[PYTHON] Add `nan_count` to `RowGroupMetaData`

[Fokko]

Describe the enhancement requested

Iceberg relies on statistics (called Metrics in Iceberg) to speed up the queries. Most of the metrics are available and can be easily extracted using the MetadataCollector, except for the NaN counts. If someone does an isNaN expression on a FLOAT/DOUBLE field, Iceberg tries to skip Parquet files by looking at the metrics that it has stored in the manifest files. It would be awesome if next to null_count also nan_count can be added:

➜  Desktop python3 
Python 3.11.3 (main, Apr  7 2023, 20:13:31) [Clang 14.0.0 (clang-1400.0.29.202)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import pyarrow as pa
>>> table = pa.table({'n_legs': [2, 2, 4, 4, 5, 100],
...                   'animal': ["Flamingo", "Parrot", "Dog", "Horse",
...                              "Brittle stars", "Centipede"]})
>>> metadata_collector = []
>>> import pyarrow.parquet as pq
>>> pq.write_to_dataset(
...     table, '/tmp/table',
...      metadata_collector=metadata_collector)
>>> metadata_collector
[<pyarrow._parquet.FileMetaData object at 0x11f955850>
  created_by: parquet-cpp-arrow version 11.0.0
  num_columns: 2
  num_rows: 6
  num_row_groups: 1
  format_version: 1.0
  serialized_size: 0]

>>> metadata_collector[0].row_group(0)
<pyarrow._parquet.RowGroupMetaData object at 0x105837d80>
  num_columns: 2
  num_rows: 6
  total_byte_size: 256

>>> metadata_collector[0].row_group(0).to_dict()
{
	'num_columns': 2,
	'num_rows': 6,
	'total_byte_size': 256,
	'columns': [{
		'file_offset': 119,
		'file_path': 'c569c5eaf90c4395885f31e012068b69-0.parquet',
		'physical_type': 'INT64',
		'num_values': 6,
		'path_in_schema': 'n_legs',
		'is_stats_set': True,
		'statistics': {
			'has_min_max': True,
			'min': 2,
			'max': 100,
			'null_count': 0,
			'distinct_count': 0,
			'num_values': 6,
			'physical_type': 'INT64'
		},
		'compression': 'SNAPPY',
		'encodings': ('PLAIN_DICTIONARY', 'PLAIN', 'RLE'),
		'has_dictionary_page': True,
		'dictionary_page_offset': 4,
		'data_page_offset': 46,
		'total_compressed_size': 115,
		'total_uncompressed_size': 117
	}, {
		'file_offset': 359,
		'file_path': 'c569c5eaf90c4395885f31e012068b69-0.parquet',
		'physical_type': 'BYTE_ARRAY',
		'num_values': 6,
		'path_in_schema': 'animal',
		'is_stats_set': True,
		'statistics': {
			'has_min_max': True,
			'min': 'Brittle stars',
			'max': 'Parrot',
			'null_count': 0,
			'distinct_count': 0,
			'num_values': 6,
			'physical_type': 'BYTE_ARRAY'
		},
		'compression': 'SNAPPY',
		'encodings': ('PLAIN_DICTIONARY', 'PLAIN', 'RLE'),
		'has_dictionary_page': True,
		'dictionary_page_offset': 215,
		'data_page_offset': 302,
		'total_compressed_size': 144,
		'total_uncompressed_size': 139
	}]
}

In addition to this, Parquet itself is also looking into this: apache/parquet-format#196

Component(s)

Python

[mapleFU]

https://github.com/apache/parquet-format/blob/master/src/main/thrift/parquet.thrift#L888
Seems currently we don't have a nan-count here?

[Fokko]

@mapleFU That's right, that's being introduced in apache/parquet-format#196. In the Iceberg spec it is already there (and implemented many times), the field is called nan_value_counts.

[wgtmac]

@Fokko Did you have any comment or suggestion on the proposal you mentioned above? It would be great if it can align with the requirement from Apache Iceberg.