**Describe the unexpected behaviour**
Clickhouse does not support parquet with 'large_utf8' columns (only 'utf8'). From my understanding, the only difference is offsets are u64 in 'large_utf8' instead of u32

**How to reproduce**

```
import pyarrow
import pyarrow.parquet
import subprocess


for schema in (None,pyarrow.schema({"a": pyarrow.large_utf8()})):
    a = pyarrow.table({"a": ["00000"]}, schema=schema)
    pyarrow.parquet.write_table(a, "test.parquet")
    subprocess.run(
        """cat test.parquet | clickhouse local \
            --input-format "Parquet" \
            --structure "a String" \
            --query "select * from table"\
        """,
        shell=True,
        check=True,
    )

```
gives
```
00000
Code: 50. DB::Exception: Unsupported Parquet type 'large_utf8' of an input column 'a'.: While executing ParquetBlockInputFormat: While executing File. (UNKNOWN_TYPE)
```



if (name_to_column_ptr.contains(search_nested_table_name))
                {
                    if (!nested_tables.contains(search_nested_table_name))
                    {
                        std::shared_ptr<arrow::ChunkedArray> arrow_column = name_to_column_ptr[search_nested_table_name];
                        ColumnsWithTypeAndName cols = {readColumnFromArrowColumn(
                            arrow_column, nested_table_name, format_name, false, dictionary_values, true, true, false, skipped)};
                        BlockPtr block_ptr = std::make_shared<Block>(cols);
                        auto column_extractor = std::make_shared<NestedColumnExtractHelper>(*block_ptr, case_insensitive_matching);
                        nested_tables[search_nested_table_name] = {block_ptr, column_extractor};
                    }
                    auto nested_column = nested_tables[search_nested_table_name].second->extractColumn(search_column_name);
                    if (nested_column)
                    {
                        column = *nested_column;
                        if (case_insensitive_matching)
                            column.name = header_column.name;
                        read_from_nested = true;
                    }
                }
            }
            if (!read_from_nested)
            {
                if (!allow_missing_columns)
                    throw Exception{ErrorCodes::THERE_IS_NO_COLUMN, "Column '{}' is not presented in input data.", header_column.name};
                else
                {
                    column.name = header_column.name;
                    column.type = header_column.type;
                    column.column = header_column.column->cloneResized(num_rows);