Help implementing 'parallel' writing to a RealizationSink with BiocParallel

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#20 建立於 2018年5月21日 4 則留言 0 個 reaction 已指派 0 人在 GitHub 檢視

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評估

難度: 5/5
預估耗時: 一週以上
新手友好度: 25/100

Issue 類型: 功能
描述清晰度: 需要釐清
活躍度: 停滯
技術堆疊: r
領域: backend-api-design, data, distributed-systems

研究方向

從玩具範例中的 DelayedArray:::RealizationSink、write_block_to_sink()、RegularArrayGrid() 和 BiocParallel::bplapply() 呼叫開始。使用 SerialParam()、MulticoreParam() 和 SnowParam()，比較 HDF5Array、記憶體中的 arrayRealizationSink 和 RleArray 的結果；當區塊寫入是安全的，且傳回的 DelayedArray 包含所有產生的值時，即表示完成。

由索引模型根據 Issue 內容生成。

描述

I'm trying to implement writing to an arbitrary RealizationSink backend via BiocParallel::bplapply() with an arbitrary BiocParallelParam backend. That is, I want to be able to construct blocks of output, possibly in parallel, and then safely write each block to a HDF5Array, RleArray, etc. (controllable by the user) after each block is generated.

I've managed to get this set up for an HDF5RealizationSink (my main use case) by using the inter-process locks available in BiocParallel to ensure the writes are safe (@mtmorgan am I using these correctly?). But I've not had any luck using the same code for an arrayRealizationSink. Nor can I get it to work for the RleArray backend, although here the problem seems to be slightly different.

Below is a toy example that tries to construct a DelayedMatrix column-by-column using this strategy, in conjunction with different DelayedArray backends:

suppressPackageStartupMessages(library(DelayedArray))
suppressPackageStartupMessages(library(BiocParallel))

FUN_with_IPC_lock <- function(b, nrow, sink, grid, ipcid) {
    # Ensure DelayedArray package is loaded on worker (needed for backends
    # other than MulticoreParam).
    suppressPackageStartupMessages(library("DelayedArray"))
    if (is(sink, "HDF5RealizationSink")) {
        # Ensure HDF5Array package is loaded on worker, if required.
        # NOTE: Feels a little clunky that this is necessary; would be good if
        #       this was automatically loaded, properly.
        suppressPackageStartupMessages(library("HDF5Array"))
    }
    message("Processing block = ", b, " on PID = ", Sys.getpid())
    tmp <- matrix(seq_len(nrow) + (b - 1L) * nrow, ncol = 1)
    ipclock(ipcid)
    write_block_to_sink(tmp, sink, grid[[b]])
    ipcunlock(ipcid)
}

g <- function(FUN, BPPARAM, nrow = 100L, ncol = 10L) {
    # Construct RealizationSink
    backend <- getRealizationBackend()
    message("The backend is ", if (is.null(backend)) "NULL" else backend)
    sink <- DelayedArray:::RealizationSink(dim = c(nrow, ncol), type = "integer")
    # Consruct ArrayGrid over columns of RealizationSink
    grid <- RegularArrayGrid(dim(sink), c(nrow(sink), 1L))
    # Fill the RealizationSink
    n_block <- length(grid)
    # Construct an IPC mutex ID
    ipcid <- ipcid()
    # Apply function with BiocParallel
    bplapply(seq_len(n_block), FUN, BPPARAM = BPPARAM, nrow = nrow, sink = sink,
             grid = grid, ipcid = ipcid)
    # Return the RealizationSink as a DelayedArray
    as(sink, "DelayedArray")
}

