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Posted to commits@hbase.apache.org by sy...@apache.org on 2017/03/20 17:41:43 UTC
[10/28] hbase git commit: HBASE-17707 New More Accurate Table Skew
cost function/generator - revert due to test failure
HBASE-17707 New More Accurate Table Skew cost function/generator - revert due to test failure
Project: http://git-wip-us.apache.org/repos/asf/hbase/repo
Commit: http://git-wip-us.apache.org/repos/asf/hbase/commit/0ed50f42
Tree: http://git-wip-us.apache.org/repos/asf/hbase/tree/0ed50f42
Diff: http://git-wip-us.apache.org/repos/asf/hbase/diff/0ed50f42
Branch: refs/heads/hbase-12439
Commit: 0ed50f42e71599a86738643822e1ec4f2e432026
Parents: a69c23a
Author: tedyu <yu...@gmail.com>
Authored: Thu Mar 16 19:08:45 2017 -0700
Committer: tedyu <yu...@gmail.com>
Committed: Thu Mar 16 19:08:45 2017 -0700
----------------------------------------------------------------------
.../hbase/master/balancer/BaseLoadBalancer.java | 74 ----
.../master/balancer/StochasticLoadBalancer.java | 441 +------------------
.../balancer/TestStochasticLoadBalancer.java | 35 +-
.../balancer/TestStochasticLoadBalancer2.java | 4 -
4 files changed, 5 insertions(+), 549 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/hbase/blob/0ed50f42/hbase-server/src/main/java/org/apache/hadoop/hbase/master/balancer/BaseLoadBalancer.java
----------------------------------------------------------------------
diff --git a/hbase-server/src/main/java/org/apache/hadoop/hbase/master/balancer/BaseLoadBalancer.java b/hbase-server/src/main/java/org/apache/hadoop/hbase/master/balancer/BaseLoadBalancer.java
index b0e088c..0f1b1a2 100644
--- a/hbase-server/src/main/java/org/apache/hadoop/hbase/master/balancer/BaseLoadBalancer.java
+++ b/hbase-server/src/main/java/org/apache/hadoop/hbase/master/balancer/BaseLoadBalancer.java
@@ -53,7 +53,6 @@ import org.apache.hadoop.hbase.master.RackManager;
import org.apache.hadoop.hbase.master.RegionPlan;
import org.apache.hadoop.hbase.master.balancer.BaseLoadBalancer.Cluster.Action.Type;
import org.apache.hadoop.hbase.security.access.AccessControlLists;
-import org.apache.hadoop.hbase.util.Pair;
import org.apache.hadoop.util.StringUtils;
import com.google.common.annotations.VisibleForTesting;
@@ -141,7 +140,6 @@ public abstract class BaseLoadBalancer implements LoadBalancer {
int[] initialRegionIndexToServerIndex; //regionIndex -> serverIndex (initial cluster state)
int[] regionIndexToTableIndex; //regionIndex -> tableIndex
int[][] numRegionsPerServerPerTable; //serverIndex -> tableIndex -> # regions
- int[] numRegionsPerTable; // tableIndex -> number of regions that table has
int[] numMaxRegionsPerTable; //tableIndex -> max number of regions in a single RS
int[] regionIndexToPrimaryIndex; //regionIndex -> regionIndex of the primary
boolean hasRegionReplicas = false; //whether there is regions with replicas
@@ -332,7 +330,6 @@ public abstract class BaseLoadBalancer implements LoadBalancer {
numTables = tables.size();
numRegionsPerServerPerTable = new int[numServers][numTables];
- numRegionsPerTable = new int[numTables];
for (int i = 0; i < numServers; i++) {
for (int j = 0; j < numTables; j++) {
@@ -342,7 +339,6 @@ public abstract class BaseLoadBalancer implements LoadBalancer {
for (int i=0; i < regionIndexToServerIndex.length; i++) {
if (regionIndexToServerIndex[i] >= 0) {
- numRegionsPerTable[regionIndexToTableIndex[i]]++;
numRegionsPerServerPerTable[regionIndexToServerIndex[i]][regionIndexToTableIndex[i]]++;
}
}
@@ -474,76 +470,6 @@ public abstract class BaseLoadBalancer implements LoadBalancer {
}
}
- /**
- * Returns the minimum number of regions of a table T each server would store if T were
- * perfectly distributed (i.e. round-robin-ed) across the cluster
- */
- public int minRegionsIfEvenlyDistributed(int table) {
- return numRegionsPerTable[table] / numServers;
- }
-
- /**
- * Returns the maximum number of regions of a table T each server would store if T were
- * perfectly distributed (i.e. round-robin-ed) across the cluster
- */
- public int maxRegionsIfEvenlyDistributed(int table) {
- int min = minRegionsIfEvenlyDistributed(table);
- return numRegionsPerTable[table] % numServers == 0 ? min : min + 1;
