Data.table: Déséquilibre de la pile en fread

@HughParsonage , cela ressemble à # 2457. Essayez peut-être de passer showProgress=FALSE et voyez si cela se termine.
@mattdowle aurait-il pu y avoir une régression depuis le 09/11/2017?

Lancer avec showProgress=FALSE a en effet retourné le résultat (avec uniquement les avertissements attendus).

Merci pour toutes les informations détaillées. Je doute qu'il y ait eu une régression depuis le 09/11/2017, mais peut-être que la longue sortie verbose=TRUE un impact similaire sur la sortie ETA. Le fichier doit être relu, ce qui signifie que plus de sortie est générée. Je crains que le rapport de @HughParsonage que ShowProgress = œuvres vrai pour lui est fausse et que le problème va se passer s'il est exécuté 5-10 fois avec verbose = TRUE.

Il n'y a pas de messages détaillés imprimés à partir de la section parallèle (autre que l'ETA de progression qui est déjà corrigé.) Cependant, il y a des messages verbeux après la première lecture et avant le début de la deuxième relecture (ce qui se produit pour ce fichier). Je suppose qu'il est possible que si ces impressions déclenchent le 100ème CheckUserInterrupt (voir # 2457), cela pourrait provoquer l'échec de la 2ème région parallèle (cependant étrange). Pour exclure cela de toute façon, je viens de modifier tous les messages détaillés pour utiliser REprintf plutôt que Rprintf (même correctif que # 2457 pour l'ETA). Cela a échoué car les tests ne trouvent pas la sortie sur stderr - corrigera. Une fois passé, le fichier .zip de Windows sera automatiquement créé, puis vous pouvez réessayer s'il vous plaît. Je mettrai à jour ici lorsque vous serez prêt.

Ok, la deuxième tentative réussit les vérifications et Windows.zip est disponible. @HughParsonage pourriez -vous réessayer s'il vous plaît? J'ai ajouté un appel à R_FlushConsole () après les messages en mode verbeux juste avant la relecture. Ce flush n'est jamais nécessaire que sur Windows. Je suppose que sans le vidage, la console se met parfois à jour un peu plus tard lorsque la relecture parallèle se produit et que cela pose des problèmes. Veuillez répéter 10 fois, toujours avec verbose=TRUE et showProgress=TRUE . Si vous voyez 10 pistes claires, nous dirons que c'est tout. Sinon, je vais devoir réfléchir à nouveau.

Malheureusement, non corrigé:

> library(data.table)
data.table 1.10.5 IN DEVELOPMENT built 2017-11-15 00:36:41 UTC; appveyor
  The fastest way to learn (by data.table authors): https://www.datacamp.com/courses/data-analysis-the-data-table-way
  Documentation: ?data.table, example(data.table) and browseVignettes("data.table")
  Release notes, videos and slides: http://r-datatable.com
> fread("SA2-by-DJZ-2011.csv", header = FALSE, na.strings = "", verbose = FALSE)
Read 26%. ETA 00:00 Warning: stack imbalance in '$', 20 then 22
Read 52%. ETA 00:00 Warning: stack imbalance in '$', 36 then 35
Warning: stack imbalance in '$', 21 then 22
Read 59%. ETA 00:00 Error in fread("SA2-by-DJZ-2011.csv", header = FALSE, na.strings = "",  : 
  unprotect_ptr: pointer not found
In addition: Warning: stack imbalance in '$', 26 then 28
Warning messages:
1: Warning: stack imbalance in '$', 26 then 27
In fread("SA2-by-DJZ-2011.csv", header = FALSE, na.strings = "",  :
  Starting data input on line 12 <<"Goulburn","110018063",3499,>> with 4 fields and discarding line 11 <<"Main Statistical Area Structu>> before it because it has a different number of fields (3).
2: In fread("SA2-by-DJZ-2011.csv", header = FALSE, na.strings = "",  :
  Found the last consistent line but text exists afterwards. Consider fill=TRUE and/or blank.lines.skip=TRUE. First 200 characters of discarded line: <<"Dataset: 2011 Census of Population and Housing">>
Warning: stack imbalance in 'lapply', 31 then 30
Warning: stack imbalance in '$', 14 then 15

En utilisant verbose=TRUE, showProgress=TRUE même après 10 exécutions, je n'obtiens aucune erreur. Voici le résultat de la 10e sortie:

Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 12 threads (omp_get_max_threads()=12, nth=12)
  NAstrings = [<<>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file SA2-by-DJZ-2011.csv
  File opened, size = 349.4MB (366418725 bytes).
  Memory mapping ... ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \r-only line endings are not allowed because \n is found in the data
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Australian Bureau of Statistic>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 89 lines of 4 fields using quote rule 0
  Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 4
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to false
  Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
  Type codes (jump 000)    : 1551  Quote rule 0
  Type codes (jump 100)    : 11051  Quote rule 0
  =====
  Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 12 to the end of last row: 366418143
  Line length: mean=16.02 sd=0.21 min=16 max=29
  Estimated number of rows: 366418143 / 16.02 = 22877178
  Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 11051
[10] Allocate memory for the datatable
  Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
[12] Finalizing the datatable
Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:02.094 wall clock time
Thread buffers were grown 0 times (if all 1 threads each grew once, this figure would be 1)
Final type counts
         0 : drop     
         1 : bool8    
         0 : bool8    
         0 : bool8    
         0 : bool8    
         1 : int32    
         0 : int64    
         0 : float64  
         0 : float64  
         0 : float64  
         2 : string   
Rereading 1 columns due to out-of-sample type exceptions.
Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
Read 99%. ETA 00:00 
[12] Finalizing the datatable
Reread 22885380 rows x 1 columns in 00:01.752
Read 22885380 rows. Exactly what was estimated and allocated up front
=============================
   0.004s (  0%) Memory map 0.341GB file
   0.008s (  0%) sep=',' ncol=4 and header detection
   0.001s (  0%) Column type detection using 10027 sample rows
   0.173s (  4%) Allocation of 22885380 rows x 4 cols (0.469GB)
   3.660s ( 95%) Reading 360 chunks of 0.971MB (63547 rows) using 1 threads
   =    0.009s (  0%) Finding first non-embedded \n after each jump
   +    1.946s ( 51%) Parse to row-major thread buffers
   +    1.098s ( 29%) Transpose
   +    0.608s ( 16%) Waiting
   1.752s ( 46%) Rereading 1 columns due to out-of-sample type exceptions
   3.846s        Total
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 12 threads (omp_get_max_threads()=12, nth=12)
  NAstrings = [<<>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file SA2-by-DJZ-2011.csv
  File opened, size = 349.4MB (366418725 bytes).
  Memory mapping ... ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \r-only line endings are not allowed because \n is found in the data
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Australian Bureau of Statistic>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 89 lines of 4 fields using quote rule 0
  Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 4
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to false
  Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
  Type codes (jump 000)    : 1551  Quote rule 0
  Type codes (jump 100)    : 11051  Quote rule 0
  =====
  Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 12 to the end of last row: 366418143
  Line length: mean=16.02 sd=0.21 min=16 max=29
  Estimated number of rows: 366418143 / 16.02 = 22877178
  Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 11051
[10] Allocate memory for the datatable
  Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
[12] Finalizing the datatable
Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:02.589 wall clock time
Thread buffers were grown 0 times (if all 1 threads each grew once, this figure would be 1)
Final type counts
         0 : drop     
         1 : bool8    
         0 : bool8    
         0 : bool8    
         0 : bool8    
         1 : int32    
         0 : int64    
         0 : float64  
         0 : float64  
         0 : float64  
         2 : string   
Rereading 1 columns due to out-of-sample type exceptions.
Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
Read 99%. ETA 00:00 
[12] Finalizing the datatable
Reread 22885380 rows x 1 columns in 00:01.418
Read 22885380 rows. Exactly what was estimated and allocated up front
=============================
   0.001s (  0%) Memory map 0.341GB file
   0.003s (  0%) sep=',' ncol=4 and header detection
   0.001s (  0%) Column type detection using 10027 sample rows
   0.574s ( 14%) Allocation of 22885380 rows x 4 cols (0.469GB)
   3.428s ( 86%) Reading 360 chunks of 0.971MB (63547 rows) using 1 threads
   =    0.010s (  0%) Finding first non-embedded \n after each jump
   +    1.988s ( 50%) Parse to row-major thread buffers
   +    1.137s ( 28%) Transpose
   +    0.292s (  7%) Waiting
   1.418s ( 35%) Rereading 1 columns due to out-of-sample type exceptions
   4.007s        Total
There were 20 warnings (use warnings() to see them)

@HughParsonage Merci! Je suis confus cependant. Vous dites que cela fonctionne bien avec verbose=TRUE, showProgress=TRUE ce que nous espérions - yay! Cela a échoué avant, n'est-ce pas? La valeur par défaut pour showProgress est de toute façon TRUE, mais lorsque vous exécutez la valeur par défaut FALSE pour verbose , _alors_ cela ne fonctionne pas et vous voyez le déséquilibre de la pile? C'est étrange que la sortie _less_ fasse échouer. Veuillez confirmer. Si c'est le cas, alors peut-être que j'aboie le mauvais arbre. Cela fonctionne bien ici pour moi sous Linux, donc je compte sur vos tests sur Windows. Merci.
(De plus, en bas de la sortie de la 10e exécution, il y a eu 20 avertissements. Je suppose que ce sont les 2 avertissements affichés plus haut, répétés 10 fois. Si oui, cela a du sens.)

Salut désolé pour la confusion, Matt.

Vous avez raison de dire que le problème d'origine n'entraîne plus de plantage, à savoir que les travaux suivants fonctionnent comme prévu:

fread("SA2-by-DJZ-2011.csv", header = FALSE, na.strings = "")

Pour clarifier, dans l'original, quand verbose =FALSE (la valeur par défaut) j'ai eu un crash. Je l'ai exécuté avec verbose = TRUE avant de déposer le problème, et j'ai remarqué un avertissement de «déséquilibre de la pile» mais je n'ai pas rencontré de plantage. Avec la dernière version, je n'obtiens pas de plantage (ni même de problèmes) avec verbose = FALSE .

La raison pour laquelle j'ai dit `` non corrigé '' est que j'ai remarqué les messages d'avertissement:

Warning messages:
Warning: stack imbalance in '$', 26 then 27
Warning: stack imbalance in 'lapply', 31 then 30
Warning: stack imbalance in '$', 14 then 15

qui semblait étrange et je pensais que cela pourrait indiquer un problème étroitement lié mais pas identique. Cela dit, ce matin en Australie, je ne peux plus reproduire les messages d'avertissement.

OK je vois. Ces messages d'avertissement sur le déséquilibre de la pile sont essentiellement des erreurs, oui. Nous ne pouvons pas les sauter. J'appelle cet avertissement concernant le déséquilibre de la pile un crash, même s'il ne s'est pas encore écrasé. (Ce n'est qu'une question de temps jusqu'à ce qu'il se bloque après avoir vu cet avertissement.)

Lorsque vous effectuez les 10 exécutions dans une nouvelle session R avec verbose=TRUE, showProgress=TRUE , il y a l'un des 20 avertissements sur le déséquilibre de la pile ou tous ces 20 avertissements réguliers sont-ils simplement les suivants.

1: In fread("SA2-by-DJZ-2011.csv", header = FALSE, na.strings = "",  :
  Starting data input on line 12 <<"Goulburn","110018063",3499,>> with 4 fields and discarding line 11 <<"Main Statistical Area Structu>> before it because it has a different number of fields (3).
2: In fread("SA2-by-DJZ-2011.csv", header = FALSE, na.strings = "",  :
  Found the last consistent line but text exists afterwards. Consider fill=TRUE and/or blank.lines.skip=TRUE. First 200 characters of discarded line: <<"Dataset: 2011 Census of Population and Housing">>

Une fois qu'un avertissement de déséquilibre de pile s'est produit, veuillez démarrer une nouvelle session R. Nous ne pouvons faire confiance à rien de R après que cela se soit produit une seule fois.

J'ai réussi à avoir un crash quand j'ai couru avec verbose=TRUE, showProgress=TRUE . Quelque chose à propos d'un const char avec un SEXP . J'essaie de reproduire cela à partir de la ligne de commande (malheureusement, cela s'est produit dans RStudio et RStudio s'est fermé avant que je puisse lire le message entier).

