parquet functions causing segfault

[bschilder]

1. Bug description

Any parquet functions cause a segfault error when running unit tests with "Test" or "Check" buttons in Rstudio, but not when running manually or with "Run test" button.

Expected behaviour

Functions work in all conditions.

2. Reproducible example

Code

## devtools::test()
  dat <- echodata::BST1
  path <- echodata::write_parquet(dat)
  #### Read the parquet file back into R ####
  dat2 <- echodata::read_parquet(path=path)

Console output

==> devtools::test()

ℹ Testing echodata
✔ | F W  S  OK | Context
⠏ |          0 | assign_lead_SNP                            + leadSNP missing. Assigning new one by min p-value.
✔ |          4 | assign_lead_SNP
✔ |          1 | column_dictionary                          
⠏ |          0 | construct_colmap                           Assuming fullSS_path summary stats have already been processed with MungeSumstats.
Assuming fullSS_path summary stats have already been processed with MungeSumstats.
✔ |          3 | construct_colmap
⠏ |          0 | coords_to_rsids                            Searching for RSIDs using: hg19
Loading required namespace: SNPlocs.Hsapiens.dbSNP144.GRCh37
5 / 5 SNPs annotated with RSIDs.
✔ |          5 | coords_to_rsids [6.6s]                     
✔ |          3 | createDT                                   
⠏ |          0 | dt_to_granges                              Converting dat to GRanges object.
dat is already a GRanges object.
✔ |          6 | dt_to_granges
⠏ |          0 | example_fullSS                             Writing file to ==> /var/folders/rd/rbc_wrdj4k3djf3brk6z0_dc0000gp/T//RtmpgfuhvU/nalls2019.fullSS_subset.tsv
Writing file to ==> /var/folders/rd/rbc_wrdj4k3djf3brk6z0_dc0000gp/T//RtmpgfuhvU/kunkle2019.fullSS_subset.tsv
✔ |          4 | example_fullSS                             
⠏ |          0 | extract_loci                               + Mapping colnames from MungeSumstats ==> echolocatoR
BIN1
CLU
CR1*
EPHA1
MS4A2
PICALM
PTK2B
SPI1*
   Locus SNPs
1   BIN1   55
2    CLU   17
3   CR1*   22
4  EPHA1    5
5  MS4A2  210
6 PICALM   61
7  PTK2B   17
8  SPI1*  149
✔ |          2 | extract_loci
⠏ |          0 | fillNA_CS_PP                               + Filling NAs in CS cols with 0.
+ Filling NAs in PP cols with 0.
✔ |          4 | fillNA_CS_PP
⠏ |          0 | filter_snps                                FILTER:: Filtering by SNP features.
+ FILTER:: Post-filtered data: 2913 x 26
FILTER:: Filtering by SNP features.
+ FILTER:: Post-filtered data: 6216 x 26
FILTER:: Filtering by SNP features.
+ FILTER:: Removing specified variants: rs4541502,rs34559912,rs4389574,rs35519415,rs3756246
+ FILTER:: Post-filtered data: 2908 x 26
FILTER:: Filtering by SNP features.
+ FILTER:: Post-filtered data: 2913 x 26
FILTER:: Filtering by SNP features.
BIOMART:: Trimming data to only include SNPs within gene coordinates.
BIOMART:: 3154 SNPs left after trimming.
+ leadSNP missing. Assigning new one by min p-value.
+ FILTER:: Post-filtered data: 1610 x 26
⠼ |          5 | filter_snps                                FILTER:: Filtering by SNP features.
BIOMART:: Trimming data to only include SNPs within gene coordinates.
BIOMART:: 0 SNPs left after trimming.
+ leadSNP missing. Assigning new one by min p-value.
+ FILTER:: Post-filtered data: 0 x 26
⠴ |          6 | filter_snps                                FILTER:: Filtering by SNP features.
BIOMART:: Trimming data to only include SNPs within gene coordinates.
