read-parquet-3.md
In nanoparquet: Read and Write 'Parquet' Files

TIMESTAMP

Code
  as.data.frame(read_parquet(tmp))
Output
                     ts
  1 2024-08-20 20:37:35
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name  r_type  type type_length repetition_type   converted_type
  1 schema    <NA>  <NA>          NA            <NA>             <NA>
  2     ts POSIXct INT64          NA        REQUIRED TIMESTAMP_MILLIS
    logical_type num_children scale precision field_id
  1                         1    NA        NA       NA
  2 TIMESTAM....           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  $type
  [1] "TIMESTAMP"

  $is_adjusted_to_utc
  [1] TRUE

  $unit
  [1] "MILLIS"

  attr(,"class")
  [1] "nanoparquet_logical_type"

Code
  as.data.frame(read_parquet(tmp))
Output
                     ts
  1 2024-08-20 20:37:35
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name  r_type  type type_length repetition_type   converted_type
  1 schema    <NA>  <NA>          NA            <NA>             <NA>
  2     ts POSIXct INT64          NA        REQUIRED TIMESTAMP_MICROS
    logical_type num_children scale precision field_id
  1                         1    NA        NA       NA
  2 TIMESTAM....           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  $type
  [1] "TIMESTAMP"

  $is_adjusted_to_utc
  [1] TRUE

  $unit
  [1] "MICROS"

  attr(,"class")
  [1] "nanoparquet_logical_type"

Code
  as.data.frame(read_parquet(tmp))
Output
                     ts
  1 2024-08-20 20:37:35
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name  r_type  type type_length repetition_type converted_type logical_type
  1 schema    <NA>  <NA>          NA            <NA>           <NA>             
  2     ts POSIXct INT64          NA        REQUIRED           <NA> TIMESTAM....
    num_children scale precision field_id
  1            1    NA        NA       NA
  2           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  $type
  [1] "TIMESTAMP"

  $is_adjusted_to_utc
  [1] TRUE

  $unit
  [1] "NANOS"

  attr(,"class")
  [1] "nanoparquet_logical_type"

TIMESTAMP, dictionary

Code
  as.data.frame(read_parquet(tmp))
Output
                     ts
  1 2024-08-20 20:37:35
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name  r_type  type type_length repetition_type   converted_type
  1 schema    <NA>  <NA>          NA            <NA>             <NA>
  2     ts POSIXct INT64          NA        REQUIRED TIMESTAMP_MILLIS
    logical_type num_children scale precision field_id
  1                         1    NA        NA       NA
  2 TIMESTAM....           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  $type
  [1] "TIMESTAMP"

  $is_adjusted_to_utc
  [1] TRUE

  $unit
  [1] "MILLIS"

  attr(,"class")
  [1] "nanoparquet_logical_type"

Code
  read_parquet_metadata(tmp)[["column_chunks"]][["encodings"]]
Output
  [[1]]
  [1] "PLAIN"          "RLE_DICTIONARY"

Code
  as.data.frame(read_parquet(tmp))
Output
                     ts
  1 2024-08-20 20:37:35
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name  r_type  type type_length repetition_type   converted_type
  1 schema    <NA>  <NA>          NA            <NA>             <NA>
  2     ts POSIXct INT64          NA        REQUIRED TIMESTAMP_MICROS
    logical_type num_children scale precision field_id
  1                         1    NA        NA       NA
  2 TIMESTAM....           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  $type
  [1] "TIMESTAMP"

  $is_adjusted_to_utc
  [1] TRUE

  $unit
  [1] "MICROS"

  attr(,"class")
  [1] "nanoparquet_logical_type"

Code
  read_parquet_metadata(tmp)[["column_chunks"]][["encodings"]]
Output
  [[1]]
  [1] "PLAIN"          "RLE_DICTIONARY"

Code
  as.data.frame(read_parquet(tmp))
Output
                     ts
  1 2024-08-20 20:37:35
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name  r_type  type type_length repetition_type converted_type logical_type
  1 schema    <NA>  <NA>          NA            <NA>           <NA>             
  2     ts POSIXct INT64          NA        REQUIRED           <NA> TIMESTAM....
    num_children scale precision field_id
  1            1    NA        NA       NA
  2           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  $type
  [1] "TIMESTAMP"

  $is_adjusted_to_utc
  [1] TRUE

  $unit
  [1] "NANOS"

  attr(,"class")
  [1] "nanoparquet_logical_type"