Impossible de reproduire le crash. Voici le résultat après le redémarrage. Il y avait un avertissement de déséquilibre de la pile:

> library(data.table)
data.table 1.10.5 IN DEVELOPMENT built 2017-11-15 00:36:41 UTC; appveyor
  The fastest way to learn (by data.table authors): https://www.datacamp.com/courses/data-analysis-the-data-table-way
  Documentation: ?data.table, example(data.table) and browseVignettes("data.table")
  Release notes, videos and slides: http://r-datatable.com
> for (i in 1:10) fread("SA2-by-DJZ-2011.csv", header = FALSE, na.strings = "", verbose = TRUE, showProgress = TRUE)
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 12 threads (omp_get_max_threads()=12, nth=12)
  NAstrings = [<<>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file SA2-by-DJZ-2011.csv
  File opened, size = 349.4MB (366418725 bytes).
  Memory mapping ... ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \r-only line endings are not allowed because \n is found in the data
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Australian Bureau of Statistic>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 89 lines of 4 fields using quote rule 0
  Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 4
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to false
  Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
  Type codes (jump 000)    : 1551  Quote rule 0
  Type codes (jump 100)    : 11051  Quote rule 0
  =====
  Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 12 to the end of last row: 366418143
  Line length: mean=16.02 sd=0.21 min=16 max=29
  Estimated number of rows: 366418143 / 16.02 = 22877178
  Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 11051
[10] Allocate memory for the datatable
  Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
[12] Finalizing the datatable
Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:01.212 wall clock time
Thread buffers were grown 0 times (if all 12 threads each grew once, this figure would be 12)
Final type counts
         0 : drop     
         1 : bool8    
         0 : bool8    
         0 : bool8    
         0 : bool8    
         1 : int32    
         0 : int64    
         0 : float64  
         0 : float64  
         0 : float64  
         2 : string   
Rereading 1 columns due to out-of-sample type exceptions.
Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
Read 31%. ETA 00:00 Warning: stack imbalance in '$', 24 then 23
Read 91%. ETA 00:00 Warning: stack imbalance in '$', 27 then 26
Read 95%. ETA 00:00 Warning: stack imbalance in '$', 28 then 29
Read 98%. ETA 00:00 
[12] Finalizing the datatable
Reread 22885380 rows x 1 columns in 00:00.895
Read 22885380 rows. Exactly what was estimated and allocated up front
=============================
   0.002s (  0%) Memory map 0.341GB file
   0.029s (  1%) sep=',' ncol=4 and header detection
   0.001s (  0%) Column type detection using 10027 sample rows
   0.314s ( 15%) Allocation of 22885380 rows x 4 cols (0.469GB)
   1.761s ( 84%) Reading 360 chunks of 0.971MB (63547 rows) using 12 threads
   =    0.015s (  1%) Finding first non-embedded \n after each jump
   +    0.599s ( 28%) Parse to row-major thread buffers
   +    0.400s ( 19%) Transpose
   +    0.746s ( 35%) Waiting
   0.895s ( 42%) Rereading 1 columns due to out-of-sample type exceptions
   2.107s        Total
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 12 threads (omp_get_max_threads()=12, nth=12)
  NAstrings = [<<>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file SA2-by-DJZ-2011.csv
  File opened, size = 349.4MB (366418725 bytes).
  Memory mapping ... ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \r-only line endings are not allowed because \n is found in the data
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Australian Bureau of Statistic>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 89 lines of 4 fields using quote rule 0
  Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 4
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to false
  Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
  Type codes (jump 000)    : 1551  Quote rule 0
  Type codes (jump 100)    : 11051  Quote rule 0
  =====
  Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 12 to the end of last row: 366418143
  Line length: mean=16.02 sd=0.21 min=16 max=29
  Estimated number of rows: 366418143 / 16.02 = 22877178
  Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 11051
[10] Allocate memory for the datatable
  Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
[12] Finalizing the datatable
Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:01.335 wall clock time
Thread buffers were grown 0 times (if all 12 threads each grew once, this figure would be 12)
Final type counts
         0 : drop     
         1 : bool8    
         0 : bool8    
         0 : bool8    
         0 : bool8    
         1 : int32    
         0 : int64    
         0 : float64  
         0 : float64  
         0 : float64  
         2 : string   
Rereading 1 columns due to out-of-sample type exceptions.
Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
Read 98%. ETA 00:00 
[12] Finalizing the datatable
Reread 22885380 rows x 1 columns in 00:01.049
Read 22885380 rows. Exactly what was estimated and allocated up front
=============================
   0.002s (  0%) Memory map 0.341GB file
   0.006s (  0%) sep=',' ncol=4 and header detection
   0.001s (  0%) Column type detection using 10027 sample rows
   0.402s ( 17%) Allocation of 22885380 rows x 4 cols (0.469GB)
   1.974s ( 83%) Reading 360 chunks of 0.971MB (63547 rows) using 12 threads
   =    0.001s (  0%) Finding first non-embedded \n after each jump
   +    0.209s (  9%) Parse to row-major thread buffers
   +    0.864s ( 36%) Transpose
   +    0.900s ( 38%) Waiting
   1.049s ( 44%) Rereading 1 columns due to out-of-sample type exceptions
   2.385s        Total
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 12 threads (omp_get_max_threads()=12, nth=12)
  NAstrings = [<<>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file SA2-by-DJZ-2011.csv
  File opened, size = 349.4MB (366418725 bytes).
  Memory mapping ... ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \r-only line endings are not allowed because \n is found in the data
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Australian Bureau of Statistic>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 89 lines of 4 fields using quote rule 0
  Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 4
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to false
  Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
  Type codes (jump 000)    : 1551  Quote rule 0
  Type codes (jump 100)    : 11051  Quote rule 0
  =====
  Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 12 to the end of last row: 366418143
  Line length: mean=16.02 sd=0.21 min=16 max=29
  Estimated number of rows: 366418143 / 16.02 = 22877178
  Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 11051
[10] Allocate memory for the datatable
  Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
[12] Finalizing the datatable
Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:01.212 wall clock time
Thread buffers were grown 0 times (if all 12 threads each grew once, this figure would be 12)
Final type counts
         0 : drop     
         1 : bool8    
         0 : bool8    
         0 : bool8    
         0 : bool8    
         1 : int32    
         0 : int64    
         0 : float64  
         0 : float64  
         0 : float64  
         2 : string   
Rereading 1 columns due to out-of-sample type exceptions.
Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
Read 96%. ETA 00:00 
[12] Finalizing the datatable
Reread 22885380 rows x 1 columns in 00:00.414
Read 22885380 rows. Exactly what was estimated and allocated up front
=============================
   0.002s (  0%) Memory map 0.341GB file
   0.007s (  0%) sep=',' ncol=4 and header detection
   0.002s (  0%) Column type detection using 10027 sample rows
   0.293s ( 18%) Allocation of 22885380 rows x 4 cols (0.469GB)
   1.322s ( 81%) Reading 360 chunks of 0.971MB (63547 rows) using 12 threads
   =    0.001s (  0%) Finding first non-embedded \n after each jump
   +    0.199s ( 12%) Parse to row-major thread buffers
   +    0.822s ( 51%) Transpose
   +    0.301s ( 19%) Waiting
   0.414s ( 25%) Rereading 1 columns due to out-of-sample type exceptions
   1.626s        Total
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 12 threads (omp_get_max_threads()=12, nth=12)
  NAstrings = [<<>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file SA2-by-DJZ-2011.csv
  File opened, size = 349.4MB (366418725 bytes).
  Memory mapping ... ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \r-only line endings are not allowed because \n is found in the data
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Australian Bureau of Statistic>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 89 lines of 4 fields using quote rule 0
  Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 4
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to false
  Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
  Type codes (jump 000)    : 1551  Quote rule 0
  Type codes (jump 100)    : 11051  Quote rule 0
  =====
  Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 12 to the end of last row: 366418143
  Line length: mean=16.02 sd=0.21 min=16 max=29
  Estimated number of rows: 366418143 / 16.02 = 22877178
  Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 11051
[10] Allocate memory for the datatable
  Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
[12] Finalizing the datatable
Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:01.451 wall clock time
Thread buffers were grown 0 times (if all 12 threads each grew once, this figure would be 12)
Final type counts
         0 : drop     
         1 : bool8    
         0 : bool8    
         0 : bool8    
         0 : bool8    
         1 : int32    
         0 : int64    
         0 : float64  
         0 : float64  
         0 : float64  
         2 : string   
Rereading 1 columns due to out-of-sample type exceptions.
Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
Read 97%. ETA 00:00 
[12] Finalizing the datatable
Reread 22885380 rows x 1 columns in 00:00.409
Read 22885380 rows. Exactly what was estimated and allocated up front
=============================
   0.002s (  0%) Memory map 0.341GB file
   0.006s (  0%) sep=',' ncol=4 and header detection
   0.001s (  0%) Column type detection using 10027 sample rows
   0.403s ( 22%) Allocation of 22885380 rows x 4 cols (0.469GB)
   1.448s ( 78%) Reading 360 chunks of 0.971MB (63547 rows) using 12 threads
   =    0.001s (  0%) Finding first non-embedded \n after each jump
   +    0.194s ( 10%) Parse to row-major thread buffers
   +    0.974s ( 52%) Transpose
   +    0.279s ( 15%) Waiting
   0.409s ( 22%) Rereading 1 columns due to out-of-sample type exceptions
   1.860s        Total
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 12 threads (omp_get_max_threads()=12, nth=12)
  NAstrings = [<<>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file SA2-by-DJZ-2011.csv
  File opened, size = 349.4MB (366418725 bytes).
  Memory mapping ... ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \r-only line endings are not allowed because \n is found in the data
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Australian Bureau of Statistic>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 89 lines of 4 fields using quote rule 0
  Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 4
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to false
  Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
  Type codes (jump 000)    : 1551  Quote rule 0
  Type codes (jump 100)    : 11051  Quote rule 0
  =====
  Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 12 to the end of last row: 366418143
  Line length: mean=16.02 sd=0.21 min=16 max=29
  Estimated number of rows: 366418143 / 16.02 = 22877178
  Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 11051
[10] Allocate memory for the datatable
  Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
[12] Finalizing the datatable
Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:01.480 wall clock time
Thread buffers were grown 0 times (if all 12 threads each grew once, this figure would be 12)
Final type counts
         0 : drop     
         1 : bool8    
         0 : bool8    
         0 : bool8    
         0 : bool8    
         1 : int32    
         0 : int64    
         0 : float64  
         0 : float64  
         0 : float64  
         2 : string   
Rereading 1 columns due to out-of-sample type exceptions.
Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
Read 99%. ETA 00:00 
[12] Finalizing the datatable
Reread 22885380 rows x 1 columns in 00:00.412
Read 22885380 rows. Exactly what was estimated and allocated up front
=============================
   0.002s (  0%) Memory map 0.341GB file
   0.007s (  0%) sep=',' ncol=4 and header detection
   0.001s (  0%) Column type detection using 10027 sample rows
   0.459s ( 24%) Allocation of 22885380 rows x 4 cols (0.469GB)
   1.424s ( 75%) Reading 360 chunks of 0.971MB (63547 rows) using 12 threads
   =    0.001s (  0%) Finding first non-embedded \n after each jump
   +    0.197s ( 10%) Parse to row-major thread buffers
   +    0.938s ( 50%) Transpose
   +    0.288s ( 15%) Waiting
   0.412s ( 22%) Rereading 1 columns due to out-of-sample type exceptions
   1.892s        Total
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 12 threads (omp_get_max_threads()=12, nth=12)
  NAstrings = [<<>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file SA2-by-DJZ-2011.csv
  File opened, size = 349.4MB (366418725 bytes).
  Memory mapping ... ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \r-only line endings are not allowed because \n is found in the data
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Australian Bureau of Statistic>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 89 lines of 4 fields using quote rule 0
  Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 4
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to false
  Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
  Type codes (jump 000)    : 1551  Quote rule 0
  Type codes (jump 100)    : 11051  Quote rule 0
  =====
  Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 12 to the end of last row: 366418143
  Line length: mean=16.02 sd=0.21 min=16 max=29
  Estimated number of rows: 366418143 / 16.02 = 22877178
  Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 11051
[10] Allocate memory for the datatable
  Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
[12] Finalizing the datatable
Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:01.381 wall clock time
Thread buffers were grown 0 times (if all 12 threads each grew once, this figure would be 12)
Final type counts
         0 : drop     
         1 : bool8    
         0 : bool8    
         0 : bool8    
         0 : bool8    
         1 : int32    
         0 : int64    
         0 : float64  
         0 : float64  
         0 : float64  
         2 : string   
Rereading 1 columns due to out-of-sample type exceptions.
Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
Read 97%. ETA 00:00 
[12] Finalizing the datatable
Reread 22885380 rows x 1 columns in 00:00.401
Read 22885380 rows. Exactly what was estimated and allocated up front
=============================
   0.002s (  0%) Memory map 0.341GB file
   0.005s (  0%) sep=',' ncol=4 and header detection
   0.001s (  0%) Column type detection using 10027 sample rows
   0.384s ( 22%) Allocation of 22885380 rows x 4 cols (0.469GB)
   1.389s ( 78%) Reading 360 chunks of 0.971MB (63547 rows) using 12 threads
   =    0.001s (  0%) Finding first non-embedded \n after each jump
   +    0.196s ( 11%) Parse to row-major thread buffers
   +    0.911s ( 51%) Transpose
   +    0.281s ( 16%) Waiting
   0.401s ( 22%) Rereading 1 columns due to out-of-sample type exceptions
   1.781s        Total
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 12 threads (omp_get_max_threads()=12, nth=12)
  NAstrings = [<<>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file SA2-by-DJZ-2011.csv
  File opened, size = 349.4MB (366418725 bytes).
  Memory mapping ... ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \r-only line endings are not allowed because \n is found in the data
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Australian Bureau of Statistic>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 89 lines of 4 fields using quote rule 0
  Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 4
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to false
  Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
  Type codes (jump 000)    : 1551  Quote rule 0
  Type codes (jump 100)    : 11051  Quote rule 0
  =====
  Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 12 to the end of last row: 366418143
  Line length: mean=16.02 sd=0.21 min=16 max=29
  Estimated number of rows: 366418143 / 16.02 = 22877178
  Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 11051
[10] Allocate memory for the datatable
  Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
[12] Finalizing the datatable
Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:01.384 wall clock time
Thread buffers were grown 0 times (if all 12 threads each grew once, this figure would be 12)
Final type counts
         0 : drop     
         1 : bool8    
         0 : bool8    
         0 : bool8    
         0 : bool8    
         1 : int32    
         0 : int64    
         0 : float64  
         0 : float64  
         0 : float64  
         2 : string   
Rereading 1 columns due to out-of-sample type exceptions.
Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
Read 98%. ETA 00:00 
[12] Finalizing the datatable
Reread 22885380 rows x 1 columns in 00:00.480
Read 22885380 rows. Exactly what was estimated and allocated up front
=============================
   0.002s (  0%) Memory map 0.341GB file
   0.006s (  0%) sep=',' ncol=4 and header detection
   0.002s (  0%) Column type detection using 10027 sample rows
   0.476s ( 26%) Allocation of 22885380 rows x 4 cols (0.469GB)
   1.378s ( 74%) Reading 360 chunks of 0.971MB (63547 rows) using 12 threads
   =    0.001s (  0%) Finding first non-embedded \n after each jump
   +    0.192s ( 10%) Parse to row-major thread buffers
   +    0.833s ( 45%) Transpose
   +    0.352s ( 19%) Waiting
   0.480s ( 26%) Rereading 1 columns due to out-of-sample type exceptions
   1.864s        Total
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 12 threads (omp_get_max_threads()=12, nth=12)
  NAstrings = [<<>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file SA2-by-DJZ-2011.csv
  File opened, size = 349.4MB (366418725 bytes).
  Memory mapping ... ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \r-only line endings are not allowed because \n is found in the data
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Australian Bureau of Statistic>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 89 lines of 4 fields using quote rule 0
  Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 4
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to false
  Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
  Type codes (jump 000)    : 1551  Quote rule 0
  Type codes (jump 100)    : 11051  Quote rule 0
  =====
  Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 12 to the end of last row: 366418143
  Line length: mean=16.02 sd=0.21 min=16 max=29
  Estimated number of rows: 366418143 / 16.02 = 22877178
  Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 11051
[10] Allocate memory for the datatable
  Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
[12] Finalizing the datatable
Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:01.374 wall clock time
Thread buffers were grown 0 times (if all 12 threads each grew once, this figure would be 12)
Final type counts
         0 : drop     
         1 : bool8    
         0 : bool8    
         0 : bool8    
         0 : bool8    
         1 : int32    
         0 : int64    
         0 : float64  
         0 : float64  
         0 : float64  
         2 : string   
Rereading 1 columns due to out-of-sample type exceptions.
Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
Read 98%. ETA 00:00 
[12] Finalizing the datatable
Reread 22885380 rows x 1 columns in 00:00.507
Read 22885380 rows. Exactly what was estimated and allocated up front
=============================
   0.002s (  0%) Memory map 0.341GB file
   0.006s (  0%) sep=',' ncol=4 and header detection
   0.001s (  0%) Column type detection using 10027 sample rows
   0.311s ( 17%) Allocation of 22885380 rows x 4 cols (0.469GB)
   1.562s ( 83%) Reading 360 chunks of 0.971MB (63547 rows) using 12 threads
   =    0.001s (  0%) Finding first non-embedded \n after each jump
   +    0.193s ( 10%) Parse to row-major thread buffers
   +    0.988s ( 52%) Transpose
   +    0.381s ( 20%) Waiting
   0.507s ( 27%) Rereading 1 columns due to out-of-sample type exceptions
   1.881s        Total
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 12 threads (omp_get_max_threads()=12, nth=12)
  NAstrings = [<<>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file SA2-by-DJZ-2011.csv
  File opened, size = 349.4MB (366418725 bytes).
  Memory mapping ... ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \r-only line endings are not allowed because \n is found in the data
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Australian Bureau of Statistic>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 89 lines of 4 fields using quote rule 0
  Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 4
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to false
  Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
  Type codes (jump 000)    : 1551  Quote rule 0
  Type codes (jump 100)    : 11051  Quote rule 0
  =====
  Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 12 to the end of last row: 366418143
  Line length: mean=16.02 sd=0.21 min=16 max=29
  Estimated number of rows: 366418143 / 16.02 = 22877178
  Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 11051
[10] Allocate memory for the datatable
  Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
[12] Finalizing the datatable
Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:01.318 wall clock time
Thread buffers were grown 0 times (if all 12 threads each grew once, this figure would be 12)
Final type counts
         0 : drop     
         1 : bool8    
         0 : bool8    
         0 : bool8    
         0 : bool8    
         1 : int32    
         0 : int64    
         0 : float64  
         0 : float64  
         0 : float64  
         2 : string   
Rereading 1 columns due to out-of-sample type exceptions.
Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
Read 96%. ETA 00:00 
[12] Finalizing the datatable
Reread 22885380 rows x 1 columns in 00:00.493
Read 22885380 rows. Exactly what was estimated and allocated up front
=============================
   0.002s (  0%) Memory map 0.341GB file
   0.006s (  0%) sep=',' ncol=4 and header detection
   0.001s (  0%) Column type detection using 10027 sample rows
   0.306s ( 17%) Allocation of 22885380 rows x 4 cols (0.469GB)
   1.496s ( 83%) Reading 360 chunks of 0.971MB (63547 rows) using 12 threads
   =    0.001s (  0%) Finding first non-embedded \n after each jump
   +    0.193s ( 11%) Parse to row-major thread buffers
   +    0.935s ( 52%) Transpose
   +    0.367s ( 20%) Waiting
   0.493s ( 27%) Rereading 1 columns due to out-of-sample type exceptions
   1.811s        Total
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 12 threads (omp_get_max_threads()=12, nth=12)
  NAstrings = [<<>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file SA2-by-DJZ-2011.csv
  File opened, size = 349.4MB (366418725 bytes).
  Memory mapping ... ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \r-only line endings are not allowed because \n is found in the data
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Australian Bureau of Statistic>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 89 lines of 4 fields using quote rule 0
  Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 4
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to false
  Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
  Type codes (jump 000)    : 1551  Quote rule 0
  Type codes (jump 100)    : 11051  Quote rule 0
  =====
  Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 12 to the end of last row: 366418143
  Line length: mean=16.02 sd=0.21 min=16 max=29
  Estimated number of rows: 366418143 / 16.02 = 22877178
  Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 11051
[10] Allocate memory for the datatable
  Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
[12] Finalizing the datatable
Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:01.141 wall clock time
Thread buffers were grown 0 times (if all 12 threads each grew once, this figure would be 12)
Final type counts
         0 : drop     
         1 : bool8    
         0 : bool8    
         0 : bool8    
         0 : bool8    
         1 : int32    
         0 : int64    
         0 : float64  
         0 : float64  
         0 : float64  
         2 : string   
Rereading 1 columns due to out-of-sample type exceptions.
Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
Read 98%. ETA 00:00 
[12] Finalizing the datatable
Reread 22885380 rows x 1 columns in 00:00.506
Read 22885380 rows. Exactly what was estimated and allocated up front
=============================
   0.002s (  0%) Memory map 0.341GB file
   0.007s (  0%) sep=',' ncol=4 and header detection
   0.001s (  0%) Column type detection using 10027 sample rows
   0.132s (  8%) Allocation of 22885380 rows x 4 cols (0.469GB)
   1.506s ( 91%) Reading 360 chunks of 0.971MB (63547 rows) using 12 threads
   =    0.001s (  0%) Finding first non-embedded \n after each jump
   +    0.195s ( 12%) Parse to row-major thread buffers
   +    0.938s ( 57%) Transpose
   +    0.371s ( 23%) Waiting
   0.506s ( 31%) Rereading 1 columns due to out-of-sample type exceptions
   1.647s        Total
Warning: stack imbalance in 'for', 2 then 8
There were 20 warnings (use warnings() to see them)

