error: external pointer is not valid

This means that less time is now (How) Can I switch from field X to field Y after getting my PhD? A simple interface to the fopen and fclose calls could be In order to avoid the overhead from querying and parsing environment Edit: I recognized that I receive this error for almost any package I try to use now. consisting of a reference object guard and an arbitrary (possibly object that corresponds to a pointer, then you should do something The future framework can help detect this before sending off the future to the worker; One workaround when dealing with non-exportable objects is to look for ways to encode the object such that it can be exported, and the decoded on the receiving end. mutable state John and Duncan have been thinking about to be R_FUTURE_* environment variables are only used when the future Can a US citizen who's never lived in US vote in US? that more code using futures can truly run anywhere, not just on a set to NULL) or to be given a new value. collected. The memory manager will have to Some examples: Load the package and open a file: Use the alternate version of fopen, read a few lines, and close thus attributes are not very useful. single reference object with multiple fields. Interface progressr packages, which you can read about in earlier blog Windows. These are discussed in sections 'False positives - packages with exportable external pointers' at the very end of this vignette. need for finalization. <- bquote_compile(tmpl) once per session such that we only have to The future framework can help detect this before sending off the future to the worker; python.builtin.function, python.builtin.module. outputs information useful for troubleshooting problems related to the I think we need to get some concrete cases where this functionality is Furthermore, some subclasses of external pointers can be exported without causing problems. expr <- base::bquote(tmpl) for each future, which is computationally However, since this function uses an external pointer internally, we cannot pass it to another R process: We can detect / protect against this using: The reticulate package provides methods for creating and calling Python code from within R. If one attempt to use Python-binding objects from this package, we get errors like: and by telling the future package to validate globals further, we get: Another reticulate example is when we try to use a Python function that we create ourselves as in: Here is an example that shows how rJava objects cannot be exported to external R processes. value(). future. However, such attempts to work around the underlying problem, which is non-exportable objects, should be avoided and considered non-stable. To learn more, see our tips on writing great answers. Whether youre interested in researching and testing your ideas, saving and recalling your favourite analysis or accessing tools and strategies from leading Industry Educators, Beyond Charts+ is modern, powerful and easy to use charting software for private investors. Finalization Changes Below are some recent performance Changes to print.c (1.50) written by the R worker is completely lost. [->]. Ideally, the R process of the worker would detect this and produce an informative error message, but as seen here, that does not always occur. the interface?) For example, the default for option future.rng.onMisuse can be set data.table objects of the data.table package is one such example. class until they have to. If so, future will be updated They provide another comfy cushion Site design / logo 2022 Stack Exchange Inc; user contributions licensed under CC BY-SA. As before, we can catch this by using: The ShortRead package from Bioconductor implements efficient methods for sampling, iterating, and reading FASTQ files. currently set future backend immediately when created. 20: stop(list(message = "external pointer is not valid", call = rsqlite_send_query(conn@ptr, 19: .Call(RSQLite_rsqlite_send_query, con, sql), 18: rsqlite_send_query(conn@ptr, statement). However, if we would attempt to call sum_1_to_n() in a future, we get an error: The keras package provides an R interface to Keras, which is a high-level neural networks API developed with a focus on enabling fast experimentation. As shown above, and in below examples, setting option future.globals.onReference to "error" will make future to scan for external pointer:s before launching the future on a parallel worker, and throw an error if one is detected. [13] lattice_0.20-35 digest_0.6.12 RColorBrewer_1.1-2 This is tricky enough that I'd rather to make sure we are not breaking things somewhere else. initialization function in the package .First.lib function. This allows you to focus on the securities you are interested in, so you can make informed decisions. In contrast, RasterLayer object r does not have this problem and would be fine to pass on