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--- Diff:
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Finally! Congrat!
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cc @JoshRosen
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cc @yhuai @liancheng Do you mind if I ask a quick look for this as well
please?
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Github user viirya commented on the issue:
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@gatorsmile That depends. In practice, we have many solutions to deal with
the case you mentioned. It is not making sense to keep so many tiny parquet
files.
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Of course!
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Github user uzadude commented on the issue:
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Sure.
The current method for multiplying distributed block matrices starts by
deciding which block should be shuffled to which partition to do the actual
multiplications. This stage is
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cc @cloud-fan and @liancheng for review.
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@bonitao here's a patch that fixes it
https://github.com/apache/spark/pull/14099
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And also update the documentation.
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Oh, sure!
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I just added the general xpath function that returns an array of string too.
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Github user rxin commented on the issue:
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Yup... would be great if you can update this. Otherwise LGTM.
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--- Diff:
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@@ -63,6 +68,10 @@ trait
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Github user jurriaan commented on the issue:
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I thought it should be named in line with the escapeQuotes method, but what
it's doing is more like quoting all values then escaping all. So i guess that
name could make sense after all
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Github user gatorsmile commented on the issue:
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: ) Up to you. I think we will see less perfomance gains and more
significant performance penalty when a table contains many many small parquet
files. I also think that is expected, anyway.
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--- Diff:
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@@ -74,13 +74,71 @@ object RDDConversions {
}
}
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Github user viirya commented on the issue:
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@gatorsmile As I said, it is not an important issue here. What we want to
confirm is there is no significant performance penalty..
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Github user gatorsmile commented on the issue:
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@viirya Yeah, it is not easy to get a full performance picture. I do not
know how Spark community did it in the past. When I working for the mainframe
team, we had dedicated PQAs for measuring
Github user ueshin commented on a diff in the pull request:
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}
}
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ping @cloud-fan : )
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Github user cloud-fan commented on the issue:
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LGTM, cc @liancheng to take another look
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}
Github user viirya commented on the issue:
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@gatorsmile I think the times I run the benchmark is not enough to confirm
there is 5% performance difference. But I think it is not important here
because we don't want to measure the exact
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Github user gatorsmile commented on the issue:
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@viirya If you run multiple times and still see 5% performance difference,
you can confirm the penalty is around 5%. However, this might also depend on
the other factors, e.g., the total time.
Github user rxin commented on the issue:
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Can you fix Python?
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@gatorsmile BTW, if the TPC-DS performance is measured with 2.0 codebase,
this should benefit the performance.
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Github user viirya commented on the issue:
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@gatorsmile You know that the benchmark results will not the same every
time even you run it with the same codes. If the difference is under a small
range, we can assume they have no significant
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GitHub user petermaxlee opened a pull request:
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[SPARK-16436][SQL] checkEvaluation support NaN and RuntimeReplaceable
## What changes were proposed in this pull request?
This small patch modifies ExpressionEvalHelper. checkEvaluation to
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cc @cloud-fan
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Github user gatorsmile commented on the issue:
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Great! Around 5% performance penalty looks OK to me. Maybe we can send the
code changes to the performance team for seeing TPC-DS improvement. CC @jfchen
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I pushed a new change to this. We now have better error messages and test
coverage for those. These expressions also now require foldable paths.
I also changed the test values to make
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Github user viirya commented on the issue:
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Python UDT in python side only serializes the python data to sql type
defined in the Python UDT. The problem now is happened at the serialization to
row in java side on the serialized python data. I
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--- Diff:
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@@ -45,35 +45,28 @@ case class CatalogFunction(
*/
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cc @tdas
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cc @cloud-fan @rxin @liancheng
I did optimization for Literal `part`, so we don't need to check for every
row. But since we may not assume in all circumstances the `part` is Literal, I
keep
Github user jerryshao commented on a diff in the pull request:
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--- Diff: yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala ---
@@ -390,8 +390,9 @@ private[spark] class Client(
// Upload Spark and
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