Curieusement, cette certitude est excellente. Merci. Cela signifie que le flush n'a pas fonctionné et que je devrai trouver un moyen d'éviter Rprintf après tout. Cela fonctionne de manière fiable avec verbose=FALSE, showProgress=FALSE Je suppose (vous avez écrit cela vers le haut de ce problème, donc je compte sur cela.) "Fiable" signifie 10 courses consécutives avec seulement les deux avertissements attendus et aucune vue de la pile avertissement de déséquilibre.
Laissez-moi alors. Merci encore.

@HughParsonage Ok, veuillez réessayer avec cette deuxième tentative récente. Il n'est pas encore fusionné dans master, alors veillez à récupérer le Windows.zip de la branche ici . Comme auparavant, veuillez fournir le résultat complet de toute façon afin que je puisse le vérifier. Merci!

La première tentative de ce qui suit a entraîné un crash (quelque chose à propos d'un pointeur).

La deuxième tentative (après le redémarrage) entraîne un avertissement stack imbalance in '$', 16 then 15 .

# Assert that `data.table` is not installed:
stopifnot(!requireNamespace("data.table", quietly = TRUE))

install.packages("https://ci.appveyor.com/api/buildjobs/bpsehtwybbbgbyy3/artifacts/data.table_1.10.5.zip",
                 repos = NULL)
# Installing package into ‘C:/Users/hughp/Documents/R/win-library/3.4’
# (as ‘lib’ is unspecified)
# trying URL 'https://ci.appveyor.com/api/buildjobs/bpsehtwybbbgbyy3/artifacts/data.table_1.10.5.zip'
# Content type 'application/octet-stream' length 1557502 bytes (1.5 MB)
# downloaded 1.5 MB

library(data.table)
# data.table 1.10.5 IN DEVELOPMENT built 2017-11-17 01:38:17 UTC; appveyor
# The fastest way to learn (by data.table authors): https://www.datacamp.com/courses/data-analysis-the-data-table-way
# Documentation: ?data.table, example(data.table) and browseVignettes("data.table")
# Release notes, videos and slides: http://r-datatable.com

setwd("~/ABS-data/inbox/SA2-by-DJZ-2011/")
fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "", header = FALSE)
# Input contains no \n. Taking this to be a filename to open
# [01] Check arguments
# Using 12 threads (omp_get_max_threads()=12, nth=12)
# NAstrings = [<<>>]
# None of the NAstrings look like numbers.
# show progress = 1
# 0/1 column will be read as boolean
# [02] Opening the file
# Opening file SA2-by-DJZ-2011.csv
# File opened, size = 349.4MB (366418725 bytes).
# Memory mapping ... ok
# [03] Detect and skip BOM
# [04] Arrange mmap to be \0 terminated
# \r-only line endings are not allowed because \n is found in the data
# [05] Skipping initial rows if needed
# Positioned on line 1 starting: <<Australian Bureau of Statistic>>
#   [06] Detect separator, quoting rule, and ncolumns
# Detecting sep ...
# sep=','  with 89 lines of 4 fields using quote rule 0
# Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
#   Quote rule picked = 0
# fill=false and the most number of columns found is 4
# [07] Detect column types, good nrow estimate and whether first row is column names
# 'header' changed by user from 'auto' to false
# Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
# Type codes (jump 000)    : 1551  Quote rule 0
# Type codes (jump 100)    : 1A51  Quote rule 0
# =====
#   Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
# Bytes from first data row on line 12 to the end of last row: 366418143
# Line length: mean=16.02 sd=0.21 min=16 max=29
# Estimated number of rows: 366418143 / 16.02 = 22877178
# Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
# =====
#   [08] Assign column names
# [09] Apply user overrides on column types
# After 0 type and 0 drop user overrides : 1A51
# [10] Allocate memory for the datatable
# Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
# [11] Read the data
# jumps=[0..360), chunk_size=1017828, total_size=366418143
# Read 78%. ETA 00:00 Warning: stack imbalance in '$', 16 then 15
# Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:02.677 wall clock time
# [12] Finalizing the datatable
# Type counts:
#   1 : bool8     '1'
# 1 : int32     '5'
# 2 : string    'A'
# =============================
#   0.002s (  0%) Memory map 0.341GB file
# 0.007s (  0%) sep=',' ncol=4 and header detection
# 0.001s (  0%) Column type detection using 10027 sample rows
# 0.297s ( 11%) Allocation of 25164895 rows x 4 cols (0.469GB) of which 22885380 ( 91%) rows used
# 2.369s ( 89%) Reading 360 chunks of 0.971MB (63547 rows) using 12 threads
# =    0.003s (  0%) Finding first non-embedded \n after each jump
# +    0.273s ( 10%) Parse to row-major thread buffers (grown 0 times)
# +    1.313s ( 49%) Transpose
# +    0.780s ( 29%) Waiting
# 0.893s ( 33%) Rereading 1 columns due to out-of-sample type exceptions
# 2.677s        Total
# Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
# V1        V2      V3 V4
# 1: Goulburn 110018063    3499 NA
# 2:       NA 110018064     812 NA
# 3:       NA 110018065    2158 NA
# 4:       NA 110019999     402 NA
# 5:       NA 110028068      10 NA
# ---                              
#   22885376:       NA 997999799       0 NA
# 22885377:       NA 998999899      64 NA
# 22885378:       NA 994999499      34 NA
# 22885379:       NA 0&&&&&&&&  250796 NA
# 22885380:       NA 0@@@@@@@@ 7305367 NA
# Warning messages:
#   1: In fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "",  :
#                 Starting data input on line 12 <<"Goulburn","110018063",3499,>> with 4 fields and discarding line 11 <<"Main Statistical Area Structu>> before it because it has a different number of fields (3).
#               2: In fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "",  :
#               Found the last consistent line but text exists afterwards. Consider fill=TRUE and/or blank.lines.skip=TRUE. First 200 characters of discarded line: <<"Dataset: 2011 Census of Population and Housing">>

Salut, @mattdowle. Il existe des versions de GCC encore utilisées dont OpenMP est au mieux 3.1, pas 4.0. J'ai rencontré ce problème dans l'un de mes packages sur CRAN ( Delaporte ) où j'ai essayé d'utiliser une directive SIMD (OpenMP 4.0) compilée avec Rtools pour Windows (basé sur 4.9.3) mais jeté une erreur sur la machine Linux de quelqu'un utilisant toujours gcc 4.8.0. Même Windows ne peut utiliser que les appels 4.0 et non 4.5, si je me souviens bien. Peut-être que cela contribue au problème?

