HDFS-14904. Add Option to let Balancer prefer highly utilized nodes in each iteration (#2483). Contributed by Leon Gao.
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60201cbf69
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6ff2409b31
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@ -29,10 +29,12 @@ import java.util.Arrays;
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import java.util.Collection;
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import java.util.Collections;
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import java.util.Date;
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import java.util.HashMap;
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import java.util.HashSet;
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import java.util.Iterator;
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import java.util.LinkedList;
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import java.util.List;
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import java.util.Map;
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import java.util.Set;
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import java.util.concurrent.TimeUnit;
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@ -199,7 +201,10 @@ public class Balancer {
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+ "\tWhether to run the balancer during an ongoing HDFS upgrade."
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+ "This is usually not desired since it will not affect used space "
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+ "on over-utilized machines."
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+ "\n\t[-asService]\tRun as a long running service.";
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+ "\n\t[-asService]\tRun as a long running service."
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+ "\n\t[-sortTopNodes]"
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+ "\tSort datanodes based on the utilization so "
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+ "that highly utilized datanodes get scheduled first.";
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@VisibleForTesting
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private static volatile boolean serviceRunning = false;
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@ -215,6 +220,7 @@ public class Balancer {
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private final double threshold;
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private final long maxSizeToMove;
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private final long defaultBlockSize;
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private final boolean sortTopNodes;
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// all data node lists
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private final Collection<Source> overUtilized = new LinkedList<Source>();
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@ -328,6 +334,7 @@ public class Balancer {
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this.policy = p.getBalancingPolicy();
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this.sourceNodes = p.getSourceNodes();
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this.runDuringUpgrade = p.getRunDuringUpgrade();
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this.sortTopNodes = p.getSortTopNodes();
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this.maxSizeToMove = getLongBytes(conf,
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DFSConfigKeys.DFS_BALANCER_MAX_SIZE_TO_MOVE_KEY,
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@ -374,6 +381,8 @@ public class Balancer {
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policy.accumulateSpaces(r);
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}
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policy.initAvgUtilization();
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// Store the capacity % of over utilized nodes for sorting, if needed.
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Map<Source, Double> overUtilizedPercentage = new HashMap<>();
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// create network topology and classify utilization collections:
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// over-utilized, above-average, below-average and under-utilized.
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@ -409,6 +418,7 @@ public class Balancer {
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} else {
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overLoadedBytes += percentage2bytes(thresholdDiff, capacity);
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overUtilized.add(s);
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overUtilizedPercentage.put(s, utilization);
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}
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g = s;
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} else {
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@ -424,6 +434,10 @@ public class Balancer {
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}
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}
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if (sortTopNodes) {
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sortOverUtilized(overUtilizedPercentage);
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}
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logUtilizationCollections();
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Preconditions.checkState(dispatcher.getStorageGroupMap().size()
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@ -435,6 +449,21 @@ public class Balancer {
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return Math.max(overLoadedBytes, underLoadedBytes);
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}
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private void sortOverUtilized(Map<Source, Double> overUtilizedPercentage) {
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Preconditions.checkState(overUtilized instanceof List,
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"Collection overUtilized is not a List.");
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LOG.info("Sorting over-utilized nodes by capacity" +
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" to bring down top used datanode capacity faster");
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List<Source> list = (List<Source>) overUtilized;
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list.sort(
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(Source source1, Source source2) ->
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(Double.compare(overUtilizedPercentage.get(source2),
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overUtilizedPercentage.get(source1)))
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);
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}
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private static long computeMaxSize2Move(final long capacity, final long remaining,
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final double utilizationDiff, final long max) {
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final double diff = Math.abs(utilizationDiff);
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@ -961,6 +990,10 @@ public class Balancer {
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} else if ("-asService".equalsIgnoreCase(args[i])) {
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b.setRunAsService(true);
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LOG.info("Balancer will run as a long running service");
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} else if ("-sortTopNodes".equalsIgnoreCase(args[i])) {
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b.setSortTopNodes(true);
