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[GitHub] [spark] zero323 opened a new pull request #29813: [SPARK-32799][R] Add allowMissingColumns to SparkR unionByName
zero323 opened a new pull request #29813:
URL: https://github.com/apache/spark/pull/29813
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Add optional `allowMissingColumns` argument to SparkR `unionByName`.
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Feature parity.
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`unionByName` supports `allowMissingColumns`.
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Existing unit tests. New unit tests targeting this feature.
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[GitHub] [spark] zero323 commented on a change in pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
zero323 commented on a change in pull request #29813:
URL: https://github.com/apache/spark/pull/29813#discussion_r491709568
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2863,11 +2863,19 @@ setMethod("unionAll",
#' \code{UNION ALL} and \code{UNION DISTINCT} in SQL as column positions are not taken
#' into account. Input SparkDataFrames can have different data types in the schema.
#'
+#' When the parameter `allowMissingColumns` is `TRUE`, this function allows
Review comment:
Sounds good, but for consistency it should fixed in Python and Scala as well.
Should it be
> columns will be filled as null.
or
> columns will be filled with null.
though?
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[GitHub] [spark] MichaelChirico commented on a change in pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
MichaelChirico commented on a change in pull request #29813:
URL: https://github.com/apache/spark/pull/29813#discussion_r491705832
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2863,11 +2863,19 @@ setMethod("unionAll",
#' \code{UNION ALL} and \code{UNION DISTINCT} in SQL as column positions are not taken
#' into account. Input SparkDataFrames can have different data types in the schema.
#'
+#' When the parameter `allowMissingColumns` is `TRUE`, this function allows
Review comment:
Grammar revision:
> When the parameter `allowMissingColumns` is `TRUE`, the set of column names in `x` and `y` can differ; missing columns will be filled as null. Further, the missing columns of `x` will be added at the end in the schema of the union result.
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2863,11 +2863,19 @@ setMethod("unionAll",
#' \code{UNION ALL} and \code{UNION DISTINCT} in SQL as column positions are not taken
#' into account. Input SparkDataFrames can have different data types in the schema.
#'
+#' When the parameter `allowMissingColumns` is `TRUE`, this function allows
+#' different set of column names between two `SparkDataFrames`.
+#' Missing columns at each side, will be filled with null values.
+#' The missing columns at left `SparkDataFrame` will be added at the end in the schema
+#' of the union result.
+#'
#' Note: This does not remove duplicate rows across the two SparkDataFrames.
#' This function resolves columns by name (not by position).
#'
#' @param x A SparkDataFrame
#' @param y A SparkDataFrame
+#' @param allowMissingColumns logical
+#' @param ... further arguments to be passed to or from other methods.
Review comment:
`...` is not actually supported?
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2880,12 +2888,15 @@ setMethod("unionAll",
#' df1 <- select(createDataFrame(mtcars), "carb", "am", "gear")
#' df2 <- select(createDataFrame(mtcars), "am", "gear", "carb")
#' head(unionByName(df1, df2))
+#'
+#' df3 <- select(createDataFrame(mtcars), "carb")
+#' head(unionByName(df1, df3))
Review comment:
an example where `allowMissingColumns=TRUE` would be helpfl
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2863,11 +2863,19 @@ setMethod("unionAll",
#' \code{UNION ALL} and \code{UNION DISTINCT} in SQL as column positions are not taken
#' into account. Input SparkDataFrames can have different data types in the schema.
#'
+#' When the parameter `allowMissingColumns` is `TRUE`, this function allows
+#' different set of column names between two `SparkDataFrames`.
+#' Missing columns at each side, will be filled with null values.
+#' The missing columns at left `SparkDataFrame` will be added at the end in the schema
+#' of the union result.
+#'
#' Note: This does not remove duplicate rows across the two SparkDataFrames.
#' This function resolves columns by name (not by position).
#'
#' @param x A SparkDataFrame
#' @param y A SparkDataFrame
+#' @param allowMissingColumns logical
+#' @param ... further arguments to be passed to or from other methods.
Review comment:
nvm, seen below it's added to the generic
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2863,11 +2863,19 @@ setMethod("unionAll",
#' \code{UNION ALL} and \code{UNION DISTINCT} in SQL as column positions are not taken
#' into account. Input SparkDataFrames can have different data types in the schema.
#'
+#' When the parameter `allowMissingColumns` is `TRUE`, this function allows
+#' different set of column names between two `SparkDataFrames`.
