When the mempool fills the verbose `getrawmempool` RPC call gets really slow.  It can take minutes for >100k transactions in the mempool.

The culprit is the univalue library.  Objects are implemented as a big list, but the library checks for duplicate keys.  So inserting n key-value pairs into an object takes O(n^2).

Possible fixes:

- Improve univalue library by using linked hash maps.
- change the RPC output format of getrawmempool to use a list of objects, instead of an object of objects.  But this breaks existing code.
- hack the library to be able to skip the duplicate check.

int nTxDiff = pindex->nChainTx - pindexPast->nChainTx;
    UniValue ret(UniValue::VOBJ);
    ret.pushKV("time", (int64_t)pindex->nTime);
    ret.pushKV("txcount", (int64_t)pindex->nChainTx);
    ret.pushKV("window_final_block_hash", pindex->GetBlockHash().GetHex());
    ret.pushKV("window_block_count", blockcount);
    if (blockcount > 0) {
        ret.pushKV("window_tx_count", nTxDiff);
        ret.pushKV("window_interval", nTimeDiff);
        if (nTimeDiff > 0) {
            ret.pushKV("txrate", ((double)nTxDiff) / nTimeDiff);
        }
    }
    return ret;
}
template<typename T>
static T CalculateTruncatedMedian(std::vector<T>& scores)
{
    size_t size = scores.size();
    if (size == 0) {
        return 0;
    }
    std::sort(scores.begin(), scores.end());
    if (size % 2 == 0) {
        return (scores[size / 2 - 1] + scores[size / 2]) / 2;
    } else {
        return scores[size / 2];
    }
}
void CalculatePercentilesByWeight(CAmount result[NUM_GETBLOCKSTATS_PERCENTILES], std::vector<std::pair<CAmount, int64_t>>& scores, int64_t total_weight)