[[backing-up-your-cluster]]
=== Backing Up Your Cluster
As with any software that stores data, it is important to routinely back up your
data. ((("clusters", "backing up")))((("post-deployment", "backing up your cluster")))((("backing up your cluster"))) Elasticsearch replicas provide high availability during runtime; they allow
you to tolerate sporadic node loss without an interruption of service.
Replicas do not provide protection from catastrophic failure, however. For that,
you need a real backup of your cluster--a complete copy in case something goes
wrong.
To back up your cluster, you can use the `snapshot` API.((("snapshot-restore API"))) This will take the current
state and data in your cluster and save it to a shared repository. This
backup process is "smart." Your first snapshot will be a complete copy of data,
but all subsequent snapshots will save the _delta_ between the existing
snapshots and the new data. Data is incrementally added and deleted as you snapshot
data over time. This means subsequent backups will be substantially
faster since they are transmitting far less data.
To use this functionality, you must first create a repository to save data.
There are several repository types that you may choose from:
- Shared filesystem, such as a NAS
- Amazon S3
- HDFS (Hadoop Distributed File System)
- Azure Cloud
==== Creating the Repository
Let's set up a shared ((("backing up your cluster", "creating the repository")))((("filesystem repository")))filesystem repository:
[source,js]
----
PUT _snapshot/my_backup <1>
{
"type": "fs", <2>
"settings": {
"location": "/mount/backups/my_backup" <3>
}
}
----
<1> We provide a name for our repository, in this case it is called `my_backup`.
<2> We specify that the type of the repository should be a shared filesystem.
<3> And finally, we provide a mounted drive as the destination.
NOTE: The shared filesystem path must be accessible from all nodes in your
cluster!
This will create the repository and required metadata at the mount point. There
are also some other options that you may want to configure, depending on the
performance profile of your nodes, network, and repository location:
`max_snapshot_bytes_per_sec`::
When snapshotting data into the repo, this controls
the throttling of that process. The default is `20mb` per second.
`max_restore_bytes_per_sec`::
When restoring data from the repo, this controls
how much the restore is throttled so that your network is not saturated. The
default is `20mb` per second.
Let's assume we have a very fast network and are OK with extra traffic, so we
can increase the defaults:
[source,js]
----
POST _snapshot/my_backup/ <1>
{
"type": "fs",
"settings": {
"location": "/mount/backups/my_backup",
"max_snapshot_bytes_per_sec" : "50mb", <2>
"max_restore_bytes_per_sec" : "50mb"
}
}
----
<1> Note that we are using a `POST` instead of `PUT`. This will update the settings
of the existing repository.
<2> Then add our new settings.
==== Snapshotting All Open Indices
A repository can contain multiple snapshots.((("indices", "open, snapshots on")))((("backing up your cluster", "snapshots on all open indexes"))) Each snapshot is associated with a
certain set of indices (for example, all indices, some subset, or a single index). When
creating a snapshot, you specify which indices you are interested in and
give the snapshot a unique name.
Let's start with the most basic snapshot command:
[source,js]
----
PUT _snapshot/my_backup/snapshot_1
----
This will back up all open indices into a snapshot named `snapshot_1`, under the
`my_backup` repository. This call will return immediately, and the snapshot will
proceed in the background.
[TIP]
==================================================
Usually you'll want your snapshots to proceed as a background process, but occasionally
you may want to wait for completion in your script. This can be accomplished by
adding a `wait_for_completion` flag:
[source,js]
----
PUT _snapshot/my_backup/snapshot_1?wait_for_completion=true
----
This will block the call until the snapshot has completed. Note that large snapshots
may take a long time to return!
==================================================
==== Snapshotting Particular Indices
The default behavior is to back up all open indices.((("indices", "snapshotting particular")))((("backing up your cluster", "snapshotting particular indices"))) But say you are using Marvel,
and don't really want to back up all the diagnostic `.marvel` indices. You
just don't have enough space to back up everything.
In that case, you can specify which indices to back up when snapshotting your cluster:
[source,js]
----
PUT _snapshot/my_backup/snapshot_2
{
"indices": "index_1,index_2"
}
----
This snapshot command will now back up only `index1` and `index2`.
==== Listing Information About Snapshots
Once you start accumulating snapshots in your repository, you may forget the details((("backing up your cluster", "listing information about snapshots")))
relating to each--particularly when the snapshots are named based on time
demarcations (for example, `backup_2014_10_28`).
To obtain information about a single snapshot, simply issue a `GET` reguest against
the repo and snapshot name:
[source,js]
----
GET _snapshot/my_backup/snapshot_2
----
This will return a small response with various pieces of information regarding
the snapshot:
[source,js]
----
{
"snapshots": [
{
"snapshot": "snapshot_1",
"indices": [
".marvel_2014_28_10",
"index1",
"index2"
],
"state": "SUCCESS",
"start_time": "2014-09-02T13:01:43.115Z",
"start_time_in_millis": 1409662903115,
"end_time": "2014-09-02T13:01:43.439Z",
"end_time_in_millis": 1409662903439,
"duration_in_millis": 324,
"failures": [],
"shards": {
"total": 10,
"failed": 0,
"successful": 10
}
}
]
}
----
For a complete listing of all snapshots in a repository, use the `_all` placeholder
instead of a snapshot name:
[source,js]
----
GET _snapshot/my_backup/_all
----
==== Deleting Snapshots
Finally, we need a command to delete old snapshots that ((("backing up your cluster", "deleting old snapshots")))are no longer useful.
