Reindex API

The most basic form of _reindex just copies documents from one index to another. This will copy documents from the twitter index into the new_twitter index:

POST _reindex
{
  "source": {
    "index": "twitter"
  },
  "dest": {
    "index": "new_twitter"
  }
}

That will return something like this:

{
  "took" : 147,
  "timed_out": false,
  "created": 120,
  "updated": 0,
  "deleted": 0,
  "batches": 1,
  "version_conflicts": 0,
  "noops": 0,
  "retries": {
    "bulk": 0,
    "search": 0
  },
  "throttled_millis": 0,
  "requests_per_second": -1.0,
  "throttled_until_millis": 0,
  "total": 120,
  "failures" : [ ]
}

Just like _update_by_query, _reindex gets a snapshot of the source index but its target must be a different index so version conflicts are unlikely. The dest element can be configured like the index API to control optimistic concurrency control. Just leaving out version_type (as above) or setting it to internal will cause Elasticsearch to blindly dump documents into the target, overwriting any that happen to have the same type and id:

POST _reindex
{
  "source": {
    "index": "twitter"
  },
  "dest": {
    "index": "new_twitter",
    "version_type": "internal"
  }
}

Setting version_type to external will cause Elasticsearch to preserve the version from the source, create any documents that are missing, and update any documents that have an older version in the destination index than they do in the source index:

POST _reindex
{
  "source": {
    "index": "twitter"
  },
  "dest": {
    "index": "new_twitter",
    "version_type": "external"
  }
}

Settings op_type to create will cause _reindex to only create missing documents in the target index. All existing documents will cause a version conflict:

POST _reindex
{
  "source": {
    "index": "twitter"
  },
  "dest": {
    "index": "new_twitter",
    "op_type": "create"
  }
}

By default version conflicts abort the _reindex process but you can just count them by settings "conflicts": "proceed" in the request body:

POST _reindex
{
  "conflicts": "proceed",
  "source": {
    "index": "twitter"
  },
  "dest": {
    "index": "new_twitter",
    "op_type": "create"
  }
}

You can limit the documents by adding a type to the source or by adding a query. This will only copy tweets made by kimchy into new_twitter:

POST _reindex
{
  "source": {
    "index": "twitter",
    "type": "_doc",
    "query": {
      "term": {
        "user": "kimchy"
      }
    }
  },
  "dest": {
    "index": "new_twitter"
  }
}

index and type in source can both be lists, allowing you to copy from lots of sources in one request. This will copy documents from the _doc and post types in the twitter and blog index. The copied documents would include the post type in the twitter index and the _doc type in the blog index. For more specific parameters, you can use query.

The Reindex API makes no effort to handle ID collisions. For such issues, the target index will remain valid, but it’s not easy to predict which document will survive because the iteration order isn’t well defined.

POST _reindex
{
  "source": {
    "index": ["twitter", "blog"],
    "type": ["_doc", "post"]
  },
  "dest": {
    "index": "all_together"
  }
}

It’s also possible to limit the number of processed documents by setting size. This will only copy a single document from twitter to new_twitter:

POST _reindex
{
  "size": 1,
  "source": {
    "index": "twitter"
  },
  "dest": {
    "index": "new_twitter"
  }
}

If you want a particular set of documents from the twitter index you’ll need to use sort. Sorting makes the scroll less efficient but in some contexts it’s worth it. If possible, prefer a more selective query to size and sort. This will copy 10000 documents from twitter into new_twitter:

POST _reindex
{
  "size": 10000,
  "source": {
    "index": "twitter",
    "sort": { "date": "desc" }
  },
  "dest": {
    "index": "new_twitter"
  }
}

The source section supports all the elements that are supported in a search request. For instance, only a subset of the fields from the original documents can be reindexed using source filtering as follows:

POST _reindex
{
  "source": {
    "index": "twitter",
    "_source": ["user", "_doc"]
  },
  "dest": {
    "index": "new_twitter"
  }
}

Like _update_by_query, _reindex supports a script that modifies the document. Unlike _update_by_query, the script is allowed to modify the document’s metadata. This example bumps the version of the source document:

POST _reindex
{
  "source": {
    "index": "twitter"
  },
  "dest": {
    "index": "new_twitter",
    "version_type": "external"
  },
  "script": {
    "source": "if (ctx._source.foo == 'bar') {ctx._version++; ctx._source.remove('foo')}",
    "lang": "painless"
  }
}

Just as in _update_by_query, you can set ctx.op to change the operation that is executed on the destination index:

Setting ctx.op to anything else will return an error, as will setting any other field in ctx.