- }
-
- /**
- * Returns the number of servers that should hold maxRegionsIfEvenlyDistributed for a given
- * table. A special case here is if maxRegionsIfEvenlyDistributed == minRegionsIfEvenlyDistributed,
- * in which case all servers should hold the max
- */
- public int numServersWithMaxRegionsIfEvenlyDistributed(int table) {
- int numWithMax = numRegionsPerTable[table] % numServers;
- if (numWithMax == 0) {
- return numServers;
- } else {
- return numWithMax;
- }
- }
-
- /**
- * Returns true iff at least one server in the cluster stores either more than the min/max load
- * per server when all regions are evenly distributed across the cluster
- */
- public boolean hasUnevenRegionDistribution() {
- int minLoad = numRegions / numServers;
- int maxLoad = numRegions % numServers == 0 ? minLoad : minLoad + 1;
- for (int server = 0; server < numServers; server++) {
- int numRegions = getNumRegions(server);
- if (numRegions > maxLoad || numRegions < minLoad) {
- return true;
- }
- }
- return false;
- }
-
- /**
- * Returns a pair where the first server is that with the least number of regions across the
- * cluster and the second server is that with the most number of regions across the cluster
- */
- public Pair<Integer, Integer> findLeastAndMostLoadedServers() {
- int minServer = 0;
- int maxServer = 0;
- int minLoad = getNumRegions(minServer);
- int maxLoad = minLoad;
- for (int server = 1; server < numServers; server++) {
- int numRegions = getNumRegions(server);
- if (numRegions < minLoad) {
- minServer = server;
- minLoad = numRegions;
- }
- if (numRegions > maxLoad) {
- maxServer = server;
- maxLoad = numRegions;
- }
- }
- return Pair.newPair(minServer, maxServer);
- }
-
/** An action to move or swap a region */
public static class Action {
public static enum Type {
http://git-wip-us.apache.org/repos/asf/hbase/blob/0ed50f42/hbase-server/src/main/java/org/apache/hadoop/hbase/master/balancer/StochasticLoadBalancer.java
----------------------------------------------------------------------
diff --git a/hbase-server/src/main/java/org/apache/hadoop/hbase/master/balancer/StochasticLoadBalancer.java b/hbase-server/src/main/java/org/apache/hadoop/hbase/master/balancer/StochasticLoadBalancer.java
index 8cbdd1e..5c92973 100644
--- a/hbase-server/src/main/java/org/apache/hadoop/hbase/master/balancer/StochasticLoadBalancer.java
+++ b/hbase-server/src/main/java/org/apache/hadoop/hbase/master/balancer/StochasticLoadBalancer.java
@@ -18,14 +18,10 @@
package org.apache.hadoop.hbase.master.balancer;
import java.util.ArrayDeque;
-import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collection;
-import java.util.Collections;
-import java.util.Comparator;
import java.util.Deque;
import java.util.HashMap;
-import java.util.Iterator;
import java.util.LinkedList;
import java.util.List;
import java.util.Map;
@@ -34,6 +30,7 @@ import java.util.Random;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
+import org.apache.hadoop.hbase.classification.InterfaceAudience;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.ClusterStatus;
import org.apache.hadoop.hbase.HBaseInterfaceAudience;
@@ -43,7 +40,6 @@ import org.apache.hadoop.hbase.RegionLoad;
import org.apache.hadoop.hbase.ServerLoad;
import org.apache.hadoop.hbase.ServerName;
import org.apache.hadoop.hbase.TableName;
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
import org.apache.hadoop.hbase.master.MasterServices;
import org.apache.hadoop.hbase.master.RegionPlan;
import org.apache.hadoop.hbase.master.balancer.BaseLoadBalancer.Cluster.Action;
@@ -53,10 +49,6 @@ import org.apache.hadoop.hbase.master.balancer.BaseLoadBalancer.Cluster.MoveRegi
import org.apache.hadoop.hbase.master.balancer.BaseLoadBalancer.Cluster.SwapRegionsAction;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.hbase.util.EnvironmentEdgeManager;
-import org.apache.hadoop.hbase.util.Pair;
-
-import com.google.common.base.Optional;
-import com.google.common.base.Preconditions;
/**
* <p>This is a best effort load balancer. Given a Cost function F(C) => x It will
@@ -928,225 +920,6 @@ public class StochasticLoadBalancer extends BaseLoadBalancer {
}
/**
- * Generates candidate actions to minimize the TableSkew cost function.