@HughParsonage Merci d'avoir testé si rapidement! Ok, je vais continuer à réfléchir!
@aadler C'est une bonne idée - tout est possible.

@HughParsonage Juste pour confirmer s'il vous plaît que la même commande avec un seul changement ( verbose=FALSE ) fonctionne bien? ie fread("SA2-by-DJZ-2011.csv", verbose = FALSE, na.strings = "", header = FALSE) . La jauge de progression sera toujours affichée.

Oui, exécuter cette commande (dix fois) a renvoyé le résultat attendu (c'est-à-dire la table data.table avec seulement deux avertissements car elle est mal formatée). Aucun avertissement de déséquilibre de pile.

Merci. Cela semble donc être lié à la sortie de la console. Quelques autres choses à essayer ...

En mode verbeux, il y a des branches à l'intérieur de la région parallèle qui appellent wallclock() . J'ai court-circuité cela pour toujours renvoyer 0.0 et éviter l'appel système, pour l'exclure. Je pensais que c'était thread-safe, mais peut-être pas. Veuillez essayer le nouveau Windows.zip de la branche reconstruite ici .

Premier essai:

install.packages("https://ci.appveyor.com/api/buildjobs/o0pn9ttkrbqgqw2k/artifacts/data.table_1.10.5.zip",
                 repos = NULL)
# Installing package into ‘C:/Users/hughp/Documents/R/win-library/3.4’
# (as ‘lib’ is unspecified)
# trying URL 'https://ci.appveyor.com/api/buildjobs/o0pn9ttkrbqgqw2k/artifacts/data.table_1.10.5.zip'
# Content type 'application/octet-stream' length 1556972 bytes (1.5 MB)
# downloaded 1.5 MB
# 
# package ‘data.table’ successfully unpacked and MD5 sums checked

library(data.table)
# data.table 1.10.5 IN DEVELOPMENT built 2017-11-17 03:49:20 UTC; appveyor
# The fastest way to learn (by data.table authors): https://www.datacamp.com/courses/data-analysis-the-data-table-way
# Documentation: ?data.table, example(data.table) and browseVignettes("data.table")
# Release notes, videos and slides: http://r-datatable.com
fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "", header = FALSE)

Deuxième tentative, j'obtiens les avertissements suivants:

Read 22%. ETA 00:00 Error in fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "",  : 
  unprotect_ptr: pointer not found
In addition: Warning messages:
1: In fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "",  :
  Starting data input on line 12 <<"Goulburn","110018063",3499,>> with 4 fields and discarding line 11 <<"Main Statistical Area Structu>> before it because it has a different number of fields (3).
2: In fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "",  :
 Warning: stack imbalance in '$', 29 then 28
 Found the last consistent line but text exists afterwards. Consider fill=TRUE and/or blank.lines.skip=TRUE. First 200 characters of discarded line: <<"Dataset: 2011 Census of Population and Housing">>
Warning: stack imbalance in 'lapply', 125 then 126
Warning: stack imbalance in 'lapply', 55 then 53
Warning: stack imbalance in 'lapply', 30 then 34
Warning: stack imbalance in '<-', 28 then 31
Warning: stack imbalance in '{', 24 then 27
Warning: stack imbalance in '{', 18 then 21

Juste une pensée: cela pourrait-il être un problème avec RStudio? L'exécution du script à partir du terminal ne semble pas se reproduire aussi facilement. Je cours depuis RStudio car cela facilite la copie de la sortie de la console.

Quand vous dites qu'il ne se reproduit pas _ aussi facilement_ en dehors de RStudio, est-ce qu'il reproduit _à tout_? Même si cela ne se produit que dans RStudio, c'est toujours quelque chose que j'essaierais de corriger du côté data.table. Je demande juste comme une autre route de confirmer qu'il s'agit bien d'une sortie de console "juste" et non d'un autre véritable déséquilibre de pile dans la logique fread.

Je n'ai pas encore reproduit en dehors de RStudio, et je peux reproduire de manière fiable à l'intérieur (c'est-à-dire que je peux reproduire un avertissement ou un crash). J'ai essayé l'invite de commande Windows et le shell git (sous Windows).

J'utilise RStudio version 1.1.383 sur Windows. Cela vous serait-il utile que je soulève également cette question avec eux, ou aimeriez-vous que j'attende?

Merci. C'est vraiment utile de savoir que c'est juste à l'intérieur de RStudio. Inutile de le soulever avec eux. Cela signifie simplement que c'est quelque chose à voir avec la mise en mémoire tampon de la console de sortie (ou similaire). Je suis allé de l'avant avec un travail autour et sur le point de pousser.

Je ne vois pas pourquoi Windows ne compile pas ce changement:
fread.c:1054:3: warning: too many arguments for format [-Wformat-extra-args]
Fonctionne très bien ici sous Linux et sur Travis. Cela empêche la création de Windows.zip pour que vous puissiez tester cette solution de contournement. Je vais devoir dormir dessus.
(Il se plaint de la ligne 1054 mais pas de la toute prochaine ligne 1055 qui est exactement la même chose. Il doit y avoir une différence.% Llu un problème avec __VA_ARGS__ sous Windows - sûrement pas.)

Ok, enfin windows.zip est prêt pour que vous réessayiez ici .

Il existe actuellement plusieurs solutions de contournement dans cette branche. Si cela fonctionne, je commencerai à supprimer les solutions de contournement pour déterminer laquelle il s'agissait. Les avertissements du compilateur llu semblent les plus prometteurs car cela entraînerait un déséquilibre de la pile dans la sortie verbeuse, cohérent avec l'explication @ st-pasha trouvée ici . Peut-être que la couche Rprintf cachait cela au compilateur et il peut maintenant voir qu'il utilise directement fprintf .

À la deuxième tentative (après le redémarrage)

stopifnot(!requireNamespace("data.table", quietly = TRUE))
install.packages("https://ci.appveyor.com/api/buildjobs/1pi0ae5iuyj9rhj8/artifacts/data.table_1.10.5.zip",
                 repos = NULL)
# Installing package into ‘C:/Users/hughp/Documents/R/win-library/3.4’
# (as ‘lib’ is unspecified)
# trying URL 'https://ci.appveyor.com/api/buildjobs/1pi0ae5iuyj9rhj8/artifacts/data.table_1.10.5.zip'
# Content type 'application/octet-stream' length 1559167 bytes (1.5 MB)
# downloaded 1.5 MB
# 
# package ‘data.table’ successfully unpacked and MD5 sums checked

library(data.table)
# data.table 1.10.5 IN DEVELOPMENT built 2017-11-18 04:58:23 UTC; appveyor
# The fastest way to learn (by data.table authors): https://www.datacamp.com/courses/data-analysis-the-data-table-way
# Documentation: ?data.table, example(data.table) and browseVignettes("data.table")
# Release notes, videos and slides: http://r-datatable.com

fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "", header = FALSE)
Log file:  C:\Users\hughp\AppData\Local\Temp\RtmpIT9H0D/fread.out 
Input contains no \n. Taking this to be a filename to open
Read 11%. ETA 00:00 Warning: stack imbalance in '$', 19 then 20
Read 28%. ETA 00:00 Warning: stack imbalance in '$', 19 then 20
Read 48%. ETA 00:00 Warning: stack imbalance in '$', 20 then 19
Read 98%. ETA 00:00 [01] Check arguments
  Using 12 threads (omp_get_max_threads()=12, nth=12)
  NAstrings = [<<>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file SA2-by-DJZ-2011.csv
  File opened, size = 349.4MB (366418725 bytes).
  Memory mapped ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \n has been found in the data so any mixture of line endings is allowed other than \r-only line endings. This is common and ideal.
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Australian Bureau of Statistic>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 89 lines of 4 fields using quote rule 0
  Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 4
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to false
  Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
  Type codes (jump 000)    : 1551  Quote rule 0
  Type codes (jump 100)    : 1A51  Quote rule 0
  =====
  Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 12 to the end of last row: 366418143
  Line length: mean=16.02 sd=0.21 min=16 max=29
  Estimated number of rows: 366418143 / 16.02 = 22877178
  Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 1A51
[10] Allocate memory for the datatable
  Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:02.822 wall clock time
[12] Finalizing the datatable
  Type counts:
         1 : bool8     '1'
         1 : int32     '5'
         2 : string    'A'
=============================
   0.000s (  0%) Memory map 0.341GB file
   0.001s (  0%) sep=',' ncol=4 and header detection
   0.000s (  0%) Column type detection using 10027 sample rows
   0.291s ( 10%) Allocation of 25164895 rows x 4 cols (0.469GB) of which 22885380 ( 91%) rows used
   2.531s ( 90%) Reading 360 chunks of 0.971MB (63547 rows) using 12 threads
   =    0.002s (  0%) Finding first non-embedded \n after each jump
   +    0.282s ( 10%) Parse to row-major thread buffers (grown 0 times)
   +    1.537s ( 54%) Transpose
   +    0.710s ( 25%) Waiting
   0.842s ( 30%) Rereading 1 columns due to out-of-sample type exceptions
   2.822s        Total
Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
                V1        V2      V3 V4
       1: Goulburn 110018063    3499 NA
       2:       NA 110018064     812 NA
       3:       NA 110018065    2158 NA
       4:       NA 110019999     402 NA
       5:       NA 110028068      10 NA
      ---                              
22885376:       NA 997999799       0 NA
22885377:       NA 998999899      64 NA
22885378:       NA 994999499      34 NA
22885379:       NA 0&&&&&&&&  250796 NA
22885380:       NA 0@@@@@@@@ 7305367 NA
Warning messages:
1: In fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "",  :
  Starting data input on line 12 <<"Goulburn","110018063",3499,>> with 4 fields and discarding line 11 <<"Main Statistical Area Structu>> before it because it has a different number of fields (3).
2: In fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "",  :
  Found the last consistent line but text exists afterwards. Consider fill=TRUE and/or blank.lines.skip=TRUE. First 200 characters of discarded line: <<"Dataset: 2011 Census of Population and Housing">>

Encore une fois, non reproductible en dehors de RStudio.

Merci d'avoir testé si rapidement. Eh bien, cela exclut certainement beaucoup de choses alors! Il reste deux idées. Le premier poussé et passant. Veuillez essayer le nouveau Windows.zip ici . Ce alloca est sur la pile et a à voir avec na.strings que vous définissez au fur et à mesure. Certainement dans la bonne zone (déséquilibre de la pile) et vaut la peine d'essayer.

Pas de problème - je serai absent pour les 12 prochaines heures environ, donc je ne peux pas tester d'ici là.
Le samedi 18 novembre 2017 à 17h20, Matt Dowle [email protected] a écrit:

Merci d'avoir testé si rapidement. Eh bien, cela exclut certainement beaucoup de choses alors!
Il reste deux idées. Le premier poussé et passant. Veuillez essayer le nouveau Windows.zip
Ici
https://ci.appveyor.com/project/Rdatatable/data-table/build/1.0.1363/job/fo02vnbu5ebhwy3w/artifacts .
Cet allocation est alloué sur la pile et a à voir avec na.strings qui
vous réglez comme il se passe. Certainement dans la bonne zone (pile
déséquilibre) et vaut la peine d'être essayé.

-
Vous recevez cela parce que vous avez été mentionné.

Répondez directement à cet e-mail, affichez-le sur GitHub
https://github.com/Rdatatable/data.table/issues/2481#issuecomment-345421856 ,
ou couper le fil
https://github.com/notifications/unsubscribe-auth/AHvGDGa5Qnls5eSFBMaQO5s8DElfrpKSks5s3ncqgaJpZM4QcuPc
.

