[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16342487#comment-16342487
]
Hyukjin Kwon commented on SPARK-21727:
--
(y)
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil Alexander McQuarrie
>Assignee: Neil Alexander McQuarrie
>Priority: Major
> Fix For: 2.3.0, 2.4.0
>
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16334892#comment-16334892
]
Apache Spark commented on SPARK-21727:
--
User 'neilalex' has created a pull request for this issue:
https://github.com/apache/spark/pull/20352
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil Alexander McQuarrie
>Assignee: Neil Alexander McQuarrie
>Priority: Major
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16333733#comment-16333733
]
Felix Cheung commented on SPARK-21727:
--
how are we doing?
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil Alexander McQuarrie
>Assignee: Neil Alexander McQuarrie
>Priority: Major
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16320439#comment-16320439
]
Neil Alexander McQuarrie commented on SPARK-21727:
--
Okay great. Implemented and tests are passing. I'll submit a PR shortly. Thanks
for the help.
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil Alexander McQuarrie
>Assignee: Neil Alexander McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16319855#comment-16319855
]
Felix Cheung commented on SPARK-21727:
--
good call...
if (
(is.atomic(object) && !is.raw(object)) &&
length(object) > 1
)
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil Alexander McQuarrie
>Assignee: Neil Alexander McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16319647#comment-16319647
]
Neil Alexander McQuarrie commented on SPARK-21727:
--
Oh -- interesting... thanks.
I think "raw" type is atomic though?
Is
{code}is.atomic(object) & !is.raw(object){code}
too clunky?
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil Alexander McQuarrie
>Assignee: Neil Alexander McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16315434#comment-16315434
]
Felix Cheung commented on SPARK-21727:
--
I think we should use
is.atomic(object)
?
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil Alexander McQuarrie
>Assignee: Neil Alexander McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16312466#comment-16312466
]
Neil Alexander McQuarrie commented on SPARK-21727:
--
I was able to get a version working by checking for length > 1, as well as
whether the type is integer, character, logical, double, numeric, Date,
POSIXlt, or POSIXct.
[https://github.com/neilalex/spark/blob/neilalex-sparkr-arraytype/R/pkg/R/serialize.R#L39]
The reason I'm checking the specific type is that it seems quite a few objects
flow through getSerdeType() besides just the object we're converting -- for
example, after calling 'as.DataFrame(myDf)' per above, I saw a jobj "Java ref
type org.apache.spark.sql.SparkSession id 1" of length 2, as well as a raw
object of length ~700, both pass through getSerdeType(). So, it seems we can't
just check length?
Also, in general this makes me a little nervous -- will there be scenarios when
a 2+ length vector of one of the above types should also not be converted to
array? I'll familiarize myself further with how getSerdeType() is called, to
see if I can think this through.
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil Alexander McQuarrie
>Assignee: Neil Alexander McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16307277#comment-16307277
]
Neil Alexander McQuarrie commented on SPARK-21727:
--
[~felixcheung] Okay thanks -- sorry, need a few more days
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil Alexander McQuarrie
>Assignee: Neil Alexander McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16305157#comment-16305157
]
Felix Cheung commented on SPARK-21727:
--
[~neilalex] How it is going?
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil Alexander McQuarrie
>Assignee: Neil Alexander McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16300965#comment-16300965
]
Felix Cheung commented on SPARK-21727:
--
Neil McQuarrie is going to work on this
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil McQuarrie
>Assignee: Neil McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16153194#comment-16153194
]
Yanbo Liang commented on SPARK-21727:
-
[~neilalex] Please feel free to take this task. Thanks.
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16152973#comment-16152973
]
Felix Cheung commented on SPARK-21727:
--
precisely.
as far as I can tell, everything should "just work" if we return `array` from
`getSerdeType()` for this case when length > 1.
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16152766#comment-16152766
]
Neil McQuarrie commented on SPARK-21727:
Happy to take on the change this side... (unless [~yanboliang] you had intended
to?)
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16152764#comment-16152764
]
Neil McQuarrie commented on SPARK-21727:
Well, if class is "numeric" (or "integer", "character", etc.), then technically
it is always a vector? (There are no distinct scalars in R?) We could look at
length > 1?
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16152639#comment-16152639
]
Yanbo Liang commented on SPARK-21727:
-
[~felixcheung] What do you mean for this comment?
{quote}
But with that said, I think we could and should make a minor change to support
that implicitly
https://github.com/apache/spark/blob/master/R/pkg/R/serialize.R#L39
{quote}
How we can get the SerDe type of atomic vector? Just like I mentioned above,
{code}
> class(rep(0, 20))
[1] "numeric"
> class(as.list(rep(0, 20)))
[1] "list"
{code}
_class_ function can't return type _vector_, how we can determine the type of
object is _vector_ or _numeric_ ? Thanks.