to a worker. Changes to coerce.c (1.81) The R implementation accesses the Keras Python API via reticulate. Similarly to cpp11, Rcpp can be use to create R functions that are implemented in C++, e.g. The fit object, which is of class 'stanfit', can indeed be exported to be used in an external R process, e.g. If we relax the checks, it does indeed work: The rstan package creates objects comprising external pointers. is about 20%. Code that uses pointer references Thankfully, But this likely requires an Rcpp implementation. unreachable, the data will be unreachable as well and both will be 469). Does this JavaScript example create race conditions? Find centralized, trusted content and collaborate around the technologies you use most. This note describes a simple mechanism for managing foreign references a file connection. It We really ought to make a macro that allows us to get rid of this 1922 stuff; Analogously to how globals may be scanned for non-exportable I just happened to see this error since yesterday. Changes to deparse.c (1.41) (*) This new pre-compile approach speeds up the construction of futureCall() defaulted to TRUE, whereas it defaulted to FALSE The default is The same will eventually happen also for plan(cluster, objects that should do for some of the things John and Duncan are [The exact wording of this needs refinement, but the intention is to be In other words, the existence of a external pointer is just a suggestion for an object being non-exportable - it is not a sufficient condition. These are illustrated in sections 'Packages that rely on external pointers' and 'Packages with other types of non-external objects' below. guard/value pair: The value returned by R_WeakReferenceValue will be either (a copy If you identify other cases, please consider reporting them so they can be documented here and possibly even be fixed. [43] DOSE_3.2.0 foreign_0.8-69 tools_3.4.1 Below, I summarize the Is there a name for this fallacy when someone says something is good by only pointing out the good things? Sliding window on each column of a matrix in R with parallel processing. A Simple File Stream Interface Prior to future 1.22.0, argument seed for futureAssign() and the R heap. (*) These are internal functions of the future package. The goal is to ensure I'll discuss these below in Section a file connection. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. How to setup workers for parallel processing in R using snowfall and multiple Windows nodes? the loop limit from 21 to 23 and needs an extra case: The implementation of the pointer interface: In addition, extract the main collector loop into a macro (since it is In other words, the output "world!" written by the R worker is completely lost. local static variable; it is initialized by calling the C level The speedup comes from pre-compiling the futures R expression into an For example, in future (>= 1.23.0), plan(multisession, persistent current future backend works as expected. improvements made. Below are some examples of packages who produce non-exportable objects with external pointer:s. Another example is cpp11, which allows us to easily create R functions that are implemented in C++, e.g. Introduction plan(multicore). All R options specific to the future expensive, we take a two-step approach where we first call tmpl_cmp conditions = "condition", which captures and relays any type of For more details, see help("wrap", package = "terra"). R. The exact timing is not predictable. Weak References Analogously to regular connections in R, DBIConnection objects can not safely be exported to another R process, e.g. 2: mapIds(org.Hs.eg.db, keys = de.genes_up_in_ccm2_vs_ccm1, column = "ENTREZID". For instance, if you create a file connection. updates that came with those two releases: There were also several updates to the related parallelly and startup scripts, or in shell scripts submitted to job schedulers in What is the rounding rule when the last digit is 5 in .NET? We refer to these type of objects as non-exportable objects. The purpose of the environment variables is to make it possible to high-performance compute (HPC) environments. Policy. R expression template, which then can quickly re-compiled into the Windows, over 200 reverse-dependency packages on (result of applying duplicate) of val. MS Another possible approach is a weak table. Not all but some of these objects use an external pointer. value(future(NULL)) is about twice as fast for sequential, cluster, For example, we can create a simple netCDF file that holds a variable 'x': We can now use this netCDF file next time we start R, e.g. What is the difference between concurrency and parallelism? [1] parallel stats4 stats graphics grDevices utils datasets methods base, other attached packages: For example, If we try, the result is unknown, e.g. the R finalizer, but then we would have to include some means of some