[GitHub] spark issue #17758: [SPARK-20460][SPARK-21144][SQL] Make it more consistent ...

2017-07-03 Thread cloud-fan
Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/17758 Actually after more thoughts, I think it's ok to do the validation in `RunnableCommand.run`, as it's still done in the driver side. --- If your project is set up for it, you can reply to this

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2017-07-03 Thread maropu
Github user maropu commented on the issue: https://github.com/apache/spark/pull/17758 Who calls `DDLCommand.validate`? Do you assume a new analyzer rule like `DDLCommandAnalysis`? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub

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2017-07-03 Thread cloud-fan
Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/17758 one more comment: putting all validating logic in `ProcessDDLCommand` looks not that good, how about we create a `DDLCommand` trait with a `def validate(): Unit` interface, so that each DDL

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2017-07-03 Thread maropu
Github user maropu commented on the issue: https://github.com/apache/spark/pull/17758 Aha, ok. I'll move there. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and

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2017-07-03 Thread cloud-fan
Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/17758 > In other cases, we need to ad-hoc check the duplication (e.g., JDBCRelation) I think `DataSource.resolveRelation` is a good place to do it. --- If your project is set up for it, you

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2017-07-02 Thread maropu
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2017-07-02 Thread maropu
Github user maropu commented on the issue: https://github.com/apache/spark/pull/17758 BTW (I think this is not related to this pr though), I saw many validation checks in `RunnableCommand.run()`. IMHO these checks also should be done in an analyzer phase (e.g.,

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2017-07-02 Thread maropu
Github user maropu commented on the issue: https://github.com/apache/spark/pull/17758 Based on the suggestion @cloud-fan did, I brushed up this code again and fixed the policy to check the duplication; The check for the SQL(DDL) case: - This check should be done in

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2017-06-30 Thread maropu
Github user maropu commented on the issue: https://github.com/apache/spark/pull/17758 ok, I'll recheck the policy and put the summary here. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have

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2017-06-30 Thread cloud-fan
Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/17758 It's a little messy about where we need to add this check, @maropu can you give a summary about it? thanks! --- If your project is set up for it, you can reply to this email and have your reply

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[GitHub] spark issue #17758: [SPARK-20460][SPARK-21144][SQL] Make it more consistent ...

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[GitHub] spark issue #17758: [SPARK-20460][SPARK-21144][SQL] Make it more consistent ...

2017-06-27 Thread SparkQA
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2017-06-26 Thread maropu
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