# Everything works with the HDF5Array backend
setRealizationBackend("HDF5Array")
#> Loading required package: rhdf5
# Works
g(FUN_with_IPC_lock, SerialParam())
#> The backend is HDF5Array
#> Processing block = 1 on PID = 5740
#> Processing block = 2 on PID = 5740
#> Processing block = 3 on PID = 5740
#> Processing block = 4 on PID = 5740
#> Processing block = 5 on PID = 5740
#> Processing block = 6 on PID = 5740
#> Processing block = 7 on PID = 5740
#> Processing block = 8 on PID = 5740
#> Processing block = 9 on PID = 5740
#> Processing block = 10 on PID = 5740
#> <100 x 10> DelayedMatrix object of type "integer":
#>         [,1]  [,2]  [,3]  [,4] ...  [,7]  [,8]  [,9] [,10]
#>   [1,]     1   101   201   301   .   601   701   801   901
#>   [2,]     2   102   202   302   .   602   702   802   902
#>   [3,]     3   103   203   303   .   603   703   803   903
#>   [4,]     4   104   204   304   .   604   704   804   904
#>   [5,]     5   105   205   305   .   605   705   805   905
#>    ...     .     .     .     .   .     .     .     .     .
#>  [96,]    96   196   296   396   .   696   796   896   996
#>  [97,]    97   197   297   397   .   697   797   897   997
#>  [98,]    98   198   298   398   .   698   798   898   998
#>  [99,]    99   199   299   399   .   699   799   899   999
#> [100,]   100   200   300   400   .   700   800   900  1000
# Works: the IPC lock does its job!
g(FUN_with_IPC_lock, MulticoreParam(2L))
#> The backend is HDF5Array
#> <100 x 10> DelayedMatrix object of type "integer":
#>         [,1]  [,2]  [,3]  [,4] ...  [,7]  [,8]  [,9] [,10]
#>   [1,]     1   101   201   301   .   601   701   801   901
#>   [2,]     2   102   202   302   .   602   702   802   902
#>   [3,]     3   103   203   303   .   603   703   803   903
#>   [4,]     4   104   204   304   .   604   704   804   904
#>   [5,]     5   105   205   305   .   605   705   805   905
#>    ...     .     .     .     .   .     .     .     .     .
#>  [96,]    96   196   296   396   .   696   796   896   996
#>  [97,]    97   197   297   397   .   697   797   897   997
#>  [98,]    98   198   298   398   .   698   798   898   998
#>  [99,]    99   199   299   399   .   699   799   899   999
#> [100,]   100   200   300   400   .   700   800   900  1000
# Works: the IPC lock does its job!
g(FUN_with_IPC_lock, SnowParam(2L))
#> The backend is HDF5Array
#> Loading required package: HDF5Array
#> Loading required package: rhdf5
#> Processing block = 1 on PID = 5755
#> Processing block = 2 on PID = 5755
#> Processing block = 3 on PID = 5755
#> Processing block = 4 on PID = 5755
#> Processing block = 5 on PID = 5755
#> Loading required package: HDF5Array
#> Loading required package: rhdf5
#> Processing block = 6 on PID = 5761
#> Processing block = 7 on PID = 5761
#> Processing block = 8 on PID = 5761
#> Processing block = 9 on PID = 5761
#> Processing block = 10 on PID = 5761
#> <100 x 10> DelayedMatrix object of type "integer":
#>         [,1]  [,2]  [,3]  [,4] ...  [,7]  [,8]  [,9] [,10]
#>   [1,]     1   101   201   301   .   601   701   801   901
#>   [2,]     2   102   202   302   .   602   702   802   902
#>   [3,]     3   103   203   303   .   603   703   803   903
#>   [4,]     4   104   204   304   .   604   704   804   904
#>   [5,]     5   105   205   305   .   605   705   805   905
#>    ...     .     .     .     .   .     .     .     .     .
#>  [96,]    96   196   296   396   .   696   796   896   996
#>  [97,]    97   197   297   397   .   697   797   897   997
#>  [98,]    98   198   298   398   .   698   798   898   998
#>  [99,]    99   199   299   399   .   699   799   899   999
#> [100,]   100   200   300   400   .   700   800   900  1000