+#' Missing columns at each side, will be filled with null values.
+#' The missing columns at left `SparkDataFrame` will be added at the end in the schema
+#' of the union result.
+#'
#' Note: This does not remove duplicate rows across the two SparkDataFrames.
#' This function resolves columns by name (not by position).
#'
#' @param x A SparkDataFrame
#' @param y A SparkDataFrame
+#' @param allowMissingColumns logical
+#' @param ... further arguments to be passed to or from other methods.
Review comment:
The way you've done it looks natural to me
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2863,11 +2863,19 @@ setMethod("unionAll",
#' \code{UNION ALL} and \code{UNION DISTINCT} in SQL as column positions are not taken
#' into account. Input SparkDataFrames can have different data types in the schema.
#'
+#' When the parameter `allowMissingColumns` is `TRUE`, this function allows
Review comment:
good catch, with null is better
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[GitHub] [spark] MichaelChirico commented on a change in pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
MichaelChirico commented on a change in pull request #29813:
URL: https://github.com/apache/spark/pull/29813#discussion_r491706032
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2863,11 +2863,19 @@ setMethod("unionAll",
#' \code{UNION ALL} and \code{UNION DISTINCT} in SQL as column positions are not taken
#' into account. Input SparkDataFrames can have different data types in the schema.
#'
+#' When the parameter `allowMissingColumns` is `TRUE`, this function allows
+#' different set of column names between two `SparkDataFrames`.
+#' Missing columns at each side, will be filled with null values.
+#' The missing columns at left `SparkDataFrame` will be added at the end in the schema
+#' of the union result.
+#'
#' Note: This does not remove duplicate rows across the two SparkDataFrames.
#' This function resolves columns by name (not by position).
#'
#' @param x A SparkDataFrame
#' @param y A SparkDataFrame
+#' @param allowMissingColumns logical
+#' @param ... further arguments to be passed to or from other methods.
Review comment:
nvm, seen below it's added to the generic
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[GitHub] [spark] SparkQA commented on pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #29813:
URL: https://github.com/apache/spark/pull/29813#issuecomment-695748225
**[Test build #128908 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/128908/testReport)** for PR 29813 at commit [`94d8317`](https://github.com/apache/spark/commit/94d83172f95f510812a6d4fdc050e0d6fd600ba7).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #29813:
URL: https://github.com/apache/spark/pull/29813#issuecomment-695818204
**[Test build #128920 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/128920/testReport)** for PR 29813 at commit [`0597724`](https://github.com/apache/spark/commit/059772426eab15e85f78dd3076b957800ebd0217).
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[GitHub] [spark] zero323 commented on a change in pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
zero323 commented on a change in pull request #29813:
URL: https://github.com/apache/spark/pull/29813#discussion_r491707650
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2863,11 +2863,19 @@ setMethod("unionAll",
#' \code{UNION ALL} and \code{UNION DISTINCT} in SQL as column positions are not taken
#' into account. Input SparkDataFrames can have different data types in the schema.
#'
+#' When the parameter `allowMissingColumns` is `TRUE`, this function allows
+#' different set of column names between two `SparkDataFrames`.
+#' Missing columns at each side, will be filled with null values.
+#' The missing columns at left `SparkDataFrame` will be added at the end in the schema
+#' of the union result.
+#'
#' Note: This does not remove duplicate rows across the two SparkDataFrames.
#' This function resolves columns by name (not by position).
#'
#' @param x A SparkDataFrame
#' @param y A SparkDataFrame
+#' @param allowMissingColumns logical
+#' @param ... further arguments to be passed to or from other methods.
Review comment:
That's correct, but I am not sure if there is a better way of handling that.
Right now we have generic as follows:
```R
setGeneric("unionByName", function(x, y, ...) { standardGeneric("unionByName") })
```
‒ as far as I am aware this is the convention for handling optional arguments we use in SparkR.
Technically speaking we could have
```R
setGeneric("unionByName", function(x, y, allowMissingColumns) { standardGeneric("unionByName") })
```
but then we'd have to support
```R
signature(x = "SparkDataFrame", y = "SparkDataFrame", allowMissingColumns = "missing")
```
and
```R
signature(x = "SparkDataFrame", y = "SparkDataFrame", allowMissingColumns = "logical")
```
if I am not mistaken, and in the past I've been told that's too much.
Do I miss something?
