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import { CpfpCluster, CpfpInfo, CpfpSummary, MempoolTransactionExtended, TransactionExtended } from '../mempool.interfaces';
import { GraphTx, convertToGraphTx, expandRelativesGraph, initializeRelatives, mempoolComparator, removeAncestors, setAncestorScores } from './mini-miner';
import memPool from './mempool';
const CPFP_UPDATE_INTERVAL = 60_000; // update CPFP info at most once per 60s per transaction
const MAX_CLUSTER_ITERATIONS = 100;
export function calculateFastBlockCpfp(height: number, transactions: TransactionExtended[], saveRelatives: boolean = false): CpfpSummary {
const clusters: CpfpCluster[] = []; // list of all cpfp clusters in this block
const clusterMap: { [txid: string]: CpfpCluster } = {}; // map transactions to their cpfp cluster
let clusterTxs: TransactionExtended[] = []; // working list of elements of the current cluster
let ancestors: { [txid: string]: boolean } = {}; // working set of ancestors of the current cluster root
const txMap: { [txid: string]: TransactionExtended } = {};
// initialize the txMap
for (const tx of transactions) {
txMap[tx.txid] = tx;
}
// reverse pass to identify CPFP clusters
for (let i = transactions.length - 1; i >= 0; i--) {
const tx = transactions[i];
if (!ancestors[tx.txid]) {
let totalFee = 0;
let totalVSize = 0;
clusterTxs.forEach(tx => {
totalFee += tx?.fee || 0;
totalVSize += (tx.weight / 4);
});
const effectiveFeePerVsize = totalFee / totalVSize;
let cluster: CpfpCluster;
if (clusterTxs.length > 1) {
cluster = {
root: clusterTxs[0].txid,
height,
txs: clusterTxs.map(tx => { return { txid: tx.txid, weight: tx.weight, fee: tx.fee || 0 }; }),
effectiveFeePerVsize,
};
clusters.push(cluster);
}
clusterTxs.forEach(tx => {
txMap[tx.txid].effectiveFeePerVsize = effectiveFeePerVsize;
if (cluster) {
clusterMap[tx.txid] = cluster;
}
});
// reset working vars
clusterTxs = [];
ancestors = {};
}
clusterTxs.push(tx);
tx.vin.forEach(vin => {
ancestors[vin.txid] = true;
});
}
// forward pass to enforce ancestor rate caps
for (const tx of transactions) {
let minAncestorRate = tx.effectiveFeePerVsize;
for (const vin of tx.vin) {
if (txMap[vin.txid]?.effectiveFeePerVsize) {
minAncestorRate = Math.min(minAncestorRate, txMap[vin.txid].effectiveFeePerVsize);
}
}
// check rounded values to skip cases with almost identical fees
const roundedMinAncestorRate = Math.ceil(minAncestorRate);
const roundedEffectiveFeeRate = Math.floor(tx.effectiveFeePerVsize);
if (roundedMinAncestorRate < roundedEffectiveFeeRate) {
tx.effectiveFeePerVsize = minAncestorRate;
if (!clusterMap[tx.txid]) {
// add a single-tx cluster to record the dependent rate
const cluster = {
root: tx.txid,
height,
txs: [{ txid: tx.txid, weight: tx.weight, fee: tx.fee || 0 }],
effectiveFeePerVsize: minAncestorRate,
};
clusterMap[tx.txid] = cluster;
clusters.push(cluster);
} else {
// update the existing cluster with the dependent rate
clusterMap[tx.txid].effectiveFeePerVsize = minAncestorRate;
}
}
}
if (saveRelatives) {
for (const cluster of clusters) {
cluster.txs.forEach((member, index) => {
txMap[member.txid].descendants = cluster.txs.slice(0, index).reverse();
txMap[member.txid].ancestors = cluster.txs.slice(index + 1).reverse();
txMap[member.txid].effectiveFeePerVsize = cluster.effectiveFeePerVsize;
});
}
}
return {
transactions,
clusters,
};
}
export function calculateGoodBlockCpfp(height: number, transactions: TransactionExtended[]): CpfpSummary {
return calculateFastBlockCpfp(height, transactions, true);
}
/**
