Important Configuration Changesedit

Elasticsearch ships with very good defaults, especially when it comes to performance- related settings and options. When in doubt, just leave the settings alone. We have witnessed countless dozens of clusters ruined by errant settings because the administrator thought he could turn a knob and gain 100-fold improvement.

Please read this entire section! All configurations presented are equally important, and are not listed in any particular order. Please read through all configuration options and apply them to your cluster.

Other databases may require tuning, but by and large, Elasticsearch does not. If you are hitting performance problems, the solution is usually better data layout or more nodes. There are very few "magic knobs" in Elasticsearch. If there were, we’d have turned them already!

With that said, there are some logistical configurations that should be changed for production. These changes are necessary either to make your life easier, or because there is no way to set a good default (because it depends on your cluster layout).

Assign Namesedit

Elasticseach by default starts a cluster named elasticsearch. It is wise to rename your production cluster to something else, simply to prevent accidents whereby someone’s laptop joins the cluster. A simple change to elasticsearch_production can save a lot of heartache.

This can be changed in your elasticsearch.yml file: elasticsearch_production

Similarly, it is wise to change the names of your nodes. As you’ve probably noticed by now, Elasticsearch assigns a random Marvel superhero name to your nodes at startup. This is cute in development—​but less cute when it is 3a.m. and you are trying to remember which physical machine was Tagak the Leopard Lord.

More important, since these names are generated on startup, each time you restart your node, it will get a new name. This can make logs confusing, since the names of all the nodes are constantly changing.

Boring as it might be, we recommend you give each node a name that makes sense to you—​a plain, descriptive name. This is also configured in your elasticsearch.yml: elasticsearch_005_data


By default, Elasticsearch will place the plug-ins, logs, and—​most important—​your data in the installation directory. This can lead to unfortunate accidents, whereby the installation directory is accidentally overwritten by a new installation of Elasticsearch. If you aren’t careful, you can erase all your data.

Don’t laugh—​we’ve seen it happen more than a few times.

The best thing to do is relocate your data directory outside the installation location. You can optionally move your plug-in and log directories as well.

This can be changed as follows: /path/to/data1,/path/to/data2 

# Path to log files:
path.logs: /path/to/logs

# Path to where plugins are installed:
path.plugins: /path/to/plugins

Notice that you can specify more than one directory for data by using comma-separated lists.

Data can be saved to multiple directories, and if each directory is mounted on a different hard drive, this is a simple and effective way to set up a software RAID 0. Elasticsearch will automatically stripe data between the different directories, boosting performance.

Multiple data path safety and performance

Like any RAID 0 configuration, only a single copy of your data is saved to the hard drives. If you lose a hard drive, you are guaranteed to lose a portion of your data on that machine. With luck you’ll have replicas elsewhere in the cluster which can recover the data, and/or a recent backup.

Elasticsearch attempts to minimize the extent of data loss by striping entire shards to a drive. That means that Shard 0 will be placed entirely on a single drive. Elasticsearch will not stripe a shard across multiple drives, since the loss of one drive would corrupt the entire shard.

This has ramifications for performance: if you are adding multiple drives to improve the performance of a single index, it is unlikely to help since most nodes will only have one shard, and thus one active drive. Multiple data paths only helps if you have many indices/shards on a single node.

Multiple data paths is a nice convenience feature, but at the end of the day, Elasticsearch is not a software RAID package. If you need more advanced configuration, robustness and flexibility, we encourage you to use actual software RAID packages instead of the multiple data path feature.

Minimum Master Nodesedit

The minimum_master_nodes setting is extremely important to the stability of your cluster. This setting helps prevent split brains, the existence of two masters in a single cluster.

When you have a split brain, your cluster is at danger of losing data. Because the master is considered the supreme ruler of the cluster, it decides when new indices can be created, how shards are moved, and so forth. If you have two masters, data integrity becomes perilous, since you have two nodes that think they are in charge.

This setting tells Elasticsearch to not elect a master unless there are enough master-eligible nodes available. Only then will an election take place.