BIOMART:: 3313 SNPs left after trimming.
+ FILTER:: Post-filtered data: 1727 x 26
✔ |          7 | filter_snps [1.3s]                         
⠏ |          0 | find_consensus_snps_no_polyfun             Identifying UCS and Consensus SNPs without PolyFun
Identifying Consensus SNPs...
+ support_thresh = 2
+ Calculating mean Posterior Probability (mean.PP)...
+ 3 fine-mapping methods used.
+ 7 Credible Set SNPs identified.
+ 1 Consensus SNPs identified.
✔ |          3 | find_consensus_snps_no_polyfun
⠏ |          0 | find_consensus_snps                        Identifying Consensus SNPs...
+ support_thresh = 2
+ Calculating mean Posterior Probability (mean.PP)...
+ 4 fine-mapping methods used.
+ 7 Credible Set SNPs identified.
+ 3 Consensus SNPs identified.
✔ |          2 | find_consensus_snps
✔ |          4 | find_top_consensus                         
⠏ |          0 | gene_locus_list                            WARNING: Dropping 97 loci not present in topSNPs: 
 - ASXL3_ASXL3
 - BAG3_BAG3
 - BIN3_BIN3
 - BRIP1_BRIP1
 - BST1_BST1
 - C5orf24_C5orf24
 - CAB39L_CAB39L
 - CAMK2D_CAMK2D
 - CASC16_CASC16
 - CD19_CD19
 - CHD9_CHD9
 - CHRNB1_CHRNB1
 - CLCN3_CLCN3
 - CNTN1_CNTN1
 - CRHR1_CRHR1
 - CRLS1_CRLS1
 - CTSB_CTSB
 - DDRGK1_DDRGK1
 - DLG2_DLG2
 - DNAH17_DNAH17
 - DYRK1A_DYRK1A
 - ELOVL7_ELOVL7
 - FAM171A2_FAM171A2
 - FAM47E_FAM47E
 - FAM47E-STBD1_FAM47E-STBD1
 - FAM49B_FAM49B
 - FBRSL1_FBRSL1
 - FCGR2A_FCGR2A
 - FGD4_FGD4
 - FGF20_FGF20
 - FYN_FYN
 - GAK_GAK
 - GALC_GALC
 - GBAP1_GBAP1
 - GBF1_GBF1
 - GCH1_GCH1
 - GPNMB_GPNMB
 - GS1-124K5.11_GS1-124K5.11
 - GXYLT1_GXYLT1
 - HIP1R_HIP1R
 - HLA-DRB5_HLA-DRB5
 - IGSF9B_IGSF9B
 - INPP5F_INPP5F
 - IP6K2_IP6K2
 - ITGA8_ITGA8
 - ITPKB_ITPKB
 - KANSL1_KANSL1
 - KCNIP3_KCNIP3
 - KCNS3_KCNS3
 - KPNA1_KPNA1
 - KRTCAP2_KRTCAP2
 - LCORL_LCORL
 - LINC00693_LINC00693
 - LOC100131289_LOC100131289
 - LRRK2_LRRK2
 - MAP3K14_MAP3K14
 - MAP4K4_MAP4K4
 - MAPT-AS1_MAPT-AS1
 - MBNL2_MBNL2
 - MCCC1_MCCC1
 - MED12L_MED12L
 - MEX3C_MEX3C
 - MIPOL1_MIPOL1
 - NOD2_NOD2
 - NSF_NSF
 - NUCKS1_NUCKS1
 - PAM_PAM
 - PMVK_PMVK
 - RAB29_RAB29
 - RETREG3_RETREG3
 - RIMS1_RIMS1
 - RIT2_RIT2
 - RNF141_RNF141
 - RPS12_RPS12
 - RPS6KL1_RPS6KL1
 - SATB1_SATB1
 - SCAF11_SCAF11
 - SCARB2_SCARB2
 - SEMA4A_SEMA4A
 - SETD1A_SETD1A
 - SH3GL2_SH3GL2
 - SIPA1L2_SIPA1L2
 - SLC44A4_SLC44A4
 - SNCA_SNCA
 - SPPL2B_SPPL2B
 - SPTSSB_SPTSSB
 - STK39_STK39
 - SYT17_SYT17
 - TMEM163_TMEM163
 - TMEM175_TMEM175
 - TRIM40_TRIM40
 - UBAP2_UBAP2
 - UBTF_UBTF
 - VAMP4_VAMP4
 - VPS13C_VPS13C
 - WNT3_WNT3
 - ZNF608_ZNF608
Reassigning gene-specific locus names.
Reassigning gene-specific locus names.
✔ |          3 | gene_locus_list
✔ |          1 | get_data                                   
✔ |          3 | get_header                                 
⠏ |          0 | get_Nalls2019_loci                         Writing fine-mapped locus data ==> /var/folders/rd/rbc_wrdj4k3djf3brk6z0_dc0000gp/T//RtmpgfuhvU/Nalls23andMe_2019/BST1.multi_finemap.csv.gz
Writing fine-mapped locus data ==> /var/folders/rd/rbc_wrdj4k3djf3brk6z0_dc0000gp/T//RtmpgfuhvU/Nalls23andMe_2019/LRRK2.multi_finemap.csv.gz
Writing fine-mapped locus data ==> /var/folders/rd/rbc_wrdj4k3djf3brk6z0_dc0000gp/T//RtmpgfuhvU/Nalls23andMe_2019/MEX3C.multi_finemap.csv.gz
✔ |          2 | get_Nalls2019_loci
⠏ |          0 | get_sample_size                            Preparing sample size column (N).
Computing effective sample size using the LDSC method:
