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WARNING: Version 2.1 of Elasticsearch has passed its EOL date.
This documentation is no longer being maintained and may be removed. If you are running this version, we strongly advise you to upgrade. For the latest information, see the current release documentation.
Shard Allocation Awareness
editShard Allocation Awareness
editWhen running nodes on multiple VMs on the same physical server, on multiple racks, or across multiple awareness zones, it is more likely that two nodes on the same physical server, in the same rack, or in the same awareness zone will crash at the same time, rather than two unrelated nodes crashing simultaneously.
If Elasticsearch is aware of the physical configuration of your hardware, it can ensure that the primary shard and its replica shards are spread across different physical servers, racks, or zones, to minimise the risk of losing all shard copies at the same time.
The shard allocation awareness settings allow you to tell Elasticsearch about your hardware configuration.
As an example, let’s assume we have several racks. When we start a node, we
can tell it which rack it is in by assigning it an arbitrary metadata
attribute called rack_id
— we could use any attribute name. For example:
Now, we need to setup shard allocation awareness by telling Elasticsearch
which attributes to use. This can be configured in the elasticsearch.yml
file on all master-eligible nodes, or it can be set (and changed) with the
cluster-update-settings API.
For our example, we’ll set the value in the config file:
cluster.routing.allocation.awareness.attributes: rack_id
With this config in place, let’s say we start two nodes with node.rack_id
set to rack_one
, and we create an index with 5 primary shards and 1 replica
of each primary. All primaries and replicas are allocated across the two
nodes.
Now, if we start two more nodes with node.rack_id
set to rack_two
,
Elasticsearch will move shards across to the new nodes, ensuring (if possible)
that no two copies of the same shard will be in the same rack. However if rack_two
were to fail, taking down both of its nodes, Elasticsearch will still allocate the lost
shard copies to nodes in rack_one
.
Multiple awareness attributes can be specified, in which case the combination of values from each attribute is considered to be a separate value.
cluster.routing.allocation.awareness.attributes: rack_id,zone
When using awareness attributes, shards will not be allocated to nodes that don’t have values set for those attributes.
Number of primary/replica of a shard allocated on a specific group of nodes with the same awareness attribute value is determined by the number of attribute values. When the number of nodes in groups is unbalanced and there are many replicas, replica shards may be left unassigned.
Forced Awareness
editImagine that you have two awareness zones and enough hardware across the two zones to host all of your primary and replica shards. But perhaps the hardware in a single zone, while sufficient to host half the shards, would be unable to host ALL the shards.
With ordinary awareness, if one zone lost contact with the other zone, Elasticsearch would assign all of the missing replica shards to a single zone. But in this example, this sudden extra load would cause the hardware in the remaining zone to be overloaded.
Forced awareness solves this problem by NEVER allowing copies of the same shard to be allocated to the same zone.
For example, lets say we have an awareness attribute called zone
, and
we know we are going to have two zones, zone1
and zone2
. Here is how
we can force awareness on a node:
cluster.routing.allocation.awareness.force.zone.values: zone1,zone2 cluster.routing.allocation.awareness.attributes: zone
Now, if we start 2 nodes with node.zone
set to zone1
and create an index
with 5 shards and 1 replica. The index will be created, but only the 5 primary
shards will be allocated (with no replicas). Only when we start more shards
with node.zone
set to zone2
will the replicas be allocated.
The cluster.routing.allocation.awareness.*
settings can all be updated
dynamically on a live cluster with the
cluster-update-settings API.
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