i3wangyi commented on a change in pull request #639: Refine the WAGED
rebalancer to minimize the partial rebalance workload.
URL: https://github.com/apache/helix/pull/639#discussion_r354626614
##########
File path:
helix-core/src/main/java/org/apache/helix/controller/rebalancer/waged/WagedRebalancer.java
##########
@@ -389,50 +376,89 @@ public void close() {
return finalIdealStateMap;
}
- // TODO make the Baseline calculation async if complicated algorithm is used
for the Baseline
- private void refreshBaseline(ResourceControllerDataProvider clusterData,
- Map<HelixConstants.ChangeType, Set<String>> clusterChanges, Map<String,
Resource> resourceMap,
- final CurrentStateOutput currentStateOutput)
+ /**
+ * Global rebalance calculates for a new baseline assignment.
+ * The new baseline assignment will be persisted and leveraged by the
partial rebalance.
+ * @param clusterData
+ * @param resourceMap
+ * @param currentStateOutput
+ * @param algorithm
+ * @throws HelixRebalanceException
+ */
+ private void globalRebalance(ResourceControllerDataProvider clusterData,
+ Map<String, Resource> resourceMap, final CurrentStateOutput
currentStateOutput,
+ RebalanceAlgorithm algorithm)
throws HelixRebalanceException {
+ _changeDetector.updateSnapshots(clusterData);
+ // Get all the changed items' information. Filter for the items that have
content changed.
+ final Map<HelixConstants.ChangeType, Set<String>> clusterChanges =
+ _changeDetector.getChangeTypes().stream()
+ .collect(Collectors.toMap(changeType -> changeType, changeType -> {
+ Set<String> itemKeys = new HashSet<>();
+ itemKeys.addAll(_changeDetector.getAdditionsByType(changeType));
+ itemKeys.addAll(_changeDetector.getChangesByType(changeType));
+ itemKeys.addAll(_changeDetector.getRemovalsByType(changeType));
+ return itemKeys;
+ })).entrySet().stream().filter(changeEntry ->
!changeEntry.getValue().isEmpty())
+ .collect(Collectors
+ .toMap(changeEntry -> changeEntry.getKey(), changeEntry ->
changeEntry.getValue()));
+
if (clusterChanges.keySet().stream()
.anyMatch(GLOBAL_REBALANCE_REQUIRED_CHANGE_TYPES::contains)) {
- LOG.info("Start calculating the new baseline.");
- _globalBaselineCalcCounter.increment(1L);
- _globalBaselineCalcLatency.startMeasuringLatency();
-
- // For baseline calculation
+ // Build the cluster model for rebalance calculation.
+ // Note, for a Baseline calculation,
// 1. Ignore node status (disable/offline).
- // 2. Use the baseline as the previous best possible assignment since
there is no "baseline" for
- // the baseline.
- // Read the baseline from metadata store
+ // 2. Use the previous Baseline as the only parameter about the previous
assignment.
Map<String, ResourceAssignment> currentBaseline =
getBaselineAssignment(_assignmentMetadataStore, currentStateOutput,
resourceMap.keySet());
- Map<String, ResourceAssignment> newBaseline =
- calculateAssignment(clusterData, clusterChanges, resourceMap,
- clusterData.getAllInstances(), Collections.emptyMap(),
currentBaseline);
-
- // Write the new baseline to metadata store
- if (_assignmentMetadataStore != null) {
- try {
- _writeLatency.startMeasuringLatency();
- _assignmentMetadataStore.persistBaseline(newBaseline);
- _writeLatency.endMeasuringLatency();
- } catch (Exception ex) {
- throw new HelixRebalanceException("Failed to persist the new
baseline assignment.",
- HelixRebalanceException.Type.INVALID_REBALANCER_STATUS, ex);
- }
- } else {
- LOG.debug("Assignment Metadata Store is empty. Skip persist the
baseline assignment.");
+ ClusterModel clusterModel;
+ try {
+ clusterModel = ClusterModelProvider
+ .generateClusterModelForBaseline(clusterData, resourceMap,
+ clusterData.getAllInstances(), clusterChanges,
currentBaseline);
+ } catch (Exception ex) {
+ throw new HelixRebalanceException("Failed to generate cluster model
for global rebalance.",
+ HelixRebalanceException.Type.INVALID_CLUSTER_STATUS, ex);
}
- _globalBaselineCalcLatency.endMeasuringLatency();
- LOG.info("Finish calculating the new baseline.");
+
+ refreshBaseline(clusterModel, algorithm);
}
}
+ /**
+ * Calculate and update the Baseline assignment
+ * @param clusterModel
+ * @param algorithm
+ * @throws HelixRebalanceException
+ */
+ private void refreshBaseline(ClusterModel clusterModel, RebalanceAlgorithm
algorithm)
+ throws HelixRebalanceException {
+ LOG.info("Start calculating the new baseline.");
+ _globalBaselineCalcCounter.increment(1L);
+ _globalBaselineCalcLatency.startMeasuringLatency();
+
+ Map<String, ResourceAssignment> newBaseline =
calculateAssignment(clusterModel, algorithm);
+ // Write the new baseline to metadata store
+ if (_assignmentMetadataStore != null) {
+ try {
+ _writeLatency.startMeasuringLatency();
+ _assignmentMetadataStore.persistBaseline(newBaseline);
+ _writeLatency.endMeasuringLatency();
+ } catch (Exception ex) {
Review comment:
Is it some I/O exceptions, can we be specific>
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