- *
- * For efficiency reasons, the cluster must be passed in when this generator is
- * constructed. Every move generated is applied to the cost function
- * (i.e. it is assumed that every action we generate is applied to the cluster).
- * This means we can adjust our cost incrementally for the cluster, rather than
- * recomputing at each iteration.
- */
- static class TableSkewCandidateGenerator extends CandidateGenerator {
-
- // Mapping of table -> true iff too many servers in the cluster store at least
- // cluster.maxRegionsIfEvenlydistributed(table)
- boolean[] tablesWithEnoughServersWithMaxRegions = null;
-
- @Override
- Action generate(Cluster cluster) {
- if (tablesWithEnoughServersWithMaxRegions == null || tablesWithEnoughServersWithMaxRegions.length != cluster.numTables) {
- tablesWithEnoughServersWithMaxRegions = new boolean[cluster.numTables];
- }
- if (cluster.hasUnevenRegionDistribution()) {
- Pair<Integer, Integer> leastAndMostLoadedServers = cluster.findLeastAndMostLoadedServers();
- return moveFromTableWithEnoughRegions(cluster, leastAndMostLoadedServers.getSecond(), leastAndMostLoadedServers.getFirst());
- } else {
- Optional<TableAndServer> tableServer = findSkewedTableServer(cluster);
- if (!tableServer.isPresent()) {
- return Cluster.NullAction;
- }
- return findBestActionForTableServer(cluster, tableServer.get());
- }
- }
-
- /**
- * Returns a move fromServer -> toServer such that after the move fromServer will still have at least
- * the min # regions in terms of table skew calculation
- */
- private Action moveFromTableWithEnoughRegions(Cluster cluster, int fromServer, int toServer) {
- for (int table : getShuffledRangeOfInts(0, cluster.numTables)) {
- int min = cluster.minRegionsIfEvenlyDistributed(table);
- if (cluster.numRegionsPerServerPerTable[fromServer][table] > min) {
- return getAction(fromServer, pickRandomRegionFromTableOnServer(cluster, fromServer, table), toServer, -1);
- }
- }
- return Cluster.NullAction;
- }
-
- /**
- * Picks a random subset of tables, then for each table T checks across cluster and returns first
- * server (if any) which holds too many regions from T. Returns Optional.absent() if no servers
- * are found that hold too many regions.
- */
- private Optional<TableAndServer> findSkewedTableServer(Cluster cluster) {
- Optional<TableAndServer> tableServer = Optional.absent();
- List<Integer> servers = getShuffledRangeOfInts(0, cluster.numServers);
- Iterator<Integer> tableIter = getShuffledRangeOfInts(0, cluster.numTables).iterator();
- while (tableIter.hasNext() && !tableServer.isPresent()) {
- int table = tableIter.next();
- int maxRegions = cluster.maxRegionsIfEvenlyDistributed(table);
- int numShouldHaveMaxRegions = cluster.numServersWithMaxRegionsIfEvenlyDistributed(table);
- int numWithMaxRegions = 0;
- for (int server : servers) {
- int numRegions = cluster.numRegionsPerServerPerTable[server][table];
- // if more than max, server clearly has too many regions
- if (numRegions > maxRegions) {
- tableServer = Optional.of(new TableAndServer(table, server));
- break;
- }
- // if equal to max, check to see if we are within acceptable limit
- if (numRegions == maxRegions) {
- numWithMaxRegions++;
- }
- }
-
- tablesWithEnoughServersWithMaxRegions[table] = numWithMaxRegions >= numShouldHaveMaxRegions;
- // If we have found a table with more than max, we are done
- if (tableServer.isPresent()) {
- break;
- }
-
- // Otherwise, check to see if there are too many servers with maxRegions
- if (numWithMaxRegions > numShouldHaveMaxRegions) {
- for (int server : servers) {
- int numRegions = cluster.numRegionsPerServerPerTable[server][table];
- if (numRegions == maxRegions) {
- tableServer = Optional.of(new TableAndServer(table, server));