 Neff = (N_CAS+N_CON) * (N_CAS/(N_CAS+N_CON)) / mean((N_CAS/(N_CAS+N_CON))[(N_CAS+N_CON)==max(N_CAS+N_CON)]))
+ Mapping colnames from MungeSumstats ==> echolocatoR
Preparing sample size column (N).
Computing effective sample size using the LDSC method:
 Neff = (N_CAS+N_CON) * (N_CAS/(N_CAS+N_CON)) / mean((N_CAS/(N_CAS+N_CON))[(N_CAS+N_CON)==max(N_CAS+N_CON)]))
+ Mapping colnames from MungeSumstats ==> echolocatoR
Preparing sample size column (N).
Computing effective sample size using the LDSC method:
 Neff = (N_CAS+N_CON) * (N_CAS/(N_CAS+N_CON)) / mean((N_CAS/(N_CAS+N_CON))[(N_CAS+N_CON)==max(N_CAS+N_CON)]))
+ Mapping colnames from MungeSumstats ==> echolocatoR
Preparing sample size column (N).
Computing effective sample size using the LDSC method:
 Neff = (N_CAS+N_CON) * (N_CAS/(N_CAS+N_CON)) / mean((N_CAS/(N_CAS+N_CON))[(N_CAS+N_CON)==max(N_CAS+N_CON)]))
+ Mapping colnames from MungeSumstats ==> echolocatoR
Preparing sample size column (N).
Computing effective sample size using the LDSC method:
 Neff = (N_CAS+N_CON) * (N_CAS/(N_CAS+N_CON)) / mean((N_CAS/(N_CAS+N_CON))[(N_CAS+N_CON)==max(N_CAS+N_CON)]))
+ Mapping colnames from MungeSumstats ==> echolocatoR
Preparing sample size column (N).
Computing effective sample size using the GIANT method:
 Neff = 2 / (1/N_CAS + 1/N_CON)
+ Mapping colnames from MungeSumstats ==> echolocatoR
Preparing sample size column (N).
Computing effective sample size using the METAL method:
 Neff = 4 / (1/N_CAS + 1/N_CON)
+ Mapping colnames from MungeSumstats ==> echolocatoR
Preparing sample size column (N).
Computing sample size using the sum method:
 N = N_CAS + N_CON
+ Mapping colnames from MungeSumstats ==> echolocatoR
Preparing sample size column (N).
Assigning N=10000 for all SNPs.
+ Mapping colnames from MungeSumstats ==> echolocatoR
Preparing sample size column (N).
Numeric vector supplied to compute_n.
Preparing sample size column (N).
Numeric vector supplied to compute_n.
✔ |         13 | get_sample_size
⠏ |          0 | get_SNPgroup_counts                        All loci (75) : 
           Total.SNPs          nom.sig.GWAS              sig.GWAS 
              4948.16                924.68                 82.36 
                   CS             Consensus          topConsensus 
                 7.88                  2.69                  1.47 
topConsensus.leadGWAS 
                 0.41 
Loci with at least one Consensus SNP (69) : 
           Total.SNPs          nom.sig.GWAS              sig.GWAS 
              5019.07                911.41                 84.28 
                   CS             Consensus          topConsensus 
                 7.77                  2.93                  1.59 
topConsensus.leadGWAS 
                 0.45 
✔ |          1 | get_SNPgroup_counts                        
⠏ |          0 | granges_to_bed                             Converting dat to GRanges object.
Converting 1 GRanges object to separate BED files.
Saving BED file ==> /var/folders/rd/rbc_wrdj4k3djf3brk6z0_dc0000gp/T//RtmpgfuhvU/granges1.bed.txt
✔ |          1 | granges_to_bed
⠏ |          0 | import_topSNPs                             Renaming column: BP ==> POS
Renaming column: P, all studies ==> P
Renaming column: Beta, all studies ==> Effect
Renaming column: Nearest Gene ==> Locus
Renaming column: QTL Nominated Gene (nearest QTL) ==> Gene
[1] "+ Assigning Gene and Locus independently."
Standardising column headers.
First line of summary statistics file: 
