```py
## writing ArrowStream file from python
import pyarrow as pa
data = [
    pa.array([1, 2, 3, 4, 5]),
    pa.array(["one", "two", "three", "four", "five"]).dictionary_encode(),
    pa.array([1, 2, 3, 4, 5]).dictionary_encode(),
    pa.array([True, False, True, True, True])
]
batch = pa.record_batch(data, names=['id', 'lc_nullable', 'lc_int_nullable', 'bool_nullable'])
writer = pa.ipc.new_stream("test4.arrows", batch.schema)
writer.write_batch(batch)
writer.close()
```

```
clickhouse-local --query='SELECT * FROM table FORMAT TSVWithNamesAndTypes' --stacktrace --input-format=ArrowStream < test4.arrows
id	lc_nullable	lc_int_nullable	bool_nullable
Nullable(Int64)	LowCardinality(Nullable(String))	LowCardinality(Nullable(Int64))	Nullable(UInt8)
1		0	1
2	one	1	0
3	two	2	1
4	three	3	1
5	four	4	1
```

0 in LowCardianality dictionary in ClickHouse have special meaning (null/default), while in Arrow it's a regular values.

Probably remapping needed... :|
{
            auto arrow_nested_column = getNestedArrowColumn(arrow_column);
            auto nested_column = readColumnFromArrowColumn(arrow_nested_column, column_name, format_name, false, dictionary_values, read_ints_as_dates, allow_null_type, skip_columns_with_unsupported_types, skipped);
            if (skipped)
                return {};
            auto offsets_column = readOffsetsFromArrowListColumn(arrow_column);
            const auto * tuple_column = assert_cast<const ColumnTuple *>(nested_column.column.get());
            const auto * tuple_type = assert_cast<const DataTypeTuple *>(nested_column.type.get());
            auto map_column = ColumnMap::create(tuple_column->getColumnPtr(0), tuple_column->getColumnPtr(1), offsets_column);
            auto map_type = std::make_shared<DataTypeMap>(tuple_type->getElements()[0], tuple_type->getElements()[1]);
            return {std::move(map_column), std::move(map_type), column_name};
        }
        case arrow::Type::LIST:
        {
            auto arrow_nested_column = getNestedArrowColumn(arrow_column);
            auto nested_column = readColumnFromArrowColumn(arrow_nested_column, column_name, format_name, false, dictionary_values, read_ints_as_dates, allow_null_type, skip_columns_with_unsupported_types, skipped);
            if (skipped)
                return {};
            auto offsets_column = readOffsetsFromArrowListColumn(arrow_column);
            auto array_column = ColumnArray::create(nested_column.column, offsets_column);
            auto array_type = std::make_shared<DataTypeArray>(nested_column.type);
            return {std::move(array_column), std::move(array_type), column_name};
        }
        case arrow::Type::STRUCT:
        {
            auto arrow_type = arrow_column->type();
            auto * arrow_struct_type = assert_cast<arrow::StructType *>(arrow_type.get());
            std::vector<arrow::ArrayVector> nested_arrow_columns(arrow_struct_type->num_fields());
            for (size_t chunk_i = 0, num_chunks = static_cast<size_t>(arrow_column->num_chunks()); chunk_i < num_chunks; ++chunk_i)
            {