# Only SerialParam() works for the in-memory backend. The in-memory backend,
# an arrayRealizationSink, is implemented as an array inside an environment.
setRealizationBackend(NULL)
# Works
g(FUN_with_IPC_lock, SerialParam())
#> The backend is NULL
#> Processing block = 1 on PID = 5740
#> Processing block = 2 on PID = 5740
#> Processing block = 3 on PID = 5740
#> Processing block = 4 on PID = 5740
#> Processing block = 5 on PID = 5740
#> Processing block = 6 on PID = 5740
#> Processing block = 7 on PID = 5740
#> Processing block = 8 on PID = 5740
#> Processing block = 9 on PID = 5740
#> Processing block = 10 on PID = 5740
#> <100 x 10> DelayedMatrix object of type "integer":
#>         [,1]  [,2]  [,3]  [,4] ...  [,7]  [,8]  [,9] [,10]
#>   [1,]     1   101   201   301   .   601   701   801   901
#>   [2,]     2   102   202   302   .   602   702   802   902
#>   [3,]     3   103   203   303   .   603   703   803   903
#>   [4,]     4   104   204   304   .   604   704   804   904
#>   [5,]     5   105   205   305   .   605   705   805   905
#>    ...     .     .     .     .   .     .     .     .     .
#>  [96,]    96   196   296   396   .   696   796   896   996
#>  [97,]    97   197   297   397   .   697   797   897   997
#>  [98,]    98   198   298   398   .   698   798   898   998
#>  [99,]    99   199   299   399   .   699   799   899   999
#> [100,]   100   200   300   400   .   700   800   900  1000
# Doesn't work: sink isn't filled. The IPC mutex isn't doing its job?
g(FUN_with_IPC_lock, MulticoreParam(2L))
#> The backend is NULL
#> <100 x 10> DelayedMatrix object of type "integer":
#>         [,1]  [,2]  [,3]  [,4] ...  [,7]  [,8]  [,9] [,10]
#>   [1,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>   [2,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>   [3,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>   [4,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>   [5,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>    ...     .     .     .     .   .     .     .     .     .
#>  [96,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>  [97,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>  [98,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>  [99,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#> [100,]    NA    NA    NA    NA   .    NA    NA    NA    NA
# Doesn't work: sink isn't filled. The IPC mutex isn't doing its job?
g(FUN_with_IPC_lock, SnowParam(2L))
#> The backend is NULL
#> Processing block = 6 on PID = 5777
#> Processing block = 7 on PID = 5777
#> Processing block = 8 on PID = 5777
#> Processing block = 9 on PID = 5777
#> Processing block = 10 on PID = 5777
#> Processing block = 1 on PID = 5771
#> Processing block = 2 on PID = 5771
#> Processing block = 3 on PID = 5771
#> Processing block = 4 on PID = 5771
#> Processing block = 5 on PID = 5771
#> <100 x 10> DelayedMatrix object of type "integer":
#>         [,1]  [,2]  [,3]  [,4] ...  [,7]  [,8]  [,9] [,10]
#>   [1,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>   [2,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>   [3,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>   [4,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>   [5,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>    ...     .     .     .     .   .     .     .     .     .
#>  [96,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>  [97,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>  [98,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#>  [99,]    NA    NA    NA    NA   .    NA    NA    NA    NA
#> [100,]    NA    NA    NA    NA   .    NA    NA    NA    NA

# Only SerialParam() works for the RleArray backend.
setRealizationBackend("RleArray")
# Works
g(FUN_with_IPC_lock, SerialParam())
#> The backend is RleArray
#> Processing block = 1 on PID = 5740
#> Processing block = 2 on PID = 5740
#> Processing block = 3 on PID = 5740
#> Processing block = 4 on PID = 5740
#> Processing block = 5 on PID = 5740
#> Processing block = 6 on PID = 5740
#> Processing block = 7 on PID = 5740
#> Processing block = 8 on PID = 5740
#> Processing block = 9 on PID = 5740
#> Processing block = 10 on PID = 5740
#> <100 x 10> RleMatrix object of type "integer":
#>         [,1]  [,2]  [,3]  [,4] ...  [,7]  [,8]  [,9] [,10]
#>   [1,]     1   101   201   301   .   601   701   801   901
#>   [2,]     2   102   202   302   .   602   702   802   902
#>   [3,]     3   103   203   303   .   603   703   803   903
#>   [4,]     4   104   204   304   .   604   704   804   904
#>   [5,]     5   105   205   305   .   605   705   805   905
#>    ...     .     .     .     .   .     .     .     .     .
#>  [96,]    96   196   296   396   .   696   796   896   996
#>  [97,]    97   197   297   397   .   697   797   897   997
#>  [98,]    98   198   298   398   .   698   798   898   998
#>  [99,]    99   199   299   399   .   699   799   899   999
#> [100,]   100   200   300   400   .   700   800   900  1000
# Doesn't work: Don't understand why.
g(FUN_with_IPC_lock, MulticoreParam(2L))
#> The backend is RleArray
#> Error in validObject(.Object): invalid class "ChunkedRleArraySeed" object: 
#>     length of object data [0] does not match object dimensions
#>     [product 1000]
# Doesn't work: don't understand why I get this error.
g(FUN_with_IPC_lock, SnowParam(2L))
#> The backend is RleArray
#> Processing block = 6 on PID = 5793
#> Processing block = 7 on PID = 5793
#> Processing block = 8 on PID = 5793
#> Processing block = 9 on PID = 5793
#> Processing block = 10 on PID = 5793
#> Processing block = 1 on PID = 5787
#> Processing block = 2 on PID = 5787
#> Processing block = 3 on PID = 5787
#> Processing block = 4 on PID = 5787
#> Processing block = 5 on PID = 5787
#> Error in validObject(.Object): invalid class "ChunkedRleArraySeed" object: 
#>     length of object data [0] does not match object dimensions
#>     [product 1000]

