Coordinator Process

For basic tuning guidance for the Coordinator process, see .

HTTP endpoints

For a list of API endpoints supported by the Coordinator, see .

Overview

The Druid Coordinator process is primarily responsible for segment management and distribution. More specifically, the Druid Coordinator process communicates to Historical processes to load or drop segments based on configurations. The Druid Coordinator is responsible for loading new segments, dropping outdated segments, ensuring that segments are “replicated” (that is, loaded on multiple different Historical nodes) proper (configured) number of times, and moving (“balancing”) segments between Historical nodes to keep the latter evenly loaded.

The Druid Coordinator runs its duties periodically and the time between each run is a configurable parameter. On each run, the Coordinator assesses the current state of the cluster before deciding on the appropriate actions to take. Similar to the Broker and Historical processes, the Druid Coordinator maintains a connection to a Zookeeper cluster for current cluster information. The Coordinator also maintains a connection to a database containing information about “used” segments (that is, the segments that should be loaded in the cluster) and the loading rules.

Before any unassigned segments are serviced by Historical processes, the Historical processes for each tier are first sorted in terms of capacity, with least capacity servers having the highest priority. Unassigned segments are always assigned to the processes with least capacity to maintain a level of balance between processes. The Coordinator does not directly communicate with a historical process when assigning it a new segment; instead the Coordinator creates some temporary information about the new segment under load queue path of the historical process. Once this request is seen, the historical process will load the segment and begin servicing it.

Rules

Segments can be automatically loaded and dropped from the cluster based on a set of rules. For more information on rules, see .

Cleaning up segments

On each run, the Druid Coordinator compares the set of used segments in the database with the segments served by some Historical nodes in the cluster. Coordinator sends requests to Historical nodes to unload unused segments or segments that are removed from the database.

Segments that are overshadowed (their versions are too old and their data has been replaced by newer segments) are marked as unused. During the next Coordinator’s run, they will be unloaded from Historical nodes in the cluster.

Balancing segment load

To ensure an even distribution of segments across Historical processes in the cluster, the Coordinator process will find the total size of all segments being served by every Historical process each time the Coordinator runs. For every Historical process tier in the cluster, the Coordinator process will determine the Historical process with the highest utilization and the Historical process with the lowest utilization. The percent difference in utilization between the two processes is computed, and if the result exceeds a certain threshold, a number of segments will be moved from the highest utilized process to the lowest utilized process. There is a configurable limit on the number of segments that can be moved from one process to another each time the Coordinator runs. Segments to be moved are selected at random and only moved if the resulting utilization calculation indicates the percentage difference between the highest and lowest servers has decreased.

Automatic compaction

The Druid Coordinator manages the automatic compaction system. Each run, the Coordinator compacts segments by merging small segments or splitting a large one. This is useful when the size of your segments is not optimized which may degrade query performance. See for details.

The Coordinator first finds the segments to compact based on the segment search policy. Once some segments are found, it issues a to compact those segments. The maximum number of running compaction tasks is . Note that even if min(sum of worker capacity * slotRatio, maxSlots) = 0, at least one compaction task is always submitted if the compaction is enabled for a dataSource. See Automatic compaction configuration API and to enable and configure automatic compaction.

Compaction tasks might fail due to the following reasons:

• If the input segments of a compaction task are removed or overshadowed before it starts, that compaction task fails immediately.
• If a task of a higher priority acquires a time chunk lock for an interval overlapping with the interval of a compaction task, the compaction task fails.

Once a compaction task fails, the Coordinator simply checks the segments in the interval of the failed task again, and issues another compaction task in the next run.

Note that Compacting Segments Coordinator Duty is automatically enabled and run as part of the Indexing Service Duties group. However, Compacting Segments Coordinator Duty can be configured to run in isolation as a separate Coordinator duty group. This allows changing the period of Compacting Segments Coordinator Duty without impacting the period of other Indexing Service Duties. This can be done by setting the following properties. For more details, see .

druid.coordinator.dutyGroups=[<SOME_GROUP_NAME>]
druid.coordinator.<SOME_GROUP_NAME>.duties=["compactSegments"]
druid.coordinator.<SOME_GROUP_NAME>.period=<PERIOD_TO_RUN_COMPACTING_SEGMENTS_DUTY>

At every Coordinator run, this policy looks up time chunks from newest to oldest and checks whether the segments in those time chunks need compaction. A set of segments needs compaction if all conditions below are satisfied:

1. Total size of segments in the time chunk is smaller than or equal to the configured inputSegmentSizeBytes.

Here are some details with an example. Suppose we have two dataSources (, bar) as seen below:

• foo
  • foo_2017-11-01T00:00:00.000Z_2017-12-01T00:00:00.000Z_VERSION
  • foo_2017-11-01T00:00:00.000Z_2017-12-01T00:00:00.000Z_VERSION_1
  • foo_2017-09-01T00:00:00.000Z_2017-10-01T00:00:00.000Z_VERSION
• bar
  • bar_2017-10-01T00:00:00.000Z_2017-11-01T00:00:00.000Z_VERSION

If the Coordinator has enough task slots for compaction, this policy will continue searching for the next segments and return bar_2017-10-01T00:00:00.000Z_2017-11-01T00:00:00.000Z_VERSION and bar_2017-10-01T00:00:00.000Z_2017-11-01T00:00:00.000Z_VERSION_1. Finally, foo_2017-09-01T00:00:00.000Z_2017-10-01T00:00:00.000Z_VERSION will be picked up even though there is only one segment in the time chunk of 2017-09-01T00:00:00.000Z/2017-10-01T00:00:00.000Z.

The search start point can be changed by setting . If this is set, this policy will ignore the segments falling into the time chunk of (the end time of the most recent segment - skipOffsetFromLatest). This is to avoid conflicts between compaction tasks and realtime tasks. Note that realtime tasks have a higher priority than compaction tasks by default. Realtime tasks will revoke the locks of compaction tasks if their intervals overlap, resulting in the termination of the compaction task. For more information, see .

FAQ

1. Do clients ever contact the Coordinator process?

   The Coordinator is not involved in a query.

   Historical processes never directly contact the Coordinator process. The Druid Coordinator tells the Historical processes to load/drop data via Zookeeper, but the Historical processes are completely unaware of the Coordinator.

   Brokers also never contact the Coordinator. Brokers base their understanding of the data topology on metadata exposed by the Historical processes via ZK and are completely unaware of the Coordinator.