This is simply a `DELETE` HTTP call to the repo/snapshot name:
[source,js]
----
DELETE _snapshot/my_backup/snapshot_2
----
It is important to use the API to delete snapshots, and not some other mechanism
(such as deleting by hand, or using automated cleanup tools on S3). Because snapshots are
incremental, it is possible that many snapshots are relying on old segments.
The `delete` API understands what data is still in use by more recent snapshots,
and will delete only unused segments.
If you do a manual file delete, however, you are at risk of seriously corrupting
your backups because you are deleting data that is still in use.
==== Monitoring Snapshot Progress
The `wait_for_completion` flag provides a rudimentary form of monitoring, but
really isn't sufficient when snapshotting or restoring even moderately sized clusters.
Two other APIs will give you more-detailed status about the
state of the snapshotting. First you can execute a `GET` to the snapshot ID,
just as we did earlier get information about a particular snapshot:
[source,js]
----
GET _snapshot/my_backup/snapshot_3
----
If the snapshot is still in progress when you call this, you'll see information
about when it was started, how long it has been running, and so forth. Note, however,
that this API uses the same threadpool as the snapshot mechanism. If you are
snapshotting very large shards, the time between status updates can be quite large,
since the API is competing for the same threadpool resources.
A better option is to poll the `_status` API:
[source,js]
----
GET _snapshot/my_backup/snapshot_3/_status
----
The `_status` API returns immediately and gives a much more verbose output of
statistics:
[source,js]
----
{
"snapshots": [
{
"snapshot": "snapshot_3",
"repository": "my_backup",
"state": "IN_PROGRESS", <1>
"shards_stats": {
"initializing": 0,
"started": 1, <2>
"finalizing": 0,
"done": 4,
"failed": 0,
"total": 5
},
"stats": {
"number_of_files": 5,
"processed_files": 5,
"total_size_in_bytes": 1792,
"processed_size_in_bytes": 1792,
"start_time_in_millis": 1409663054859,
"time_in_millis": 64
},
"indices": {
"index_3": {
"shards_stats": {
"initializing": 0,
"started": 0,
"finalizing": 0,
"done": 5,
"failed": 0,
"total": 5
},
"stats": {
"number_of_files": 5,
"processed_files": 5,
"total_size_in_bytes": 1792,
"processed_size_in_bytes": 1792,
"start_time_in_millis": 1409663054859,
"time_in_millis": 64
},
"shards": {
"0": {
"stage": "DONE",
"stats": {
"number_of_files": 1,
"processed_files": 1,
"total_size_in_bytes": 514,
"processed_size_in_bytes": 514,
"start_time_in_millis": 1409663054862,
"time_in_millis": 22
}
},
...
----
<1> A snapshot that is currently running will show `IN_PROGRESS` as its status.
<2> This particular snapshot has one shard still transferring (the other four have already completed).
The response includes the overall status of the snapshot, but also drills down into
per-index and per-shard statistics. This gives you an incredibly detailed view
of how the snapshot is progressing. Shards can be in various states of completion:
`INITIALIZING`::
The shard is checking with the cluster state to see whether it can
be snapshotted. This is usually very fast.
`STARTED`::
Data is being transferred to the repository.
`FINALIZING`::
Data transfer is complete; the shard is now sending snapshot metadata.
`DONE`::
Snapshot complete!
`FAILED`::
An error was encountered during the snapshot process, and this shard/index/snapshot
could not be completed. Check your logs for more information.
==== Canceling a Snapshot
Finally, you may want to cancel a snapshot or restore.((("backing up your cluster", "canceling a snapshot"))) Since these are long-running
processes, a typo or mistake when executing the operation could take a long time to
resolve--and use up valuable resources at the same time.
To cancel a snapshot, simply delete the snapshot while it is in progress:
[source,js]
----
DELETE _snapshot/my_backup/snapshot_3
----
This will halt the snapshot process. Then proceed to delete the half-completed
snapshot from the repository.