- break;
- }
- }
- }
- }
-
- return tableServer;
- }
-
- /**
- * Returns an list of integers that stores [upper - lower] unique integers in random order
- * s.t. for each integer i lower <= i < upper
- */
- private List<Integer> getShuffledRangeOfInts(int lower, int upper) {
- Preconditions.checkArgument(lower < upper);
- ArrayList<Integer> arr = new ArrayList<Integer>(upper - lower);
- for (int i = lower; i < upper; i++) {
- arr.add(i);
- }
- Collections.shuffle(arr);
- return arr;
- }
-
- /**
- * Pick a random region from the specified server and table. Returns -1 if no regions from
- * the given table lie on the given server
- */
- protected int pickRandomRegionFromTableOnServer(Cluster cluster, int server, int table) {
- if (server < 0 || table < 0) {
- return -1;
- }
- List<Integer> regionsFromTable = new ArrayList<>();
- for (int region : cluster.regionsPerServer[server]) {
- if (cluster.regionIndexToTableIndex[region] == table) {
- regionsFromTable.add(region);
- }
- }
- return regionsFromTable.get(RANDOM.nextInt(regionsFromTable.size()));
- }
-
- /**
- * Returns servers in the cluster that store fewer than k regions for the given table (sorted by
- * servers with the fewest regions from givenTable first)
- */
- public List<Integer> getServersWithFewerThanKRegionsFromTable(final Cluster cluster, final int givenTable, int k) {
- List<Integer> serversWithFewerThanK = new ArrayList<>();
- for (int server = 0; server < cluster.numServers; server++) {
- if (cluster.numRegionsPerServerPerTable[server][givenTable] < k) {
- serversWithFewerThanK.add(server);
- }
- }
- Collections.sort(serversWithFewerThanK, new Comparator<Integer>() {
- @Override
- public int compare(Integer o1, Integer o2) {
- return cluster.numRegionsPerServerPerTable[o1.intValue()][givenTable] - cluster.numRegionsPerServerPerTable[o2.intValue()][givenTable];
- }
- });
- return serversWithFewerThanK;
- }
-
- /**
- * Given a table T for which server S stores too many regions, attempts to find a
- * SWAP operation that will better balance the cluster
- */
- public Action findBestActionForTableServer(Cluster cluster, TableAndServer tableServer) {
- int fromTable = tableServer.getTable();
- int fromServer = tableServer.getServer();
-
- int minNumRegions = cluster.minRegionsIfEvenlyDistributed(fromTable);
- int maxNumRegions = cluster.maxRegionsIfEvenlyDistributed(fromTable);
- List<Integer> servers;
- if (tablesWithEnoughServersWithMaxRegions[fromTable]) {
- servers = getServersWithFewerThanKRegionsFromTable(cluster, fromTable, minNumRegions);
- } else {
- servers = getServersWithFewerThanKRegionsFromTable(cluster, fromTable, maxNumRegions);
- }
-
- if (servers.isEmpty()) {
- return Cluster.NullAction;
- }
-
- Optional<Action> swap = trySwap(cluster, fromServer, fromTable, servers);
- if (swap.isPresent()) {
- return swap.get();
- }
-
- // If we cannot perform a swap, we should do nothing
- return Cluster.NullAction;
- }
-
- /**
- * Given server1, table1, we try to find server2 and table2 such that
- * at least 3 of the following 4 criteria are met
- *
- * 1) server1 has too many regions of table1
- * 2) server1 has too few regions of table2
- * 3) server2 has too many regions of table2
- * 4) server2 has too few regions of table1
- *
- * We consider N regions from table T
- * too few if: N < cluster.minRegionsIfEvenlyDistributed(T)
- * too many if: N > cluster.maxRegionsIfEvenlyDistributed(T)
- *
- * Because (1) and (4) are true apriori, we only need to check for (2) and (3).
- *
- * If 3 of the 4 criteria are met, we return a swap operation between
- * randomly selected regions from table1 on server1 and from table2 on server2.
- *
- * Optional.absent() is returned if we could not find such a SWAP.
