Description Usage Arguments Details Value References See Also Examples
Convert input matrix or data.frame into a distributed data.frame.
1 |
input |
input matrix or data.frame that will be converted to dframe. |
psize |
size of each partition as a vector specifying number of rows and columns. |
If partition size (psize) is missing then the input matrix/data.frame is row partitioned and striped across the cluster, i.e., the returned distributed frame has approximately as many partitions as the number of R instances in the session.
The last set of partitions may have fewer rows or columns if input matrix size is not an integer multiple of partition size. If 'A' is a 5x5 matrix, then 'as.dframe(A, psize=c(2,5))' is a distributed frame with three partitions. The first two partitions have two rows each but the last partition has only one row. All three partitions have five columns.
To create a distributed frame with just one partition, pass the dimension of the input frame, i.e. 'as.dframe(A, psize=dim(A))'
Returns a distributed data.frame with dimensions equal to that of the input matrix and partitioned according to argument 'psize'. Data may reside as partitions on remote nodes.
Prasad, S., Fard, A., Gupta, V., Martinez, J., LeFevre, J., Xu, V., Hsu, M., Roy, I. Large scale predictive analytics in Vertica: Fast data transfer, distributed model creation and in-database prediction. _Sigmod 2015_, 1657-1668.
Venkataraman, S., Bodzsar, E., Roy, I., AuYoung, A., and Schreiber, R. (2013) Presto: Distributed Machine Learning and Graph Processing with Sparse Matrices. _EuroSys 2013_, 197-210.
Homepage: https://github.com/vertica/ddR
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ## Not run:
##Create 4x4 matrix
mtx<-matrix(sample(0:1, 16, replace=T), nrow=4)
##Create distributed frame spread across the cluster
df<-as.dframe(mtx)
psize(df)
##Create distributed frame with single partition
db<-as.dframe(mtx, psize=dim(mtx))
psize(db)
##Create distributed frame with two partitions
dc<- as.dframe(mtx, psize=c(2,4))
psize(dc)
##Fetch first partition
collect(dc,1)
#creating of dframe with data.frame
dfa <- c(2,3,4)
dfb <- c("aa","bb","cc")
dfc <- c(TRUE,FALSE,TRUE)
df <- data.frame(dfa,dfb,dfc)
#creating dframe from data.frame with default block size
ddf <- as.dframe(df)
collect(ddf)
#creating dframe from data.frame with 1x1 block size
ddf <- as.dframe(df,psize=c(1,1))
collect(ddf)
## End(Not run)
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Welcome to 'ddR' (Distributed Data-structures in R)!
For more information, visit: https://github.com/vertica/ddR
Attaching package: 'ddR'
The following objects are masked from 'package:base':
cbind, rbind
[,1] [,2]
[1,] 4 4
[,1] [,2]
[1,] 4 4
[,1] [,2]
[1,] 2 4
[2,] 2 4
X1 X2 X3 X4
1 0 1 0 0
2 0 0 0 1
dfa dfb dfc
1 2 aa TRUE
2 3 bb FALSE
3 4 cc TRUE
dfa dfb dfc
1 2 aa TRUE
2 3 bb FALSE
3 4 cc TRUE
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