Created on 2018-05-21 by the reprex package (v0.2.0).

Session info

devtools::session_info()
#> Session info -------------------------------------------------------------
#>  setting  value                       
#>  version  R version 3.5.0 (2018-04-23)
#>  system   x86_64, darwin15.6.0        
#>  ui       X11                         
#>  language (EN)                        
#>  collate  en_AU.UTF-8                 
#>  tz       America/New_York            
#>  date     2018-05-21
#> Packages -----------------------------------------------------------------
#>  package      * version date       source        
#>  backports      1.1.2   2017-12-13 CRAN (R 3.5.0)
#>  base         * 3.5.0   2018-04-24 local         
#>  BiocGenerics * 0.27.0  2018-05-01 Bioconductor  
#>  BiocParallel * 1.15.3  2018-05-11 Bioconductor  
#>  compiler       3.5.0   2018-04-24 local         
#>  datasets     * 3.5.0   2018-04-24 local         
#>  DelayedArray * 0.7.0   2018-05-01 Bioconductor  
#>  devtools       1.13.5  2018-02-18 CRAN (R 3.5.0)
#>  digest         0.6.15  2018-01-28 CRAN (R 3.5.0)
#>  evaluate       0.10.1  2017-06-24 CRAN (R 3.5.0)
#>  graphics     * 3.5.0   2018-04-24 local         
#>  grDevices    * 3.5.0   2018-04-24 local         
#>  HDF5Array    * 1.9.0   2018-05-01 Bioconductor  
#>  htmltools      0.3.6   2017-04-28 CRAN (R 3.5.0)
#>  IRanges      * 2.15.13 2018-05-20 Bioconductor  
#>  knitr          1.20    2018-02-20 CRAN (R 3.5.0)
#>  magrittr       1.5     2014-11-22 CRAN (R 3.5.0)
#>  matrixStats  * 0.53.1  2018-02-11 CRAN (R 3.5.0)
#>  memoise        1.1.0   2017-04-21 CRAN (R 3.5.0)
#>  methods      * 3.5.0   2018-04-24 local         
#>  parallel     * 3.5.0   2018-04-24 local         
#>  Rcpp           0.12.17 2018-05-18 CRAN (R 3.5.0)
#>  rhdf5        * 2.25.0  2018-05-01 Bioconductor  
#>  Rhdf5lib       1.3.1   2018-05-17 Bioconductor  
#>  rmarkdown      1.9     2018-03-01 CRAN (R 3.5.0)
#>  rprojroot      1.3-2   2018-01-03 CRAN (R 3.5.0)
#>  S4Vectors    * 0.19.5  2018-05-20 Bioconductor  
#>  snow           0.4-2   2016-10-14 CRAN (R 3.5.0)
#>  stats        * 3.5.0   2018-04-24 local         
#>  stats4       * 3.5.0   2018-04-24 local         
#>  stringi        1.2.2   2018-05-02 CRAN (R 3.5.0)
#>  stringr        1.3.1   2018-05-10 CRAN (R 3.5.0)
#>  tools          3.5.0   2018-04-24 local         
#>  utils        * 3.5.0   2018-04-24 local         
#>  withr          2.1.2   2018-03-15 CRAN (R 3.5.0)
#>  yaml           2.1.19  2018-05-01 CRAN (R 3.5.0)

主要語言: R
星號: 29
分支: 12
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