Code
  read_parquet_metadata(tmp)[["column_chunks"]][["encodings"]]
Output
  [[1]]
  [1] "PLAIN"          "RLE_DICTIONARY"

TIMESTAMP_MILLIS, TIMESTAMP_MICROS

Code
  as.data.frame(read_parquet(tmp))
Output
                     ts
  1 2024-08-20 20:37:35
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name r_type  type type_length repetition_type   converted_type logical_type
  1 schema   <NA>  <NA>          NA            <NA>             <NA>             
  2     ts double INT64          NA        REQUIRED TIMESTAMP_MILLIS             
    num_children scale precision field_id
  1            1    NA        NA       NA
  2           NA    NA        NA       NA

Code
  as.data.frame(read_parquet(tmp))
Output
                     ts
  1 2024-08-20 20:37:35
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name  r_type  type type_length repetition_type   converted_type
  1 schema    <NA>  <NA>          NA            <NA>             <NA>
  2     ts POSIXct INT64          NA        REQUIRED TIMESTAMP_MICROS
    logical_type num_children scale precision field_id
  1                         1    NA        NA       NA
  2                        NA    NA        NA       NA

TIMESTAMP_MILLIS, TIMESTAMP_MICROS, dictionary

Code
  as.data.frame(read_parquet(tmp))
Output
                     ts
  1 2024-08-20 20:37:35
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name r_type  type type_length repetition_type   converted_type logical_type
  1 schema   <NA>  <NA>          NA            <NA>             <NA>             
  2     ts double INT64          NA        REQUIRED TIMESTAMP_MILLIS             
    num_children scale precision field_id
  1            1    NA        NA       NA
  2           NA    NA        NA       NA
Code
  read_parquet_metadata(tmp)[["column_chunks"]][["encodings"]]
Output
  [[1]]
  [1] "PLAIN"          "RLE_DICTIONARY"

Code
  as.data.frame(read_parquet(tmp))
Output
                     ts
  1 2024-08-20 20:37:35
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name  r_type  type type_length repetition_type   converted_type
  1 schema    <NA>  <NA>          NA            <NA>             <NA>
  2     ts POSIXct INT64          NA        REQUIRED TIMESTAMP_MICROS
    logical_type num_children scale precision field_id
  1                         1    NA        NA       NA
  2                        NA    NA        NA       NA
Code
  read_parquet_metadata(tmp)[["column_chunks"]][["encodings"]]
Output
  [[1]]
  [1] "PLAIN"          "RLE_DICTIONARY"

TIME

Code
  as.data.frame(read_parquet(tmp))
Output
          dt
  1 03:02:01
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name r_type  type type_length repetition_type converted_type logical_type
  1 schema   <NA>  <NA>          NA            <NA>           <NA>             
  2     dt    hms INT32          NA        REQUIRED    TIME_MILLIS TIME, TR....
    num_children scale precision field_id
  1            1    NA        NA       NA
  2           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  $type
  [1] "TIME"

  $is_adjusted_to_utc
  [1] TRUE

  $unit
  [1] "MILLIS"

  attr(,"class")
  [1] "nanoparquet_logical_type"

Code
  as.data.frame(read_parquet(tmp))
Output
          dt
  1 03:02:01
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name r_type  type type_length repetition_type converted_type logical_type
  1 schema   <NA>  <NA>          NA            <NA>           <NA>             
  2     dt    hms INT64          NA        REQUIRED    TIME_MICROS TIME, TR....
    num_children scale precision field_id
  1            1    NA        NA       NA
  2           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  $type
  [1] "TIME"

  $is_adjusted_to_utc
  [1] TRUE

  $unit
  [1] "MICROS"

  attr(,"class")
  [1] "nanoparquet_logical_type"

Code
  as.data.frame(read_parquet(tmp))
Output
          dt
  1 03:02:01
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name r_type  type type_length repetition_type converted_type logical_type
  1 schema   <NA>  <NA>          NA            <NA>           <NA>             
  2     dt    hms INT64          NA        REQUIRED           <NA> TIME, TR....
    num_children scale precision field_id
  1            1    NA        NA       NA
  2           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  $type
  [1] "TIME"

  $is_adjusted_to_utc
  [1] TRUE

  $unit
  [1] "NANOS"

  attr(,"class")
  [1] "nanoparquet_logical_type"

