org.apache.hadoop.hdfs.net.DFSNetworkTopology Maven / Gradle / Ivy
Go to download
Show more of this group Show more artifacts with this name
Show all versions of hadoop-apache Show documentation
Show all versions of hadoop-apache Show documentation
Shaded version of Apache Hadoop for Presto
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.hadoop.hdfs.net;
import io.prestosql.hadoop.$internal.com.google.common.annotations.VisibleForTesting;
import io.prestosql.hadoop.$internal.com.google.common.base.Preconditions;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.StorageType;
import org.apache.hadoop.hdfs.DFSConfigKeys;
import org.apache.hadoop.hdfs.protocol.DatanodeInfo;
import org.apache.hadoop.hdfs.server.blockmanagement.DatanodeDescriptor;
import org.apache.hadoop.net.NetworkTopology;
import org.apache.hadoop.net.Node;
import org.apache.hadoop.net.NodeBase;
import org.apache.hadoop.util.ReflectionUtils;
import java.util.ArrayList;
import java.util.Collection;
import java.util.Random;
/**
* The HDFS specific network topology class. The main purpose of doing this
* subclassing is to add storage-type-aware chooseRandom method. All the
* remaining parts should be the same.
*
* Currently a placeholder to test storage type info.
*/
public class DFSNetworkTopology extends NetworkTopology {
private static final Random RANDOM = new Random();
public static DFSNetworkTopology getInstance(Configuration conf) {
DFSNetworkTopology nt = ReflectionUtils.newInstance(conf.getClass(
DFSConfigKeys.DFS_NET_TOPOLOGY_IMPL_KEY,
DFSConfigKeys.DFS_NET_TOPOLOGY_IMPL_DEFAULT,
DFSNetworkTopology.class), conf);
return (DFSNetworkTopology) nt.init(DFSTopologyNodeImpl.FACTORY);
}
/**
* Randomly choose one node from scope, with specified storage type.
*
* If scope starts with ~, choose one from the all nodes except for the
* ones in scope; otherwise, choose one from scope.
* If excludedNodes is given, choose a node that's not in excludedNodes.
*
* @param scope range of nodes from which a node will be chosen
* @param excludedNodes nodes to be excluded from
* @param type the storage type we search for
* @return the chosen node
*/
public Node chooseRandomWithStorageType(final String scope,
final Collection excludedNodes, StorageType type) {
netlock.readLock().lock();
try {
if (scope.startsWith("~")) {
return chooseRandomWithStorageType(
NodeBase.ROOT, scope.substring(1), excludedNodes, type);
} else {
return chooseRandomWithStorageType(
scope, null, excludedNodes, type);
}
} finally {
netlock.readLock().unlock();
}
}
/**
* Randomly choose one node from scope with the given storage type.
*
* If scope starts with ~, choose one from the all nodes except for the
* ones in scope; otherwise, choose one from scope.
* If excludedNodes is given, choose a node that's not in excludedNodes.
*
* This call would make up to two calls. It first tries to get a random node
* (with old method) and check if it satisfies. If yes, simply return it.
* Otherwise, it make a second call (with the new method) by passing in a
* storage type.
*
* This is for better performance reason. Put in short, the key note is that
* the old method is faster but may take several runs, while the new method
* is somewhat slower, and always succeed in one trial.
* See HDFS-11535 for more detail.
*
* @param scope range of nodes from which a node will be chosen
* @param excludedNodes nodes to be excluded from
* @param type the storage type we search for
* @return the chosen node
*/
public Node chooseRandomWithStorageTypeTwoTrial(final String scope,
final Collection excludedNodes, StorageType type) {
netlock.readLock().lock();
try {
String searchScope;
String excludedScope;
if (scope.startsWith("~")) {
searchScope = NodeBase.ROOT;
excludedScope = scope.substring(1);
} else {
searchScope = scope;
excludedScope = null;
}
// next do a two-trial search
// first trial, call the old method, inherited from NetworkTopology
Node n = chooseRandom(searchScope, excludedScope, excludedNodes);
if (n == null) {
if (LOG.isDebugEnabled()) {
LOG.debug("No node to choose.");
}
// this means there is simply no node to choose from
return null;
}
Preconditions.checkArgument(n instanceof DatanodeDescriptor);
DatanodeDescriptor dnDescriptor = (DatanodeDescriptor)n;
if (dnDescriptor.hasStorageType(type)) {
// the first trial succeeded, just return
return dnDescriptor;
} else {
// otherwise, make the second trial by calling the new method
LOG.debug("First trial failed, node has no type {}, " +
"making second trial carrying this type", type);
return chooseRandomWithStorageType(searchScope, excludedScope,
excludedNodes, type);
}
} finally {
netlock.readLock().unlock();
}
}
/**
* Choose a random node based on given scope, excludedScope and excludedNodes
* set. Although in general the topology has at most three layers, this class
* will not impose such assumption.