SNP	CHR	POS	Locus	Gene	Effect allele	Other allele	Effect allele frequency	Effect	SE, all studies	P	P, COJO, all studies	P, random effects, all studies	P, Conditional 23AndMe only	P, 23AndMe only	I2, all studies	Freq1, previous studies	Beta, previous studies	StdErr, previous studies	P, previous studies	I2, previous studies	Freq1, new studies	Beta, new studies	StdErr, new studies	P, new studies	I2, new studies	Passes pooled 23andMe QC	Known GWAS locus within 1MB	Failed final filtering and QC	Locus within 250KB	Locus Number	
Returning unmapped column names without making them uppercase.
+ Mapping colnames from MungeSumstats ==> echolocatoR
⠋ |          1 | import_topSNPs                             Renaming column: BP ==> POS
Renaming column: P, all studies ==> P
Renaming column: Beta, all studies ==> Effect
Renaming column: Nearest Gene ==> Locus
Renaming column: QTL Nominated Gene (nearest QTL) ==> Gene
[1] "+ Assigning Gene and Locus independently."
Standardising column headers.
First line of summary statistics file: 
SNP	CHR	POS	Locus	Gene	Effect allele	Other allele	Effect allele frequency	Effect	SE, all studies	P	P, COJO, all studies	P, random effects, all studies	P, Conditional 23AndMe only	P, 23AndMe only	I2, all studies	Freq1, previous studies	Beta, previous studies	StdErr, previous studies	P, previous studies	I2, previous studies	Freq1, new studies	Beta, new studies	StdErr, new studies	P, new studies	I2, new studies	Passes pooled 23andMe QC	Known GWAS locus within 1MB	Failed final filtering and QC	Locus within 250KB	Locus Number	
Returning unmapped column names without making them uppercase.
+ Mapping colnames from MungeSumstats ==> echolocatoR
✔ |          6 | import_topSNPs [1.6s]                      
⠏ |          0 | is_empty                                   Subset file looks good.
No SNPs identified within the summary stats file that met your criterion. :o
✔ |          6 | is_empty
✔ |          2 | is_ggbio                                   
✔ |          2 | is_ggplot                                  
✔ |          2 | is_url                                     
⠏ |          0 | limit_snps                                 Limiting to only 500 SNPs.
+ Reduced number of SNPs: 6,216 ==> 500
✔ |          2 | limit_snps
⠏ |          0 | melt_finemapping_results                   Melting PP and CS from 5 fine-mapping methods.
✔ |          4 | melt_finemapping_results
⠏ |          0 | merge_finemapping_results                  + Gathering all fine-mapping results from storage...
+ 3 multi-finemap files found.
+ Removing duplicate Multi-finemap files per locus.
+ Importing results... RtmpgfuhvU
+ Importing results... RtmpgfuhvU
+ Importing results... RtmpgfuhvU
Identifying Consensus SNPs...
+ support_thresh = 2
+ Calculating mean Posterior Probability (mean.PP)...
+ 4 fine-mapping methods used.
+ 20 Credible Set SNPs identified.
+ 9 Consensus SNPs identified.
+ Saving merged results ==> /var/folders/rd/rbc_wrdj4k3djf3brk6z0_dc0000gp/T//RtmpgfuhvU/file13a997e13e3bdmerged_results.csv.gz
✔ |          4 | merge_finemapping_results                  
✔ |          5 | merge_robust                               
⠏ |          0 | mungesumstats                              + Mapping colnames from MungeSumstats ==> echolocatoR
✔ |          5 | mungesumstats
⠏ |          0 | parquet                                    Loading required namespace: arrow
Failed with error:  'bad value'
Writing parquet file ==> /var/folders/rd/rbc_wrdj4k3djf3brk6z0_dc0000gp/T//RtmpgfuhvU/file13a994bcccdf5.parquet

