Elasticsearch 学习之不停止服务，完成升级重启维护操作

? Upgrade ElasticsearchFull cluster restart upgrade ?

Rolling upgrades

A rolling upgrade allows an Elasticsearch cluster to be upgraded one node at a time so upgrading does not interrupt service. Running multiple versions of Elasticsearch in the same cluster beyond the duration of an upgrade is not supported, as shards cannot be replicated from upgraded nodes to nodes running the older version.

It is best to upgrade the master-eligible nodes in your cluster after all of the other nodes. Once you have started to upgrade the master-eligible nodes they may form a cluster that nodes of older versions cannot join. If you upgrade the master-eligible nodes last then all the other nodes will not be running an older version and so they will be able to join the cluster.

Rolling upgrades are supported:

Between minor versions
From 5.6 to 6.7
From 6.7 to 7.0.1

Upgrading directly to 7.0.1 from 6.6 or earlier requires a full cluster restart.

Preparing to upgrade

It is important to prepare carefully before starting an upgrade. Once you have started to upgrade your cluster to version 7.0.1 you must complete the upgrade. As soon as the cluster contains nodes of version 7.0.1 it may make changes to its internal state that cannot be reverted. If you cannot complete the upgrade then you should discard the partially-upgraded cluster, deploy an empty cluster of the version before the upgrade, and restore its contents from a snapshot.

Before you start to upgrade your cluster to version 7.0.1 you should do the following.

Check the deprecation log to see if you are using any deprecated features and update your code accordingly.
Review the breaking changes and make any necessary changes to your code and configuration for version 7.0.1.
If you use any plugins, make sure there is a version of each plugin that is compatible with Elasticsearch version 7.0.1.
Test the upgrade in an isolated environment before upgrading your production cluster.
Back up your data by taking a snapshot!

Upgrading your cluster

To perform a rolling upgrade to 7.0.1:

Disable shard allocation.

When you shut down a node, the allocation process waits for index.unassigned.node_left.delayed_timeout (by default, one minute) before starting to replicate the shards on that node to other nodes in the cluster, which can involve a lot of I/O. Since the node is shortly going to be restarted, this I/O is unnecessary. You can avoid racing the clock by disabling allocation of replicas before shutting down the node:
```
PUT _cluster/settings
{
  "persistent": {
    "cluster.routing.allocation.enable": "primaries"
  }
}
```
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Stop non-essential indexing and perform a synced flush. (Optional)

While you can continue indexing during the upgrade, shard recovery is much faster if you temporarily stop non-essential indexing and perform a synced-flush.
```
POST _flush/synced
```
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When you perform a synced flush, check the response to make sure there are no failures. Synced flush operations that fail due to pending indexing operations are listed in the response body, although the request itself still returns a 200 OK status. If there are failures, reissue the request.
Temporarily stop the tasks associated with active machine learning jobs and datafeeds. (Optional)

If your machine learning indices were created before 6.x, you must reindex the indices.

If your machine learning indices were created in 6.x, you can:
- Leave your machine learning jobs running during the upgrade. When you shut down a machine learning node, its jobs automatically move to another node and restore the model states. This option enables your jobs to continue running during the upgrade but it puts increased load on the cluster.
- Temporarily halt the tasks associated with your machine learning jobs and datafeeds and prevent new jobs from opening by using the set upgrade mode API:
```
POST _ml/set_upgrade_mode?enabled=true
```
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  When you disable upgrade mode, the jobs resume using the last model state that was automatically saved. This option avoids the overhead of managing active jobs during the upgrade and is faster than explicitly stopping datafeeds and closing jobs.
- Stop all datafeeds and close all jobs. This option saves the model state at the time of closure. When you reopen the jobs after the upgrade, they use the exact same model. However, saving the latest model state takes longer than using upgrade mode, especially if you have a lot of jobs or jobs with large model states.
Shut down a single node.
- If you are running Elasticsearch with systemd:
```
sudo systemctl stop elasticsearch.service
```
- If you are running Elasticsearch with SysV init:
```
sudo -i service elasticsearch stop
```
- If you are running Elasticsearch as a daemon:
```
kill $(cat pid)
```
Upgrade the node you shut down.

To upgrade using a Debian or RPM package:
- Use rpm or dpkg to install the new package. All files are installed in the appropriate location for the operating system and Elasticsearch config files are not overwritten.
To upgrade using a zip or compressed tarball:
1. Extract the zip or tarball to a new directory. This is critical if you are not using external config and data directories.
2. Set the ES_PATH_CONF environment variable to specify the location of your external config directory and jvm.options file. If you are not using an external config directory, copy your old configuration over to the new installation.
3. Set path.data in config/elasticsearch.yml to point to your external data directory. If you are not using an external data directory, copy your old data directory over to the new installation.
  