OK, pas de problème. Merci! J'ai poussé la deuxième idée maintenant aussi. Il me semble me souvenir que \r causé un problème sous Windows dans le passé, mais je ne me souviens pas d'un déséquilibre de pile. Quoi qu'il en soit, pour exclure cela, j'ai supprimé le \r de la jauge de progression. Le message de déséquilibre de pile semble être imprimé là où les lignes ETA apparaissent. Il est possible que la console attrape \r et le traite différemment afin que la dernière ligne soit remplacée. Vous devriez maintenant voir une nouvelle ligne chaque fois que l'ETA est mis à jour. Juste temporairement pour écarter cela. Nouveau Windows.zip construit et passant ici .

fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "", header = FALSE)
Log file:  C:\Users\hughp\AppData\Local\Temp\RtmpcVjZ1f/fread.out 
Input contains no \n. Taking this to be a filename to open
Read 5%. ETA 00:00
Read 8%. ETA 00:00
Read 11%. ETA 00:00
Read 15%. ETA 00:00
Read 18%. ETA 00:00
Read 21%. ETA 00:00
Read 25%. ETA 00:00
Read 28%. ETA 00:00
Read 31%. ETA 00:00
Read 35%. ETA 00:00
Read 38%. ETA 00:00
Read 41%. ETA 00:00
Read 45%. ETA 00:00
Read 48%. ETA 00:00
Read 51%. ETA 00:00
Read 55%. ETA 00:00
Warning: stack imbalance in '$', 30 then 31
Warning: stack imbalance in '$', 17 then 16
Read 58%. ETA 00:00
Read 61%. ETA 00:00
Read 65%. ETA 00:00
Read 68%. ETA 00:00
Read 71%. ETA 00:00
Read 75%. ETA 00:00
Read 78%. ETA 00:00
Read 81%. ETA 00:00
Read 85%. ETA 00:00
Read 88%. ETA 00:00
Read 91%. ETA 00:00
Read 95%. ETA 00:00
Read 98%. ETA 00:00
[01] Check arguments
  Using 12 threads (omp_get_max_threads()=12, nth=12)
  NAstrings = [<<>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file SA2-by-DJZ-2011.csv
  File opened, size = 349.4MB (366418725 bytes).
  Memory mapped ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \n has been found in the data so any mixture of line endings is allowed other than \r-only line endings. This is common and ideal.
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Australian Bureau of Statistic>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 89 lines of 4 fields using quote rule 0
  Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 4
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to false
  Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
  Type codes (jump 000)    : 1551  Quote rule 0
  Type codes (jump 100)    : 1A51  Quote rule 0
  =====
  Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 12 to the end of last row: 366418143
  Line length: mean=16.02 sd=0.21 min=16 max=29
  Estimated number of rows: 366418143 / 16.02 = 22877178
  Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 1A51
[10] Allocate memory for the datatable
  Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:02.894 wall clock time
[12] Finalizing the datatable
  Type counts:
         1 : bool8     '1'
         1 : int32     '5'
         2 : string    'A'
=============================
   0.001s (  0%) Memory map 0.341GB file
   0.003s (  0%) sep=',' ncol=4 and header detection
   0.000s (  0%) Column type detection using 10027 sample rows
   0.316s ( 11%) Allocation of 25164895 rows x 4 cols (0.469GB) of which 22885380 ( 91%) rows used
   2.574s ( 89%) Reading 360 chunks of 0.971MB (63547 rows) using 12 threads
   =    0.004s (  0%) Finding first non-embedded \n after each jump
   +    0.284s ( 10%) Parse to row-major thread buffers (grown 0 times)
   +    1.450s ( 50%) Transpose
   +    0.837s ( 29%) Waiting
   0.953s ( 33%) Rereading 1 columns due to out-of-sample type exceptions
   2.894s        Total
Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
                V1        V2      V3 V4
       1: Goulburn 110018063    3499 NA
       2:       NA 110018064     812 NA
       3:       NA 110018065    2158 NA
       4:       NA 110019999     402 NA
       5:       NA 110028068      10 NA
      ---                              
22885376:       NA 997999799       0 NA
22885377:       NA 998999899      64 NA
22885378:       NA 994999499      34 NA
22885379:       NA 0&&&&&&&&  250796 NA
22885380:       NA 0@@@@@@@@ 7305367 NA
Warning messages:
1: In fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "",  :
  Starting data input on line 12 <<"Goulburn","110018063",3499,>> with 4 fields and discarding line 11 <<"Main Statistical Area Structu>> before it because it has a different number of fields (3).
2: In fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "",  :
  Found the last consistent line but text exists afterwards. Consider fill=TRUE and/or blank.lines.skip=TRUE. First 200 characters of discarded line: <<"Dataset: 2011 Census of Population and Housing">>

FYI: Je n'ai pas pu reproduire cette erreur de déséquilibre de pile sur une autre machine Windows avec une version légèrement plus ancienne de RStudio.

Dans ce cas, il semble qu'il soit temps de demander l'assistance RStudio comme vous l'avez suggéré, alors s'il vous plaît. J'ai revu le code fread et je suis à court d'idées de mon côté. Veuillez leur indiquer les deux numéros de version de RStudio. Cela ne signifie pas nécessairement que c'est RStudio, cela pourrait être une faute du côté de data.table qui se trouve juste sur une version de RStudio. Mais il est étrange que cela semble lié à la sortie de la console et que ce soit quelque chose de différent et spécifique à RStudio. J'ai recherché "RStudio stack imabalance" mais beaucoup de problèmes surviennent à propos des défauts de paquets, pas RStudio en soi. Problème difficile à rechercher. Gardons la question ouverte ici et voyons ce qu'ils disent.

Je doute que cette dernière tentative vous aidera, mais pour être complet, veuillez essayer ici . Peut-être que le compilateur MinGW qui est utilisé sur Windows fait quelque chose d'étrange avec ces deux entiers. L'un d'eux est la constante 0 qui est peut-être optimisée et provoque alors un déséquilibre de la pile.

Cependant, ce message de déséquilibre de pile particulier provient de eval.c: 491 dans R lui-même. Certains threads doivent exécuter cette ligne mais je ne pense pas que ce soit fread ou data.table . Ce check_stack_balance() n'est appelé qu'à partir de 5 endroits dans R internes:
en names.c à la fin de do_internal()
en objects.c , deux fois en applyMethod()
en eval.c , deux fois en eval()
Je ne vois pas comment l'un d'entre eux peut être atteint alors que fread.c est dans sa section parallèle. Le seul point d'entrée appelé est REprintf et je ne vois pas comment cela pourrait atteindre check_stack_balance() . Tout ce que je peux penser actuellement, c'est que RStudio a un thread qui fait quelque chose en arrière-plan qui interagit peut-être avec la sortie de la console, peut-être différemment sous Windows.
Enfin, pour être complet, il semble que l'utilisation de REprintf soit la bonne voie à suivre car la base R l'utilise (plutôt que Rprintf) dans son indicateur de progression dans libcurl.c: 354 et internet.c: 409 . C'est dommage que la barre de progression de R au niveau C ne soit pas disponible dans l'API de R (elle semble également être implémentée deux fois en R au niveau C).

@mattdowle , cela serait-il utile? https://github.com/r-lib/progress

@aader Oui - merci! Sa source contient ce commentaire :
// In R Studio we should print to stdout, because printing a \r
// to stderr is buggy (reported)
Mais j'ai déjà supprimé le \r et le déséquilibre de la pile se produit toujours. Je me demande où cela a été signalé.

Peut être ça?

https://support.rstudio.com/hc/en-us/community/posts/203136268-Carriage-return-does-not-work-on-stderr-

La dernière version n'a pas non plus fonctionné:

Rapporté à https://community.rstudio.com/t/stack-imbalance-possably-in-stderr/3009

Question opportune sur R-devel: [Rd] Rprintf et REprintf sont-ils thread-safe?

Upshot "Rprintf et REprintf ne sont pas thread-safe."

Yoiks!

Merci à tous pour les liens et Hugh pour avoir soulevé le problème avec RStudio.

data.table::fwrite() et data.table::fread() sont conscients que Rprintf et REprintf ne sont pas thread-safe donc pour leurs compteurs de progression, ils les appellent uniquement à partir du thread maître. Non seulement deux threads data.table n'appellent jamais ce point d'entrée R en même temps, mais seul le thread maître l'appelle également, et c'est le seul point d'entrée R appelé par l'un des threads à tout moment pendant le section parallèle. Cependant, Rprintf appelle R_CheckUserInterrupt toutes les 100 impressions. Je pense que c'est la partie qui n'est probablement pas à l'abri même du fil maître. C'est la raison pour laquelle vous utilisez maintenant REprintf car cela n'appelle pas R_CheckUserInterrupt . Les internes R utilisent REprintf pour les compteurs de progression, donc passer à REprintf pour la cohérence avec le noyau R est logique; c'est-à-dire que ce choix n'a rien à voir avec stderr vs stdout, en soi.

@kevinushey pourrais-tu jeter un œil à ce fil et me dire tout ce que je peux essayer? Cela pourrait-il être lié à RStudio, d'une manière ou d'une autre, peut-être lié à un fil d'arrière-plan? Si RStudio a un thread d'arrière-plan, il se peut que Rprintf / REprintf puisse être appelé à partir de deux threads en même temps. Mais si tel avait été le cas, nous aurions déjà vu beaucoup plus de problèmes. Cela semble donc très improbable. Peut-être que RStudio remplace les rappels ptr_* mentionnés dans la section 8.1.2 de R-exts - ceux-ci sont liés à la sortie et à l'interaction de la console. Cependant, cette section commence par "For unix-alikes", donc je ne sais pas comment Windows entre en jeu. Peut-être que les problèmes de threads de la section

Je vais sortir jusqu'au début du mois de décembre, donc je n'aurai malheureusement pas l'occasion de jeter un coup d'œil d'ici là. Cependant, RStudio exécute presque tout sur le thread principal en utilisant la boucle d'événements R; les seules exceptions sont, par exemple, pour l'indexation de fichiers au niveau du projet et ces threads d'arrière-plan ne touchent généralement aucune API R.

RStudio prend en charge les divers callbacks ptr_* pour gérer l'entrée et la sortie de la console; Je ne peux pas penser immédiatement à la façon dont ils pourraient être une cause ici, mais j'essaierai de regarder de plus près quand je serai de retour.

Ok, veuillez essayer celui-ci ici . Avant, il mettait à jour l'état d'avancement tous les 2%. Dans votre cas, votre fichier ne prend qu'un peu moins de 3 secondes, il s'agissait donc d'une nouvelle mise à jour de progression de la console RStudio toutes les 0,06 secondes. Peut-être que c'était trop pour RStudio. Donc, cette tentative imprime une barre. Il n'utilise pas du tout \r . Cela devrait être mieux pour les rapports et les fichiers journaux où le \r pourrait remplir la sortie.

Étant donné que votre minutage de 3 secondes est assez rapide, j'ai réduit la barre de progression pour commencer à 1 seconde s'il y a un ETA de 1 seconde à partir de là. Sinon, il ne s'afficherait pas du tout et ne fonctionnerait pas pour votre fichier simplement parce qu'il n'était pas affiché. Après avoir testé, je passerai à ce que fwrite a; c'est-à-dire commencer à 2 secondes si ETA est à 2 secondes de là.

Bonjour, @mattdowle. Mon dernier commentaire dans # 2503 peut également être lié à ce problème.

Cela semble bon! Aucun avertissement (après 5 courses). Exécutez d'abord ci-dessous (notez que les espaces de début sont différents dans la sortie réelle):

stopifnot(!requireNamespace("data.table", quietly = TRUE))
install.packages("https://ci.appveyor.com/api/buildjobs/1o9s06o31v8i3ljr/artifacts/data.table_1.10.5.zip",
                 repos = NULL)
# Installing package into ‘C:/Users/hughp/Documents/R/win-library/3.4’
# (as ‘lib’ is unspecified)
# trying URL 'https://ci.appveyor.com/api/buildjobs/1o9s06o31v8i3ljr/artifacts/data.table_1.10.5.zip'
# Content type 'application/octet-stream' length 1557423 bytes (1.5 MB)
# downloaded 1.5 MB
# 
# package ‘data.table’ successfully unpacked and MD5 sums checked