* Takes a mempool transaction and a copy of the current mempool, and calculates the CPFP data for
* that transaction (and all others in the same cluster)
*/
export function calculateMempoolTxCpfp(tx: MempoolTransactionExtended, mempool: { [txid: string]: MempoolTransactionExtended }): CpfpInfo {
if (tx.cpfpUpdated && Date.now() < (tx.cpfpUpdated + CPFP_UPDATE_INTERVAL)) {
tx.cpfpDirty = false;
return {
ancestors: tx.ancestors || [],
bestDescendant: tx.bestDescendant || null,
descendants: tx.descendants || [],
effectiveFeePerVsize: tx.effectiveFeePerVsize || tx.adjustedFeePerVsize || tx.feePerVsize,
sigops: tx.sigops,
adjustedVsize: tx.adjustedVsize,
acceleration: tx.acceleration
};
}
const ancestorMap = new Map<string, GraphTx>();
const graphTx = convertToGraphTx(tx, memPool.getSpendMap());
ancestorMap.set(tx.txid, graphTx);
const allRelatives = expandRelativesGraph(mempool, ancestorMap, memPool.getSpendMap());
const relativesMap = initializeRelatives(allRelatives);
const cluster = calculateCpfpCluster(tx.txid, relativesMap);
let totalVsize = 0;
let totalFee = 0;
for (const tx of cluster.values()) {
totalVsize += tx.vsize;
totalFee += tx.fees.base;
}
const effectiveFeePerVsize = totalFee / totalVsize;
for (const tx of cluster.values()) {
mempool[tx.txid].effectiveFeePerVsize = effectiveFeePerVsize;
mempool[tx.txid].ancestors = Array.from(tx.ancestors.values()).map(tx => ({ txid: tx.txid, weight: tx.weight, fee: tx.fees.base }));
mempool[tx.txid].descendants = Array.from(cluster.values()).filter(entry => entry.txid !== tx.txid && !tx.ancestors.has(entry.txid)).map(tx => ({ txid: tx.txid, weight: tx.weight, fee: tx.fees.base }));
mempool[tx.txid].bestDescendant = null;
mempool[tx.txid].cpfpChecked = true;
mempool[tx.txid].cpfpDirty = true;
mempool[tx.txid].cpfpUpdated = Date.now();
}
tx = mempool[tx.txid];
return {
ancestors: tx.ancestors || [],
bestDescendant: tx.bestDescendant || null,
descendants: tx.descendants || [],
effectiveFeePerVsize: tx.effectiveFeePerVsize || tx.adjustedFeePerVsize || tx.feePerVsize,
sigops: tx.sigops,
adjustedVsize: tx.adjustedVsize,
acceleration: tx.acceleration
};
}
/**
* Given a root transaction and a list of in-mempool ancestors,
* Calculate the CPFP cluster
*
* @param tx
* @param ancestors
*/
function calculateCpfpCluster(txid: string, graph: Map<string, GraphTx>): Map<string, GraphTx> {
const tx = graph.get(txid);
if (!tx) {
return new Map<string, GraphTx>([]);
}
// Initialize individual & ancestor fee rates
graph.forEach(entry => setAncestorScores(entry));
// Sort by descending ancestor score
let sortedRelatives = Array.from(graph.values()).sort(mempoolComparator);
// Iterate until we reach a cluster that includes our target tx
let maxIterations = MAX_CLUSTER_ITERATIONS;
let best = sortedRelatives.shift();
let bestCluster = new Map<string, GraphTx>(best?.ancestors?.entries() || []);
while (sortedRelatives.length && best && (best.txid !== tx.txid && !best.ancestors.has(tx.txid)) && maxIterations > 0) {
maxIterations--;
if ((best && best.txid === tx.txid) || (bestCluster && bestCluster.has(tx.txid))) {
break;
} else {
// Remove this cluster (it doesn't include our target tx)
// and update scores, ancestor totals and dependencies for the survivors
removeAncestors(bestCluster, graph);
// re-sort
sortedRelatives = Array.from(graph.values()).sort(mempoolComparator);
// Grab the next highest scoring entry
best = sortedRelatives.shift();
if (best) {
bestCluster = new Map<string, GraphTx>(best?.ancestors?.entries() || []);
bestCluster.set(best?.txid, best);
}
}
}
bestCluster.set(tx.txid, tx);
return bestCluster;
}