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--- Diff:
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Github user rxin commented on the issue:
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i didn't look at your new code, but is your old code safe? e.g. a project
that depends on the new alias.
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@felixcheung . If the question is about writer versions, Spark/Hive works
on top of ORC/Parquet library. ORC/Parquet library already writes its specific
version for that purpose. For me, it
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First glance this looks like a lot of nice simplification, will take a
proper look over this tomorrow
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--- Diff: sql/core/benchmarks/DataSourceReadBenchmark-results.txt ---
@@ -2,268 +2,268 @@
SQL Single Numeric Column Scan
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SQL Single Numeric Column Scan
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Thank you for review, @felixcheung . Could you elaborate a little bit more?
Here, three writers are used: new native ORC writer, old Hive ORC writer, and
native Parquet writer.
> a prop
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Github user uzadude commented on the issue:
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this is the original query. we can see the explode followed by the shuffle:
```
import org.apache.spark.sql.functions._
import org.apache.spark.sql.expressions._
val N = 1
Github user felixcheung commented on a diff in the pull request:
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@felixcheung SPARK_HOME has been getting filtered out since #10329
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--- Diff: R/pkg/R/functions.R ---
@@ -1663,9 +1692,24 @@ setMethod("toDegrees",
#' @aliases toRadians toRadians,Column-method
#' @note
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retest this please
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@cloud-fan I have a simpler fix for this issue. Can you take another look?
Thanks.
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Github user MaxGekk commented on the issue:
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I made a fix for broken array and map in `JsonToStructs` because inside of
`FailureSafeParser` is not clear from where the call came. I am still not sure
that wrapping actual type by `StructType`
Github user srowen commented on the issue:
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I'd escalate to dev@ for more visibility. It has some longer-term
consequences, and I'd like to hear current thinking on how much these APIs
should change, etc.
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Github user mgaido91 commented on the issue:
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@srowen I think it would not be a big deal if we would change the return
type of these to Double, since they are now private. If that is the only change
needed we may be able to reuse the
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--- Diff: mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala ---
@@ -521,19 +521,21 @@ object MLUtils extends Logging {
* The bound
Github user cloud-fan commented on the issue:
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since this is a bug fix, shall we also backport it?
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--- Diff: R/pkg/R/functions.R ---
@@ -319,6 +319,27 @@ setMethod("acos",
column(jc)
})
+#' @details
+#'
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Github user srowen commented on the issue:
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Aha. On the one hand, I suppose they can't extend that class because of the
signature difference, and indeed it says it's the superclass of regression and
classification models. I can imagine that
Github user uzadude commented on the issue:
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The whole idea is that we'll get one shuffle and it will be before the
explode as the window's partition is contained in the repartition.
I'll show the physical plan.
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@dongjoon-hyun @yucai
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--- Diff:
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@@ -32,9 +32,11 @@ import org.apache.spark.sql.types._
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Github user mgaido91 commented on the issue:
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@erikerlandson @srowen actually we already have a `PredictionModel` for
this. am not sure why clustering algorithms are not extending it though, but
in that class the method returns a `Double`,
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[PARK-25965][SQL] Add avro read benchmark
## What changes were proposed in this pull request?
Add read benchmark for Avro, which is missing for a period.
The benchmark is similar
Github user hvanhovell commented on the issue:
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@uzadude where is this relevant? You will end up with two shuffles if you
do this.
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shall we also remove the end-to-end tests which are now not needed anymore?
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Yeah it's a good point and I wonder if @jkbradley or @mengxr or @MLnick
want to weigh in. If this superclass method existed, I think it would be
`predict(Vector):Int` anyway, so seems pretty
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