- */
- private Optional<Action> trySwap(Cluster cluster, int server1, int table1, List<Integer> candidateServers) {
- // Because conditions (1) and (4) are true apriori, we only need to meet one of conditions (2) or (3)
- List<Integer> tables = getShuffledRangeOfInts(0, cluster.numTables);
- for (int table2 : tables) {
- int minRegions = cluster.minRegionsIfEvenlyDistributed(table2);
- int maxRegions = cluster.maxRegionsIfEvenlyDistributed(table2);
- for (int server2 : candidateServers) {
- int numRegions1 = cluster.numRegionsPerServerPerTable[server1][table2];
- int numRegions2 = cluster.numRegionsPerServerPerTable[server2][table2];
- if (numRegions2 == 0) {
- continue;
- }
- if ((numRegions1 < minRegions || numRegions2 > maxRegions) ||
- (minRegions != maxRegions && numRegions1 == minRegions && numRegions2 == maxRegions)) {
- int region1 = pickRandomRegionFromTableOnServer(cluster, server1, table1);
- int region2 = pickRandomRegionFromTableOnServer(cluster, server2, table2);
- return Optional.of(getAction(server1, region1, server2, region2));
- }
- }
- }
- return Optional.absent();
- }
- }
-
- /**
* Base class of StochasticLoadBalancer's Cost Functions.
*/
abstract static class CostFunction {
@@ -1193,7 +966,8 @@ public class StochasticLoadBalancer extends BaseLoadBalancer {
break;
case SWAP_REGIONS:
SwapRegionsAction a = (SwapRegionsAction) action;
- regionSwapped(a.fromRegion, a.fromServer, a.toRegion, a.toServer);
+ regionMoved(a.fromRegion, a.fromServer, a.toServer);
+ regionMoved(a.toRegion, a.toServer, a.fromServer);
break;
default:
throw new RuntimeException("Uknown action:" + action.type);
@@ -1203,11 +977,6 @@ public class StochasticLoadBalancer extends BaseLoadBalancer {
protected void regionMoved(int region, int oldServer, int newServer) {
}
- protected void regionSwapped(int region1, int server1, int region2, int server2) {
- regionMoved(region1, server1, server2);
- regionMoved(region2, server2, server1);
- }
-
abstract double cost();
/**
@@ -1401,188 +1170,9 @@ public class StochasticLoadBalancer extends BaseLoadBalancer {
"hbase.master.balancer.stochastic.tableSkewCost";
private static final float DEFAULT_TABLE_SKEW_COST = 35;
- /**
- * Ranges from 0.0 to 1.0 and is the proportion of how much the most skewed table
- * (as opposed to the average skew across all tables) should affect TableSkew cost
- */
- private static final String MAX_TABLE_SKEW_WEIGHT_KEY =
- "hbase.master.balancer.stochastic.maxTableSkewWeight";
- private float DEFAULT_MAX_TABLE_SKEW_WEIGHT = 0.0f;
-
- private final float maxTableSkewWeight;
- private final float avgTableSkewWeight;
-
- // Number of moves for each table required to bring the cluster to a perfectly balanced
- // state (i.e. as if you had round-robin-ed regions across cluster)
- private int[] numMovesPerTable;
-
TableSkewCostFunction(Configuration conf) {
super(conf);
this.setMultiplier(conf.getFloat(TABLE_SKEW_COST_KEY, DEFAULT_TABLE_SKEW_COST));
- maxTableSkewWeight = conf.getFloat(MAX_TABLE_SKEW_WEIGHT_KEY, DEFAULT_MAX_TABLE_SKEW_WEIGHT);
- Preconditions.checkArgument(0.0 <= maxTableSkewWeight && maxTableSkewWeight <= 1.0);
- avgTableSkewWeight = 1 - maxTableSkewWeight;
- }
-
- /**
- * Computes cost by:
- *
- * 1) Computing a skew score for each table (based on the number of regions
- * from that table that would have to be moved to reach an evenly balanced state)
- *
- * 2) Taking a weighted average of the highest skew score with the average skew score
- *
- * 3) Square rooting that value to more evenly distribute the values between 0-1
- * (since we have observed they are generally very small).
