[jira] [Updated] (SPARK-26759) Arrow optimization in SparkR's interoperability

2019-05-02 Thread Hyukjin Kwon (JIRA) 


 [ 
https://issues.apache.org/jira/browse/SPARK-26759?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Hyukjin Kwon updated SPARK-26759:
-
Fix Version/s: 3.0.0

> Arrow optimization in SparkR's interoperability
> ---
>
> Key: SPARK-26759
> URL: https://issues.apache.org/jira/browse/SPARK-26759
> Project: Spark
>  Issue Type: Umbrella
>  Components: SparkR, SQL
>Affects Versions: 3.0.0
>Reporter: Hyukjin Kwon
>Assignee: Hyukjin Kwon
>Priority: Major
>  Labels: release-notes
> Fix For: 3.0.0
>
>
> Arrow 0.12.0 is release and it contains R API. We could optimize Spark 
> DaraFrame <> R DataFrame interoperability.
> For instance see the examples below:
>  - {{dapply}}
> {code:java}
> df <- createDataFrame(mtcars)
> collect(dapply(df,
>function(r.data.frame) {
>  data.frame(r.data.frame$gear)
>},
>structType("gear long")))
> {code}
>  - {{gapply}}
> {code:java}
> df <- createDataFrame(mtcars)
> collect(gapply(df,
>"gear",
>function(key, group) {
>  data.frame(gear = key[[1]], disp = mean(group$disp) > 
> group$disp)
>},
>structType("gear double, disp boolean")))
> {code}
>  - R DataFrame -> Spark DataFrame
> {code:java}
> createDataFrame(mtcars)
> {code}
>  - Spark DataFrame -> R DataFrame
> {code:java}
> collect(df)
> head(df)
> {code}
> Currently, some of communication path between R side and JVM side has to 
> buffer the data and flush it at once due to ARROW-4512. I don't target to fix 
> it under this umbrella.



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[jira] [Updated] (SPARK-26759) Arrow optimization in SparkR's interoperability

2019-02-19 Thread Hyukjin Kwon (JIRA) 


 [ 
https://issues.apache.org/jira/browse/SPARK-26759?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Hyukjin Kwon updated SPARK-26759:
-
Description: 
Arrow 0.12.0 is release and it contains R API. We could optimize Spark 
DaraFrame <> R DataFrame interoperability.

For instance see the examples below:
 - {{dapply}}

{code:java}
df <- createDataFrame(mtcars)
collect(dapply(df,
   function(r.data.frame) {
 data.frame(r.data.frame$gear)
   },
   structType("gear long")))
{code}
 - {{gapply}}

{code:java}
df <- createDataFrame(mtcars)
collect(gapply(df,
   "gear",
   function(key, group) {
 data.frame(gear = key[[1]], disp = mean(group$disp) > 
group$disp)
   },
   structType("gear double, disp boolean")))
{code}
 - R DataFrame -> Spark DataFrame

{code:java}
createDataFrame(mtcars)
{code}
 - Spark DataFrame -> R DataFrame

{code:java}
collect(df)
head(df)
{code}


Currently, some of communication path between R side and JVM side has to buffer 
the data and flush it at once due to ARROW-4512. I don't target to fix it under 
this umbrella.

  was:
Arrow 0.12.0 is release and it contains R API. We could optimize Spark 
DaraFrame <> R DataFrame interoperability.

For instance see the examples below:
 - {{dapply}}

{code:java}
df <- createDataFrame(mtcars)
collect(dapply(df,
   function(r.data.frame) {
 data.frame(r.data.frame$gear)
   },
   structType("gear long")))
{code}
 - {{gapply}}

{code:java}
df <- createDataFrame(mtcars)
collect(gapply(df,
   "gear",
   function(key, group) {
 data.frame(gear = key[[1]], disp = mean(group$disp) > 
group$disp)
   },
   structType("gear double, disp boolean")))
{code}
 - R DataFrame -> Spark DataFrame