*
* At high level, the idea is like this, say:
*
* R has two children A and B, and storage type is X, say:
* A has X = 6 (rooted at A there are 6 datanodes with X) and B has X = 8.
*
* Then R will generate a random int between 1~14, if it's <= 6, recursively
* call into A, otherwise B. This will maintain a uniformed randomness of
* choosing datanodes.
*
* The tricky part is how to handle excludes.
*
* For excludedNodes, since this set is small: currently the main reason of
* being an excluded node is because it already has a replica. So randomly
* picking up this node again should be rare. Thus we only check that, if the
* chosen node is excluded, we do chooseRandom again.
*
* For excludedScope, we locate the root of the excluded scope. Subtracting
* all it's ancestors' storage counters accordingly, this way the excluded
* root is out of the picture.
*
* @param scope the scope where we look for node.
* @param excludedScope the scope where the node must NOT be from.
* @param excludedNodes the returned node must not be in this set
* @return a node with required storage type
*/
@VisibleForTesting
Node chooseRandomWithStorageType(final String scope,
String excludedScope, final Collection excludedNodes,
StorageType type) {
if (excludedScope != null) {
if (scope.startsWith(excludedScope)) {
return null;
}
if (!excludedScope.startsWith(scope)) {
excludedScope = null;
}
}
Node node = getNode(scope);
if (node == null) {
LOG.debug("Invalid scope {}, non-existing node", scope);
return null;
}
if (!(node instanceof DFSTopologyNodeImpl)) {
// a node is either DFSTopologyNodeImpl, or a DatanodeDescriptor
return ((DatanodeDescriptor)node).hasStorageType(type) ? node : null;
}
DFSTopologyNodeImpl root = (DFSTopologyNodeImpl)node;
Node excludeRoot = excludedScope == null ? null : getNode(excludedScope);
// check to see if there are nodes satisfying the condition at all
int availableCount = root.getSubtreeStorageCount(type);
if (excludeRoot != null && root.isAncestor(excludeRoot)) {
if (excludeRoot instanceof DFSTopologyNodeImpl) {
availableCount -= ((DFSTopologyNodeImpl)excludeRoot)
.getSubtreeStorageCount(type);
} else {
availableCount -= ((DatanodeDescriptor)excludeRoot)
.hasStorageType(type) ? 1 : 0;
}
}
if (excludedNodes != null) {
for (Node excludedNode : excludedNodes) {
if (excludedNode instanceof DatanodeDescriptor) {
availableCount -= ((DatanodeDescriptor) excludedNode)
.hasStorageType(type) ? 1 : 0;
} else if (excludedNode instanceof DFSTopologyNodeImpl) {
availableCount -= ((DFSTopologyNodeImpl) excludedNode)
.getSubtreeStorageCount(type);
} else if (excludedNode instanceof DatanodeInfo) {
// find out the corresponding DatanodeDescriptor object, beacuse
// we need to get its storage type info.
// could be expensive operation, fortunately the size of excluded
// nodes set is supposed to be very small.
String nodeLocation = excludedNode.getNetworkLocation()
+ "/" + excludedNode.getName();
DatanodeDescriptor dn = (DatanodeDescriptor)getNode(nodeLocation);
availableCount -= dn.hasStorageType(type)? 1 : 0;
} else {
LOG.error("Unexpected node type: {}.", excludedNode.getClass());
}
}
}
if (availableCount <= 0) {
// should never be <0 in general, adding <0 check for safety purpose
return null;
}
// to this point, it is guaranteed that there is at least one node
// that satisfies the requirement, keep trying until we found one.
Node chosen;
do {
chosen = chooseRandomWithStorageTypeAndExcludeRoot(root, excludeRoot,
type);
if (excludedNodes == null || !excludedNodes.contains(chosen)) {
break;
} else {
LOG.debug("Node {} is excluded, continuing.", chosen);
}
} while (true);
LOG.debug("chooseRandom returning {}", chosen);
return chosen;
}
/**
* Choose a random node that has the required storage type, under the given
* root, with an excluded subtree root (could also just be a leaf node).
