question filled me in on that Access SQL Query from another DB My question is: How does a JOIN fit into this framework Is it SELECT [field] FROM [Table] IN 'Network Location' JOIN [Table2] ON [Table2].field = [Table].field; or SELECT [field] FROM [Table] JOIN [Table2] ON [Table2].field = [Table].field IN 'Network Location' ; it feels like the former is the correct one. SQL statements are supposed to be like

How to join two rows that have the same keys and complementary values

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问题 My goal is to collapse the below table into one single column and this question deals specifically with the blue row below. The table has three categorical variables and 6 analysis/quantitative variables. Columns C1 and C2 are the only variables that need to match for a successful join. All blank cells are NaNs and python code for copying is below. These rows are exported independently because they have information found in other related tables, not included in the export. Question . (Blue)

MySQL Slow join - but not always and not on all tables

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问题 We're experiencing a performance issue with a MySQL database that's so weird we need another set of eyes to tell us whether we're going crazy or not. We've got 2 MySQL Certified Developers in the team, but all they can say is : "this is impossible". Anyway, here's the situation : we have a query that in theory should be reasonbly fast, but in reality is slow. If we slim down the query by removing 1 join, the query becomes extremely fast. If we remove a different join, it's still very slow,

Look up a list of values in the ranges (bins) as defined by two columns in another table and get the corresponding value from the third column

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问题 Hello I have two tables T1 and T2. T1 has a column of integer values. And T2 has ranges defined by two columns and a corresponding value for each range... Something like this: range_min range_max corr_value 5 10 1020 11 15 5000 Suppose I want to be able to get the "value" from T2 for each integer of T1 depending on which range the integer value falls into. Say, I have 6, 7, and 12 in T1. Then, the ideal result would look like this: integer_val corr_value 6 1020 7 1020 12 5000 Note that I don

sql joins

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内连接 select <字段> from tableA A inner join tableB B on A.key = B.key; 左连接 select <字段> from tableA A left join tableB B on A.key = B.key; 右连接 select <字段> from tableA A right join tableB B on A.key = B.key; select <字段> from tableA A left join tableB B on A.key = B.key where B.key is null; 5. select <字段> from tableA A right join tableB B on A.key = B.key where A.key is null; 6. 全连接 select <字段> from tableA A full out join tableB B on A.key = B.key ; 7. select <字段> from tableA A full out join tableB B on A.key = B.key where A.key is null or B.key is null; **帅气的远远啊** 来源： CSDN 作者： yuanyuan啊链接： https:/

Is it faster to programmatic join tables or use SQL Join statements when one table is much smaller?

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问题 Is it faster to programmatically join tables or use SQL Join statements when one table is much smaller? More specifically, how does grabbing a string from a hashmap<int, string> of the smaller table and setting its value to the objects returned from the larger table compare to pre-joining the tables on the database? Does the relative sizes of the two tables make a difference? Update: To rephrase my question. Does grabbing the subset of the larger table (the 5,000 - 20,000 records I care about

Merge 'left', but override 'right' values where possible

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问题 Objective I've reviewed pandas documentation on merge but have a question on overriding values efficiently in a 'left' merge. I can do this simply for one pair of values (as seen here), but it becomes cluttered when trying to do multiple pairs. Setup If I take the following dataframes: a = pd.DataFrame({ 'id': [0,1,2,3,4,5,6,7,8,9], 'val': [100,100,100,100,100,100,100,100,100,100] }) b = pd.DataFrame({ 'id':[0,2,7], 'val': [500, 500, 500] }) I can merge them: df = a.merge(b, on=['id'], how=

Merge 'left', but override 'right' values where possible

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Is there any performance issue with Inner Join?

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问题 Currently I am using lot of inner join's(around 7) in my sp, does it have any impact on sp performance. does left outer join gives better performance then inner join. one more thing if i m joining two tables a and b which has column id and id1, both r not nullable. i suppose here i can go for inner join as these columns r indexed. 回答1: Outer joins are more expensive than inner joins. What I am about to say is going to be controversial to many. If you tune the database right and if you don't