Github user mcvsubbu commented on a diff in the pull request:
https://github.com/apache/helix/pull/145#discussion_r174528962
--- Diff:
helix-core/src/main/java/org/apache/helix/util/WeightAwareRebalanceUtil.java ---
@@ -0,0 +1,141 @@
+package org.apache.helix.util;
+
+import org.apache.helix.HelixException;
+import org.apache.helix.ZNRecord;
+import org.apache.helix.api.config.RebalanceConfig;
+import
org.apache.helix.api.rebalancer.constraint.AbstractRebalanceHardConstraint;
+import
org.apache.helix.api.rebalancer.constraint.AbstractRebalanceSoftConstraint;
+import org.apache.helix.controller.common.PartitionStateMap;
+import org.apache.helix.controller.common.ResourcesStateMap;
+import
org.apache.helix.controller.rebalancer.strategy.ConstraintRebalanceStrategy;
+import org.apache.helix.controller.stages.ClusterDataCache;
+import org.apache.helix.model.*;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+/**
+ * A rebalance tool that generate an resource partition assignment based
on the input.
+ * Note the assignment won't be automatically applied to the cluster.
Applications are supposed to
+ * apply the change.
+ */
+public class WeightAwareRebalanceUtil {
+ private final ClusterConfig _clusterConfig;
+ private final Map<String, InstanceConfig> _instanceConfigMap = new
HashMap<>();
+ // For the possible customized state models.
+ private final Map<String, StateModelDefinition> _stateModelDefs = new
HashMap<>();
+ private final ClusterDataCache _dataCache;
+
+ public enum RebalanceOption {
+ INIT,
+ REASSIGN
+ }
+
+ public WeightAwareRebalanceUtil(ClusterConfig clusterConfig,
+ List<InstanceConfig> instanceConfigs) {
+ for (InstanceConfig instanceConfig : instanceConfigs) {
+ _instanceConfigMap.put(instanceConfig.getInstanceName(),
instanceConfig);
+ }
+ _clusterConfig = clusterConfig;
+
+ _dataCache = new ClusterDataCache();
+ _dataCache.setInstanceConfigMap(_instanceConfigMap);
+ _dataCache.setClusterConfig(_clusterConfig);
+ List<LiveInstance> liveInstanceList = new ArrayList<>();
+ for (String instance : _instanceConfigMap.keySet()) {
+ LiveInstance liveInstance = new LiveInstance(instance);
+ liveInstanceList.add(liveInstance);
+ }
+ _dataCache.setLiveInstances(liveInstanceList);
+ }
+
+ /**
+ * The method to generate partition assignment mappings.
+ *
+ * @param resourceConfigs Config of all the resources that need to be
rebalanced.
+ * The tool throws Exception if any resource
has no IS or broken/uninitialized IS.
+ * The tool throws Exception if any resource
is in full-auto mode.
+ * @param existingAssignment The existing partition assignment of the
input resources.
+ * @param option INIT or REASSIGN
+ * INIT: Keep existing assignment. Only
generate new partition assignment.
--- End diff --
If you are having difficulty naming the variable, use two different APIs.
buildIncrementalRebalanceAssignment()
buildFullRebalanceAssignment()
Or some such.
I still don't understand the difference between the two.
I suppose incremental means to calculate idealstate assignment for new
partitions, given the old partition assignment. Right? In that case the list of
new partitions should be taken as an argument, but it is not. Old partitions
are not touched. Am I right?
I suppose full rebalance means to re-assign existing partitions around (but
no new partitions added). Am I right? In this case, we rebalance the
partitions, but minimize movement. Am I right?
---
