**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)
```



{
    auto internal_type = std::make_shared<DataTypeDateTime>();
    auto internal_column = internal_type->createColumn();
    auto & column_data = assert_cast<ColumnVector<UInt32> &>(*internal_column).getData();
    column_data.reserve(arrow_column->length());
    for (size_t chunk_i = 0, num_chunks = static_cast<size_t>(arrow_column->num_chunks()); chunk_i < num_chunks; ++chunk_i)
    {
        auto & chunk = dynamic_cast<arrow::Date64Array &>(*(arrow_column->chunk(chunk_i)));
        for (size_t value_i = 0, length = static_cast<size_t>(chunk.length()); value_i < length; ++value_i)
        {
            auto timestamp = static_cast<UInt32>(chunk.Value(value_i) / 1000); 
            column_data.emplace_back(timestamp);
        }
    }
    return {std::move(internal_column), std::move(internal_type), column_name};
}
static ColumnWithTypeAndName readColumnWithTimestampData(std::shared_ptr<arrow::ChunkedArray> & arrow_column, const String & column_name)