- *
- * @return the table skew cost for the cluster
- */
- @Override
- double cost() {
- double[] skewPerTable = computeSkewPerTable();
- if (skewPerTable.length == 0) {
- return 0;
- }
- double maxTableSkew = max(skewPerTable);
- double avgTableSkew = average(skewPerTable);
-
- return Math.sqrt(maxTableSkewWeight * maxTableSkew + avgTableSkewWeight * avgTableSkew);
- }
-
- @Override
- void init(Cluster cluster) {
- super.init(cluster);
- numMovesPerTable = computeNumMovesPerTable();
- }
-
- /**
- * Adjusts computed number of moves after two regions have been swapped
- */
- @Override
- protected void regionSwapped(int region1, int server1, int region2, int server2) {
- // If different tables, simply perform two moves
- if (cluster.regionIndexToTableIndex[region1] != cluster.regionIndexToTableIndex[region2]) {
- super.regionSwapped(region1, server1, region2, server2);
- return;
- }
- // If same table, do nothing
- }
-
- /**
- * Adjusts computed number of moves per table after a region has been moved
- */
- @Override
- protected void regionMoved(int region, int oldServer, int newServer) {
- int table = cluster.regionIndexToTableIndex[region];
- numMovesPerTable[table] = computeNumMovesForTable(table);
- }
-
- /**
- * Returns a mapping of table -> numMoves, where numMoves is the number of regions required to bring
- * each table to a fully balanced state (i.e. as if its regions had been round-robin-ed across the cluster).
- */
- private int[] computeNumMovesPerTable() {
- // Determine # region moves required for each table to have regions perfectly distributed across cluster
- int[] numMovesPerTable = new int[cluster.numTables];
- for (int table = 0; table < cluster.numTables; table++) {
- numMovesPerTable[table] = computeNumMovesForTable(table);
- }
- return numMovesPerTable;
- }
-
- /**
- * Computes the number of moves required across all servers to bring the given table to a balanced state
- * (i.e. as if its regions had been round-robin-ed across the cluster). We only consider moves as # of regions
- * that need to be sent, not received, so that we do not double count region moves.
- */
- private int computeNumMovesForTable(int table) {
- int numMinRegions = cluster.minRegionsIfEvenlyDistributed(table);
- int numMaxRegions = cluster.maxRegionsIfEvenlyDistributed(table);
- int numMaxServersRemaining = cluster.numServersWithMaxRegionsIfEvenlyDistributed(table);
- int numMoves = 0;
-
- for (int server = 0; server < cluster.numServers; server++) {
- int numRegions = cluster.numRegionsPerServerPerTable[server][table];
- if (numRegions >= numMaxRegions && numMaxServersRemaining > 0) {
- numMoves += numRegions - numMaxRegions;
- numMaxServersRemaining--;
- } else if (numRegions > numMinRegions) {
- numMoves += numRegions - numMinRegions;
- }
- }
- return numMoves;
- }
-
- /**
- * Returns mapping of tableIndex -> tableSkewScore, where tableSkewScore is a double between 0 to 1 with
- * 0 indicating no table skew (i.e. perfect distribution of regions among servers), and 1 representing
- * pathological table skew (i.e. all of a servers regions belonging to one table).
- */
- private double[] computeSkewPerTable() {
- if (numMovesPerTable == null) {
- numMovesPerTable = computeNumMovesPerTable();
- }
- double[] scaledSkewPerTable = new double[numMovesPerTable.length];
- for (int table = 0; table < numMovesPerTable.length; table++) {
- int numTotalRegions = cluster.numRegionsPerTable[table];
- int maxRegions = cluster.maxRegionsIfEvenlyDistributed(table);
- int pathologicalNumMoves = numTotalRegions - maxRegions;
- scaledSkewPerTable[table] = pathologicalNumMoves == 0 ? 0 : (double) numMovesPerTable[table] / pathologicalNumMoves;
- }
- return scaledSkewPerTable;
- }
-
- /**
- * Returns the max of the values in the passed array
- */
- private double max(double[] arr) {
- double max = arr[0];
- for (double d : arr) {
- if (d > max) {
- max = d;
- }
- }
- return max;
- }
-
- /**
- * Returns the average of the values in the passed array
- */
- private double average(double[] arr) {
- double sum = 0;
- for (double d : arr) {
- sum += d;
- }
- return sum / arr.length;
- }
- }
-
- /**
- * Compute the cost of a potential cluster configuration based upon how evenly
- * distributed tables are.
- *
- * @deprecated replaced by TableSkewCostFunction
- * This function only considers the maximum # of regions of each table stored
- * on any one server. This, however, neglects a number of cases. Consider the case
- * where N servers store 1 more region than as if the regions had been round robin-ed
- * across the cluster, but then K servers stored 0 regions of the table. The maximum
- * # regions stored would not properly reflect the table-skew of the cluster.
