mcvsubbu commented on a change in pull request #6165:
URL: https://github.com/apache/incubator-pinot/pull/6165#discussion_r509405315



##########
File path: 
pinot-controller/src/main/java/org/apache/pinot/controller/helix/core/PinotHelixResourceManager.java
##########
@@ -1641,23 +1643,30 @@ public void addNewSegment(String tableName, 
SegmentMetadata segmentMetadata, Str
       Map<InstancePartitionsType, InstancePartitions> instancePartitionsMap = 
Collections
           .singletonMap(InstancePartitionsType.OFFLINE, InstancePartitionsUtils
               .fetchOrComputeInstancePartitions(_helixZkManager, 
offlineTableConfig, InstancePartitionsType.OFFLINE));
-      HelixHelper.updateIdealState(_helixZkManager, offlineTableName, 
idealState -> {
-        assert idealState != null;
-        Map<String, Map<String, String>> currentAssignment = 
idealState.getRecord().getMapFields();
-        if (currentAssignment.containsKey(segmentName)) {
-          LOGGER.warn("Segment: {} already exists in the IdealState for table: 
{}, do not update", segmentName,
-              offlineTableName);
-        } else {
-          List<String> assignedInstances =
-              segmentAssignment.assignSegment(segmentName, currentAssignment, 
instancePartitionsMap);
-          LOGGER.info("Assigning segment: {} to instances: {} for table: {}", 
segmentName, assignedInstances,
-              offlineTableName);
-          currentAssignment.put(segmentName,
-              SegmentAssignmentUtils.getInstanceStateMap(assignedInstances, 
SegmentStateModel.ONLINE));
+      if (_tableUpdaterLockMap.get(offlineTableName) == null) {
+        synchronized (_tableUpdaterLockMap) {
+          if (_tableUpdaterLockMap.get(offlineTableName) == null) {
+            _tableUpdaterLockMap.put(offlineTableName, new Object());

Review comment:
       Also, we hold the lock while backing off, so a single cross-controller 
contention will start building a queue? I think a better solution may to simply 
reduce the backoff time and try more often?
   
   Also, we have clusters with 1000s of tables, and in this case, the hash 
table will contain all of them.




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