 *** caught segfault ***
address 0x0, cause 'invalid permissions'

Traceback:
 1: compute__GetFunctionNames()
 2: list_compute_functions()
 3: create_binding_cache()
 4: fun(libname, pkgname)
 5: doTryCatch(return(expr), name, parentenv, handler)
 6: tryCatchOne(expr, names, parentenv, handlers[[1L]])
 7: tryCatchList(expr, classes, parentenv, handlers)
 8: tryCatch(fun(libname, pkgname), error = identity)
 9: runHook(".onLoad", env, package.lib, package)
10: loadNamespace(x)
11: echodata::write_parquet(dat)
12: eval(code, test_env)
13: eval(code, test_env)
14: withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error)
15: doTryCatch(return(expr), name, parentenv, handler)
16: tryCatchOne(expr, names, parentenv, handlers[[1L]])
17: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
18: doTryCatch(return(expr), name, parentenv, handler)
19: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]),     names[nh], parentenv, handlers[[nh]])
20: tryCatchList(expr, classes, parentenv, handlers)
21: tryCatch(withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error), error = handle_fatal,     skip = function(e) {    })
22: test_code(desc, code, env = parent.frame(), default_reporter = local_interactive_reporter())
23: test_that("read/write_parquet works", {    dat <- echodata::BST1    path <- echodata::write_parquet(dat)    dat2 <- echodata::read_parquet(path = path)})
24: eval(code, test_env)
25: eval(code, test_env)
26: withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error)
27: doTryCatch(return(expr), name, parentenv, handler)
28: tryCatchOne(expr, names, parentenv, handlers[[1L]])
29: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
30: doTryCatch(return(expr), name, parentenv, handler)
31: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]),     names[nh], parentenv, handlers[[nh]])
32: tryCatchList(expr, classes, parentenv, handlers)
33: tryCatch(withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error), error = handle_fatal,     skip = function(e) {    })
34: test_code(test = NULL, code = exprs, env = env, default_reporter = StopReporter$new())
35: source_file(path, env = env(env), desc = desc, error_call = error_call)
36: FUN(X[[i]], ...)
37: lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call)
38: doTryCatch(return(expr), name, parentenv, handler)
39: tryCatchOne(expr, names, parentenv, handlers[[1L]])
40: tryCatchList(expr, classes, parentenv, handlers)
41: tryCatch(code, testthat_abort_reporter = function(cnd) {    cat(conditionMessage(cnd), "\n")    NULL})
42: with_reporter(reporters$multi, lapply(test_paths, test_one_file,     env = env, desc = desc, error_call = error_call))
43: test_files_serial(test_dir = test_dir, test_package = test_package,     test_paths = test_paths, load_helpers = load_helpers, reporter = reporter,     env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning,     desc = desc, load_package = load_package, error_call = error_call)
44: test_files(test_dir = path, test_paths = test_paths, test_package = package,     reporter = reporter, load_helpers = load_helpers, env = env,     stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning,     load_package = load_package, parallel = parallel)
45: test_dir(test_path, package = package, reporter = reporter, ...,     load_package = load_package)
46: testthat::test_local(pkg$path, filter = filter, stop_on_failure = stop_on_failure,     load_package = load_package, ...)
47: devtools::test()
An irrecoverable exception occurred. R is aborting now ...