Think of the possibilities! Just be careful; you are able to change:

Setting _version to null or clearing it from the ctx map is just like not sending the version in an indexing request; it will cause the document to be overwritten in the target index regardless of the version on the target or the version type you use in the _reindex request.

By default if _reindex sees a document with routing then the routing is preserved unless it’s changed by the script. You can set routing on the dest request to change this:

For example, you can use the following request to copy all documents from the source index with the company name cat into the dest index with routing set to cat.

POST _reindex
{
  "source": {
    "index": "source",
    "query": {
      "match": {
        "company": "cat"
      }
    }
  },
  "dest": {
    "index": "dest",
    "routing": "=cat"
  }
}

By default _reindex uses scroll batches of 1000. You can change the batch size with the size field in the source element:

POST _reindex
{
  "source": {
    "index": "source",
    "size": 100
  },
  "dest": {
    "index": "dest",
    "routing": "=cat"
  }
}

Reindex can also use the Ingest Node feature by specifying a pipeline like this:

POST _reindex
{
  "source": {
    "index": "source"
  },
  "dest": {
    "index": "dest",
    "pipeline": "some_ingest_pipeline"
  }
}

Reindex supports reindexing from a remote Elasticsearch cluster:

POST _reindex
{
  "source": {
    "remote": {
      "host": "http://otherhost:9200",
      "username": "user",
      "password": "pass"
    },
    "index": "source",
    "query": {
      "match": {
        "test": "data"
      }
    }
  },
  "dest": {
    "index": "dest"
  }
}

The host parameter must contain a scheme, host, and port (e.g. https://otherhost:9200). The username and password parameters are optional, and when they are present _reindex will connect to the remote Elasticsearch node using basic auth. Be sure to use https when using basic auth or the password will be sent in plain text.

Remote hosts have to be explicitly whitelisted in elasticsearch.yml using the reindex.remote.whitelist property. It can be set to a comma delimited list of allowed remote host and port combinations (e.g. otherhost:9200, another:9200, 127.0.10.*:9200, localhost:*). Scheme is ignored by the whitelist - only host and port are used, for example:

reindex.remote.whitelist: "otherhost:9200, another:9200, 127.0.10.*:9200, localhost:*"

The whitelist must be configured on any nodes that will coordinate the reindex.

This feature should work with remote clusters of any version of Elasticsearch you are likely to find. This should allow you to upgrade from any version of Elasticsearch to the current version by reindexing from a cluster of the old version.

To enable queries sent to older versions of Elasticsearch the query parameter is sent directly to the remote host without validation or modification.

Reindexing from a remote server uses an on-heap buffer that defaults to a maximum size of 100mb. If the remote index includes very large documents you’ll need to use a smaller batch size. The example below sets the batch size to 10 which is very, very small.

POST _reindex
{
  "source": {
    "remote": {
      "host": "http://otherhost:9200"
    },
    "index": "source",
    "size": 10,
    "query": {
      "match": {
        "test": "data"
      }
    }
  },
  "dest": {
    "index": "dest"
  }
}

It is also possible to set the socket read timeout on the remote connection with the socket_timeout field and the connection timeout with the connect_timeout field. Both default to 30 seconds. This example sets the socket read timeout to one minute and the connection timeout to 10 seconds:

POST _reindex
{
  "source": {
    "remote": {
      "host": "http://otherhost:9200",
      "socket_timeout": "1m",
      "connect_timeout": "10s"
    },
    "index": "source",
    "query": {
      "match": {
        "test": "data"
      }
    }
  },
  "dest": {
    "index": "dest"
  }
}

In addition to the standard parameters like pretty, the Reindex API also supports refresh, wait_for_completion, wait_for_active_shards, timeout, scroll and requests_per_second.

Sending the refresh url parameter will cause all indexes to which the request wrote to be refreshed. This is different than the Index API’s refresh parameter which causes just the shard that received the new data to be refreshed.

If the request contains wait_for_completion=false then Elasticsearch will perform some preflight checks, launch the request, and then return a task which can be used with Tasks APIs to cancel or get the status of the task. Elasticsearch will also create a record of this task as a document at .tasks/task/${taskId}. This is yours to keep or remove as you see fit. When you are done with it, delete it so Elasticsearch can reclaim the space it uses.

wait_for_active_shards controls how many copies of a shard must be active before proceeding with the reindexing. See here for details. timeout controls how long each write request waits for unavailable shards to become available. Both work exactly how they work in the Bulk API. As _reindex uses scroll search, you can also specify the scroll parameter to control how long it keeps the "search context" alive, (e.g. ?scroll=10m). The default value is 5 minutes.

requests_per_second can be set to any positive decimal number (1.4, 6, 1000, etc) and throttles the rate at which _reindex issues batches of index operations by padding each batch with a wait time. The throttling can be disabled by setting requests_per_second to -1.