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LOG.info("Balancer will sort nodes by" +
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" capacity usage percentage to prioritize top used nodes");
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} else {
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throw new IllegalArgumentException("args = "
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+ Arrays.toString(args));
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@ -47,6 +47,8 @@ final class BalancerParameters {
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private final boolean runAsService;
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private final boolean sortTopNodes;
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static final BalancerParameters DEFAULT = new BalancerParameters();
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private BalancerParameters() {
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@ -63,6 +65,7 @@ final class BalancerParameters {
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this.blockpools = builder.blockpools;
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this.runDuringUpgrade = builder.runDuringUpgrade;
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this.runAsService = builder.runAsService;
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this.sortTopNodes = builder.sortTopNodes;
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}
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BalancingPolicy getBalancingPolicy() {
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@ -101,16 +104,21 @@ final class BalancerParameters {
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return this.runAsService;
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}
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boolean getSortTopNodes() {
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return this.sortTopNodes;
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}
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@Override
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public String toString() {
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return String.format("%s.%s [%s," + " threshold = %s,"
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+ " max idle iteration = %s," + " #excluded nodes = %s,"
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+ " #included nodes = %s," + " #source nodes = %s,"
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+ " #blockpools = %s," + " run during upgrade = %s]",
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+ " #blockpools = %s," + " run during upgrade = %s]"
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+ " sort top nodes = %s",
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Balancer.class.getSimpleName(), getClass().getSimpleName(), policy,
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threshold, maxIdleIteration, excludedNodes.size(),
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includedNodes.size(), sourceNodes.size(), blockpools.size(),
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runDuringUpgrade);
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runDuringUpgrade, sortTopNodes);
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}
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static class Builder {
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@ -125,6 +133,7 @@ final class BalancerParameters {
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private Set<String> blockpools = Collections.<String> emptySet();
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private boolean runDuringUpgrade = false;
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private boolean runAsService = false;
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private boolean sortTopNodes = false;
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Builder() {
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}
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@ -174,6 +183,11 @@ final class BalancerParameters {
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return this;
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}
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Builder setSortTopNodes(boolean shouldSortTopNodes) {
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this.sortTopNodes = shouldSortTopNodes;
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return this;
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}
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BalancerParameters build() {
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return new BalancerParameters(this);
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}
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@ -20,6 +20,7 @@ package org.apache.hadoop.hdfs.server.balancer;
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import static org.apache.hadoop.fs.CommonConfigurationKeys.IPC_CLIENT_CONNECT_MAX_RETRIES_ON_SASL_KEY;
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import static org.apache.hadoop.fs.StorageType.DEFAULT;
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import static org.apache.hadoop.fs.StorageType.RAM_DISK;
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import static org.apache.hadoop.hdfs.DFSConfigKeys.DFS_BALANCER_MAX_SIZE_TO_MOVE_KEY;
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import static org.apache.hadoop.hdfs.DFSConfigKeys.DFS_CLIENT_HTTPS_KEYSTORE_RESOURCE_KEY;
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import static org.apache.hadoop.hdfs.DFSConfigKeys.DFS_SERVER_HTTPS_KEYSTORE_RESOURCE_KEY;
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import static org.apache.hadoop.hdfs.client.HdfsClientConfigKeys.DFS_DATA_TRANSFER_PROTECTION_KEY;
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@ -46,6 +47,7 @@ import static org.apache.hadoop.hdfs.DFSConfigKeys.DFS_WEB_AUTHENTICATION_KERBER
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import static org.apache.hadoop.test.PlatformAssumptions.assumeNotWindows;
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import org.apache.hadoop.hdfs.protocol.ErasureCodingPolicy;
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import org.apache.hadoop.hdfs.server.datanode.DataNodeTestUtils;
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import org.junit.AfterClass;
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import static org.junit.Assert.assertEquals;
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import static org.junit.Assert.assertTrue;
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@ -2209,6 +2211,106 @@ public class TestBalancer {
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getBlocksMaxQps, getBlockCallsPerSecond <= getBlocksMaxQps);
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}
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@Test(timeout = 60000)
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public void testBalancerWithSortTopNodes() throws Exception {
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final Configuration conf = new HdfsConfiguration();
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initConf(conf);
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conf.setInt(DFS_HEARTBEAT_INTERVAL_KEY, 30000);
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final long capacity = 1000L;
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final int diffBetweenNodes = 50;
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// Set up the datanodes with two groups:
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// 5 over-utilized nodes with 80%, 85%, 90%, 95%, 100% usage
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// 2 under-utilizaed nodes with 0%, 5% usage
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// With sortTopNodes option, 100% and 95% used ones will be chosen.