*
* Note that excludedNode is checked after a random node, so it is not being
* handled here.
*
* @param root the root node where we start searching for a datanode
* @param excludeRoot the root of the subtree what should be excluded
* @param type the expected storage type
* @return a random datanode, with the storage type, and is not in excluded
* scope
*/
private Node chooseRandomWithStorageTypeAndExcludeRoot(
DFSTopologyNodeImpl root, Node excludeRoot, StorageType type) {
Node chosenNode;
if (root.isRack()) {
// children are datanode descriptor
ArrayList candidates = new ArrayList<>();
for (Node node : root.getChildren()) {
if (node.equals(excludeRoot)) {
continue;
}
DatanodeDescriptor dnDescriptor = (DatanodeDescriptor)node;
if (dnDescriptor.hasStorageType(type)) {
candidates.add(node);
}
}
if (candidates.size() == 0) {
return null;
}
// to this point, all nodes in candidates are valid choices, and they are
// all datanodes, pick a random one.
chosenNode = candidates.get(RANDOM.nextInt(candidates.size()));
} else {
// the children are inner nodes
ArrayList candidates =
getEligibleChildren(root, excludeRoot, type);
if (candidates.size() == 0) {
return null;
}
// again, all children are also inner nodes, we can do this cast.
// to maintain uniformality, the search needs to be based on the counts
// of valid datanodes. Below is a random weighted choose.
int totalCounts = 0;
int[] countArray = new int[candidates.size()];
for (int i = 0; i < candidates.size(); i++) {
DFSTopologyNodeImpl innerNode = candidates.get(i);
int subTreeCount = innerNode.getSubtreeStorageCount(type);
totalCounts += subTreeCount;
countArray[i] = subTreeCount;
}
// generate a random val between [1, totalCounts]
int randomCounts = RANDOM.nextInt(totalCounts) + 1;
int idxChosen = 0;
// searching for the idxChosen can potentially be done with binary
// search, but does not seem to worth it here.
for (int i = 0; i < countArray.length; i++) {
if (randomCounts <= countArray[i]) {
idxChosen = i;
break;
}
randomCounts -= countArray[i];
}
DFSTopologyNodeImpl nextRoot = candidates.get(idxChosen);
chosenNode = chooseRandomWithStorageTypeAndExcludeRoot(
nextRoot, excludeRoot, type);
}
return chosenNode;
}
/**
* Given root, excluded root and storage type. Find all the children of the
* root, that has the storage type available. One check is that if the
* excluded root is under a children, this children must subtract the storage
* count of the excluded root.
* @param root the subtree root we check.
* @param excludeRoot the root of the subtree that should be excluded.
* @param type the storage type we look for.
* @return a list of possible nodes, each of them is eligible as the next
* level root we search.
*/
private ArrayList getEligibleChildren(
DFSTopologyNodeImpl root, Node excludeRoot, StorageType type) {
ArrayList candidates = new ArrayList<>();
int excludeCount = 0;
if (excludeRoot != null && root.isAncestor(excludeRoot)) {
// the subtree to be excluded is under the given root,
// find out the number of nodes to be excluded.
if (excludeRoot instanceof DFSTopologyNodeImpl) {
// if excludedRoot is an inner node, get the counts of all nodes on
// this subtree of that storage type.
excludeCount = ((DFSTopologyNodeImpl) excludeRoot)
.getSubtreeStorageCount(type);
} else {
// if excludedRoot is a datanode, simply ignore this one node
if (((DatanodeDescriptor) excludeRoot).hasStorageType(type)) {
excludeCount = 1;
}
}
}
// have calculated the number of storage counts to be excluded.
// walk through all children to check eligibility.
for (Node node : root.getChildren()) {
DFSTopologyNodeImpl dfsNode = (DFSTopologyNodeImpl) node;
int storageCount = dfsNode.getSubtreeStorageCount(type);
if (excludeRoot != null && excludeCount != 0 &&
(dfsNode.isAncestor(excludeRoot) || dfsNode.equals(excludeRoot))) {
storageCount -= excludeCount;
}
if (storageCount > 0) {
candidates.add(dfsNode);
}
}
return candidates;
}
}