Data.table: Desequilibrio de pila en carga

@HughParsonage , esto se parece a # 2457. Quizás intente pasar showProgress=FALSE y vea si se completa.
@mattdowle ¿ podría haber habido una regresión desde 2017-11-09?

Ejecutar con showProgress=FALSE efectivamente devolvió el resultado (con solo las advertencias esperadas).

Gracias por toda la información detallada. Dudo que haya habido una regresión desde 2017-11-09, pero tal vez la salida larga de verbose=TRUE tenga un impacto similar a la salida de ETA. El archivo necesita una nueva lectura, lo que significa que se genera más salida. Me temo que el informe @HughParsonage 's que showProgress = TRUE obras para él es falsa y que el problema va a pasar si se ejecuta 5-10 veces con verbosa = TRUE.

No hay ningún mensaje detallado impreso desde dentro de la sección paralela (aparte del progreso ETA que ya está arreglado). Sin embargo, hay mensajes detallados después de la primera lectura y antes de que comience la segunda lectura (lo que está sucediendo para este archivo). Supongo que es posible que si esas impresiones desencadenan la 100th CheckUserInterrupt (ver # 2457), podría causar que la segunda región paralela falle (aunque es extraño). Para descartar eso de todos modos, acabo de cambiar todos los mensajes detallados para usar REprintf en lugar de Rprintf (la misma solución que # 2457 para la ETA). Eso falló porque las pruebas no encuentran el resultado en stderr, se solucionará. Una vez que pase, el .zip de Windows se creará automáticamente y, a continuación, puede intentarlo de nuevo. Actualizaré aquí cuando esté listo.

Ok, el segundo intento es pasar las comprobaciones y Windows.zip está disponible. @HughParsonage, ¿te importaría intentarlo de nuevo, por favor? Agregué una llamada a R_FlushConsole () después de los mensajes en modo detallado justo antes de volver a leer. Esa descarga solo es necesaria en Windows. Supongo que sin la descarga, la consola a veces se actualiza un poquito más tarde cuando se realiza la relectura paralela y se sabe que eso causa problemas. Repita 10 veces, siempre con verbose=TRUE y showProgress=TRUE . Si ve 10 carreras claras, diremos que eso fue todo. De lo contrario, tendré que pensarlo de nuevo.

Desafortunadamente, no arreglado:

> 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

Usando verbose=TRUE, showProgress=TRUE incluso después de 10 ejecuciones, no obtengo ningún error. Aquí está el resultado de la décima salida:

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 ¡Gracias! Aunque estoy confundido. Dices que funciona bien con verbose=TRUE, showProgress=TRUE que es lo que esperábamos, ¡yay! Eso falló antes, ¿no? El valor predeterminado para showProgress es VERDADERO de todos modos, pero cuando ejecuta con el valor predeterminado FALSO para verbose , _entonces_ no funciona y ve el desequilibrio de la pila. Es extraño que la salida _less_ haga que falle. Por favor confirmar. Si ese es el caso, entonces tal vez estoy ladrando al árbol equivocado. Funciona bien aquí para mí en Linux, así que dependo de que pruebes en Windows. Gracias.
(Además, en la parte inferior de la salida de la décima ejecución, dice que hubo 20 advertencias. Supongo que esas son las 2 advertencias que se muestran más arriba, repetidas 10 veces. Si es así, tiene sentido).

Hola, perdón por la confusión, Matt.

Tiene razón en que el problema original ya no resulta en un bloqueo, es decir, lo siguiente funciona como se esperaba:

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

Para aclarar, en el original, cuando verbose =FALSE (el valor predeterminado) tuve un bloqueo. Lo ejecuté con verbose = TRUE antes de presentar el problema y noté una advertencia de 'desequilibrio de pila' pero no encontré un bloqueo. Con la última versión, no obtengo un bloqueo (ni ningún problema) con verbose = FALSE .

La razón por la que dije 'no arreglado' fue que noté los mensajes de advertencia:

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

que parecía extraño y pensé que podría indicar un problema estrechamente relacionado, aunque no idéntico. Dicho esto, esta mañana en Australia ya no puedo reproducir los mensajes de advertencia.