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final int numOfOverUtilizedDn = 5;
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final int numOfUnderUtilizedDn = 2;
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final int totalNumOfDn = numOfOverUtilizedDn + numOfUnderUtilizedDn;
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final long[] capacityArray = new long[totalNumOfDn];
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Arrays.fill(capacityArray, capacity);
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cluster = new MiniDFSCluster.Builder(conf)
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.numDataNodes(totalNumOfDn)
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.simulatedCapacities(capacityArray)
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.build();
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cluster.setDataNodesDead();
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List<DataNode> dataNodes = cluster.getDataNodes();
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// Create top used nodes
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for (int i = 0; i < numOfOverUtilizedDn; i++) {
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// Bring one node alive
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DataNodeTestUtils.triggerHeartbeat(dataNodes.get(i));
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DataNodeTestUtils.triggerBlockReport(dataNodes.get(i));
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// Create nodes with: 80%, 85%, 90%, 95%, 100%.
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int capacityForThisDatanode = (int)capacity
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- diffBetweenNodes * (numOfOverUtilizedDn - i - 1);
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createFile(cluster, new Path("test_big" + i),
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capacityForThisDatanode, (short) 1, 0);
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cluster.setDataNodesDead();
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}
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// Create under utilized nodes
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for (int i = numOfUnderUtilizedDn - 1; i >= 0; i--) {
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int index = i + numOfOverUtilizedDn;
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// Bring one node alive
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DataNodeTestUtils.triggerHeartbeat(dataNodes.get(index));
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DataNodeTestUtils.triggerBlockReport(dataNodes.get(index));
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// Create nodes with: 5%, 0%
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int capacityForThisDatanode = diffBetweenNodes * i;
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createFile(cluster,
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new Path("test_small" + i),
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capacityForThisDatanode, (short) 1, 0);
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cluster.setDataNodesDead();
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}
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// Bring all nodes alive
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cluster.triggerHeartbeats();
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cluster.triggerBlockReports();
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cluster.waitFirstBRCompleted(0, 6000);
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final BalancerParameters p = Balancer.Cli.parse(new String[] {
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"-policy", BalancingPolicy.Node.INSTANCE.getName(),
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"-threshold", "1",
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"-sortTopNodes"
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});
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client = NameNodeProxies.createProxy(conf,
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cluster.getFileSystem(0).getUri(),
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ClientProtocol.class).getProxy();
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// Set max-size-to-move to small number
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// so only top two nodes will be chosen in one iteration.
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conf.setLong(DFS_BALANCER_MAX_SIZE_TO_MOVE_KEY, 99L);
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final Collection<URI> namenodes = DFSUtil.getInternalNsRpcUris(conf);
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List<NameNodeConnector> connectors = NameNodeConnector
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.newNameNodeConnectors(namenodes,
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Balancer.class.getSimpleName(), Balancer.BALANCER_ID_PATH, conf,
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BalancerParameters.DEFAULT.getMaxIdleIteration());
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final Balancer b = new Balancer(connectors.get(0), p, conf);
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Result balancerResult = b.runOneIteration();
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cluster.triggerDeletionReports();
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cluster.triggerBlockReports();
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cluster.triggerHeartbeats();
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DatanodeInfo[] datanodeReport = client
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.getDatanodeReport(DatanodeReportType.ALL);
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long maxUsage = 0;
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for (int i = 0; i < totalNumOfDn; i++) {
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maxUsage = Math.max(maxUsage, datanodeReport[i].getDfsUsed());
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}
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assertEquals(200, balancerResult.bytesAlreadyMoved);
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// 100% and 95% used nodes will be balanced, so top used will be 900
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assertEquals(900, maxUsage);
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}
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/**
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* @param args
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*/
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