I have a model that already has a couple dozen of columns that will be filled most of the time. Now I need to add fields that might be different each time.
what's the best approach? I don't like the EAV pattern. I don't like the idea of having a sparse table either, especially considering how these extra properties could be very different.
Example:
WorkOrder:
PK id
FK assigned_to
FK contractor
DATE expected_completion
DATE actual_completion
... (many more)
Now I want to add properties like:
ep_1 (extra_property)
ep_2
ep_3
ep_4
... (many more)
These extra properties can be wildly different from record to record, and most of the time there will be a limited number of them, but there are no guarantees.
Think of records as:
id | assigned_to | contractor | ... | ep_1 | ep_2 | ep_3 | ... | ep_n
1 | 2 | 3 | ... | XYZ | NULL | NULL | ..开发者_StackOverflow社区. | 23
2 | 3 | 5 | ... | NULL | 1 | NULL | ... | NULL
3 | 2 | 1 | ... | NULL | 0 | NULL | ... | NULL
4 | 4 | 1 | ... | XYZ | NUL | NULL | ... | 45
I want to be able to list, filter, and search records as if those extra properties were actually columns, eg: I should be able to make queries like SELECT fields FROM table WHERE ep_n > 20
and SELECT fields FROM table WHERE ep_1='ABC'
What's the best solution to this?
What database? With SQL Server for instance, you can consider using Sparse Columns which are optimized for sparse tables. For EAV modeling I recommend reading the whitepaper on the subject from the SQL Server customer adviser team: Best Practices for Semantic Data Modeling for Performance and Scalability. Many of the recommendations apply to other vendors too, are not SQL Server specific.
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