[
https://issues.apache.org/jira/browse/SPARK-17752?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Kevin Ushey updated SPARK-17752:
--------------------------------
Description:
Run the following code (modify SPARK_HOME to point to a Spark 2.0.0
installation as necessary):
{code:r}
SPARK_HOME <- path.expand("~/Library/Caches/spark/spark-2.0.0-bin-hadoop2.7")
Sys.setenv(SPARK_HOME = SPARK_HOME)
library(SparkR, lib.loc = c(file.path(Sys.getenv("SPARK_HOME"), "R", "lib")))
sparkR.session(master = "local[*]", sparkConfig = list(spark.driver.memory =
"2g"))
n <- 1E3
df <- as.data.frame(replicate(n, 1L, FALSE))
names(df) <- paste("X", 1:n, sep = "")
path <- tempfile()
write.table(df, file = path, row.names = FALSE, col.names = TRUE, sep = ",",
quote = FALSE)
tbl <- as.DataFrame(df)
cache(tbl) # works fine without this
cl <- collect(tbl)
identical(df, cl) # FALSE
{code}
Although this is reproducible with SparkR, it seems more likely that this is an
error in the Java / Scala Spark sources.
For posterity:
> sessionInfo()
R version 3.3.1 Patched (2016-07-30 r71015)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: macOS Sierra (10.12)
was:
Run the following code (modify SPARK_HOME to point to a Spark 2.0.0
installation as necessary):
{{
SPARK_HOME <- path.expand("~/Library/Caches/spark/spark-2.0.0-bin-hadoop2.7")
Sys.setenv(SPARK_HOME = SPARK_HOME)
library(SparkR, lib.loc = c(file.path(Sys.getenv("SPARK_HOME"), "R", "lib")))
sparkR.session(master = "local[*]", sparkConfig = list(spark.driver.memory =
"2g"))
n <- 1E3
df <- as.data.frame(replicate(n, 1L, FALSE))
names(df) <- paste("X", 1:n, sep = "")
path <- tempfile()
write.table(df, file = path, row.names = FALSE, col.names = TRUE, sep = ",",
quote = FALSE)
tbl <- as.DataFrame(df)
cache(tbl) # works fine without this
cl <- collect(tbl)
identical(df, cl) # FALSE
}}
Although this is reproducible with SparkR, it seems more likely that this is an
error in the Java / Scala Spark sources.
For posterity:
> sessionInfo()
R version 3.3.1 Patched (2016-07-30 r71015)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: macOS Sierra (10.12)
> Spark returns incorrect result when 'collect()'ing a cached Dataset with many
> columns
> -------------------------------------------------------------------------------------
>
> Key: SPARK-17752
> URL: https://issues.apache.org/jira/browse/SPARK-17752
> Project: Spark
> Issue Type: Bug
> Components: SparkR
> Affects Versions: 2.0.0
> Reporter: Kevin Ushey
> Priority: Critical
>
> Run the following code (modify SPARK_HOME to point to a Spark 2.0.0
> installation as necessary):
> {code:r}
> SPARK_HOME <- path.expand("~/Library/Caches/spark/spark-2.0.0-bin-hadoop2.7")
> Sys.setenv(SPARK_HOME = SPARK_HOME)
> library(SparkR, lib.loc = c(file.path(Sys.getenv("SPARK_HOME"), "R", "lib")))
> sparkR.session(master = "local[*]", sparkConfig = list(spark.driver.memory =
> "2g"))
> n <- 1E3
> df <- as.data.frame(replicate(n, 1L, FALSE))
> names(df) <- paste("X", 1:n, sep = "")
> path <- tempfile()
> write.table(df, file = path, row.names = FALSE, col.names = TRUE, sep = ",",
> quote = FALSE)
> tbl <- as.DataFrame(df)
> cache(tbl) # works fine without this
> cl <- collect(tbl)
> identical(df, cl) # FALSE
> {code}
> Although this is reproducible with SparkR, it seems more likely that this is
> an error in the Java / Scala Spark sources.
> For posterity:
> > sessionInfo()
> R version 3.3.1 Patched (2016-07-30 r71015)
> Platform: x86_64-apple-darwin13.4.0 (64-bit)
> Running under: macOS Sierra (10.12)
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