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Model Performance #47

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alan-ai-learner opened this issue Sep 2, 2021 · 7 comments
Open

Model Performance #47

alan-ai-learner opened this issue Sep 2, 2021 · 7 comments

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@alan-ai-learner
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alan-ai-learner commented Sep 2, 2021

The model is working fine for smaller DBs. But when there are multiple level of foreign key connections it seems to struggle
Why is it so, any reason?

@ReinierKoops
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ReinierKoops commented Sep 3, 2021

In the Spider dataset paper (Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task by Tao Yu et al.) they created their own model. I think it also applies to this model to some extend: "The performance decreases as the database has more foreign keys. The first reason is because the model has to choose column and table names from many candidates in a complex database schema. Second, a complex database schema presents a great challenge for the model to capture the relationship between different tables with foreign keys."

@alan-ai-learner
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In the Spider dataset paper (Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task by Tao Yu et al.) they created their own model. I think it also applies to this model to some extend: "The performance decreases as the database has more foreign keys. The first reason is because the model has to choose column and table names from many candidates in a complex database schema. Second, a complex database schema presents a great challenge for the model to capture the relationship between different tables with foreign keys."

So what could be the possible solutions for the bigger databases?

@ReinierKoops
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Better mapping between potential solutions and actual solutions.

@alan-ai-learner
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alan-ai-learner commented Sep 3, 2021 via email

@ReinierKoops
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I don't think there is a solution to it yet, really.

@alan-ai-learner
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I don't think there is a solution to it yet, really.

Thanks alot for your time!

@alan-ai-learner
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Hi @OhadRubin any suggestions on this?

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