Github user sijunhe commented on the issue:
https://github.com/apache/spark/pull/17359
Would love to see this feature in Spark SQL.
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Github user gczsjdy commented on the issue:
https://github.com/apache/spark/pull/17359
Sorry, but I think this is inactive. Thanks for your attention. @wzhfy
@viirya @gatorsmile
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Github user viirya commented on the issue:
https://github.com/apache/spark/pull/17359
@gatorsmile I will try to take a look again.
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Github user wzhfy commented on the issue:
https://github.com/apache/spark/pull/17359
@gatorsmile Sure, I haven't read the context, but it's been nearly half a
year since last update, is this PR still active @gczsjdy ?
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Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/17359
cc @wzhfy @viirya Are you interested in reviewing this PR?
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Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/17359
Can one of the admins verify this patch?
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Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/17359
Can one of the admins verify this patch?
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Github user gczsjdy commented on the issue:
https://github.com/apache/spark/pull/17359
@viirya Updated, as the last sentence mentioned, I have tried to make Spark
support `GenericUDAFResolver`. But it lacks some interfaces comparing with
`AbstractGenericUDAFResolver` so this can't be
Github user gczsjdy commented on the issue:
https://github.com/apache/spark/pull/17359
@viirya Sorry for the late reply. It seems Spark cannot use Hive
`GenericUDAFnGrams`, since Spark only supports subclass of
`AbstractGenericUDAFResolver` & `UDAF` for Hive UDAF, while
Github user viirya commented on the issue:
https://github.com/apache/spark/pull/17359
Regarding the performance issue, does this change have significant
improvement compared with Hive's?
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Github user gczsjdy commented on the issue:
https://github.com/apache/spark/pull/17359
@rxin @cloud-fan @gatorsmile @viirya @tejasapatil Could you please help me
review this PR? Or is there anything I can do on this work?
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Github user chenghao-intel commented on the issue:
https://github.com/apache/spark/pull/17359
@rxin nGram is the built-in UDAF in Hive, and some users complaints they
faced performance issue when running the queries with nGram.
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Github user gczsjdy commented on the issue:
https://github.com/apache/spark/pull/17359
@rxin My fault, the example I gave is far from practical use and I have
updated. Actually, we can use it whenever the text analysis is reasonable to be
based on frequencies of word sequences. For
Github user rxin commented on the issue:
https://github.com/apache/spark/pull/17359
Why do we want this? Seems extremely low usage on this function in the wild.
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Github user gczsjdy commented on the issue:
https://github.com/apache/spark/pull/17359
cc @chenghao-intel @yucai @adrian-wang @cloud-fan @gatorsmile
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