  If you use monitoring features, re-use the data directory when you upgrade Elasticsearch. Monitoring identifies unique Elasticsearch nodes by using the persistent UUID, which is stored in the data directory.
4. Set path.logs in config/elasticsearch.yml to point to the location where you want to store your logs. If you do not specify this setting, logs are stored in the directory you extracted the archive to.
When you extract the zip or tarball packages, the elasticsearch-n.n.n directory contains the Elasticsearch config, data, logs and plugins directories.

We recommend moving these directories out of the Elasticsearch directory so that there is no chance of deleting them when you upgrade Elasticsearch. To specify the new locations, use the ES_PATH_CONF environment variable and the path.data and path.logs settings. For more information, see Important Elasticsearch configuration.

The Debian and RPM packages place these directories in the appropriate place for each operating system. In production, we recommend installing using the deb or rpm package.

You should leave cluster.initial_master_nodes unset while performing a rolling upgrade. Each upgraded node is joining an existing cluster so there is no need for cluster bootstrapping. You must configure either discovery.seed_hosts or discovery.seed_providers on every node.
Upgrade any plugins.

Use the elasticsearch-plugin script to install the upgraded version of each installed Elasticsearch plugin. All plugins must be upgraded when you upgrade a node.
If you use Elasticsearch security features to define realms, verify that your realm settings are up-to-date. The format of realm settings changed in version 7.0, in particular, the placement of the realm type changed. See Realm settings.
Start the upgraded node.

Start the newly-upgraded node and confirm that it joins the cluster by checking the log file or by submitting a _cat/nodes request:
```
GET _cat/nodes
```
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Reenable shard allocation.

Once the node has joined the cluster, remove the cluster.routing.allocation.enable setting to enable shard allocation and start using the node:
```
PUT _cluster/settings
{
  "persistent": {
    "cluster.routing.allocation.enable": null
  }
}
```
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Wait for the node to recover.

Before upgrading the next node, wait for the cluster to finish shard allocation. You can check progress by submitting a _cat/health request:
```
GET _cat/health?v
```
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Wait for the status column to switch from yellow to green. Once the node is green, all primary and replica shards have been allocated.

During a rolling upgrade, primary shards assigned to a node running the new version cannot have their replicas assigned to a node with the old version. The new version might have a different data format that is not understood by the old version.

If it is not possible to assign the replica shards to another node (there is only one upgraded node in the cluster), the replica shards remain unassigned and status stays yellow.

In this case, you can proceed once there are no initializing or relocating shards (check the init and relo columns).

As soon as another node is upgraded, the replicas can be assigned and the status will change to green.

Shards that were not sync-flushed might take longer to recover. You can monitor the recovery status of individual shards by submitting a _cat/recovery request:
```
GET _cat/recovery
```
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If you stopped indexing, it is safe to resume indexing as soon as recovery completes.
Repeat

When the node has recovered and the cluster is stable, repeat these steps for each node that needs to be updated.
Restart machine learning jobs.

If you temporarily halted the tasks associated with your machine learning jobs, use the set upgrade mode API to return them to active states:
```
POST _ml/set_upgrade_mode?enabled=false
```
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If you closed all machine learning jobs before the upgrade, open the jobs and start the datafeeds from Kibana or with the open jobs and start datafeed APIs.

During a rolling upgrade, the cluster continues to operate normally. However, any new functionality is disabled or operates in a backward compatible mode until all nodes in the cluster are upgraded. New functionality becomes operational once the upgrade is complete and all nodes are running the new version. Once that has happened, there’s no way to return to operating in a backward compatible mode. Nodes running the previous major version will not be allowed to join the fully-updated cluster.

In the unlikely case of a network malfunction during the upgrade process that isolates all remaining old nodes from the cluster, you must take the old nodes offline and upgrade them to enable them to join the cluster.

If you stop half or more of the master-eligible nodes all at once during the upgrade then the cluster will become unavailable, meaning that the upgrade is no longer a rolling upgrade. If this happens, you should upgrade and restart all of the stopped master-eligible nodes to allow the cluster to form again, as if performing a full-cluster restart upgrade. It may also be necessary to upgrade all of the remaining old nodes before they can join the cluster after it re-forms.

Similarly, if you run a testing/development environment with only one master node, the master node should be upgraded last. Restarting a single master node forces the cluster to be reformed. The new cluster will initially only have the upgraded master node and will thus reject the older nodes when they re-join the cluster. Nodes that have already been upgraded will successfully re-join the upgraded master.