The throttling is done by waiting between batches so that the scroll which _reindex uses internally can be given a timeout that takes into account the padding. The padding time is the difference between the batch size divided by the requests_per_second and the time spent writing. By default the batch size is 1000, so if the requests_per_second is set to 500:

target_time = 1000 / 500 per second = 2 seconds
wait_time = target_time - write_time = 2 seconds - .5 seconds = 1.5 seconds

Since the batch is issued as a single _bulk request, large batch sizes will cause Elasticsearch to create many requests and then wait for a while before starting the next set. This is "bursty" instead of "smooth". The default value is -1.

The JSON response looks like this:

{
  "took": 639,
  "timed_out": false,
  "total": 5,
  "updated": 0,
  "created": 5,
  "deleted": 0,
  "batches": 1,
  "noops": 0,
  "version_conflicts": 2,
  "retries": {
    "bulk": 0,
    "search": 0
  },
  "throttled_millis": 0,
  "requests_per_second": 1,
  "throttled_until_millis": 0,
  "failures": [ ]
}

You can fetch the status of all running reindex requests with the Task API:

GET _tasks?detailed=true&actions=*reindex

The response looks like:

{
  "nodes" : {
    "r1A2WoRbTwKZ516z6NEs5A" : {
      "name" : "r1A2WoR",
      "transport_address" : "127.0.0.1:9300",
      "host" : "127.0.0.1",
      "ip" : "127.0.0.1:9300",
      "attributes" : {
        "testattr" : "test",
        "portsfile" : "true"
      },
      "tasks" : {
        "r1A2WoRbTwKZ516z6NEs5A:36619" : {
          "node" : "r1A2WoRbTwKZ516z6NEs5A",
          "id" : 36619,
          "type" : "transport",
          "action" : "indices:data/write/reindex",
          "status" : {    
            "total" : 6154,
            "updated" : 3500,
            "created" : 0,
            "deleted" : 0,
            "batches" : 4,
            "version_conflicts" : 0,
            "noops" : 0,
            "retries": {
              "bulk": 0,
              "search": 0
            },
            "throttled_millis": 0,
            "requests_per_second": -1,
            "throttled_until_millis": 0
          },
          "description" : "",
          "start_time_in_millis": 1535149899665,
          "running_time_in_nanos": 5926916792,
          "cancellable": true,
          "headers": {}
        }
      }
    }
  }
}

With the task id you can look up the task directly. The following example retrieves information about the task r1A2WoRbTwKZ516z6NEs5A:36619:

GET /_tasks/r1A2WoRbTwKZ516z6NEs5A:36619

The advantage of this API is that it integrates with wait_for_completion=false to transparently return the status of completed tasks. If the task is completed and wait_for_completion=false was set, it will return a results or an error field. The cost of this feature is the document that wait_for_completion=false creates at .tasks/task/${taskId}. It is up to you to delete that document.

Any Reindex can be canceled using the Task Cancel API. For example:

POST _tasks/r1A2WoRbTwKZ516z6NEs5A:36619/_cancel

The task ID can be found using the Tasks API.

Cancelation should happen quickly but might take a few seconds. The Tasks API will continue to list the task until it wakes to cancel itself.

The value of requests_per_second can be changed on a running reindex using the _rethrottle API:

POST _reindex/r1A2WoRbTwKZ516z6NEs5A:36619/_rethrottle?requests_per_second=-1

The task ID can be found using the tasks API.

Just like when setting it on the Reindex API, requests_per_second can be either -1 to disable throttling or any decimal number like 1.7 or 12 to throttle to that level. Rethrottling that speeds up the query takes effect immediately but rethrotting that slows down the query will take effect on after completing the current batch. This prevents scroll timeouts.

_reindex can be used to build a copy of an index with renamed fields. Say you create an index containing documents that look like this:

POST test/_doc/1?refresh
{
  "text": "words words",
  "flag": "foo"
}

but you don’t like the name flag and want to replace it with tag. _reindex can create the other index for you:

POST _reindex
{
  "source": {
    "index": "test"
  },
  "dest": {
    "index": "test2"
  },
  "script": {
    "source": "ctx._source.tag = ctx._source.remove(\"flag\")"
  }
}

Now you can get the new document:

GET test2/_doc/1

which will return:

{
  "found": true,
  "_id": "1",
  "_index": "test2",
  "_type": "_doc",
  "_version": 1,
  "_source": {
    "text": "words words",
    "tag": "foo"
  }
}

Reindex supports Sliced Scroll to parallelize the reindexing process. This parallelization can improve efficiency and provide a convenient way to break the request down into smaller parts.