OK veo. Esos mensajes de advertencia sobre el desequilibrio de la pila son esencialmente errores, sí. No podemos omitirlos. Llamo a esa advertencia sobre el desequilibrio de la pila un bloqueo, aunque todavía no se ha bloqueado. (Es solo cuestión de tiempo hasta que se bloquee después de ver esa advertencia).

Cuando realiza las 10 ejecuciones en una sesión R nueva con verbose=TRUE, showProgress=TRUE , ¿hay alguna de las 20 advertencias sobre el desequilibrio de la pila o todas esas 20 son solo las siguientes advertencias regulares?

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">>

Una vez que se haya producido una advertencia de desequilibrio de la pila, inicie una nueva sesión de R. No podemos confiar en nada de R después de que haya ocurrido ni una sola vez.

Me las arreglé para tener un bloqueo cuando corrí con verbose=TRUE, showProgress=TRUE . Algo sobre un const char con un SEXP . Estoy tratando de reproducir esto desde la línea de comando (desafortunadamente ocurrió en RStudio y RStudio se cerró antes de que pudiera leer el mensaje completo).

No se puede reproducir el accidente. Aquí está el resultado después de reiniciar. Hubo una advertencia de desequilibrio de la pila:

> 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)

Curiosamente, esa certeza es genial. Gracias. Eso significa que la descarga no funcionó y tendré que encontrar una manera de evitar Rprintf después de todo. Funciona de manera confiable con verbose=FALSE, showProgress=FALSE Supongo (escribiste eso cerca de la parte superior de este problema, así que confío en eso). "De manera confiable", lo que significa 10 carreras seguidas con solo las dos advertencias esperadas y sin ver la pila. advertencia de desequilibrio.
Déjamelo entonces. Gracias de nuevo.

@HughParsonage Ok, inténtalo de nuevo con ese segundo intento reciente. Aún no se ha fusionado con el master, así que tenga cuidado de obtener el archivo Windows.zip de la rama aquí . Como antes, proporcione el resultado completo de cualquier manera para que pueda verificarlo. ¡Gracias!

El primer intento de lo siguiente resultó en un bloqueo (algo sobre un puntero).

El segundo intento (después de reiniciar) da como resultado una advertencia 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">>

Hola, @mattdowle. Hay versiones de GCC todavía en uso cuyo OpenMP es, en el mejor de los casos, 3.1, no 4.0. Me encontré con ese problema en uno de mis paquetes en CRAN ( Delaporte ) donde intenté usar una directiva SIMD (OpenMP 4.0) que se compiló con Rtools para Windows (basado en 4.9.3) pero arrojó un error en la máquina Linux de alguien que todavía usa gcc 4.8.0. Incluso Windows solo puede usar llamadas 4.0 y no 4.5, si no recuerdo mal. ¿Quizás eso está contribuyendo al problema?

@HughParsonage ¡ Gracias por probar tan rápido! Ok, ¡seguiré pensando entonces!
@aadler Eso es un buen pensamiento, todo es posible.

@HughParsonage ¿ Solo para confirmar, por favor, que el mismo comando con un solo cambio ( verbose=FALSE ) funciona bien? es decir, fread("SA2-by-DJZ-2011.csv", verbose = FALSE, na.strings = "", header = FALSE) . El medidor de progreso seguirá mostrándose.

Sí, ejecutar ese comando (diez veces) devolvió el resultado esperado (es decir, la tabla de datos con solo dos advertencias porque está mal formateado). Sin advertencias de desequilibrio de pila.

Gracias. Entonces parece estar relacionado con la salida de la consola. Un par de cosas más para probar ...

En modo detallado, hay algunas ramas dentro de la región paralela que llaman wallclock() . Lo cortocircuité para devolver siempre 0.0 y evitar la llamada al sistema, para descartar eso. Pensé que era seguro para subprocesos, pero tal vez no. Pruebe el nuevo archivo Windows.zip de la rama reconstruida aquí .

Primer intento:

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)

Segundo intento, recibo las siguientes advertencias:

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

Solo un pensamiento: ¿podría ser esto un problema con RStudio? La ejecución del script desde la terminal no parece reproducirse tan fácilmente. Estoy ejecutando desde RStudio porque facilita la copia de la salida de la consola.

