similar to: Saving R-objects to a database

Dear R-Users, I need a very fast and reliable database solution so I try to serialize a data.frame (to binary data) and to store this data to an SQLite database. This is what I tried to do: library(RSQLite) con <- dbDriver("SQLite") db <- dbConnect(con, "test") dbSendQuery(db, 'CREATE TABLE frames("simID" INT, "data" BLOB)') data.bin <-

I ran into an interesting error unserializing a file created with ascii=TRUE: R 3.5.1 (Windows or Linux): > unserialize(serialize(list(raw=as.raw(c(39,41))), NULL, version=2, ascii=TRUE)) Error in unserialize(serialize(list(raw = as.raw(c(39, 41))), NULL, version = 2, : ReadItem: unknown type 29, perhaps written by later version of R The same error happens when the

Hi, While debugging a network server I'm developing I noticed something unusual - call to unserialize() resulted in an error about loading a namespace. I was a bit taken back by this - why should unserializing an object cause a namespace lookup? Are there any other side-effects of unserialize() that I should be cautious about? I've been digging through the R_Unserialize() call, I

Hi all, I am not able to export an ALTREP object when `gctorture` is on in the worker. The package simplemmap can be used to reproduce the problem. See the example below ``` ## Create a temporary file filePath <- tempfile() con <- file(filePath, "wrb") writeBin(rep(0.0,10),con) close(con) library(simplemmap) library(parallel) cl <- makeCluster(1) x <- mmap(filePath,

I stumbled upon the following: f <- parallel::mcparallel(raw(0L)) parallel::mccollect(f) # $`77083` # NULL but f <- parallel::mcparallel(raw(1L)) parallel::mccollect(f) # Error in unserialize(r) : read error traceback() # 2: unserialize(r) # 1: parallel::mccollect(f) (restarting because the above appears to corrupt the R session) f <- parallel::mcparallel(raw(2L))

Dear R people, In typing names of functions (built in or from a package) I often guess wrong, and have to look the name up. In other words, I don't understand the logic in naming functions (if there is any): - most names are plain, lower case: cos, plot, sapply, t, toupper, unserialize, (etc) - some are capitalized: Filter, Machine, Map, NCOL, RNGversion, T (etc) -

This Index: src/main/altrep.c =================================================================== --- src/main/altrep.c (revision 79385) +++ src/main/altrep.c (working copy) @@ -275,10 +275,11 @@ SEXP psym = ALTREP_SERIALIZED_CLASS_PKGSYM(info); SEXP class = LookupClass(csym, psym); if (class == NULL) { - SEXP pname = ScalarString(PRINTNAME(psym)); + SEXP pname =

Daniel, thanks for the test case. I did run it in valgrind but nothing showed up, however ... I'm starting to have a suspicion that this has something to do with identical() - look at this: > identical(M1,M2) [1] FALSE > all(serialize(M1,NULL)==serialize(M2,NULL)) [1] TRUE > identical(unserialize(serialize(M1,NULL)),unserialize(serialize(M2,NULL))) [1] FALSE >

I noticed today that in R 2.3.1, I get > serialize(list(1,2,3), NULL, ascii = TRUE) [1] "A\n2\n131841\n131840\n19\n3\n14\n1\n1\n14\n1\n2\n14\n1\n3\n" > but in R 2.4.0 alpha I get > serialize(list(1,2,3), NULL, ascii = TRUE) [1] 41 0a 32 0a 31 33 32 30 39 36 0a 31 33 31 38 34 30 0a 31 39 0a 33 0a 31 34 [26] 0a 31 0a 31 0a 31 34 0a 31 0a 32 0a 31 34 0a 31 0a 33 0a >

Hi folks, I've attached a patch to the svn trunk that improves the performance of the serialize/unserialize interface for vector types. The current implementation: a) invokes the R_XDREncode operation for each element of the vector type, and b) uses a switch statement to determine the stream type for each element of the vector type. I've added R_XDREncodeVector/R_XDRDecodeVector functions

Hello, I have some code which generates lattice objects. The function recieves serialized forms of the lattice objects which it then unserializes and then adds to an ArrayList<REXP>. REXPRaw rser = new REXPRaw( target ); //target contains the raw serialized forms of lattice objects rconn.assign("temp",rser); REXP ret =

I noticed the following peculiarity with `serialize()' when `ascii = TRUE' is used. In today's (svn r37299) R-devel, I get > set.seed(10) > x <- rnorm(10) > > a <- serialize(x, con = NULL, ascii = TRUE) > b <- unserialize(a) > > identical(x, b) ## FALSE [1] FALSE > x - b [1] -3.469447e-18 2.775558e-17 -4.440892e-16 0.000000e+00

Hi Simon, I'm having trouble with nested parallel workers, specifically, forking inside socket connections. When mclapply is called inside a SOCK, PSOCK or FORK worker I get an error in unserialize(). cl <- makeCluster(1, "SOCK") fun = function(i) { library(parallel) mclapply(1:2, sqrt) } Failure occurs after multiple calls to clusterApply: > clusterApply(cl, 1,

I don''t even know if this is possible. I want to use an object as an attribute for one of my classes. I can save it to the db fine, looks like...but I need to be able to use it after I pull the object from the db. Right now the attribute is just a String, but I need it to be a Runt::Intersect object. Does anyone know how I can unserialize the attribute so I can use it as an object?

On 03/25/2015 07:48 PM, Simon Urbanek wrote: > On Mar 25, 2015, at 3:46 PM, Valerie Obenchain <vobencha at fredhutch.org> wrote: > >> Hi Simon, >> >> I'm having trouble with nested parallel workers, specifically, forking inside socket connections. >> > > You simply can't by definition - when you fork *all* the workers share the same connection

Hi all, I'm working with some huge array in R and I need to load several ones to apply some functions that requires to have all my arrays values for each cell... To make it possible, I would like to load only a part (for example 100 cells) of all my arrays, apply my function, delete all cells loaded, loaded following cells and so on. Is it possible to unserialize (or load) only a

I have a database field called dates in which I am trying to serialize an array of DateTime objects. When I unserialize them, they are coming back in as Time objects. I know this, because I am getting errors that say "comparison between Time and DateTime failed. Why is this happening? Is there a way to prevent it?? Thanks Shelby -------------- next part -------------- An HTML attachment

Hi, I am developing a tool for converting a large data frame stored in an uncompressed binary (XDR) RData file to a delimited text file. The data frame is too large to load() and extract rows from on a typical PC. I'm looking to parse through the file and extract individual entries without loading the whole thing into memory. In terms of some C source functions, instead of doing

Hi, sorry if this question is trivial or unclear, this is my first venture into mixed C/R programming (I am reasonably experienced in each separately). I am trying to write a serialization function for a format called typedbytes, which is used as an interchange format in Hadoop circles. Since I would need to serialize according to the internal R format many small R objects I looked at the c

hello, I'm using R 1.8.1 with the lastest snow package on FreeBSD 4.9. However, when I try to using socket clusters, it's very unstable. Sometimes it dies half way when I run parSapply(), sometimes it dies when cluster connection is idle. I create a socket cluster by following cmd cl = makeCluster("foo", type = "SOCK", outfile="/tmp/rafanlog");