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2880,12 +2888,15 @@ setMethod("unionAll",
#' df1 <- select(createDataFrame(mtcars), "carb", "am", "gear")
#' df2 <- select(createDataFrame(mtcars), "am", "gear", "carb")
#' head(unionByName(df1, df2))
+#'
+#' df3 <- select(createDataFrame(mtcars), "carb")
+#' head(unionByName(df1, df3))
Review comment:
Thanks, this is suppose to be the one. Fixed.
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2863,11 +2863,19 @@ setMethod("unionAll",
#' \code{UNION ALL} and \code{UNION DISTINCT} in SQL as column positions are not taken
#' into account. Input SparkDataFrames can have different data types in the schema.
#'
+#' When the parameter `allowMissingColumns` is `TRUE`, this function allows
Review comment:
Sounds good, but for consistency it should fixed in Python and Scala as well.
Should it be
> columns will be filled as null.
or
> columns will be filled with null.
though?
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[GitHub] [spark] HyukjinKwon commented on pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #29813:
URL: https://github.com/apache/spark/pull/29813#issuecomment-695858636
Merged to master.
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URL: https://github.com/apache/spark/pull/29813#issuecomment-695745994
**[Test build #128908 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/128908/testReport)** for PR 29813 at commit [`94d8317`](https://github.com/apache/spark/commit/94d83172f95f510812a6d4fdc050e0d6fd600ba7).
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[GitHub] [spark] zero323 commented on a change in pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
zero323 commented on a change in pull request #29813:
URL: https://github.com/apache/spark/pull/29813#discussion_r491708886
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2880,12 +2888,15 @@ setMethod("unionAll",
#' df1 <- select(createDataFrame(mtcars), "carb", "am", "gear")
#' df2 <- select(createDataFrame(mtcars), "am", "gear", "carb")
#' head(unionByName(df1, df2))
+#'
+#' df3 <- select(createDataFrame(mtcars), "carb")
+#' head(unionByName(df1, df3))
Review comment:
Thanks, this is suppose to be the one. Fixed.
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[GitHub] [spark] MichaelChirico commented on a change in pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
MichaelChirico commented on a change in pull request #29813:
URL: https://github.com/apache/spark/pull/29813#discussion_r491705832
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2863,11 +2863,19 @@ setMethod("unionAll",
#' \code{UNION ALL} and \code{UNION DISTINCT} in SQL as column positions are not taken
#' into account. Input SparkDataFrames can have different data types in the schema.
#'
+#' When the parameter `allowMissingColumns` is `TRUE`, this function allows
Review comment:
Grammar revision:
> When the parameter `allowMissingColumns` is `TRUE`, the set of column names in `x` and `y` can differ; missing columns will be filled as null. Further, the missing columns of `x` will be added at the end in the schema of the union result.
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[GitHub] [spark] MichaelChirico commented on a change in pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
MichaelChirico commented on a change in pull request #29813:
URL: https://github.com/apache/spark/pull/29813#discussion_r491711245
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2863,11 +2863,19 @@ setMethod("unionAll",
#' \code{UNION ALL} and \code{UNION DISTINCT} in SQL as column positions are not taken
#' into account. Input SparkDataFrames can have different data types in the schema.
#'
+#' When the parameter `allowMissingColumns` is `TRUE`, this function allows
Review comment:
good catch, with null is better
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[GitHub] [spark] MichaelChirico commented on a change in pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
MichaelChirico commented on a change in pull request #29813:
URL: https://github.com/apache/spark/pull/29813#discussion_r491705999
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2880,12 +2888,15 @@ setMethod("unionAll",
#' df1 <- select(createDataFrame(mtcars), "carb", "am", "gear")
#' df2 <- select(createDataFrame(mtcars), "am", "gear", "carb")
#' head(unionByName(df1, df2))
+#'
+#' df3 <- select(createDataFrame(mtcars), "carb")
+#' head(unionByName(df1, df3))
Review comment:
an example where `allowMissingColumns=TRUE` would be helpfl
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URL: https://github.com/apache/spark/pull/29813#issuecomment-695906377
Thanks @HyukjinKwon and @MichaelChirico!
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[GitHub] [spark] MichaelChirico commented on a change in pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
MichaelChirico commented on a change in pull request #29813:
URL: https://github.com/apache/spark/pull/29813#discussion_r491705906
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2863,11 +2863,19 @@ setMethod("unionAll",
#' \code{UNION ALL} and \code{UNION DISTINCT} in SQL as column positions are not taken
#' into account. Input SparkDataFrames can have different data types in the schema.