Exited with status 139.

rstudio/reticulate#1470

3. Session info

Details

R version 4.3.1 (2023-06-16)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Ventura 13.6

Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.11.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: Europe/London
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] echodata_0.99.17

loaded via a namespace (and not attached):
  [1] DBI_1.1.3                   piggyback_0.1.5             bitops_1.0-7                testthat_3.2.0             
  [5] rlang_1.1.1                 magrittr_2.0.3              matrixStats_1.0.0           compiler_4.3.1             
  [9] vctrs_0.6.4                 echogithub_0.99.2           stringr_1.5.0               pkgconfig_2.0.3            
 [13] crayon_1.5.2                fastmap_1.1.1               dbplyr_2.3.4                XVector_0.41.1             
 [17] utf8_1.2.3                  Rsamtools_2.17.0            rmarkdown_2.25              tzdb_0.4.0                 
 [21] bit_4.0.5                   waldo_0.5.1                 purrr_1.0.2                 xfun_0.40                  
 [25] rvcheck_0.2.1               zlibbioc_1.47.0             cachem_1.0.8                badger_0.2.3               
 [29] GenomeInfoDb_1.37.6         jsonlite_1.8.7              DelayedArray_0.27.10        BiocParallel_1.35.4        
 [33] parallel_4.3.1              R6_2.5.1                    stringi_1.7.12              RColorBrewer_1.1-3         
 [37] rtracklayer_1.61.1          pkgload_1.3.3               brio_1.1.3                  GenomicRanges_1.53.2       
 [41] assertthat_0.2.1            Rcpp_1.0.11                 SummarizedExperiment_1.31.1 knitr_1.44                 
 [45] R.utils_2.12.2              readr_2.1.4                 IRanges_2.35.3              dlstats_0.1.7              
 [49] Matrix_1.6-1.1              tidyselect_1.2.0            rstudioapi_0.15.0           abind_1.4-5                
 [53] yaml_2.3.7                  codetools_0.2-19            lattice_0.21-9              tibble_3.2.1               
 [57] Biobase_2.61.0              evaluate_0.22               desc_1.4.2                  zip_2.3.0                  
 [61] Biostrings_2.69.2           pillar_1.9.0                BiocManager_1.30.22         MatrixGenerics_1.13.1      
 [65] renv_1.0.3                  DT_0.30                     stats4_4.3.1                generics_0.1.3             
 [69] rprojroot_2.0.3             RCurl_1.98-1.12             S4Vectors_0.39.3            hms_1.1.3                  
 [73] ggplot2_3.4.4               munsell_0.5.0               scales_1.2.1                BiocStyle_2.29.2           
 [77] glue_1.6.2                  tools_4.3.1                 BiocIO_1.11.0               data.table_1.14.8          
 [81] openxlsx_4.2.5.2            BSgenome_1.69.0             GenomicAlignments_1.37.0    fs_1.6.3                   
 [85] XML_3.99-0.14               grid_4.3.1                  tidyr_1.3.0                 gh_1.4.0                   
 [89] colorspace_2.1-0            GenomeInfoDbData_1.2.11     restfulr_0.0.15             cli_3.6.1                  
 [93] rworkflows_0.99.14          fansi_1.0.5                 S4Arrays_1.1.6              arrow_13.0.0.1             
 [97] dplyr_1.1.3                 gtable_0.3.4                R.methodsS3_1.8.2           yulab.utils_0.1.0          
[101] digest_0.6.33               BiocGenerics_0.47.0         SparseArray_1.1.12          rjson_0.2.21               
[105] htmlwidgets_1.6.2           memoise_2.0.1.9000          htmltools_0.5.6.1           R.oo_1.25.0                
[109] lifecycle_1.0.3             here_1.0.1                  bit64_4.0.5 