- *
- * Furthermore, this relies upon the cluster.numMaxRegionsPerTable field, which is not
- * properly updated. The values per table only increase as the cluster shifts (i.e.
- * as new maxima are found), but they do not go down when the maximum skew decreases
- * for a particular table.
- */
- @Deprecated
- static class OldTableSkewCostFunction extends CostFunction {
-
- private static final String TABLE_SKEW_COST_KEY =
- "hbase.master.balancer.stochastic.tableSkewCost";
- private static final float DEFAULT_TABLE_SKEW_COST = 35;
-
- OldTableSkewCostFunction(Configuration conf) {
- super(conf);
- this.setMultiplier(conf.getFloat(TABLE_SKEW_COST_KEY, DEFAULT_TABLE_SKEW_COST));
}
@Override
@@ -1860,8 +1450,7 @@ public class StochasticLoadBalancer extends BaseLoadBalancer {
for (int i = 0 ; i < costsPerGroup.length; i++) {
totalCost += costsPerGroup[i];
}
- // Still return high cost for single region replicas being cohosted even as cluster scales
- return Math.sqrt(scale(0, maxCost, totalCost));
+ return scale(0, maxCost, totalCost);
}
/**
@@ -2000,31 +1589,9 @@ public class StochasticLoadBalancer extends BaseLoadBalancer {
}
/**
- * Data structure that holds table and server indexes
- */
- static class TableAndServer {
- private final int table;
- private final int server;
-
- public TableAndServer(int table, int server) {
- this.table = table;
- this.server = server;
- }
-
- public int getTable() {
- return table;
- }
-
- public int getServer() {
- return server;
- }
- }
-
- /**
* A helper function to compose the attribute name from tablename and costfunction name
*/
public static String composeAttributeName(String tableName, String costFunctionName) {
return tableName + TABLE_FUNCTION_SEP + costFunctionName;
}
-
}
http://git-wip-us.apache.org/repos/asf/hbase/blob/0ed50f42/hbase-server/src/test/java/org/apache/hadoop/hbase/master/balancer/TestStochasticLoadBalancer.java
----------------------------------------------------------------------
diff --git a/hbase-server/src/test/java/org/apache/hadoop/hbase/master/balancer/TestStochasticLoadBalancer.java b/hbase-server/src/test/java/org/apache/hadoop/hbase/master/balancer/TestStochasticLoadBalancer.java
index 37ff35f..9d193d2 100644
--- a/hbase-server/src/test/java/org/apache/hadoop/hbase/master/balancer/TestStochasticLoadBalancer.java
+++ b/hbase-server/src/test/java/org/apache/hadoop/hbase/master/balancer/TestStochasticLoadBalancer.java
@@ -48,8 +48,6 @@ import org.apache.hadoop.hbase.master.MockNoopMasterServices;
import org.apache.hadoop.hbase.master.RackManager;
import org.apache.hadoop.hbase.master.RegionPlan;
import org.apache.hadoop.hbase.master.balancer.BaseLoadBalancer.Cluster;
-import org.apache.hadoop.hbase.master.balancer.StochasticLoadBalancer.CandidateGenerator;
-import org.apache.hadoop.hbase.master.balancer.StochasticLoadBalancer.TableSkewCandidateGenerator;
import org.apache.hadoop.hbase.testclassification.FlakeyTests;
import org.apache.hadoop.hbase.testclassification.MediumTests;
import org.apache.hadoop.hbase.util.Bytes;
@@ -120,9 +118,7 @@ public class TestStochasticLoadBalancer extends BalancerTestBase {
*/
@Test
public void testBalanceCluster() throws Exception {
- float oldMinCostNeedBalance = conf.getFloat(StochasticLoadBalancer.MIN_COST_NEED_BALANCE_KEY, 0.05f);
- conf.setFloat(StochasticLoadBalancer.MIN_COST_NEED_BALANCE_KEY, 0.02f);
- loadBalancer.setConf(conf);
+
for (int[] mockCluster : clusterStateMocks) {
Map<ServerName, List<HRegionInfo>> servers = mockClusterServers(mockCluster);
List<ServerAndLoad> list = convertToList(servers);
@@ -138,9 +134,6 @@ public class TestStochasticLoadBalancer extends BalancerTestBase {
