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@shaneknapp, I just got this in since that's orthogonal to this PR :-) .
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Hi @gengliangwang , Yes the parameter is not used from the beginning.
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Thank you, @heary-cao , @yucai , @wangyum , and @HyukjinKwon .
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I don't think we should map decimals to float. It will loses precisions and
it's a breaking change.
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One part of Spark MLlib Kmean Logic Performance problem
[SPARK-25868][MLlib] One part of Spark MLlib Kmean Logic Performance problem
## What changes were proposed in this pull request?
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anymore comments on this @cloud-fan @maryannxue @viirya ?
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Github user jamal119 commented on the issue:
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How did you end up solving that problemï¼reinstall the spark ï¼ Which
version did you installï¼Can you offer a final solutionï¼thanks
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Please fix the PR title as described in
https://spark.apache.org/contributing.html and read it.
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Also please fill the PR description. How much performance does it gain?
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How much performance does it gain in end-to-end test, and how does it
provide better performance?
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--- Diff: sql/core/src/test/resources/sample.json ---
@@ -0,0 +1,2 @@
+{"a" : "2" ,"b" : "blah", "c_!@(3)":1}
--- End diff --
why add
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Github user dongjoon-hyun commented on the issue:
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@heary-cao . You had better merge in GitHub. GitHub provides merge button
for that.
Usually, merging PR is giving a credit to the person.
In Apache Spark, we don't copy someone's
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Github user 351zyf commented on the issue:
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> Then, you can convert the type into double or floats in Spark DataFrame.
This is super easily able to work around at Pandas DataFrame or Spark's
DataFrame. I don't think we should add this flag.
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--- Diff: sql/core/benchmarks/JSONBenchmarks-results.txt ---
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--- Diff:
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@@ -16,30 +16,31 @@
*/
package
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SPARK-25881
## What changes were proposed in this pull request?
https://github.com/apache/spark/pull/22888
decimal type should consider as a number but not object (string)
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> I think you can just manually convert from Pandas DataFrame, no?
If I'm using function toPandas, I dont think decimal to object is right.
Isn't decimal values usually a value to
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--- Diff: sql/core/benchmarks/JSONBenchmarks-results.txt ---
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Github user HyukjinKwon commented on the issue:
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Then, you can convert the type into double or floats in Spark DataFrame.
This is super easily able to work around at Pandas DataFrame or Spark's
DataFrame. I don't think we should add this
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Github user HyukjinKwon commented on the issue:
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You're introducing a flag to convert. I think it's virtually same enabling
the flag vs calling a function to convert.
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--- Diff: sql/core/benchmarks/CSVBenchmarks-results.txt ---
@@ -0,0 +1,27 @@
Github user ScrapCodes commented on the issue:
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@mccheah and @skonto Do you have suggestion how to go forward from here? I
wanted to write more tests, like how to recover from checkpoints etc...
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OK
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@@ -0,0 +1,65 @@
+/*
+ * Licensed to
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and this also have no effect on timestamp values.
tested.
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The failure seems to be the same.
```
Using `mvn` from path:
/home/jenkins/workspace/SparkPullRequestBuilder/build/apache-maven-3.5.4/bin/mvn
[ERROR] Failed to execute goal
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Retest this please.
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I would close this, @351zyf.
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GitHub user arman1371 opened a pull request:
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[SPARK-25882][SQL] Added a function to join two datasets using one column
with join type parameter
## What changes were proposed in this pull request?
Added a function to join two datasets
Github user linhong-intel commented on the issue:
https://github.com/apache/spark/pull/18745
@caneGuy Thanks for you fixing. I'm facing this problem as well and your
fix works very well.
But the streaming sub-module still generate test jar twice same as your PR
description. How
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[SPARK-25883][SQL][Minor] Override method `prettyName` in
`from_avro`/`to_avro`
## What changes were proposed in this pull request?
Previously in from_avro/to_avro, we override
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