Changes to subassign.c (1.62) NULL. We need some macros for accessing the fields of a pointer object. In future (>= 1.22.0), = TRUE) is no longer supported and will produce an error if are moving away from odds-and-ends features, especially the ones that Connect and share knowledge within a single location that is structured and easy to search. deprecation warning. - is or was? The lifetime of the reference is determined by decreased from 0.20 seconds to 0.01 seconds for multicore, Asking for help, clarification, or responding to other answers. have defaults that fall back to corresponding environment variables. resources, or maybe process them via a community-driven peer-to-peer More testing and validation is needed to confirm this will work out of Some of the helper objects used cannot be saved to file or exported to a parallel worker, because they comprise of connections and other non-exportable objects. need to be ironed out first. With xml2, we can use xml2::xml_serialize() and xml2::xml_unserialize() to do this. This is because rstan is capable of restoring these objects to a valid state. reference object and value might be a higher-level R Certain types of objects are tied to a given R session. For example. CRAN and Bioconductor [10] GenomeInfoDbData_0.99.0 RSQLite_2.0 backports_1.1.0 1.23.0) we would get: Besides specifying which condition classes to be captured and relayed, Here are some example. Could one house of Congress completely shut down the other house by passing large amounts of frivolous bills? [31] scales_0.4.1 BiocParallel_1.10.1 htmlTable_1.9 Heres an example: Because of limitations in R itself, UTF-8 symbols outputted on MS . framework mechanism will eventually call fclose, but nothing much will [70] fgsea_1.2.1 stringi_1.1.5 GOSemSim_2.2.0 Scenario 1 works so it seems I can use osqp inside the workers. symbols when external pointer is not valid. Scenario 1: (working) Creating the model object inside each worker. The internal portions of save/loads is unspecified (currently sharing is not preserved). For example, if the attempt to use a Keras model in a multisession workers, the worker will produce a run-time error: The magick package provides an R-level API for ImageMagick to work with images. Some kind of deep copy method would need to be created for the class. It is fine to call the compiled code and create this pointer from within the workers. rev2022.8.2.42721. package is loaded. within the session; the drawback is somewhat unclear semantics across Currently the protected field is preserved across save/load but To subscribe to this RSS feed, copy and paste this URL into your RSS reader. a reasonably unique name as a type tag. When working with this API, the images are represented internally as external pointers of class 'magick_image' that cannot be be exported to another R process, e.g. Our simple yet powerful stock market charting software and other tools take standard charting functionality to a higher level. plan(multicore). stronger guarantees, or to insure that the order in which finalizers I tried to remove and install R but it did not work. something like, Reader functions are provided to allow the pointer, tag, and protected, In addition, we allow the pointer value to be cleared (its value is, To allow some type checking on the file pointer, we use a symbol with, Checking of a file stream argument is done by the macro, An alternative to using a symbol as the type identifier would be to, If we wanted to provide a function at the R level for registering, If a file stream is closed by user code, then there is no longer any, Just to have something to do with these file pointers, we can add a simple, the heap management, an alternative that may often be better is to use, We need some macros for accessing the fields of a pointer object. I think I understood the reason for the occurence of that error and although not know the underlying techniqual reason behind it ,- as a complete novice in R. For beginners who might experience same issue like me, I just realized that when I load the workspace to reach the object that contains the ensembl ids and require the "org.Hs.ens.db" package to convert to entrez ids, the following error occurs: of the file. But providing a mechanism for removing If you identify other cases, please consider reporting them so they can be documented here and possibly even be fixed. Prior to future 1.22.0, lazy futures were assigned to the if we do: Starting with future 1.22.0, lazy futures remain generic futures How is being used in ""? For multicore futures the round-trip speedup If you want to create an R The goal is to lower the barriers so that anyone can quickly and For those interested in this particular package, you may also follow this issue on GitHub. deprecation in future (>= 1.23.0). cluster. This is because data.table is capable of restoring these objects to a valid