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16151589#comment-16151589
]
Felix Cheung commented on SPARK-21727:
--
any taker of this change?
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16151588#comment-16151588
]
Felix Cheung commented on SPARK-21727:
--
That is true. I think the documentation is unclear in this case - it should say
the vector should be converted to list or similar.
In fact the code explicitly does not support column with atomic vector values
into array column type
https://github.com/apache/spark/blob/master/R/pkg/R/serialize.R#L54
But with that said, I think we could and should make a minor change to support
that implicitly
https://github.com/apache/spark/blob/master/R/pkg/R/serialize.R#L39
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
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]
Neil McQuarrie commented on SPARK-21727:
Ah yes and I realize I posted incorrectly -- the code embeds an integer vector,
not integer list. (And converting it to a list first creates a workaround for
me -- thank you.)
This said, according to Spark
[documentation|https://spark.apache.org/docs/2.2.0/sql-programming-guide.html#data-types],
both R vectors and lists should be supported?
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16151437#comment-16151437
]
Felix Cheung commented on SPARK-21727:
--
hmm.. I think that's what the error message is saying
{code}
java.lang.Double is not a valid external type for schema of array
{code}
it's finding a double and not an array of double
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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[jira] [Commented] (SPARK-21727) Operating on an ArrayType in a SparkR DataFrame throws error
[
https://issues.apache.org/jira/browse/SPARK-21727?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16150657#comment-16150657
]
Yanbo Liang commented on SPARK-21727:
-
I can run successfully with minor change:
{code}
indices <- 1:4
myDf <- data.frame(indices)
myDf$data <- list(as.list(rep(0, 20)))
mySparkDf <- as.DataFrame(myDf)
collect(mySparkDf)
{code}
This is because rep(0, 20) is not type of list, we should convert it to list
explicitly.
{code}
> class(rep(0, 20))
[1] "numeric"
> class(as.list(rep(0, 20)))
[1] "list"
{code}
> Operating on an ArrayType in a SparkR DataFrame throws error
>
>
> Key: SPARK-21727
> URL: https://issues.apache.org/jira/browse/SPARK-21727
> Project: Spark
> Issue Type: Bug
> Components: SparkR
>Affects Versions: 2.2.0
>Reporter: Neil McQuarrie
>
> Previously
> [posted|https://stackoverflow.com/questions/45056973/sparkr-dataframe-with-r-lists-as-elements]
> this as a stack overflow question but it seems to be a bug.
> If I have an R data.frame where one of the column data types is an integer
> *list* -- i.e., each of the elements in the column embeds an entire R list of
> integers -- then it seems I can convert this data.frame to a SparkR DataFrame
> just fine... SparkR treats the column as ArrayType(Double).
> However, any subsequent operation on this SparkR DataFrame appears to throw
> an error.
> Create an example R data.frame:
> {code}
> indices <- 1:4
> myDf <- data.frame(indices)
> myDf$data <- list(rep(0, 20))}}
> {code}
> Examine it to make sure it looks okay:
> {code}
> > str(myDf)
> 'data.frame': 4 obs. of 2 variables:
> $ indices: int 1 2 3 4
> $ data :List of 4
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
>..$ : num 0 0 0 0 0 0 0 0 0 0 ...
> > head(myDf)
> indices data
> 1 1 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 2 2 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 3 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> 4 4 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
> {code}
> Convert it to a SparkR DataFrame:
> {code}
> library(SparkR, lib.loc=paste0(Sys.getenv("SPARK_HOME"),"/R/lib"))
> sparkR.session(master = "local[*]")
> mySparkDf <- as.DataFrame(myDf)
> {code}
> Examine the SparkR DataFrame schema; notice that the list column was
> successfully converted to ArrayType:
> {code}
> > schema(mySparkDf)
> StructType
> |-name = "indices", type = "IntegerType", nullable = TRUE
> |-name = "data", type = "ArrayType(DoubleType,true)", nullable = TRUE
> {code}
> However, operating on the SparkR DataFrame throws an error:
> {code}
> > collect(mySparkDf)
> 17/07/13 17:23:00 ERROR executor.Executor: Exception in task 0.0 in stage 1.0
> (TID 1)
> java.lang.RuntimeException: Error while encoding: java.lang.RuntimeException:
> java.lang.Double is not a valid external type for schema of array
> if (assertnotnull(input[0, org.apache.spark.sql.Row, true]).isNullAt) null
> else validateexternaltype(getexternalrowfield(assertnotnull(input[0,
> org.apache.spark.sql.Row, true]), 0, indices), IntegerType) AS indices#0
> ... long stack trace ...
> {code}
> Using Spark 2.2.0, R 3.4.0, Java 1.8.0_131, Windows 10.
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