{code:java}
createDataFrame(mtcars)
{code}
 - Spark DataFrame -> R DataFrame

{code:java}
collect(df)
head(df)
{code}


> Arrow optimization in SparkR's interoperability
> ---
>
> Key: SPARK-26759
> URL: https://issues.apache.org/jira/browse/SPARK-26759
> Project: Spark
>  Issue Type: Umbrella
>  Components: SparkR, SQL
>Affects Versions: 3.0.0
>Reporter: Hyukjin Kwon
>Assignee: Hyukjin Kwon
>Priority: Major
>  Labels: release-notes
>
> Arrow 0.12.0 is release and it contains R API. We could optimize Spark 
> DaraFrame <> R DataFrame interoperability.
> For instance see the examples below:
>  - {{dapply}}
> {code:java}
> df <- createDataFrame(mtcars)
> collect(dapply(df,
>function(r.data.frame) {
>  data.frame(r.data.frame$gear)
>},
>structType("gear long")))
> {code}
>  - {{gapply}}
> {code:java}
> df <- createDataFrame(mtcars)
> collect(gapply(df,
>"gear",
>function(key, group) {
>  data.frame(gear = key[[1]], disp = mean(group$disp) > 
> group$disp)
>},
>structType("gear double, disp boolean")))
> {code}
>  - R DataFrame -> Spark DataFrame
> {code:java}
> createDataFrame(mtcars)
> {code}
>  - Spark DataFrame -> R DataFrame
> {code:java}
> collect(df)
> head(df)
> {code}
> Currently, some of communication path between R side and JVM side has to 
> buffer the data and flush it at once due to ARROW-4512. I don't target to fix 
> it under this umbrella.



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[jira] [Updated] (SPARK-26759) Arrow optimization in SparkR's interoperability

2019-02-10 Thread Hyukjin Kwon (JIRA) 


 [ 
https://issues.apache.org/jira/browse/SPARK-26759?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Hyukjin Kwon updated SPARK-26759:
-
Description: 
Arrow 0.12.0 is release and it contains R API. We could optimize Spark 
DaraFrame <> R DataFrame interoperability.

For instance see the examples below:
 - {{dapply}}

{code:java}
df <- createDataFrame(mtcars)
collect(dapply(df,
   function(r.data.frame) {
 data.frame(r.data.frame$gear)
   },
   structType("gear long")))
{code}
 - {{gapply}}

{code:java}
df <- createDataFrame(mtcars)
collect(gapply(df,
   "gear",
   function(key, group) {
 data.frame(gear = key[[1]], disp = mean(group$disp) > 
group$disp)
   },
   structType("gear double, disp boolean")))
{code}
 - R DataFrame -> Spark DataFrame

{code:java}
createDataFrame(mtcars)
{code}
 - Spark DataFrame -> R DataFrame

{code:java}
collect(df)
head(df)
{code}

  was:Arrow 0.12.0 is release and it contains R API. We could optimize Spark 
DaraFrame <> R DataFrame interoperability.


> Arrow optimization in SparkR's interoperability
> ---
>
> Key: SPARK-26759
> URL: https://issues.apache.org/jira/browse/SPARK-26759
> Project: Spark
>  Issue Type: Umbrella
>  Components: SparkR, SQL
>Affects Versions: 3.0.0
>Reporter: Hyukjin Kwon
>Assignee: Hyukjin Kwon
>Priority: Major
>  Labels: release-notes
>
> Arrow 0.12.0 is release and it contains R API. We could optimize Spark 
> DaraFrame <> R DataFrame interoperability.
> For instance see the examples below:
>  - {{dapply}}
> {code:java}
> df <- createDataFrame(mtcars)
> collect(dapply(df,
>function(r.data.frame) {
>  data.frame(r.data.frame$gear)
>},
>structType("gear long")))
> {code}
>  - {{gapply}}
> {code:java}
> df <- createDataFrame(mtcars)
> collect(gapply(df,
>"gear",
>function(key, group) {
>  data.frame(gear = key[[1]], disp = mean(group$disp) > 
> group$disp)
>},
>structType("gear double, disp boolean")))
> {code}
>  - R DataFrame -> Spark DataFrame
> {code:java}
> createDataFrame(mtcars)
> {code}
>  - Spark DataFrame -> R DataFrame
> {code:java}
> collect(df)
> head(df)
> {code}



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[jira] [Updated] (SPARK-26759) Arrow optimization in SparkR's interoperability

2019-01-28 Thread Hyukjin Kwon (JIRA) 


 [ 
https://issues.apache.org/jira/browse/SPARK-26759?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Hyukjin Kwon updated SPARK-26759:
-
Component/s: SQL

> Arrow optimization in SparkR's interoperability
> ---
>
> Key: SPARK-26759
> URL: https://issues.apache.org/jira/browse/SPARK-26759
> Project: Spark
>  Issue Type: Umbrella
>  Components: SparkR, SQL
>Affects Versions: 3.0.0
>Reporter: Hyukjin Kwon
>Assignee: Hyukjin Kwon
>Priority: Major
>  Labels: release-notes
>
> Arrow 0.12.0 is release and it contains R API. We could optimize Spark 
> DaraFrame <> R DataFrame interoperability.



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