library(data.table)
# data.table 1.10.5 IN DEVELOPMENT built 2017-11-30 00:21:00 UTC; appveyor
# The fastest way to learn (by data.table authors): https://www.datacamp.com/courses/data-analysis-the-data-table-way
# Documentation: ?data.table, example(data.table) and browseVignettes("data.table")
# Release notes, videos and slides: http://r-datatable.com
setwd("~/ABS-data/inbox/SA2-by-DJZ-2011/")
fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "", header = FALSE)
# Input contains no \n. Taking this to be a filename to open
# [01] Check arguments
# Using 12 threads (omp_get_max_threads()=12, nth=12)
# NAstrings = [<<>>]
# None of the NAstrings look like numbers.
# show progress = 1
# 0/1 column will be read as boolean
# [02] Opening the file
# Opening file SA2-by-DJZ-2011.csv
# File opened, size = 349.4MB (366418725 bytes).
# Memory mapped ok
# [03] Detect and skip BOM
# [04] Arrange mmap to be \0 terminated
# \n has been found in the data so any mixture of line endings is allowed other than \r-only line endings. This is common and ideal.
# [05] Skipping initial rows if needed
# Positioned on line 1 starting: <<Australian Bureau of Statistic>>
#   [06] Detect separator, quoting rule, and ncolumns
# Detecting sep ...
# sep=','  with 89 lines of 4 fields using quote rule 0
# Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
#   Quote rule picked = 0
# fill=false and the most number of columns found is 4
# [07] Detect column types, good nrow estimate and whether first row is column names
# 'header' changed by user from 'auto' to false
# Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
# Type codes (jump 000)    : 1551  Quote rule 0
# Type codes (jump 100)    : 1A51  Quote rule 0
# =====
#   Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
# Bytes from first data row on line 12 to the end of last row: 366418143
# Line length: mean=16.02 sd=0.21 min=16 max=29
# Estimated number of rows: 366418143 / 16.02 = 22877178
# Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
# =====
#   [08] Assign column names
# [09] Apply user overrides on column types
# After 0 type and 0 drop user overrides : 1A51
# [10] Allocate memory for the datatable
# Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
# [11] Read the data
# jumps=[0..360), chunk_size=1017828, total_size=366418143
# jumps=[0..360), chunk_size=1017828, total_size=366418143
# |--------------------------------------------------|
#   |==================================================|
#   Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:02.280 wall clock time
# [12] Finalizing the datatable
# Type counts:
#   1 : bool8     '1'
# 1 : int32     '5'
# 2 : string    'A'
# =============================
#   0.005s (  0%) Memory map 0.341GB file
# 0.037s (  2%) sep=',' ncol=4 and header detection
# 0.000s (  0%) Column type detection using 10027 sample rows
# 0.321s ( 14%) Allocation of 25164895 rows x 4 cols (0.469GB) of which 22885380 ( 91%) rows used
# 1.917s ( 84%) Reading 360 chunks of 0.971MB (63547 rows) using 12 threads
# =    0.011s (  0%) Finding first non-embedded \n after each jump
# +    0.560s ( 25%) Parse to row-major thread buffers (grown 0 times)
# +    0.488s ( 21%) Transpose
# +    0.858s ( 38%) Waiting
# 0.999s ( 44%) Rereading 1 columns due to out-of-sample type exceptions
# 2.280s        Total
# Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
# V1        V2      V3 V4
# 1: Goulburn 110018063    3499 NA
# 2:       NA 110018064     812 NA
# 3:       NA 110018065    2158 NA
# 4:       NA 110019999     402 NA
# 5:       NA 110028068      10 NA
# ---                              
#   22885376:       NA 997999799       0 NA
# 22885377:       NA 998999899      64 NA
# 22885378:       NA 994999499      34 NA
# 22885379:       NA 0&&&&&&&&  250796 NA
# 22885380:       NA 0@@@@@@@@ 7305367 NA
# Warning messages:
#   1: In fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "",  :
#                 Starting data input on line 12 <<"Goulburn","110018063",3499,>> with 4 fields and discarding line 11 <<"Main Statistical Area Structu>> before it because it has a different number of fields (3).
#               2: In fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "",  :
#               Found the last consistent line but text exists afterwards. Consider fill=TRUE and/or blank.lines.skip=TRUE. First 200 characters of discarded line: <<"Dataset: 2011 Census of Population and Housing">>

@HughParsonage Relief! Je pense que c'est une victoire alors. Je vais ranger, fusionner et passer à autre chose. Un grand merci à vous pour les tests.

@aadler Oui a convenu que votre commentaire dans le numéro 2503 est identique. Pourriez-vous également tester la dernière version de dev et confirmer qu'elle est maintenant corrigée? En espérant que le problème avec as.IDate vous avez trouvé a effectivement été causé par le déséquilibre de pile antérieur.

Pas bien :(

> library(data.table)
data.table 1.10.5 IN DEVELOPMENT built 2017-11-30 00:21:00 UTC; appveyor
  The fastest way to learn (by data.table authors): https://www.datacamp.com/courses/data-analysis-the-data-table-way
  Documentation: ?data.table, example(data.table) and browseVignettes("data.table")
  Release notes, videos and slides: http://r-datatable.com
> sessionInfo()
R version 3.4.2 beta (2017-09-17 r73296)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows Server >= 2012 x64 (build 9200)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                           LC_TIME=English_United States.1252    

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

other attached packages:
[1] data.table_1.10.5

loaded via a namespace (and not attached):
[1] compiler_3.4.2 tools_3.4.2   
> DT <- fread('2017-11-22_1999_Performance.csv', header = TRUE, colClasses = CLS, select = SEL, key = c('LoanID', 'Month'), verbose = TRUE)
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 40 threads (omp_get_max_threads()=40, nth=40)
  NAstrings = [<<NA>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file 2017-11-22_1999_Performance.csv
  File opened, size = 6.355GB (6823372783 bytes).
  Memory mapped ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \n has been found in the data so any mixture of line endings is allowed other than \r-only line endings. This is common and ideal.
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Orig_Year,Orig_Qtr,LoanID,Mont>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 100 lines of 37 fields using quote rule 0
  Detected 37 columns on line 1. This line is either column names or first data row. Line starts as: <<Orig_Year,Orig_Qtr,LoanID,Mont>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 37
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to true
  Number of sampling jump points = 101 because (6823372781 bytes from row 1 to eof) / (2 * 12905 jump0size) == 264369
  Type codes (jump 000)    : 51AA7155A15A7111111111111771111177715  Quote rule 0
  Type codes (jump 001)    : 51AA7155A15A711111111111177111117771A  Quote rule 0
  Type codes (jump 008)    : 51AA7555A15A711111111111177111117771A  Quote rule 0
  Type codes (jump 009)    : 51AA7555AA5A71A155555557177111117775A  Quote rule 0
  Type codes (jump 042)    : 55AA7555AA5A71A155555557177111117775A  Quote rule 0
  Type codes (jump 064)    : 55AA7555AA5A71A1A5555557177111117775A  Quote rule 0
  Type codes (jump 100)    : 55AA7555AA5A71A1A5555557177111117775A  Quote rule 0
  =====
  Sampled 10049 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 1 to the end of last row: 6823372781
  Line length: mean=126.15 sd=8.30 min=100 max=359
  Estimated number of rows: 6823372781 / 126.15 = 54088821
  Initial alloc = 62279495 rows (54088821 + 15%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 4 type and 23 drop user overrides : 00AA700000000000000000070775555077750
[10] Allocate memory for the datatable
  Allocating 14 column slots (37 - 23 dropped) with 62279495 rows
[11] Read the data
  jumps=[0..6520), chunk_size=1046529, total_size=6823372422
|--------------------------------------------------|
|=======Warning: stack imbalance in '$', 27 then 26
===Warning: stack imbalance in '$', 26 then 27
================Error in fread("2017-11-22_1999_Performance.csv", header = TRUE, colClasses = CLS,  : 
  unprotect_ptr: pointer not found

@aadler Merci pour ce rapport. Je suis passé par freadR et j'ai localisé la protection. Il y a 30% de chances que cela fonctionne puisque dans votre cas, vous remplacez les types et il y avait pas mal de protections dans cette partie du code. Veuillez réessayer en utilisant cette version .

@aadler Si vous n'avez pas encore essayé la dernière version, veuillez directement essayer celle-ci . De plus, s'il est possible de me faire parvenir une copie de votre fichier, je pourrais peut-être essayer moi-même sur Windows RStudio.

:(

> library(data.table)
data.table 1.10.5 IN DEVELOPMENT built 2017-12-01 01:54:04 UTC; appveyor
  The fastest way to learn (by data.table authors): https://www.datacamp.com/courses/data-analysis-the-data-table-way
  Documentation: ?data.table, example(data.table) and browseVignettes("data.table")
  Release notes, videos and slides: http://r-datatable.com
> sessionInfo()
R version 3.4.2 beta (2017-09-17 r73296)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows Server >= 2012 x64 (build 9200)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                           LC_TIME=English_United States.1252    

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

other attached packages:
[1] data.table_1.10.5

loaded via a namespace (and not attached):
[1] compiler_3.4.2 tools_3.4.2   
> ColCLASS <- c(rep('integer', 2L), 'character', 'Date', 'numeric',
+               rep('integer', 3L), rep('character', 2L),
+               'integer', 'Date', rep('numeric', 2L), 'Date',
+               rep('numeric', 12L), rep('integer', 5),
+               rep('numeric', 3L), 'integer', 'character')
> SELCOL <- c(WHATEVER)
> DT <- fread('LargeFile.csv', header = TRUE, colClasses = ColCLASS, select = SELCOL, key = c('LoanID', 'Month'), verbose = TRUE)
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 40 threads (omp_get_max_threads()=40, nth=40)
  NAstrings = [<<NA>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file LargeFile.csv
  File opened, size = 6.355GB (6823372783 bytes).
  Memory mapped ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \n has been found in the data so any mixture of line endings is allowed other than \r-only line endings. This is common and ideal.
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Orig_Year,Orig_Qtr,LoanID,Mont>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 100 lines of 37 fields using quote rule 0
  Detected 37 columns on line 1. This line is either column names or first data row. Line starts as: <<Orig_Year,Orig_Qtr,LoanID,Mont>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 37
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to true
  Number of sampling jump points = 101 because (6823372781 bytes from row 1 to eof) / (2 * 12905 jump0size) == 264369
  Type codes (jump 000)    : 51AA7155A15A7111111111111771111177715  Quote rule 0
  Type codes (jump 001)    : 51AA7155A15A711111111111177111117771A  Quote rule 0
  Type codes (jump 008)    : 51AA7555A15A711111111111177111117771A  Quote rule 0
  Type codes (jump 009)    : 51AA7555AA5A71A155555557177111117775A  Quote rule 0
  Type codes (jump 042)    : 55AA7555AA5A71A155555557177111117775A  Quote rule 0
  Type codes (jump 064)    : 55AA7555AA5A71A1A5555557177111117775A  Quote rule 0
  Type codes (jump 100)    : 55AA7555AA5A71A1A5555557177111117775A  Quote rule 0
  =====
  Sampled 10049 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 1 to the end of last row: 6823372781
  Line length: mean=126.15 sd=8.30 min=100 max=359
  Estimated number of rows: 6823372781 / 126.15 = 54088821
  Initial alloc = 62279495 rows (54088821 + 15%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 4 type and 23 drop user overrides : 00AA700000000000000000070775555077750
[10] Allocate memory for the datatable
  Allocating 14 column slots (37 - 23 dropped) with 62279495 rows
[11] Read the data
  jumps=[0..6520), chunk_size=1046529, total_size=6823372422
|--------------------------------------------------|
|Error in fread("LargeFile.csv", header = TRUE, colClasses = ColCLASS,  : 
  unprotect_ptr: pointer not found

Grâce à @aadler sur email, je peux désormais reproduire. R 3.4.2, dernier RStudio 1.1.383 et Windows 10 Pro 10.0.16299 Build 16299.

Je vois un comportement étrange dans RStudio, enregistré ici:
https://www.youtube.com/watch?v=tl2x2vmZxMU
Il semble que RStudio génère des GC simplement en tapant. Pourquoi est-ce et est-il possible de le désactiver? Il se peut que lorsque fread() imprime sa barre de progression, la boucle d'événements séparée de RStudio pense que la sortie vers la console est l'utilisateur qui tape et appelle R ce qui donne naissance au GC et déclenche tout? Peut-être que les utilisateurs de RStudio ici le savent, pourraient me diriger dans la bonne direction, ou peut-être

Je peux reproduire le déséquilibre de la pile de manière fiable dans la console RStudio. En utilisant l'onglet Terminal RStudio, je ne peux pas du tout le reproduire, même avec gcinfo(TRUE) . Il est intéressant de noter que les GC se produisent lorsque la barre de progression s'imprime et cela semble correct, car cela convient également à Linux. Compte tenu du comportement de cette vidéo de la console RStudio, j'arrive à la conclusion qu'il s'agit d'un bogue de la console RStudio. Je n'ai pas pu copier le texte de la fenêtre du terminal RStudio (Edition-> Copier ne fonctionne pas et Ctrl-C non plus), j'ai donc pris une capture d'écran de l'onglet Terminal pour montrer que GC pendant la barre de progression est ok. Je m'attendrais à ce que ce soit correct car seul le thread principal appelle REprintf et les autres threads n'appellent aucune API R du tout.

Fonctionne bien dans RStudio Terminal:

Notez qu'il y a des GC pendant que la barre de progression est imprimée la première fois et cela fonctionne très bien dans RStudio Terminal. La barre de progression s'imprime une deuxième fois car il y a une exception de type hors échantillon dans ce fichier de test qui déclenche une relecture automatique pour ces colonnes uniquement.