[bschilder]

Related Issues:

• Segfault with r-arrow=12 rstudio/reticulate#1470
• https://stackoverflow.com/questions/68105860/r-and-rstudio-crashes-running-read-parquet-on-mac-m1
• https://community.rstudio.com/t/r-and-rstudio-crashes-running-read-parquet-on-mac-m1/108315

Seems like it might be related to the version of arrow being used.

[bschilder]

Trying to run arrow::install_arrow() but seems to hang for a very long time...

Eventually did start installing but ultimately failed:

  In file included from /var/folders/rd/rbc_wrdj4k3djf3brk6z0_dc0000gp/T/RtmpUZuKSx/R.INSTALL13acd29e4a96c/arrow/tools/cpp/src/arrow/util/simd.h:37:
In file included from /Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/nmmintrin.h:19:
In file included from /Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/smmintrin.h:17:
In file included from /Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/tmmintrin.h:17:
In file included from /Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/pmmintrin.h:17:
In file included from /Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/emmintrin.h:17:
In file included from /Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/xmmintrin.h:17:
/Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/mmintrin.h:14:2: error: "This header is only meant to be used on x86 and x64 architecture"
#error "This header is only meant to be used on x86 and x64 architecture"
 ^
/Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/mmintrin.h:37:5: error: use of undeclared identifier '__builtin_ia32_emms'; did you mean '__builtin_isless'?
    __builtin_ia32_emms();
    ^
/Library/Developer/CommandLineTools/SDKs/MacOSX14.0.sdk/usr/include/c++/v1/math.h:507:10: note: '__builtin_isless' declared here
  return __builtin_isless((type)__x, (type)__y);
         ^
In file included from /var/folders/rd/rbc_wrdj4k3djf3brk6z0_dc0000gp/T/RtmpUZuKSx/R.INSTALL13acd29e4a96c/arrow/tools/cpp/src/arrow/util/utf8.cc:28:
In file included from /var/folders/rd/rbc_wrdj4k3djf3brk6z0_dc0000gp/T/RtmpUZuKSx/R.INSTALL13acd29e4a96c/arrow/tools/cpp/src/arrow/util/utf8_internal.h:33:
In file included from /var/folders/rd/rbc_wrdj4k3djf3brk6z0_dc0000gp/T/RtmpUZuKSx/R.INSTALL13acd29e4a96c/arrow/tools/cpp/src/arrow/util/simd.h:37:
In file included from /Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/nmmintrin.h:19:
In file included from /Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/smmintrin.h:17:
In file included from /Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/tmmintrin.h:17:
In file included from /Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/pmmintrin.h:17:
In file included from /Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/emmintrin.h:17:
In file included from /Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/xmmintrin.h:17:
/Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/mmintrin.h:37:25: error: too few arguments to function call, expected 2, have 0
    __builtin_ia32_emms();
    ~~~~~~~~~~~~~~~~~~~~^
/Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/mmintrin.h:54:19: error: use of undeclared identifier '__builtin_ia32_vec_init_v2si'
    return (__m64)__builtin_ia32_vec_init_v2si(__i, 0);