#'
+#' When the parameter `allowMissingColumns` is `TRUE`, this function allows
+#' different set of column names between two `SparkDataFrames`.
+#' Missing columns at each side, will be filled with null values.
+#' The missing columns at left `SparkDataFrame` will be added at the end in the schema
+#' of the union result.
+#'
#' Note: This does not remove duplicate rows across the two SparkDataFrames.
#' This function resolves columns by name (not by position).
#'
#' @param x A SparkDataFrame
#' @param y A SparkDataFrame
+#' @param allowMissingColumns logical
+#' @param ... further arguments to be passed to or from other methods.
Review comment:
`...` is not actually supported?
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Posted by GitBox <gi...@apache.org>.
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* This patch passes all tests.
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[GitHub] [spark] HyukjinKwon closed pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
HyukjinKwon closed pull request #29813:
URL: https://github.com/apache/spark/pull/29813
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[GitHub] [spark] zero323 commented on pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/29813#issuecomment-695906377
Thanks @HyukjinKwon and @MichaelChirico!
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[GitHub] [spark] MichaelChirico commented on a change in pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
MichaelChirico commented on a change in pull request #29813:
URL: https://github.com/apache/spark/pull/29813#discussion_r491708509
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2863,11 +2863,19 @@ setMethod("unionAll",
#' \code{UNION ALL} and \code{UNION DISTINCT} in SQL as column positions are not taken
#' into account. Input SparkDataFrames can have different data types in the schema.
#'
+#' When the parameter `allowMissingColumns` is `TRUE`, this function allows
+#' different set of column names between two `SparkDataFrames`.
+#' Missing columns at each side, will be filled with null values.
+#' The missing columns at left `SparkDataFrame` will be added at the end in the schema
+#' of the union result.
+#'
#' Note: This does not remove duplicate rows across the two SparkDataFrames.
#' This function resolves columns by name (not by position).
#'
#' @param x A SparkDataFrame
#' @param y A SparkDataFrame
+#' @param allowMissingColumns logical
+#' @param ... further arguments to be passed to or from other methods.
Review comment:
The way you've done it looks natural to me
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[GitHub] [spark] HyukjinKwon commented on pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #29813:
URL: https://github.com/apache/spark/pull/29813#issuecomment-695858636
Merged to master.
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[GitHub] [spark] zero323 commented on a change in pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
zero323 commented on a change in pull request #29813:
URL: https://github.com/apache/spark/pull/29813#discussion_r491707650
##########
File path: R/pkg/R/DataFrame.R
##########
@@ -2863,11 +2863,19 @@ setMethod("unionAll",
#' \code{UNION ALL} and \code{UNION DISTINCT} in SQL as column positions are not taken
#' into account. Input SparkDataFrames can have different data types in the schema.
#'
+#' When the parameter `allowMissingColumns` is `TRUE`, this function allows
+#' different set of column names between two `SparkDataFrames`.
+#' Missing columns at each side, will be filled with null values.
+#' The missing columns at left `SparkDataFrame` will be added at the end in the schema
+#' of the union result.
+#'
#' Note: This does not remove duplicate rows across the two SparkDataFrames.
#' This function resolves columns by name (not by position).
#'
#' @param x A SparkDataFrame
#' @param y A SparkDataFrame
+#' @param allowMissingColumns logical
+#' @param ... further arguments to be passed to or from other methods.
Review comment:
That's correct, but I am not sure if there is a better way of handling that.
Right now we have generic as follows:
```R
setGeneric("unionByName", function(x, y, ...) { standardGeneric("unionByName") })
```
‒ as far as I am aware this is the convention for handling optional arguments we use in SparkR.
Technically speaking we could have
```R
setGeneric("unionByName", function(x, y, allowMissingColumns) { standardGeneric("unionByName") })
```
but then we'd have to support
```R
signature(x = "SparkDataFrame", y = "SparkDataFrame", allowMissingColumns = "missing")
```
and
```R
signature(x = "SparkDataFrame", y = "SparkDataFrame", allowMissingColumns = "logical")
```
if I am not mistaken, and in the past I've been told that's too much.
Do I miss something?
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[GitHub] [spark] HyukjinKwon closed pull request #29813: [SPARK-32799][R][SQL] Add allowMissingColumns to SparkR unionByName
Posted by GitBox <gi...@apache.org>.
HyukjinKwon closed pull request #29813:
URL: https://github.com/apache/spark/pull/29813
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