Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/14580
Sorry, I gave a wrong answer at the beginning. Next time, I will review it
more carefully before leaving the comment. Thank you for your work!
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Github user dongjoon-hyun commented on the issue:
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:) I think about this issue again.
At this stage, could you make a PR for this?
I think you're the best person to do that. You made this optimizer and
found the correct fix.
GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/14660
[SPARK-17071][SQL] Fetch Parquet schema without another Spark job when it
is a single file to touch
## What changes were proposed in this pull request?
It seems Spark executes
Github user dbtsai commented on the issue:
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@sethah Thank you for great work. I'll make another pass tomorrow.
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Github user gatorsmile commented on the issue:
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One more try:
```Scala
val splitConjunctiveConditions: Seq[Expression] =
splitConjunctivePredicates(filter.condition)
val conditions = splitConjunctiveConditions ++
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Github user gatorsmile commented on the issue:
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Another version. : )
```Scala
val splitConjunctiveConditions: Seq[Expression] =
splitConjunctivePredicates(filter.condition)
val conditions =
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Github user gatorsmile commented on the issue:
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How about another version?
```
val leftConditions =
(splitConjunctiveConditions ++
filter.constraints.filter(_.isInstanceOf[IsNotNull]))
Github user dongjoon-hyun commented on the issue:
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Oh, that would be perfect fix.
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Github user gatorsmile commented on the issue:
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How about this fix?
```
val leftHasNonNullPredicate = leftConditions.exists(canFilterOutNull) ||
filter.constraints.filter(_.isInstanceOf[IsNotNull])
.exists(expr
Github user sethah commented on the issue:
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@dbtsai Thanks for taking the time to review this! Major items right now:
* Adding derivation to the aggregator doc (this is mostly finished, just
fighting scala doc with Latex)
*
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Github user sethah commented on a diff in the pull request:
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--- Diff:
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---
@@ -0,0 +1,626 @@
+/*
+ * Licensed to the
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Github user gatorsmile commented on the issue:
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Another better fix is to use `nullable` in `Expression` for `IsNotNull`
constraints. `filter.constraints.filter(_.isInstanceOf[IsNotNull])`
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Github user gatorsmile commented on the issue:
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`canFilterOutNull ` will cover almost all the cases. Sorry, I did not read
the plan until you asked me to write a test case. Then, I realized the
implementation of natural/using join is just
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Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/14506
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Github user AmplabJenkins commented on the issue:
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Can one of the admins verify this patch?
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Github user dongjoon-hyun commented on the issue:
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Please let me think more on this issue.
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GitHub user Sherry302 opened a pull request:
https://github.com/apache/spark/pull/14659
[SPARK-16757] Set up Spark caller context to HDFS
## What changes were proposed in this pull request?
1. Pass `jobId` to Task.
2. Invoke Hadoop APIs.
A new function
Github user dongjoon-hyun commented on the issue:
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Yep. I agree. `Expr` could be anything. However, this will reduce the scope
of this optimization greatly. Is it okay for you?
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Thanks. Merging to master.
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Github user dongjoon-hyun commented on the issue:
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If that is not applicable, I agree with @gatorsmile .
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Github user gatorsmile commented on the issue:
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That just resolves a specific case. The expressions could be much more
complex. `Coalesce` can be used in a very deep layer.
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Github user dongjoon-hyun commented on the issue:
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What about this if we could exclude those functions?
```scala
val leftHasNonNullPredicate = leftConditions.exists(canFilterOutNull)
||
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Github user junyangq commented on a diff in the pull request:
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--- Diff: R/pkg/R/functions.R ---
@@ -1143,7 +1139,7 @@ setMethod("minute",
#' @export
#' @examples \dontrun{select(df,
Github user gatorsmile commented on the issue:
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The right fix is to change the following statements
```Scala
val leftHasNonNullPredicate = leftConditions.exists(canFilterOutNull) ||
Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/14580
Sorry, my above description is not clear.
`isnotnull(coalesce(b#227, c#238))` does not filter out `NULL` of `b#227`
and `c#238`. Only when both are `b#227` and `c#238` are `NULL`,
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Can you explain `isnotnull(coalesce(b#227, c#238)) does not filter out
NULL!!!`?
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Github user jkbradley commented on the issue:
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Btw, to give back-of-the-envelope estimates, we can look at 2 numbers:
(1) How many nodes will be split on each iteration?
(2) How big is the forest which is serialized and sent to workers
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Github user gatorsmile commented on the issue:
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```Scala
val df12 = df1.join(df2, $"df1.a" === $"df2.a", "fullouter")
.select(coalesce($"df1.b", $"df2.c").as("a"), $"df1.b", $"df2.c")
df12.join(df3, "a").explain(true)
Github user junyangq commented on a diff in the pull request:
https://github.com/apache/spark/pull/14558#discussion_r74874081
--- Diff: R/pkg/R/SQLContext.R ---
@@ -181,7 +181,7 @@ getDefaultSqlSource <- function() {
#' @method createDataFrame default
#' @note
GitHub user witgo opened a pull request:
https://github.com/apache/spark/pull/14658
[WIP][SPARK-5928] Remote Shuffle Blocks cannot be more than 2 GB
## What changes were proposed in this pull request?
Add class `ChunkFetchInputStream` and it have the following effects:
Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/14392#discussion_r74873932
--- Diff: R/pkg/R/generics.R ---
@@ -1279,6 +1279,13 @@ setGeneric("spark.naiveBayes", function(data,
formula, ...) { standardGeneric("s
#' @export
Github user junyangq commented on a diff in the pull request:
https://github.com/apache/spark/pull/14558#discussion_r74873867
--- Diff: R/pkg/R/mllib.R ---
@@ -298,14 +304,15 @@ setMethod("summary", signature(object =
"NaiveBayesModel"),
#' Users can call \code{summary} to
Github user WeichenXu123 commented on the issue:
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@holdenk
I think depth (2) is enough to handle large RDD and bigger depth may add
cost. I'll append test result later. Thanks!