TIME_MILLIS, TIME_MICROS

Code
  as.data.frame(read_parquet(tmp))
Output
          dt
  1 03:02:01
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name r_type  type type_length repetition_type converted_type logical_type
  1 schema   <NA>  <NA>          NA            <NA>           <NA>             
  2     dt    hms INT32          NA        REQUIRED    TIME_MILLIS             
    num_children scale precision field_id
  1            1    NA        NA       NA
  2           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  NULL

Code
  as.data.frame(read_parquet(tmp))
Output
          dt
  1 03:02:01
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name r_type  type type_length repetition_type converted_type logical_type
  1 schema   <NA>  <NA>          NA            <NA>           <NA>             
  2     dt    hms INT64          NA        REQUIRED    TIME_MICROS             
    num_children scale precision field_id
  1            1    NA        NA       NA
  2           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  NULL

TIME, dictionary

Code
  as.data.frame(read_parquet(tmp))
Output
          dt
  1 03:02:01
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name r_type  type type_length repetition_type converted_type logical_type
  1 schema   <NA>  <NA>          NA            <NA>           <NA>             
  2     dt    hms INT32          NA        REQUIRED    TIME_MILLIS TIME, TR....
    num_children scale precision field_id
  1            1    NA        NA       NA
  2           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  $type
  [1] "TIME"

  $is_adjusted_to_utc
  [1] TRUE

  $unit
  [1] "MILLIS"

  attr(,"class")
  [1] "nanoparquet_logical_type"

Code
  read_parquet_metadata(tmp)[["column_chunks"]][["encodings"]]
Output
  [[1]]
  [1] "PLAIN"          "RLE_DICTIONARY"

Code
  as.data.frame(read_parquet(tmp))
Output
          dt
  1 03:02:01
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name r_type  type type_length repetition_type converted_type logical_type
  1 schema   <NA>  <NA>          NA            <NA>           <NA>             
  2     dt    hms INT64          NA        REQUIRED    TIME_MICROS TIME, TR....
    num_children scale precision field_id
  1            1    NA        NA       NA
  2           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  $type
  [1] "TIME"

  $is_adjusted_to_utc
  [1] TRUE

  $unit
  [1] "MICROS"

  attr(,"class")
  [1] "nanoparquet_logical_type"

Code
  read_parquet_metadata(tmp)[["column_chunks"]][["encodings"]]
Output
  [[1]]
  [1] "PLAIN"          "RLE_DICTIONARY"

Code
  as.data.frame(read_parquet(tmp))
Output
          dt
  1 03:02:01
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name r_type  type type_length repetition_type converted_type logical_type
  1 schema   <NA>  <NA>          NA            <NA>           <NA>             
  2     dt    hms INT64          NA        REQUIRED           <NA> TIME, TR....
    num_children scale precision field_id
  1            1    NA        NA       NA
  2           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  $type
  [1] "TIME"

  $is_adjusted_to_utc
  [1] TRUE

  $unit
  [1] "NANOS"

  attr(,"class")
  [1] "nanoparquet_logical_type"

Code
  read_parquet_metadata(tmp)[["column_chunks"]][["encodings"]]
Output
  [[1]]
  [1] "PLAIN"          "RLE_DICTIONARY"

TIME_MILLIS, TIME_MICROS, dictionary

Code
  as.data.frame(read_parquet(tmp))
Output
          dt
  1 03:02:01
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name r_type  type type_length repetition_type converted_type logical_type
  1 schema   <NA>  <NA>          NA            <NA>           <NA>             
  2     dt    hms INT32          NA        REQUIRED    TIME_MILLIS             
    num_children scale precision field_id
  1            1    NA        NA       NA
  2           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  NULL

Code
  read_parquet_metadata(tmp)[["column_chunks"]][["encodings"]]
Output
  [[1]]
  [1] "PLAIN"          "RLE_DICTIONARY"

Code
  as.data.frame(read_parquet(tmp))
Output
          dt
  1 03:02:01
Code
  as.data.frame(read_parquet_schema(tmp))[, -1]
Output
      name r_type  type type_length repetition_type converted_type logical_type
  1 schema   <NA>  <NA>          NA            <NA>           <NA>             
  2     dt    hms INT64          NA        REQUIRED    TIME_MICROS             
    num_children scale precision field_id
  1            1    NA        NA       NA
  2           NA    NA        NA       NA
Code
  as.data.frame(read_parquet_schema(tmp))[["logical_type"]]
Output
  [[1]]
  NULL

  [[2]]
  NULL

Code
  read_parquet_metadata(tmp)[["column_chunks"]][["encodings"]]
Output
  [[1]]
  [1] "PLAIN"          "RLE_DICTIONARY"