Cuando dice que no se reproduce _ tan fácilmente_ fuera de RStudio, ¿se reproduce _ en absoluto_? Incluso si solo sucede dentro de RStudio, todavía es algo que me gustaría arreglar en el lado de data.table. Solo pido como otra ruta para confirmar que definitivamente es "solo" salida de consola y no algún otro desequilibrio de pila real en la lógica de fread.

Todavía tengo que reproducir fuera de RStudio, y puedo reproducir de manera confiable dentro de él (es decir, puedo reproducir alguna advertencia o bloqueo). Probé el símbolo del sistema de Windows y git shell (en Windows).

Estoy usando RStudio Versión 1.1.383 en Windows. ¿Le sería útil si también les planteo este problema, o le gustaría que esperara?

Gracias. Es realmente útil saber que está dentro de RStudio. No hay necesidad de planteárselo a ellos. Simplemente significa que tiene algo que ver con el almacenamiento en búfer de la consola de salida (o similar). He seguido adelante con un trabajo y estoy a punto de seguir adelante.

No veo por qué Windows no está compilando ese cambio:
fread.c:1054:3: warning: too many arguments for format [-Wformat-extra-args]
Funciona bien aquí en Linux y en Travis. Eso impide que se cree el archivo Windows.zip para que pueda probar esta solución. Tendré que dormir sobre eso.
(Se queja de la línea 1054, pero no de la siguiente línea 1055, que es exactamente lo mismo. Debe haber alguna diferencia.% Llu es un problema con __VA_ARGS__ en Windows, seguramente no).

Ok, finalmente windows.zip está listo para que lo intentes de nuevo, por favor aquí .

Ahora hay varias soluciones en esta rama. Si funciona, comenzaré a eliminar las soluciones para establecer cuál fue. Las advertencias del compilador llu parecen las más prometedoras ya que darían lugar a un desequilibrio de pila en la salida detallada, consistente con la explicación @ st-pasha encontrada aquí . Tal vez la capa Rprintf ocultaba eso del compilador, que puede ver ahora que está usando fprintf directamente.

En el segundo intento (después de reiniciar)

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">>

Nuevamente, no se puede reproducir fuera de RStudio.

Gracias por probar tan rápido. Bueno, ¡eso ciertamente descarta muchas cosas entonces! Quedan dos ideas. Primero uno empujó y pasó. Pruebe el nuevo Windows.zip aquí . Ese alloca está en la pila y tiene que ver con na.strings que está configurando a medida que sucede. Definitivamente en el área correcta (desequilibrio de pila) y vale la pena intentarlo.

No hay problema, estaré fuera durante las próximas 12 horas aproximadamente, así que no puedo probar hasta entonces.
El sábado 18 de noviembre de 2017 a las 5:20 pm, Matt Dowle [email protected] escribió:

Gracias por probar tan rápido. Bueno, ¡eso ciertamente descarta muchas cosas entonces!
Quedan dos ideas. Primero uno empujó y pasó. Pruebe el nuevo Windows.zip
Aquí
https://ci.appveyor.com/project/Rdatatable/data-table/build/1.0.1363/job/fo02vnbu5ebhwy3w/artifacts .
Esa asignación se asigna en la pila y tiene que ver con na.strings que
estás configurando como sucede. Definitivamente en el área correcta (pila
desequilibrio) y vale la pena intentarlo.

-
Estás recibiendo esto porque te mencionaron.

Responda a este correo electrónico directamente, véalo en GitHub
https://github.com/Rdatatable/data.table/issues/2481#issuecomment-345421856 ,
o silenciar el hilo
https://github.com/notifications/unsubscribe-auth/AHvGDGa5Qnls5eSFBMaQO5s8DElfrpKSks5s3ncqgaJpZM4QcuPc
.

Ok, no te preocupes. ¡Gracias! También he impulsado la segunda idea ahora. Me parece recordar que \r causó un problema en Windows en el pasado, pero no recuerdo un desequilibrio de pila. De todos modos, para descartar eso, eliminé el \r del medidor de progreso. El mensaje de desequilibrio de pila parece imprimirse donde ocurren las líneas de ETA. Es factible que la consola capture \r y lo trate de manera diferente para que se reemplace la última línea. Ahora debería ver una nueva línea cada vez que se actualiza la ETA. Solo temporalmente para descartar eso. Nuevo Windows.zip construido y pasando aquí .