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Github user gatorsmile commented on the issue:
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None of us is right. : (
```isnotnull(coalesce(b#227, c#238))``` does not filter out `NULL`!!!
Thus, the right fix is to remove the second condition.
```Scala
Github user jkbradley commented on the issue:
https://github.com/apache/spark/pull/14359
Sorry for the long delay; I've been swamped by other things for a while.
Re-emerging...
I switched to Stack and then realized Stack has been deprecated in Scala
2.11, so I reverted to
Github user gatorsmile commented on the issue:
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I found the root cause. None of us is right. : (
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Github user witgo commented on the issue:
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@hvanhovell
I will submit some small PRs and provide a more high level description of
them.
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Github user kiszk commented on the issue:
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You are right. I missed `UnsafeArrayData` is a subclass of `ArrayData`. We
can pass `UnsafeArrayData` to an projection.
I have one question.
When we directly generate `UnsafeArrayData`
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Github user HyukjinKwon commented on the issue:
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Also, if my understanding is correct, we are picking up only single file to
read footer (see
Github user HyukjinKwon commented on a diff in the pull request:
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala
---
@@ -423,6 +425,54 @@ class
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---
@@ -423,6 +425,54 @@ class
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--- Diff: R/pkg/R/mllib.R ---
@@ -414,6 +421,94 @@ setMethod("predict", signature(object = "KMeansModel"),
Github user dongjoon-hyun commented on the issue:
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Thank you, @nsyca!
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Github user BryanCutler commented on the issue:
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Thanks for the review @JoshRosen, I made the requested changes and tested
it out once more. I think it is low risk because it is pretty well isolated to
this particular issue and only improves
Github user dongjoon-hyun commented on the issue:
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Hmm.
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Github user dongjoon-hyun commented on the issue:
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Yep. Here is the output.
```scala
scala> val a = Seq((1,2),(2,3)).toDF("a","b").createOrReplaceTempView("A")
scala> val b =
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/14447#discussion_r74870955
--- Diff: R/pkg/R/mllib.R ---
@@ -414,6 +421,94 @@ setMethod("predict", signature(object = "KMeansModel"),
Github user felixcheung commented on a diff in the pull request:
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--- Diff: R/pkg/R/mllib.R ---
@@ -414,6 +421,94 @@ setMethod("predict", signature(object = "KMeansModel"),
Github user nsyca commented on the issue:
https://github.com/apache/spark/pull/14580
@dongjoon-hyun, could you please try this on your PR?
val a = Seq((1,2),(2,3)).toDF("a","b").createOrReplaceTempView("A")
val b =
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/14447#discussion_r74870693
--- Diff: R/pkg/R/mllib.R ---
@@ -414,6 +421,94 @@ setMethod("predict", signature(object = "KMeansModel"),
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Github user felixcheung commented on the issue:
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I think tests are only passing string, but we should coerce this to be safe.
LGTM
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--- Diff: R/pkg/R/mllib.R ---
@@ -632,3 +659,110 @@ setMethod("predict", signature(object =
"AFTSurvivalRegressionModel"),
Github user felixcheung commented on a diff in the pull request:
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--- Diff: R/pkg/R/mllib.R ---
@@ -632,3 +659,110 @@ setMethod("predict", signature(object =
"AFTSurvivalRegressionModel"),
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--- Diff: R/pkg/R/mllib.R ---
@@ -526,6 +533,24 @@ setMethod("write.ml", signature(object =
"KMeansModel", path = "character"),
Github user felixcheung commented on a diff in the pull request:
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--- Diff: R/pkg/R/generics.R ---
@@ -1279,6 +1279,13 @@ setGeneric("spark.naiveBayes", function(data,
formula, ...) { standardGeneric("s
#' @export
Github user felixcheung commented on a diff in the pull request:
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/r/LDAWrapper.scala ---
@@ -0,0 +1,207 @@
+/*
+ * Licensed to the Apache Software Foundation
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Github user cloud-fan commented on the issue:
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you can take a look at `GenerateUnsafeProjection`, if the `ArrayData` is
already an unsafe array, we will copy it directly, no iteration is needed.
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Github user felixcheung commented on a diff in the pull request:
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--- Diff: R/pkg/R/mllib.R ---
@@ -605,6 +701,69 @@ setMethod("spark.survreg", signature(data =
"SparkDataFrame", formula = "formula
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Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/14229#discussion_r74869578
--- Diff: R/pkg/R/mllib.R ---
@@ -605,6 +701,69 @@ setMethod("spark.survreg", signature(data =
"SparkDataFrame", formula = "formula
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