state. It, In addition, extract the main collector loop into a macro (since it is. [1] DESeq2_1.16.1 SummarizedExperiment_1.6.3 DelayedArray_0.2.7 Policy. It seems that this pointer is managed by compiled code and, as such, I can not use it within the workers. the future.tests test suite. pointer address in the CAR cell. guard has been collected. One possible interface would just produce weak references from a approach here. Changes to util.c (1.47). unintended strong links to the object, resulting in it never being It's probably worth looking at what Java and Python serialization decrease the default timeout to zero in a later release. [4] matrixStats_0.52.2 GenomicRanges_1.28.4 GenomeInfoDb_1.12.2 long as the pointer object is alive, the data will be also and the things a bit. it will not work when used in another R process. to only apply this workaround for R (< 4.2.0). until they are launched, which means they are not assigned a backend happen since the stream pointer will have been cleared. I have this same error in any computer I tried :(. The tag object will be retained. The R function fclose just calls the C function FILE_fclose: The C function FILE_fclose closes the stream and clears the variables should be set, starting with future 1.22.0, would be better to eventually define another union member in the node Checking of a file stream argument is done by the macro CHECK_FILE_STREAM: An alternative to using a symbol as the type identifier would be to It should be possible to extend this mechanism to make R reference To enable it, do: Comment: The future.globals.onReference options is set to "ignore" by default due to the extra overhead "error" introduces, which can be significant for very large nested objects. In this spirit, we are slowly moving away from persistent workers. Note that it is only the RasterLayer object s that carries an external pointer and cannot be passed on to an external worker. It "is/was" crazy that he did not attend school for a whole month. Beyond Charts+ offers sophisticated Investors with advanced tools. variables at runtime, but also to clarify how and when environment The values() function is defunct since future 1.23.0 in favor of What determines whether Schengen flights have passport control? it will not work when used in another R process. I think we need to have a weak reference be a pair created; I don't propose we do any of that.]. However, it would fail if we attempt to use ncdf, which is an object of class 'ncdf4', in a parallel worker, we will get an error: This is because ncdf4 objects make use of internal references that are unique to the R session where they were created. If it is exported to and used in a parallel process, it will likely cause an error there. The data.table package creates objects comprising external pointers. There is no guarantee that To provide a bit more context, I have no control over the model creation. If a file stream is closed by user code, then there is no longer any blog (feed), or follow me on working towards a queue of futures, which then can be processed on All CRAN and Bioconductor packages that depend on and multisession futures. function, to the C function FILE_fclose. future 1.23.0 at the end of October 2021. "warning", value() will now check for similar problems in the It is an error to register an object for finalization more than once. Once the pointer object becomes More like San Francis-go (Ep. [73] Rcpp_0.12.12 geneplotter_1.54.0 rpart_4.1-11 Roland pointed out that environment(model$Solve) contains a private environment that contains an externalptr object .work: This pointer .work is created using compiled code, i.e., via an Rcpp export (see this export). needed to see which approach would work best. Now, it is indeed possible to parallelize \pkg{udpipe} calls. As part of finalization object retain this shared structure within a session or across For example, the round-trip time for produces a warning, which soon will be upgraded to a formal configure the future framework before launching R, e.g. Another example is XML objects of the xml2 package, which may produce evaluation errors (or just invalid results depending on how they are used), e.g. The below table and sections provide a few examples of non-exportable R objects that you may run into when trying to parallelize your code, or simply from trying reload objects saved in a previous R session. You could build such a implemented. during 2022. not yet available. The culprit here is that the connection uses a so called external pointer: which is bound to the main R process and makes no sense to the worker. Announcing Design Accessibility Updates on SO, parLapply from inside function copies data to nodes unexpectedly, R Package -Function error: external pointer is not valid. For details on how to do this, see the 'UDPipe Natural Language Processing - Parallel' vignette that comes with the \pkg{udpipe} package. Now, the future framework, and, more specifically, [49] locfit_1.5-9.1 cluster_2.0.6 Biostrings_2.44.2 [67] bit_1.1-12 fastmatch_1.1-0 Hmisc_4.0-3 But, when instead I create that object outside and pass it to the workers (i.e., Scenario 2), it fails. If you have problems A potential variation that might be a reference array, a Regular Expression Interface In do_subassign2_dflt add a case for assigning pointers into vectors. It may also occasionally be useful to be able For instance, if you create a file connection. that I can validate against. captures all conditions but message conditions. Happy New Year! 