Slice a reindex request manually by providing a slice id and total number of slices to each request:

POST _reindex
{
  "source": {
    "index": "twitter",
    "slice": {
      "id": 0,
      "max": 2
    }
  },
  "dest": {
    "index": "new_twitter"
  }
}
POST _reindex
{
  "source": {
    "index": "twitter",
    "slice": {
      "id": 1,
      "max": 2
    }
  },
  "dest": {
    "index": "new_twitter"
  }
}

You can verify this works by:

GET _refresh
POST new_twitter/_search?size=0&filter_path=hits.total

which results in a sensible total like this one:

{
  "hits": {
    "total": 120
  }
}

You can also let _reindex automatically parallelize using Sliced Scroll to slice on _uid. Use slices to specify the number of slices to use:

POST _reindex?slices=5&refresh
{
  "source": {
    "index": "twitter"
  },
  "dest": {
    "index": "new_twitter"
  }
}

You can also this verify works by:

POST new_twitter/_search?size=0&filter_path=hits.total

which results in a sensible total like this one:

{
  "hits": {
    "total": 120
  }
}

Setting slices to auto will let Elasticsearch choose the number of slices to use. This setting will use one slice per shard, up to a certain limit. If there are multiple source indices, it will choose the number of slices based on the index with the smallest number of shards.

Adding slices to _reindex just automates the manual process used in the section above, creating sub-requests which means it has some quirks:

If slicing automatically, setting slices to auto will choose a reasonable number for most indices. If slicing manually or otherwise tuning automatic slicing, use these guidelines.

Query performance is most efficient when the number of slices is equal to the number of shards in the index. If that number is large (e.g. 500), choose a lower number as too many slices will hurt performance. Setting slices higher than the number of shards generally does not improve efficiency and adds overhead.

Indexing performance scales linearly across available resources with the number of slices.

Whether query or indexing performance dominates the runtime depends on the documents being reindexed and cluster resources.

If you have many indices to reindex it is generally better to reindex them one at a time rather than using a glob pattern to pick up many indices. That way you can resume the process if there are any errors by removing the partially completed index and starting over at that index. It also makes parallelizing the process fairly simple: split the list of indices to reindex and run each list in parallel.

One off bash scripts seem to work nicely for this:

for index in i1 i2 i3 i4 i5; do
  curl -HContent-Type:application/json -XPOST localhost:9200/_reindex?pretty -d'{
    "source": {
      "index": "'$index'"
    },
    "dest": {
      "index": "'$index'-reindexed"
    }
  }'
done

Notwithstanding the above advice, you can use _reindex in combination with Painless to reindex daily indices to apply a new template to the existing documents.

Assuming you have indices consisting of documents as follows:

PUT metricbeat-2016.05.30/_doc/1?refresh
{"system.cpu.idle.pct": 0.908}
PUT metricbeat-2016.05.31/_doc/1?refresh
{"system.cpu.idle.pct": 0.105}

The new template for the metricbeat-* indices is already loaded into Elasticsearch, but it applies only to the newly created indices. Painless can be used to reindex the existing documents and apply the new template.

The script below extracts the date from the index name and creates a new index with -1 appended. All data from metricbeat-2016.05.31 will be reindexed into metricbeat-2016.05.31-1.

POST _reindex
{
  "source": {
    "index": "metricbeat-*"
  },
  "dest": {
    "index": "metricbeat"
  },
  "script": {
    "lang": "painless",
    "source": "ctx._index = 'metricbeat-' + (ctx._index.substring('metricbeat-'.length(), ctx._index.length())) + '-1'"
  }
}

All documents from the previous metricbeat indices can now be found in the *-1 indices.

GET metricbeat-2016.05.30-1/_doc/1
GET metricbeat-2016.05.31-1/_doc/1

The previous method can also be used in conjunction with change the name of a field to load only the existing data into the new index and rename any fields if needed.

_reindex can be used to extract a random subset of an index for testing:

POST _reindex
{
  "size": 10,
  "source": {
    "index": "twitter",
    "query": {
      "function_score" : {
        "query" : { "match_all": {} },
        "random_score" : {}
      }
    },
    "sort": "_score"    
  },
  "dest": {
    "index": "random_twitter"
  }
}