- Introduction
- 入门
- 是什么
- 安装
- API
- 文档
- 索引
- 搜索
- 聚合
- 小结
- 分布式
- 结语
- 分布式集群
- 空集群
- 集群健康
- 添加索引
- 故障转移
- 横向扩展
- 更多扩展
- 应对故障
- 数据
- 文档
- 索引
- 获取
- 存在
- 更新
- 创建
- 删除
- 版本控制
- 局部更新
- Mget
- 批量
- 结语
- 分布式增删改查
- 路由
- 分片交互
- 新建、索引和删除
- 检索
- 局部更新
- 批量请求
- 批量格式
- 搜索
- 空搜索
- 多索引和多类型
- 分页
- 查询字符串
- 映射和分析
- 数据类型差异
- 确切值对决全文
- 倒排索引
- 分析
- 映射
- 复合类型
- 结构化查询
- 请求体查询
- 结构化查询
- 查询与过滤
- 重要的查询子句
- 过滤查询
- 验证查询
- 结语
- 排序
- 排序
- 字符串排序
- 相关性
- 字段数据
- 分布式搜索
- 查询阶段
- 取回阶段
- 搜索选项
- 扫描和滚屏
- 索引管理
- 创建删除
- 设置
- 配置分析器
- 自定义分析器
- 映射
- 根对象
- 元数据中的source字段
- 元数据中的all字段
- 元数据中的ID字段
- 动态映射
- 自定义动态映射
- 默认映射
- 重建索引
- 别名
- 深入分片
- 使文本可以被搜索
- 动态索引
- 近实时搜索
- 持久化变更
- 合并段
- 结构化搜索
- 查询准确值
- 组合过滤
- 查询多个准确值
- 包含,而不是相等
- 范围
- 处理 Null 值
- 缓存
- 过滤顺序
- 全文搜索
- 匹配查询
- 多词查询
- 组合查询
- 布尔匹配
- 增加子句
- 控制分析
- 关联失效
- 多字段搜索
- 多重查询字符串
- 单一查询字符串
- 最佳字段
- 最佳字段查询调优
- 多重匹配查询
- 最多字段查询
- 跨字段对象查询
- 以字段为中心查询
- 全字段查询
- 跨字段查询
- 精确查询
- 模糊匹配
- Phrase matching
- Slop
- Multi value fields
- Scoring
- Relevance
- Performance
- Shingles
- Partial_Matching
- Postcodes
- Prefix query
- Wildcard Regexp
- Match phrase prefix
- Index time
- Ngram intro
- Search as you type
- Compound words
- Relevance
- Scoring theory
- Practical scoring
- Query time boosting
- Query scoring
- Not quite not
- Ignoring TFIDF
- Function score query
- Popularity
- Boosting filtered subsets
- Random scoring
- Decay functions
- Pluggable similarities
- Conclusion
- Language intro
- Intro
- Using
- Configuring
- Language pitfalls
- One language per doc
- One language per field
- Mixed language fields
- Conclusion
- Identifying words
- Intro
- Standard analyzer
- Standard tokenizer
- ICU plugin
- ICU tokenizer
- Tidying text
- Token normalization
- Intro
- Lowercasing
- Removing diacritics
- Unicode world
- Case folding
- Character folding
- Sorting and collations
- Stemming
- Intro
- Algorithmic stemmers
- Dictionary stemmers
- Hunspell stemmer
- Choosing a stemmer
- Controlling stemming
- Stemming in situ
- Stopwords
- Intro
- Using stopwords
- Stopwords and performance
- Divide and conquer
- Phrase queries
- Common grams
- Relevance
- Synonyms
- Intro
- Using synonyms
- Synonym formats
- Expand contract
- Analysis chain
- Multi word synonyms
- Symbol synonyms
- Fuzzy matching
- Intro
- Fuzziness
- Fuzzy query
- Fuzzy match query
- Scoring fuzziness
- Phonetic matching
- Aggregations
- overview
- circuit breaker fd settings
- filtering
- facets
- docvalues
- eager
- breadth vs depth
- Conclusion
- concepts buckets
- basic example
- add metric
- nested bucket
- extra metrics
- bucket metric list
- histogram
- date histogram
- scope
- filtering
- sorting ordering
- approx intro
- cardinality
- percentiles
- sigterms intro
- sigterms
- fielddata
- analyzed vs not
- 地理坐标点
- 地理坐标点
- 通过地理坐标点过滤
- 地理坐标盒模型过滤器
- 地理距离过滤器
- 缓存地理位置过滤器
- 减少内存占用
- 按距离排序
- Geohashe
- Geohashe
- Geohashe映射
- Geohash单元过滤器
- 地理位置聚合
- 地理位置聚合
- 按距离聚合
- Geohash单元聚合器
- 范围(边界)聚合器
- 地理形状
- 地理形状
- 映射地理形状
- 索引地理形状
- 查询地理形状
- 在查询中使用已索引的形状
- 地理形状的过滤与缓存
- 关系
- 关系
- 应用级别的Join操作
- 扁平化你的数据
- Top hits
- Concurrency
- Concurrency solutions
- 嵌套
- 嵌套对象
- 嵌套映射
- 嵌套查询
- 嵌套排序
- 嵌套集合
- Parent Child
- Parent child
- Indexing parent child
- Has child
- Has parent
- Children agg
- Grandparents
- Practical considerations
- Scaling
- Shard
- Overallocation
- Kagillion shards
- Capacity planning
- Replica shards
- Multiple indices
- Index per timeframe
- Index templates
- Retiring data
- Index per user
- Shared index
- Faking it
- One big user
- Scale is not infinite
- Cluster Admin
- Marvel
- Health
- Node stats
- Other stats
- Deployment
- hardware
- other
- config
- dont touch
- heap
- file descriptors
- conclusion
- cluster settings
- Post Deployment
- dynamic settings
- logging
- indexing perf
- rolling restart
- backup
- restore
- conclusion