**Describe the bug**

Since we upgraded to 20.10.3.30, one of our clickhouse cluster takes much more time to start. (Up to 50 minutes, and before it took ~3 minutes)
The log file is filled with
>  <Debug> DiskLocal: Reserving 1.00 MiB on disk `default`, having unreserved 16.90 TiB

Additionally, the memory consumption increases, linearly, a lot (up to arround 230 G for us) and then drop back to normal values once clickhouse finished starting up. During that loading phase, a single CPU core is used at 100%.
If that memory is not available for the machine, clickhouse gets OOMed by the kernel.


**How to reproduce**
* Issue appeared after we upgraded to ClickHouse server version 20.10.3.30

* How could I find wich of our tables may be responsible for that ?


**Expected behavior**
A fast startup :)

if (minmax_count_projection_candidate->prewhere_info)
        {
            const auto & prewhere_info = minmax_count_projection_candidate->prewhere_info;
            if (prewhere_info->row_level_filter)
            {
                ExpressionActions(prewhere_info->row_level_filter, actions_settings).execute(query_info.minmax_count_projection_block);
                query_info.minmax_count_projection_block.erase(prewhere_info->row_level_column_name);
            }
            if (prewhere_info->prewhere_actions)
                ExpressionActions(prewhere_info->prewhere_actions, actions_settings).execute(query_info.minmax_count_projection_block);
            if (prewhere_info->remove_prewhere_column)
                query_info.minmax_count_projection_block.erase(prewhere_info->prewhere_column_name);
        }
        if (normal_parts.empty())
        {
            selected_candidate = &*minmax_count_projection_candidate;
            selected_candidate->complete = true;
            min_sum_marks = query_info.minmax_count_projection_block.rows();
        }
        else if (normal_parts.size() < parts.size())
        {
            auto normal_result_ptr = reader.estimateNumMarksToRead(
                normal_parts,
                analysis_result.required_columns,
                metadata_snapshot,
                metadata_snapshot,
                query_info,
                added_filter_nodes,
                query_context,
                settings.max_threads,