Mais dans RStudio Console, il y a soit stack imbalance ou unprotect_ptr: pointer not found :

R version 3.4.2 (2017-09-28) -- "Short Summer"
> gcinfo(TRUE)
[1] FALSE
Garbage collection 22 = 16+3+3 (level 0) ... 
25.5 Mbytes of cons cells used (80%)
6.6 Mbytes of vectors used (66%)
Garbage collection 23 = 16+4+3 (level 1) ... 
24.9 Mbytes of cons cells used (79%)
6.5 Mbytes of vectors used (64%)
Garbage collection 24 = 17+4+3 (level 0) ... 
25.1 Mbytes of cons cells used (79%)
6.5 Mbytes of vectors used (64%)
Garbage collection 25 = 18+4+3 (level 0) ... 
25.1 Mbytes of cons cells used (79%)
6.5 Mbytes of vectors used (64%)
Garbage collection 26 = 19+4+3 (level 0) ... 
25.1 Mbytes of cons cells used (79%)
6.5 Mbytes of vectors used (65%)
Garbage collection 27 = 20+4+3 (level 0) ... 
25.2 Mbytes of cons cells used (80%)
6.5 Mbytes of vectors used (65%)
Garbage collection 28 = 20+5+3 (level 1) ... 
25.1 Mbytes of cons cells used (79%)
6.5 Mbytes of vectors used (65%)
Garbage collection 29 = 21+5+3 (level 0) ... 
25.1 Mbytes of cons cells used (79%)
6.5 Mbytes of vectors used (65%)
Garbage collection 30 = 22+5+3 (level 0) ... 
25.2 Mbytes of cons cells used (80%)
6.5 Mbytes of vectors used (65%)
Garbage collection 31 = 23+5+3 (level 0) ... 
25.2 Mbytes of cons cells used (80%)
6.6 Mbytes of vectors used (66%)
Garbage collection 32 = 24+5+3 (level 0) ... 
25.3 Mbytes of cons cells used (80%)
6.6 Mbytes of vectors used (66%)
Garbage collection 33 = 25+5+3 (level 0) ... 
25.4 Mbytes of cons cells used (80%)
6.7 Mbytes of vectors used (66%)
Garbage collection 34 = 25+5+4 (level 2) ... 
24.6 Mbytes of cons cells used (61%)
6.4 Mbytes of vectors used (50%)
Garbage collection 35 = 26+5+4 (level 0) ... 
25.0 Mbytes of cons cells used (62%)
6.5 Mbytes of vectors used (52%)
> require(data.table)
Loading required package: data.table
Garbage collection 36 = 27+5+4 (level 0) ... 
27.2 Mbytes of cons cells used (68%)
7.1 Mbytes of vectors used (56%)
data.table 1.10.5 IN DEVELOPMENT built 2017-12-02 01:04:34 UTC; appveyor
  The fastest way to learn (by data.table authors): https://www.datacamp.com/courses/data-analysis-the-data-table-way
  Documentation: ?data.table, example(data.table) and browseVignettes("data.table")
  Release notes, videos and slides: http://r-datatable.com
Garbage collection 37 = 28+5+4 (level 0) ... 
27.7 Mbytes of cons cells used (69%)
7.3 Mbytes of vectors used (58%)
Garbage collection 38 = 29+5+4 (level 0) ... 
28.0 Mbytes of cons cells used (70%)
7.4 Mbytes of vectors used (58%)
Garbage collection 39 = 30+5+4 (level 0) ... 
28.1 Mbytes of cons cells used (70%)
7.4 Mbytes of vectors used (59%)
Garbage collection 40 = 31+5+4 (level 0) ... 
28.2 Mbytes of cons cells used (70%)
7.5 Mbytes of vectors used (59%)
Garbage collection 41 = 32+5+4 (level 0) ... 
28.4 Mbytes of cons cells used (71%)
7.5 Mbytes of vectors used (59%)
> DT = fread("/Users/pasha/Downloads/LargeFile.csv")
Garbage collection 42 = 32+5+5 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
7.1 Mbytes of vectors used (2%)
Garbage collection 43 = 32+5+6 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
244.7 Mbytes of vectors used (42%)
Garbage collection 44 = 32+5+7 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
482.3 Mbytes of vectors used (42%)
Garbage collection 45 = 32+5+8 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
957.4 Mbytes of vectors used (56%)
Garbage collection 46 = 32+5+9 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
1432.6 Mbytes of vectors used (63%)
Garbage collection 47 = 32+5+10 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
2145.3 Mbytes of vectors used (75%)
Garbage collection 48 = 32+5+11 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
2620.4 Mbytes of vectors used (71%)
Garbage collection 49 = 32+5+12 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
3570.8 Mbytes of vectors used (78%)
Garbage collection 50 = 32+5+13 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
4283.5 Mbytes of vectors used (75%)
Garbage collection 51 = 32+5+14 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
5709.0 Mbytes of vectors used (77%)
Garbage collection 52 = 32+5+15 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
7372.0 Mbytes of vectors used (81%)
Garbage collection 53 = 32+5+16 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
8797.5 Mbytes of vectors used (79%)
Garbage collection 54 = 32+5+17 (level 2) ... 
27.4 Mbytes of cons cells used (54%)
10935.7 Mbytes of vectors used (80%)
|--------------------------------------------------|
|=====Error in fread("LargeFile.csv") : 
  unprotect_ptr: pointer not found
> 

showProgress=FALSE résout de manière fiable dans RStudio Console. Pour se reproduire, il doit être la toute première exécution dans une nouvelle console RStudio avec showProgress=TRUE (c'est-à-dire par défaut). Semble lié à savoir s'il y a un GC pendant la mesure de progression; il y a dans la première course dans une nouvelle session. Il doit simplement s'agir d'un fichier volumineux pour que l'indicateur de progression s'affiche. Rien à voir avec la relecture ou les arguments passés à fread . Si la première exécution dans une nouvelle console RStudio est avec showProgress=FALSE pour le faire fonctionner, cette exécution étend le tas de R, puis une exécution suivante dans la même session avec showProgress=TRUE également. Mais juste parce qu'il n'y a pas de GC pendant la mesure de progression en raison de la première exécution qui étend déjà le tas.
Pourquoi un GC sur le thread maître pendant la jauge de progression est correct sous Linux et dans Windows RStudio Terminal mais pas dans RStudio Console est la question en suspens.

Ok, cela corrige le problème. Le problème était du côté data.table et non de RStudio. Fonctionne maintenant pour moi de manière fiable dans RStudio Console sous Windows. C'était un problème qui pouvait se produire sur Linux et Max aussi, c'est juste que les modèles de mémoire ne le déclenchaient pas. Les autres threads avaient un point d'entrée vers R (en poussant leurs tampons avec des colonnes de chaînes) qui pouvait se produire en même temps que la progression de l'impression du thread principal en utilisant REprintf . C'est pourquoi cela ne s'est produit que lors de la première exécution d'une nouvelle session. Lors de la deuxième exécution, toutes les chaînes du fichier avaient déjà été vues, de sorte que les recherches dans le cache frappaient (thread-safe) et non l'allocation (pas thread-safe).

Alors, @aadler et @HughParsonage , veuillez essayer celui-ci . 95% de chance que cela fonctionne maintenant!

Aucun avertissement, je ne sais pas si vous cherchez autre chose:

> gcinfo(TRUE)
[1] FALSE
> fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "", header = FALSE)
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 12 threads (omp_get_max_threads()=12, nth=12)
  NAstrings = [<<>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file SA2-by-DJZ-2011.csv
  File opened, size = 349.4MB (366418725 bytes).
  Memory mapped ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \n has been found in the data so any mixture of line endings is allowed other than \r-only line endings. This is common and ideal.
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Australian Bureau of Statistic>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 89 lines of 4 fields using quote rule 0
  Detected 4 columns on line 12. This line is either column names or first data row. Line starts as: <<"Goulburn","110018063",3499,>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 4
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to false
  Number of sampling jump points = 101 because (366418375 bytes from row 1 to eof) / (2 * 1457 jump0size) == 125744
  Type codes (jump 000)    : 1551  Quote rule 0
  Type codes (jump 100)    : 1A51  Quote rule 0
  =====
  Sampled 10027 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 12 to the end of last row: 366418143
  Line length: mean=16.02 sd=0.21 min=16 max=29
  Estimated number of rows: 366418143 / 16.02 = 22877178
  Initial alloc = 25164895 rows (22877178 + 9%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 0 type and 0 drop user overrides : 1A51
[10] Allocate memory for the datatable
  Allocating 4 column slots (4 - 0 dropped) with 25164895 rows
Garbage collection 53 = 36+5+12 (level 2) ... 
30.3 Mbytes of cons cells used (60%)
7.9 Mbytes of vectors used (1%)
[11] Read the data
  jumps=[0..360), chunk_size=1017828, total_size=366418143
|--------------------------------------------------|
|==================================================|
Garbage collection 54 = 37+5+12 (level 0) ... 
30.8 Mbytes of cons cells used (61%)
566.6 Mbytes of vectors used (74%)
Garbage collection 55 = 37+6+12 (level 1) ... 
30.8 Mbytes of cons cells used (61%)
549.2 Mbytes of vectors used (72%)
  jumps=[0..360), chunk_size=1017828, total_size=366418143
|--------------------------------------------------|
|==================================================|
Read 22885380 rows x 4 columns from 349.4MB (366418725 bytes) file in 00:02.626 wall clock time
[12] Finalizing the datatable
  Type counts:
         1 : bool8     '1'
         1 : int32     '5'
         2 : string    'A'
=============================
   0.002s (  0%) Memory map 0.341GB file
   0.005s (  0%) sep=',' ncol=4 and header detection
   0.000s (  0%) Column type detection using 10027 sample rows
   0.469s ( 18%) Allocation of 25164895 rows x 4 cols (0.469GB) of which 22885380 ( 91%) rows used
   2.150s ( 82%) Reading 360 chunks of 0.971MB (63547 rows) using 12 threads
   =    0.103s (  4%) Finding first non-embedded \n after each jump
   +    0.230s (  9%) Parse to row-major thread buffers (grown 0 times)
   +    0.718s ( 27%) Transpose
   +    1.099s ( 42%) Waiting
   0.745s ( 28%) Rereading 1 columns due to out-of-sample type exceptions
   2.626s        Total
Column 1 ("") bumped from 'bool8' to 'string' due to <<"Goulburn">> on row 0
Garbage collection 56 = 37+6+13 (level 2) ... 
31.1 Mbytes of cons cells used (62%)
531.9 Mbytes of vectors used (70%)
Garbage collection 57 = 38+6+13 (level 0) ... 
31.1 Mbytes of cons cells used (62%)
532.0 Mbytes of vectors used (70%)
                V1        V2      V3 V4
       1: Goulburn 110018063    3499 NA
       2:       NA 110018064     812 NA
       3:       NA 110018065    2158 NA
       4:       NA 110019999     402 NA
       5:       NA 110028068      10 NA
      ---                              
22885376:       NA 997999799       0 NA
22885377:       NA 998999899      64 NA
22885378:       NA 994999499      34 NA
22885379:       NA 0&&&&&&&&  250796 NA
22885380:       NA 0@@@@@@@@ 7305367 NA
Warning messages:
1: In fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "",  :
  Starting data input on line 12 <<"Goulburn","110018063",3499,>> with 4 fields and discarding line 11 <<"Main Statistical Area Structu>> before it because it has a different number of fields (3).
2: In fread("SA2-by-DJZ-2011.csv", verbose = TRUE, na.strings = "",  :
  Found the last consistent line but text exists afterwards. Consider fill=TRUE and/or blank.lines.skip=TRUE. First 200 characters of discarded line: <<"Dataset: 2011 Census of Population and Housing">>

Merci Hugh. Oui, c'est une exécution propre, en supposant que c'était dans une nouvelle session de console RStudio. Aucun signe de déséquilibre de la pile ou de messages "Unprotect_ptr: pointer not found", et la jauge de progression fonctionne correctement (deux fois dans ce cas car il y a une relecture). Maintenant, juste @aadler pour confirmer.

SUCCÈS.

Première exécution, nouvelle instance de RStudio.

> library(data.table)
data.table 1.10.5 IN DEVELOPMENT built 2017-12-02 12:05:42 UTC; appveyor
  The fastest way to learn (by data.table authors): https://www.datacamp.com/courses/data-analysis-the-data-table-way
  Documentation: ?data.table, example(data.table) and browseVignettes("data.table")
  Release notes, videos and slides: http://r-datatable.com
> sessionInfo()
R version 3.4.2 beta (2017-09-17 r73296)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows Server >= 2012 x64 (build 9200)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                           LC_TIME=English_United States.1252    

