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@yhuai yhuai commented Sep 17, 2015

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This change is for testing.

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SparkQA commented Sep 17, 2015

Test build #42616 has finished for PR 8800 at commit 604dc33.

  • This patch fails Scala style tests.
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  • This patch adds no public classes.

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Currently saveAsTable tries its best to save the table as Hive compatible format, and falls back to Spark SQL specific format if it fails. I wonder whether it's too confusing for users to reason about behavior of saveAsTable. Would it be better to have a separate SQL option to force using Hive compatible format? With this option on, users can be quite confident that if a saveAsTable call succeeds, the saved table must be Hive compatible.

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yhuai commented Sep 17, 2015

The impact of saving the metadata in a hive compatible way or not will appear when a user want to read the data. I am not sure they can remember how the metadata is stored. It is also very possible that the data producer and consumer are different persons/different teams.

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SparkQA commented Sep 17, 2015

Test build #42617 has finished for PR 8800 at commit 5874854.

  • This patch fails Spark unit tests.
  • This patch merges cleanly.
  • This patch adds no public classes.

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SparkQA commented Sep 18, 2015

Test build #1771 has finished for PR 8800 at commit 5874854.

  • This patch fails Spark unit tests.
  • This patch merges cleanly.
  • This patch adds no public classes.

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SparkQA commented Sep 18, 2015

Test build #42631 has finished for PR 8800 at commit 693939d.

  • This patch fails Spark unit tests.
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@yhuai yhuai changed the title [SPARK-10671] [SPARK-10672] [SQL] [WIP] Throws an analysis exception if we cannot find Hive UDFs and do not fail when we cannot save the metadata of a data source table in a hive compatible way [SPARK-10671] [SPARK-10672] [SQL] Throws an analysis exception if we cannot find Hive UDFs and do not fail when we cannot save the metadata of a data source table in a hive compatible way Sep 18, 2015
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hmm, it is not really safe to call dataType to trigger the evaluation of those lazy vals.

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yhuai commented Sep 18, 2015

Will split this PR to two PRs.

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SparkQA commented Sep 18, 2015

Test build #42672 has finished for PR 8800 at commit e133bee.

  • This patch passes all tests.
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@yhuai yhuai changed the title [SPARK-10671] [SPARK-10672] [SQL] Throws an analysis exception if we cannot find Hive UDFs and do not fail when we cannot save the metadata of a data source table in a hive compatible way [SPARK-10671] [SQL] Throws an analysis exception if we cannot find Hive UDFs Sep 18, 2015
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SparkQA commented Sep 18, 2015

Test build #42679 has finished for PR 8800 at commit e0e1a4d.

  • This patch fails Spark unit tests.
  • This patch merges cleanly.
  • This patch adds no public classes.

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SparkQA commented Sep 18, 2015

Test build #42692 has finished for PR 8800 at commit 4746b82.

  • This patch passes all tests.
  • This patch merges cleanly.
  • This patch adds no public classes.

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davies commented Sep 24, 2015

LGTM

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Should we add a comment here to say that we do type checking inside hive UDF class(such as HiveSimpleUDF) constructor?

asfgit pushed a commit that referenced this pull request Oct 1, 2015
…ve UDFs

Takes over #8800

Author: Wenchen Fan <[email protected]>

Closes #8941 from cloud-fan/hive-udf.
@yhuai yhuai closed this Oct 1, 2015
@yhuai yhuai deleted the udfAndDataSource branch October 1, 2015 20:26
kiszk pushed a commit to kiszk/spark-gpu that referenced this pull request Dec 26, 2015
…ve UDFs

Takes over apache/spark#8800

Author: Wenchen Fan <[email protected]>

Closes #8941 from cloud-fan/hive-udf.
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5 participants