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: No pude reproducir este error de desequilibrio de pila en una máquina Windows diferente con una versión un poco más antigua de RStudio.

En ese caso, parece que es hora de pedir ayuda a RStudio como sugirió, entonces por favor. He vuelto a echar un vistazo al código de fread y no tengo ideas de mi lado. Dígales los dos números de versión de RStudio. No necesariamente significa que sea RStudio, podría ser una falla en el lado de data.table que simplemente aparece en una versión de RStudio. Pero es extraño que parezca relacionado con la salida de la consola y eso es algo diferente y específico de RStudio. He buscado "desequilibrio de la pila de RStudio", pero surgen muchos problemas sobre fallas de paquetes, no sobre RStudio en sí. Problema difícil de buscar. Dejemos el tema abierto aquí y veamos qué dicen.

Dudo que el último intento ayude, pero para completarlo, inténtelo aquí . Quizás el compilador MinGW que se usa en Windows hace algo extraño con esos dos ints. Uno de ellos es la constante 0 que quizás se optimiza y luego causa un desequilibrio de pila de alguna manera.

Sin embargo, ese mensaje de desequilibrio de pila en particular proviene de eval.c: 491 en R mismo. Algún hilo debe estar ejecutando esa línea, pero no creo que sea fread o data.table . Ese check_stack_balance() solo se llama desde 5 lugares en R internos:
en names.c al final de do_internal()
en objects.c , dos veces en applyMethod()
en eval.c , dos veces en eval()
No veo cómo se puede llegar a ninguno de ellos mientras fread.c está en su sección paralela. El único punto de entrada al que se llama es REprintf y no veo cómo podría llegar a check_stack_balance() . Todo lo que puedo pensar actualmente es que RStudio tiene un hilo que está haciendo algo en segundo plano que quizás interactúa con la salida de la consola, quizás de manera diferente en Windows.
Finalmente, para completar, parece que usar REprintf es el camino correcto a seguir, ya que la base R está usando eso (en lugar de Rprintf) en su medidor de progreso en libcurl.c: 354 e internet.c: 409 . Es una pena que la barra de progreso de R en el nivel C no esté disponible en la API de R (parece que también se implementa dos veces en R en el nivel C).

@mattdowle , ¿sería útil esto? https://github.com/r-lib/progress

@aader Sí, ¡gracias! Su fuente contiene este comentario :
// In R Studio we should print to stdout, because printing a \r
// to stderr is buggy (reported)
Pero ya eliminé el \r y el desequilibrio de la pila todavía ocurre. Me pregunto dónde se informó.

¿Tal vez esto?

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

La última compilación tampoco funcionó:

Reportado en https://community.rstudio.com/t/stack-imbalance-possibly-in-stderr/3009

Pregunta oportuna sobre R-devel: [Rd] ¿Son Rprintf y REprintf seguros para subprocesos?

Resultado "Rprintf y REprintf no son seguros para subprocesos".

¡Yoiks!

Gracias a todos por los enlaces ya Hugh por plantear el problema con RStudio.

data.table::fwrite() y data.table::fread() saben que Rprintf y REprintf no son seguros para subprocesos, por lo que para sus medidores de progreso, solo los llaman desde el subproceso maestro. No solo dos subprocesos de data.table nunca llaman a ese punto de entrada R al mismo tiempo, sino que solo el subproceso maestro lo llama, y ​​ese es el único punto de entrada R llamado por cualquiera de los subprocesos en cualquier momento durante el sección paralela. Sin embargo, Rprintf llama a R_CheckUserInterrupt cada 100 impresiones. Creo que esa es la parte que probablemente no está a salvo incluso del hilo maestro. Esa es la razón por la que ahora se usa REprintf ya que no llama a R_CheckUserInterrupt . Los componentes internos de R usan REprintf para medidores de progreso, por lo que cambiar a REprintf para mantener la coherencia con el núcleo R tiene sentido; es decir, esa elección no tiene nada que ver con stderr vs stdout, per se.