returnServer(entry.getKey());
}
}
- // reset config
- conf.setFloat(StochasticLoadBalancer.MIN_COST_NEED_BALANCE_KEY, oldMinCostNeedBalance);
- loadBalancer.setConf(conf);
}
@Test
@@ -259,32 +252,6 @@ public class TestStochasticLoadBalancer extends BalancerTestBase {
double result = storeFileCostFunction.getRegionLoadCost(regionLoads);
// storefile size cost is simply an average of it's value over time
assertEquals(2.5, result, 0.01);
- }
-
- @Test (timeout=60000)
- public void testTableSkewCandidateGeneratorConvergesToZero() {
- int replication = 1;
- StochasticLoadBalancer.CostFunction
- costFunction = new StochasticLoadBalancer.TableSkewCostFunction(conf);
- CandidateGenerator generator = new TableSkewCandidateGenerator();
- for (int i = 0; i < 100; i++) {
- int numNodes = 1 + rand.nextInt(5 * i + 1);
- int numTables = 1 + rand.nextInt(5 * i + 1);
- int numRegions = rand.nextInt(numTables * 99) + Math.max(numTables, numNodes); // num regions between max(numTables, numNodes) - numTables*100
- int numRegionsPerServer = rand.nextInt(numRegions / numNodes) + 1; // num regions per server (except one) between 1 and numRegions / numNodes
-
- Map<ServerName, List<HRegionInfo>> serverMap = createServerMap(numNodes, numRegions, numRegionsPerServer, replication, numTables);
- BaseLoadBalancer.Cluster cluster = new Cluster(serverMap, null, null, null);
- costFunction.init(cluster);
- double cost = costFunction.cost();
- while (cost > 0) {
- Cluster.Action action = generator.generate(cluster);
- cluster.doAction(action);
- costFunction.postAction(action);
- cost = costFunction.cost();
- }
- assertEquals(0, cost, .000000000001);
- }
}
@Test
http://git-wip-us.apache.org/repos/asf/hbase/blob/0ed50f42/hbase-server/src/test/java/org/apache/hadoop/hbase/master/balancer/TestStochasticLoadBalancer2.java
----------------------------------------------------------------------
diff --git a/hbase-server/src/test/java/org/apache/hadoop/hbase/master/balancer/TestStochasticLoadBalancer2.java b/hbase-server/src/test/java/org/apache/hadoop/hbase/master/balancer/TestStochasticLoadBalancer2.java
index 03d2ef2..2f315de 100644
--- a/hbase-server/src/test/java/org/apache/hadoop/hbase/master/balancer/TestStochasticLoadBalancer2.java
+++ b/hbase-server/src/test/java/org/apache/hadoop/hbase/master/balancer/TestStochasticLoadBalancer2.java
@@ -35,7 +35,6 @@ public class TestStochasticLoadBalancer2 extends BalancerTestBase {
conf.setFloat("hbase.master.balancer.stochastic.maxMovePercent", 1.0f);
conf.setLong(StochasticLoadBalancer.MAX_STEPS_KEY, 2000000L);
conf.setFloat("hbase.master.balancer.stochastic.localityCost", 0);
-
conf.setLong("hbase.master.balancer.stochastic.maxRunningTime", 90 * 1000); // 90 sec
conf.setFloat("hbase.master.balancer.stochastic.minCostNeedBalance", 0.05f);
loadBalancer.setConf(conf);
@@ -71,7 +70,6 @@ public class TestStochasticLoadBalancer2 extends BalancerTestBase {
public void testRegionReplicasOnMidClusterHighReplication() {
conf.setLong(StochasticLoadBalancer.MAX_STEPS_KEY, 4000000L);
conf.setLong("hbase.master.balancer.stochastic.maxRunningTime", 120 * 1000); // 120 sec
- conf.setFloat("hbase.master.balancer.stochastic.tableSkewCost", 4);
loadBalancer.setConf(conf);
int numNodes = 80;
int numRegions = 6 * numNodes;
@@ -79,8 +77,6 @@ public class TestStochasticLoadBalancer2 extends BalancerTestBase {
int numRegionsPerServer = 5;
int numTables = 10;
testWithCluster(numNodes, numRegions, numRegionsPerServer, replication, numTables, false, true);
- // reset config
- conf.setFloat("hbase.master.balancer.stochastic.tableSkewCost", 35);
}
@Test (timeout = 800000)