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

other attached packages:
[1] data.table_1.10.5

loaded via a namespace (and not attached):
[1] compiler_3.4.2 tools_3.4.2   
> DT <- fread('LargeFile.csv', colClasses = colCLASS, select = colSEL, header = TRUE, key = c('LoanID', 'Month'), verbose = TRUE)
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 40 threads (omp_get_max_threads()=40, nth=40)
  NAstrings = [<<NA>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file LargeFile.csv
  File opened, size = 6.355GB (6823372783 bytes).
  Memory mapped ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \n has been found in the data so any mixture of line endings is allowed other than \r-only line endings. This is common and ideal.
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Orig_Year,Orig_Qtr,LoanID,Mont>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 100 lines of 37 fields using quote rule 0
  Detected 37 columns on line 1. This line is either column names or first data row. Line starts as: <<Orig_Year,Orig_Qtr,LoanID,Mont>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 37
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to true
  Number of sampling jump points = 101 because (6823372781 bytes from row 1 to eof) / (2 * 12905 jump0size) == 264369
  Type codes (jump 000)    : 51AA7155A15A7111111111111771111177715  Quote rule 0
  Type codes (jump 001)    : 51AA7155A15A711111111111177111117771A  Quote rule 0
  Type codes (jump 008)    : 51AA7555A15A711111111111177111117771A  Quote rule 0
  Type codes (jump 009)    : 51AA7555AA5A71A155555557177111117775A  Quote rule 0
  Type codes (jump 042)    : 55AA7555AA5A71A155555557177111117775A  Quote rule 0
  Type codes (jump 064)    : 55AA7555AA5A71A1A5555557177111117775A  Quote rule 0
  Type codes (jump 100)    : 55AA7555AA5A71A1A5555557177111117775A  Quote rule 0
  =====
  Sampled 10049 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 1 to the end of last row: 6823372781
  Line length: mean=126.15 sd=8.30 min=100 max=359
  Estimated number of rows: 6823372781 / 126.15 = 54088821
  Initial alloc = 62279495 rows (54088821 + 15%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 4 type and 23 drop user overrides : 00AA700000000000000000070775555077750
[10] Allocate memory for the datatable
  Allocating 14 column slots (37 - 23 dropped) with 62279495 rows
[11] Read the data
  jumps=[0..6520), chunk_size=1046529, total_size=6823372422
|--------------------------------------------------|
|==================================================|
Read 53945186 rows x 14 columns from 6.355GB (6823372783 bytes) file in 00:25.938 wall clock time
[12] Finalizing the datatable
  Type counts:
        23 : drop      '0'
         5 : int32     '5'
         7 : float64   '7'
         2 : string    'A'
=============================
   0.005s (  0%) Memory map 6.355GB file
   0.025s (  0%) sep=',' ncol=37 and header detection
   0.001s (  0%) Column type detection using 10049 sample rows
   4.681s ( 18%) Allocation of 62279495 rows x 37 cols (5.336GB) of which 53945186 ( 87%) rows used
  21.226s ( 82%) Reading 6520 chunks of 0.998MB (8295 rows) using 40 threads
   =    0.485s (  2%) Finding first non-embedded \n after each jump
   +    1.465s (  6%) Parse to row-major thread buffers (grown 0 times)
   +    9.095s ( 35%) Transpose
   +   10.181s ( 39%) Waiting
   0.000s (  0%) Rereading 0 columns due to out-of-sample type exceptions
  25.938s        Total

Fermé RStudio et l'a rouvert pour empêcher l'activation de la mise en cache de la chaîne et l'a réexécuté avec gcinfo(TRUE) . Bonus supplémentaire, la conversion en IDate terminée (a pris plus de 40 secondes, cependant :)).

> colCLASS <- c(rep('integer', 2L), 'character', 'Date', 'numeric',
+               rep('integer', 3L), rep('character', 2L),
+               'integer', 'Date', rep('numeric', 2L), 'Date',
+               rep('numeric', 12L), rep('integer', 5),
+               rep('numeric', 3L), 'integer', 'character')
> library(data.table)
data.table 1.10.5 IN DEVELOPMENT built 2017-12-02 12:05:42 UTC; appveyor
  The fastest way to learn (by data.table authors): https://www.datacamp.com/courses/data-analysis-the-data-table-way
  Documentation: ?data.table, example(data.table) and browseVignettes("data.table")
  Release notes, videos and slides: http://r-datatable.com
> gcinfo(TRUE)
[1] FALSE
> sessionInfo()
R version 3.4.2 beta (2017-09-17 r73296)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows Server >= 2012 x64 (build 9200)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                           LC_TIME=English_United States.1252    

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

other attached packages:
[1] data.table_1.10.5

loaded via a namespace (and not attached):
[1] compiler_3.4.2 tools_3.4.2   
Garbage collection 46 = 36+5+5 (level 0) ... 
38.6 Mbytes of cons cells used (77%)
11.2 Mbytes of vectors used (71%)
Garbage collection 47 = 37+5+5 (level 0) ... 
38.7 Mbytes of cons cells used (77%)
11.2 Mbytes of vectors used (71%)
Garbage collection 48 = 38+5+5 (level 0) ... 
38.8 Mbytes of cons cells used (77%)
11.2 Mbytes of vectors used (71%)
Garbage collection 49 = 39+5+5 (level 0) ... 
39.0 Mbytes of cons cells used (78%)
11.2 Mbytes of vectors used (71%)
Garbage collection 50 = 40+5+5 (level 0) ... 
39.1 Mbytes of cons cells used (78%)
11.3 Mbytes of vectors used (71%)
Garbage collection 51 = 40+6+5 (level 1) ... 
38.8 Mbytes of cons cells used (77%)
11.3 Mbytes of vectors used (71%)
Garbage collection 52 = 41+6+5 (level 0) ... 
38.9 Mbytes of cons cells used (77%)
11.3 Mbytes of vectors used (71%)
Garbage collection 53 = 42+6+5 (level 0) ... 
41.5 Mbytes of cons cells used (83%)
12.2 Mbytes of vectors used (77%)
Garbage collection 54 = 42+7+5 (level 1) ... 
43.4 Mbytes of cons cells used (86%)
12.8 Mbytes of vectors used (81%)
Garbage collection 55 = 42+7+6 (level 2) ... 
44.7 Mbytes of cons cells used (72%)
13.0 Mbytes of vectors used (67%)
Garbage collection 56 = 43+7+6 (level 0) ... 
46.5 Mbytes of cons cells used (74%)
13.6 Mbytes of vectors used (70%)
Garbage collection 57 = 44+7+6 (level 0) ... 
47.0 Mbytes of cons cells used (75%)
13.8 Mbytes of vectors used (71%)
Garbage collection 58 = 45+7+6 (level 0) ... 
47.4 Mbytes of cons cells used (76%)
13.9 Mbytes of vectors used (71%)
Garbage collection 59 = 46+7+6 (level 0) ... 
47.7 Mbytes of cons cells used (76%)
14.2 Mbytes of vectors used (73%)
Garbage collection 60 = 47+7+6 (level 0) ... 
48.0 Mbytes of cons cells used (77%)
14.2 Mbytes of vectors used (73%)
Garbage collection 61 = 48+7+6 (level 0) ... 
48.1 Mbytes of cons cells used (77%)
14.3 Mbytes of vectors used (73%)
> DT <- fread('LargeFile.csv', header = TRUE, colClasses = colCLASS, select = colSEL, key = c('LoanID', 'Month'), verbose = TRUE)
Input contains no \n. Taking this to be a filename to open
[01] Check arguments
  Using 40 threads (omp_get_max_threads()=40, nth=40)
  NAstrings = [<<NA>>]
  None of the NAstrings look like numbers.
  show progress = 1
  0/1 column will be read as boolean
[02] Opening the file
  Opening file LargeFile.csv
  File opened, size = 6.355GB (6823372783 bytes).
  Memory mapped ok
[03] Detect and skip BOM
[04] Arrange mmap to be \0 terminated
  \n has been found in the data so any mixture of line endings is allowed other than \r-only line endings. This is common and ideal.
[05] Skipping initial rows if needed
  Positioned on line 1 starting: <<Orig_Year,Orig_Qtr,LoanID,Mont>>
[06] Detect separator, quoting rule, and ncolumns
  Detecting sep ...
  sep=','  with 100 lines of 37 fields using quote rule 0
  Detected 37 columns on line 1. This line is either column names or first data row. Line starts as: <<Orig_Year,Orig_Qtr,LoanID,Mont>>
  Quote rule picked = 0
  fill=false and the most number of columns found is 37
[07] Detect column types, good nrow estimate and whether first row is column names
  'header' changed by user from 'auto' to true
  Number of sampling jump points = 101 because (6823372781 bytes from row 1 to eof) / (2 * 12905 jump0size) == 264369
  Type codes (jump 000)    : 51AA7155A15A7111111111111771111177715  Quote rule 0
  Type codes (jump 001)    : 51AA7155A15A711111111111177111117771A  Quote rule 0
  Type codes (jump 008)    : 51AA7555A15A711111111111177111117771A  Quote rule 0
  Type codes (jump 009)    : 51AA7555AA5A71A155555557177111117775A  Quote rule 0
  Type codes (jump 042)    : 55AA7555AA5A71A155555557177111117775A  Quote rule 0
  Type codes (jump 064)    : 55AA7555AA5A71A1A5555557177111117775A  Quote rule 0
  Type codes (jump 100)    : 55AA7555AA5A71A1A5555557177111117775A  Quote rule 0
  =====
  Sampled 10049 rows (handled \n inside quoted fields) at 101 jump points
  Bytes from first data row on line 1 to the end of last row: 6823372781
  Line length: mean=126.15 sd=8.30 min=100 max=359
  Estimated number of rows: 6823372781 / 126.15 = 54088821
  Initial alloc = 62279495 rows (54088821 + 15%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
  =====
[08] Assign column names
[09] Apply user overrides on column types
  After 4 type and 23 drop user overrides : 00AA700000000000000000070775555077750
[10] Allocate memory for the datatable
  Allocating 14 column slots (37 - 23 dropped) with 62279495 rows
Garbage collection 62 = 48+7+7 (level 2) ... 
46.5 Mbytes of cons cells used (60%)
13.6 Mbytes of vectors used (2%)
Garbage collection 63 = 48+7+8 (level 2) ... 
46.5 Mbytes of cons cells used (60%)
488.7 Mbytes of vectors used (42%)
Garbage collection 64 = 48+7+9 (level 2) ... 
46.5 Mbytes of cons cells used (60%)
963.9 Mbytes of vectors used (56%)
Garbage collection 65 = 48+7+10 (level 2) ... 
46.5 Mbytes of cons cells used (60%)
1439.1 Mbytes of vectors used (63%)
Garbage collection 66 = 48+7+11 (level 2) ... 
46.5 Mbytes of cons cells used (60%)
1914.2 Mbytes of vectors used (67%)
Garbage collection 67 = 48+7+12 (level 2) ... 
46.5 Mbytes of cons cells used (60%)
2864.5 Mbytes of vectors used (77%)
Garbage collection 68 = 48+7+13 (level 2) ... 
46.5 Mbytes of cons cells used (60%)
3577.3 Mbytes of vectors used (78%)
Garbage collection 69 = 48+7+14 (level 2) ... 
46.5 Mbytes of cons cells used (60%)
4290.0 Mbytes of vectors used (75%)
[11] Read the data
  jumps=[0..6520), chunk_size=1046529, total_size=6823372422
|--------------------------------------------------|
|============================Garbage collection 70 = 49+7+14 (level 0) ... 
76.5 Mbytes of cons cells used (99%)
5487.5 Mbytes of vectors used (96%)
=Garbage collection 71 = 49+8+14 (level 1) ... 
77.0 Mbytes of cons cells used (100%)
5487.6 Mbytes of vectors used (96%)
Garbage collection 72 = 49+8+15 (level 2) ... 
77.0 Mbytes of cons cells used (81%)
5487.1 Mbytes of vectors used (80%)
==============Garbage collection 73 = 50+8+15 (level 0) ... 
94.3 Mbytes of cons cells used (100%)
5494.0 Mbytes of vectors used (80%)
Garbage collection 74 = 50+9+15 (level 1) ... 
94.5 Mbytes of cons cells used (100%)
5494.1 Mbytes of vectors used (80%)
Garbage collection 75 = 50+9+16 (level 2) ... 
94.5 Mbytes of cons cells used (82%)
5493.1 Mbytes of vectors used (67%)
=======|
Read 53945186 rows x 14 columns from 6.355GB (6823372783 bytes) file in 00:24.772 wall clock time
[12] Finalizing the datatable
  Type counts:
        23 : drop      '0'
         5 : int32     '5'
         7 : float64   '7'
         2 : string    'A'
=============================
   0.005s (  0%) Memory map 6.355GB file
   0.018s (  0%) sep=',' ncol=37 and header detection
   0.000s (  0%) Column type detection using 10049 sample rows
   5.496s ( 22%) Allocation of 62279495 rows x 37 cols (5.336GB) of which 53945186 ( 87%) rows used
  19.253s ( 78%) Reading 6520 chunks of 0.998MB (8295 rows) using 40 threads
   =    0.433s (  2%) Finding first non-embedded \n after each jump
   +    1.482s (  6%) Parse to row-major thread buffers (grown 0 times)
   +    9.515s ( 38%) Transpose
   +    7.822s ( 32%) Waiting
   0.000s (  0%) Rereading 0 columns due to out-of-sample type exceptions
  24.772s        Total
Garbage collection 76 = 51+9+16 (level 0) ... 
105.3 Mbytes of cons cells used (91%)
5500.3 Mbytes of vectors used (67%)
Garbage collection 77 = 51+10+16 (level 1) ... 
105.4 Mbytes of cons cells used (91%)
5500.2 Mbytes of vectors used (67%)
> DT[, Month := as.IDate(Month, format = "%Y-%m-%d")]
Garbage collection 78 = 51+10+17 (level 2) ... 
107.5 Mbytes of cons cells used (76%)
8174.1 Mbytes of vectors used (81%)
Garbage collection 79 = 51+11+17 (level 1) ... 
107.5 Mbytes of cons cells used (76%)
5910.4 Mbytes of vectors used (59%)
> gcinfo(FALSE)
[1] TRUE

impressionnant! : tada: excellent travail à toutes les personnes impliquées, en particulier @mattdowle qui doit être à court de cheveux maintenant avec ça :)

Il semble que ma stratégie de `` rester en vacances jusqu'à ce que le problème soit résolu '' semble avoir fonctionné ici :-)

Y a-t-il autre chose que je devrais essayer d'examiner ou ce problème est-il considéré comme résolu?

Merci @aadler et @HughParsonage! Le soulagement.
@kevinushey Ha ha. Oui, c'était côté data.table et maintenant résolu (PR # 2488). Merci.