@kevinushey, ¿te importaría echar un vistazo a este hilo y decirme cualquier otra cosa que pueda probar? ¿Podría estar relacionado con RStudio, de alguna manera, quizás relacionado con un hilo de fondo? Si RStudio tiene un hilo en segundo plano, entonces podría ser que Rprintf / REprintf puedan llamar desde dos hilos al mismo tiempo. Pero, si ese fuera el caso, habríamos visto muchos más problemas antes. Entonces eso parece muy poco probable. Quizás RStudio reemplace las devoluciones ptr_* llamada 8.1.2 de R-exts , que están relacionadas con la salida y la interacción de la consola. Sin embargo, esa sección comienza con "Para los que tienen unix", así que no sé cómo entra Windows. Quizás la sección 8.1.5 también sea ​​relevante. Ambas son subsecciones de la sección 8: "Vinculación de GUI y otras interfaces a R".

Estaré fuera hasta principios de diciembre, así que desafortunadamente no tendré la oportunidad de echar un vistazo hasta entonces. Sin embargo, RStudio ejecuta casi todo en el hilo principal usando el bucle de eventos R; las únicas excepciones son, por ejemplo, la indexación de archivos a nivel de proyecto y esos subprocesos en segundo plano normalmente no tocan ninguna API de R.

RStudio se hace cargo de las diversas devoluciones de llamada ptr_* para manejar la entrada y salida de la consola; No puedo pensar de inmediato en cómo podrían ser una causa aquí, pero intentaré echar un vistazo más profundo cuando vuelva.

Ok, prueba este aquí . Antes, actualizaba el estado de progreso cada 2%. En su caso, su archivo solo está tomando menos de 3 segundos, por lo que fue una nueva actualización de progreso en la consola RStudio cada 0.06 segundos. Quizás eso fue demasiado para RStudio. Entonces este intento imprime una barra. No usa \r en absoluto. De todos modos, esto debería ser mejor para los informes y archivos de registro donde \r podría llenar la salida.

Dado que su tiempo de 3 segundos es bastante rápido, reduje la barra de progreso para comenzar en 1 segundo si hay 1 segundo ETA desde allí. De lo contrario, no se mostraría en absoluto y no funcionaría para su archivo solo porque no se estaba mostrando. Después de que haya probado, aumentaré a lo que tiene fwrite ; es decir, comience en 2 segundos si la ETA es de 2 segundos desde allí.

Hola, @mattdowle. Mi último comentario en el n. ° 2503 también puede estar relacionado con este problema.

¡Se ve bien! Sin advertencias (después de 5 carreras). Primero ejecute a continuación (tenga en cuenta que los espacios iniciales se ven diferentes en la salida real):

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! Entonces creo que es una victoria. Lo ordenaré, me fusionaré y seguiré adelante. Muchísimas gracias a ti por la prueba.

@aadler Yes estuvo de acuerdo en que su comentario en el número 2503 se ve igual. ¿Podrías probar lo último del desarrollador también y confirmar que ahora está arreglado? Esperamos que el problema con as.IDate que encontró fue causado por el desequilibrio de pila anterior.

No es bueno :(

> 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 Gracias por ese informe. Revisé freadR y localicé la protección. Hay un 30% de posibilidades de que funcione, ya que en su caso está anulando tipos y había bastantes protecciones en esa parte del código. Vuelve a intentarlo con esta compilación .

@aadler Si aún no ha probado la última compilación, vaya directamente a probar esta . Además, si es posible conseguirme una copia de su archivo, es posible que pueda probar yo mismo en 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

Gracias a @aadler por correo electrónico, ahora puedo reproducir. R 3.4.2, RStudio 1.1.383 más reciente y Windows 10 Pro 10.0.16299 Build 16299.

Veo un comportamiento extraño en RStudio, registrado aquí:
https://www.youtube.com/watch?v=tl2x2vmZxMU
Parece que RStudio está generando GC con solo escribir. ¿Por qué es así? ¿Hay alguna forma de apagarlo? ¿Podría ser que cuando fread() está imprimiendo su barra de progreso, el ciclo de eventos separado de RStudio está pensando que la salida a la consola es el usuario que escribe y llama a R, lo que da lugar al GC y dispara todo? Quizás los usuarios de RStudio aquí lo sepan, podrían señalarme en la dirección correcta, o quizás @kevinushey está de regreso (dijiste Kevin a principios de diciembre, y hoy es el primero: -))