                  ^
/Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/mmintrin.h:71:12: error: use of undeclared identifier '__builtin_ia32_vec_ext_v2si'
    return __builtin_ia32_vec_ext_v2si((__v2si)__m, 0);
           ^
/Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/mmintrin.h:133:19: error: use of undeclared identifier '__builtin_ia32_packsswb'
    return (__m64)__builtin_ia32_packsswb((__v4hi)__m1, (__v4hi)__m2);
                  ^
/Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/mmintrin.h:163:19: error: use of undeclared identifier '__builtin_ia32_packssdw'
    return (__m64)__builtin_ia32_packssdw((__v2si)__m1, (__v2si)__m2);
                  ^
/Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/mmintrin.h:193:19: error: use of undeclared identifier '__builtin_ia32_packuswb'
    return (__m64)__builtin_ia32_packuswb((__v4hi)__m1, (__v4hi)__m2);
                  ^
/Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/mmintrin.h:220:19: error: use of undeclared identifier '__builtin_ia32_punpckhbw'
    return (__m64)__builtin_ia32_punpckhbw((__v8qi)__m1, (__v8qi)__m2);
                  ^
/Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/mmintrin.h:243:19: error: use of undeclared identifier '__builtin_ia32_punpckhwd'
    return (__m64)__builtin_ia32_punpckhwd((__v4hi)__m1, (__v4hi)__m2);
                  ^
/Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/mmintrin.h:264:19: error: use of undeclared identifier '__builtin_ia32_punpckhdq'
    return (__m64)__builtin_ia32_punpckhdq((__v2si)__m1, (__v2si)__m2);
                  ^
/Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/mmintrin.h:291:19: error: use of undeclared identifier '__builtin_ia32_punpcklbw'
    return (__m64)__builtin_ia32_punpcklbw((__v8qi)__m1, (__v8qi)__m2);
                  ^
/Library/Developer/CommandLineTools/usr/lib/clang/15.0.0/include/mmintrin.h:314:19: error: use of undeclared identifier '__builtin_ia32_punpcklwd'
    return (__m64)__builtin_ia32_punpcklwd((__v4hi)__m1, (__v4hi)__m2);
                  ^
fatal error: too many errors emitted, stopping now [-ferror-limit=]
20 errors generated.
make[2]: *** [src/arrow/CMakeFiles/arrow_objlib.dir/util/utf8.cc.o] Error 1
make[2]: *** Waiting for unfinished jobs....
make[1]: *** [src/arrow/CMakeFiles/arrow_objlib.dir/all] Error 2
make: *** [all] Error 2
**** Complete build log may still be present at /var/folders/rd/rbc_wrdj4k3djf3brk6z0_dc0000gp/T//RtmpV9U9iU/file13e264e194e16.log 
------------------------- NOTE ---------------------------
There was an issue preparing the Arrow C++ libraries.
See https://arrow.apache.org/docs/r/articles/install.html
---------------------------------------------------------
ERROR: configuration failed for package ‘arrow’
* removing ‘/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/arrow’
* restoring previous ‘/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/arrow’

The downloaded source packages are in
	‘/private/var/folders/rd/rbc_wrdj4k3djf3brk6z0_dc0000gp/T/RtmphVgkLs/downloaded_packages’
Warning message:
In install.packages("arrow", repos = arrow_repos(repos, nightly),  :
  installation of package ‘arrow’ had non-zero exit status