This setting should always be configured to a quorum (majority) of your master-eligible nodes. A quorum is (number of master-eligible nodes / 2) + 1. Here are some examples:

  • If you have ten regular nodes (can hold data, can become master), a quorum is 6.
  • If you have three dedicated master nodes and a hundred data nodes, the quorum is 2, since you need to count only nodes that are master eligible.
  • If you have two regular nodes, you are in a conundrum. A quorum would be 2, but this means a loss of one node will make your cluster inoperable. A setting of 1 will allow your cluster to function, but doesn’t protect against split brain. It is best to have a minimum of three nodes in situations like this.

This setting can be configured in your elasticsearch.yml file:

discovery.zen.minimum_master_nodes: 2

But because Elasticsearch clusters are dynamic, you could easily add or remove nodes that will change the quorum. It would be extremely irritating if you had to push new configurations to each node and restart your whole cluster just to change the setting.

For this reason, minimum_master_nodes (and other settings) can be configured via a dynamic API call. You can change the setting while your cluster is online:

PUT /_cluster/settings
    "persistent" : {
        "discovery.zen.minimum_master_nodes" : 2

This will become a persistent setting that takes precedence over whatever is in the static configuration. You should modify this setting whenever you add or remove master-eligible nodes.

Recovery Settingsedit

Several settings affect the behavior of shard recovery when your cluster restarts. First, we need to understand what happens if nothing is configured.

Imagine you have ten nodes, and each node holds a single shard—​either a primary or a replica—​in a 5 primary / 1 replica index. You take your entire cluster offline for maintenance (installing new drives, for example). When you restart your cluster, it just so happens that five nodes come online before the other five.

Maybe the switch to the other five is being flaky, and they didn’t receive the restart command right away. Whatever the reason, you have five nodes online. These five nodes will gossip with each other, elect a master, and form a cluster. They notice that data is no longer evenly distributed, since five nodes are missing from the cluster, and immediately start replicating new shards between each other.

Finally, your other five nodes turn on and join the cluster. These nodes see that their data is being replicated to other nodes, so they delete their local data (since it is now redundant, and may be outdated). Then the cluster starts to rebalance even more, since the cluster size just went from five to ten.

During this whole process, your nodes are thrashing the disk and network, moving data around—​for no good reason. For large clusters with terabytes of data, this useless shuffling of data can take a really long time. If all the nodes had simply waited for the cluster to come online, all the data would have been local and nothing would need to move.

Now that we know the problem, we can configure a few settings to alleviate it. First, we need to give Elasticsearch a hard limit:

gateway.recover_after_nodes: 8

This will prevent Elasticsearch from starting a recovery until at least eight (data or master) nodes are present. The value for this setting is a matter of personal preference: how many nodes do you want present before you consider your cluster functional? In this case, we are setting it to 8, which means the cluster is inoperable unless there are at least eight nodes.

Then we tell Elasticsearch how many nodes should be in the cluster, and how long we want to wait for all those nodes:

gateway.expected_nodes: 10
gateway.recover_after_time: 5m

What this means is that Elasticsearch will do the following:

  • Wait for eight nodes to be present
  • Begin recovering after 5 minutes or after ten nodes have joined the cluster, whichever comes first.

These three settings allow you to avoid the excessive shard swapping that can occur on cluster restarts. It can literally make recovery take seconds instead of hours.

These settings can only be set in the config/elasticsearch.yml file or on the command line (they are not dynamically updatable) and they are only relevant during a full cluster restart.

Prefer Unicast over Multicastedit

Elasticsearch is configured to use unicast discovery out of the box to prevent nodes from accidentally joining a cluster. Only nodes running on the same machine will automatically form cluster.

While multicast is still provided as a plugin, it should never be used in production. The last thing you want is for nodes to accidentally join your production network, simply because they received an errant multicast ping. There is nothing wrong with multicast per se. Multicast simply leads to silly problems, and can be a bit more fragile (for example, a network engineer fiddles with the network without telling you—​and all of a sudden nodes can’t find each other anymore).

To use unicast, you provide Elasticsearch a list of nodes that it should try to contact. When a node contacts a member of the unicast list, it receives a full cluster state that lists all of the nodes in the cluster. It then contacts the master and joins the cluster.

This means your unicast list does not need to include all of the nodes in your cluster. It just needs enough nodes that a new node can find someone to talk to. If you use dedicated masters, just list your three dedicated masters and call it a day. This setting is configured in elasticsearch.yml: ["host1", "host2:port"]

For more information about how Elasticsearch nodes find each other, see Discovery and cluster formation in the Elasticsearch Reference.