Puedo reproducir el desequilibrio de la pila de manera confiable en RStudio Console. Usando la pestaña Terminal RStudio, no puedo reproducirlo en absoluto, incluso con gcinfo(TRUE) . Curiosamente, los GC ocurren cuando la barra de progreso se está imprimiendo y eso parece estar bien, ya que también está bien en Linux. Dado el comportamiento en ese video de RStudio Console, llego a la conclusión de que se trata de un error de RStudio Console. No pude copiar el texto de la ventana del Terminal RStudio (Editar-> Copiar no funciona y tampoco Ctrl-C), así que tomé una captura de pantalla de la pestaña Terminal para mostrar que GC durante la barra de progreso está bien. Esperaría que estuviera bien porque solo el hilo maestro llama a REprintf y los otros hilos no llaman a ninguna API de R en absoluto.

Funciona bien en RStudio Terminal:

Tenga en cuenta que hay GC mientras la barra de progreso se imprime por primera vez y eso funciona bien en RStudio Terminal. La barra de progreso se imprime por segunda vez porque hay una excepción de tipo fuera de muestra en este archivo de prueba que activa una relectura automática solo para esas columnas.

Pero en RStudio Console hay stack imbalance o 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 resuelve de manera confiable en RStudio Console. Para reproducirlo, debe ser la primera vez que se ejecute en una consola RStudio nueva con showProgress=TRUE (es decir, por defecto). Parece relacionado con si hay un GC durante el medidor de progreso; hay en la primera ejecución en una nueva sesión. Solo necesita ser un archivo grande para que se muestre el medidor de progreso. Nada que ver con releer o argumentos pasados ​​a fread . Si la primera ejecución en una consola RStudio nueva es con showProgress=FALSE para que funcione, esa ejecución expande el montón de R y luego una ejecución posterior en la misma sesión con showProgress=TRUE también funciona. Pero solo porque no hay GC durante el medidor de progreso debido a que la primera ejecución ya está expandiendo el montón.
Por qué un GC en el hilo maestro durante el medidor de progreso está bien en Linux y en Windows RStudio Terminal pero no en RStudio Console es la pregunta pendiente.

Ok, esto lo arregla. El problema estaba en el lado de data.table y no en RStudio. Funciona ahora para mí de manera confiable en RStudio Console en Windows. Era un problema que podía ocurrir en Linux y Max también, es solo que los patrones de memoria no lo activaban. Los otros subprocesos tenían un punto de entrada a R (al presionar sus búferes con columnas de cadena) que podría suceder al mismo tiempo que el progreso de impresión del subproceso maestro usando REprintf . Es por eso que solo sucedió en la primera ejecución en una sesión nueva. En la segunda ejecución en adelante, todas las cadenas en el archivo se habían visto antes, por lo que las búsquedas de caché fueron acertadas (seguras para subprocesos) y no asignaciones (no seguras para subprocesos).

Entonces, @aadler y @HughParsonage , prueben este . ¡95% de probabilidad de que esto funcione ahora!

Sin advertencia, no estoy seguro de si está buscando algo más:

> 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">>

Gracias Hugh. Sí, eso es una ejecución limpia, asumiendo que fue en una nueva sesión de consola RStudio. No hay señales de los mensajes de desequilibrio de pila o "unprotect_ptr: puntero no encontrado", y el medidor de progreso se está ejecutando correctamente (dos veces en este caso, ya que hay una nueva lectura). Ahora solo @aadler para confirmar.

ÉXITO.

Primera ejecución, instancia nueva 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

Cerró RStudio y lo volvió a abrir para evitar que se activara el almacenamiento en caché de cadenas y lo volvió a ejecutar con gcinfo(TRUE) . Bonificación adicional, la conversión a IDate se completó (aunque tomó más de 40 segundos :)).

> 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

¡increíble! : tada: gran trabajo para todos los involucrados, especialmente @mattdowle, que ya debe tener algunos pelos cortos con esto :)

Parece que mi estrategia de 'quedarme de vacaciones hasta que se solucione el problema' parece haber funcionado aquí :-)

¿Hay algo más que deba intentar analizar o se considera que este problema está resuelto?

¡Gracias @aadler y @HughParsonage! Alivio.
@kevinushey Ja, ja. Sí, era del lado de la tabla de datos y ahora se resolvió (PR # 2488). Gracias.