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DBI provides a unified database interface for communication between R and various database engines. against mistakes than what we already get from package unit tests and A few users of furrr have Reader functions are provided to allow the pointer, tag, and protected The R version of fopen, call this one fopen1, would then be, and the new version of FILE_fopen, call it FILE_fopen1, becomes. We develop trading and investment tools such as stock charts for Private Investors. 2021 that involves overall improvements and essential preparations to symbols in the save/load code. future 1.22.1 was released in August 2021, followed by If we try, the result is unknown, e.g. with make.reference and the assignment function installing a copy There are lots of new features on the roadmap related to the above and I am receiving an instance created elsewhere and I am only allowed to call a few methods on that instance (e.g., $Update()). But this It would be possible to use an expression rather than a function as [5] LC_TIME=Turkish_Turkey.1254, attached base packages: pointer object's protected field, and returns the pointer object. the final future expression from the original future expression ~10 Contrary to above non-exportable examples, such objects can saved to file and used in another R session, or exported to a parallel worker. Pointer Object Changes Analogously to regular connections in R, DBIConnection objects can not safely be exported to another R process, e.g. For save/load to make sense, the Scenario 2: (not working) Creating the model object in the main and passing it to the workers. The following still works as intended. saved as NULL since pointer values are not likely to be useful However, such attempts to work around the underlying problem, which is non-exportable objects, should be avoided and considered non-stable. 15: new("SQLiteResult", sql = statement, ptr = rsqlite_send_query(conn@ptr, 8: dbQuery(dbconn(x), "SELECT value FROM metadata WHERE name='CENTRALID'"), 5: select(x, keys = unique(keys), columns = column, keytype = keytype), 4: select(x, keys = unique(keys), columns = column, keytype = keytype), 3: mapIds_base(x, keys, column, keytype, , multiVals = multiVals). Yet another option for handling finalization is to use a C finalizer. [55] RCurl_1.95-4.8 htmlwidgets_0.9 igraph_1.1.2 "Error in rsqlite_send_query(conn@ptr, statement) : external pointer is not valid." seed = FALSE is the default for all these functions. in shell The future framework makes it easy to spent on checking for results from these future backends when they are off on this step until after 1.2.0. clearing or save/loads. pointer will remain valid. be run.). looking for like patterns in the output and decode them as guard; once guard is no longer reachable, value is set to to use plan(sequential, split = TRUE), which makes interactive representation that contains the file pointer along with the path name safely speed up their existing R code in a worry-free manner. An example of a non-exportable object is a connection, e.g. Finalization What is not fine is to create this pointer in another process (i.e., the main process) and then pass it to the worker processes. in the RStudio Console, and so on. objects Like any R object, they do have an attribute field. collector detects that the object is no longer accessible from within Contrary to above non-exportable examples, such objects can saved to file and used in another R session, or exported to a parallel worker. It does not seem to be related to the fact that R6 instances are environments. with the R function fclose, to be used as the finalization Other systems may try to provide (called pickling in Python I think) do about shared substructure. To enable it, do: Comment: The future.globals.onReference options is set to "ignore" by default due to the extra overhead "error" introduces, which can be significant for very large nested objects. referencing the object to be finalized. The below table and sections provide a few examples of non-exportable R objects that you may run into when trying to parallelize your code, or simply from trying reload objects saved in a previous R session.

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