elasticsearch/docs/reference/docs/update-by-query.asciidoc

[[docs-update-by-query]]
=== Update By Query API
++++
<titleabbrev>Update by query</titleabbrev>
++++

Updates documents that match the specified query. 
If no query is specified, performs an update on every document in the index without
modifying the source, which is useful for picking up mapping changes.

[source,console]
--------------------------------------------------
POST twitter/_update_by_query?conflicts=proceed
--------------------------------------------------
// TEST[setup:big_twitter]

////

[source,console-result]
--------------------------------------------------
{
  "took" : 147,
  "timed_out": false,
  "updated": 120,
  "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" : [ ]
}
--------------------------------------------------
// TESTRESPONSE[s/"took" : 147/"took" : "$body.took"/]

////

[[docs-update-by-query-api-request]]
==== {api-request-title}

`POST /<index>/_update_by_query`

[[docs-update-by-query-api-desc]]
==== {api-description-title}

You can specify the query criteria in the request URI or the request body
using the same syntax as the  <<search-search,Search API>>. 

When you submit an update by query request, {es} gets a snapshot of the index
when it begins processing the request and updates matching documents using
`internal` versioning. 
When the versions match, the document is updated and the version number is incremented. 
If a document changes between the time that the snapshot is taken and 
the update operation is processed, it results in a version conflict and the operation fails. 
You can opt to count version conflicts instead of halting and returning by 
setting `conflicts` to `proceed`. 

NOTE: Documents with a version equal to 0 cannot be updated using update by
query because `internal` versioning does not support 0 as a valid
version number.

While processing an update by query request, {es} performs multiple search
requests sequentially to find all of the matching documents. 
A bulk update request is performed for each batch of matching documents. 
Any query or update failures cause the update by query request to fail and 
the failures are shown in the response.
Any update requests that completed successfully still stick, they are not rolled back.

===== Refreshing shards

Specifying the `refresh` parameter refreshes all shards once the request completes. 
This is different than the update API#8217;s `refresh` parameter, which causes just the shard
that received the request to be refreshed. Unlike the update API, it does not support 
`wait_for`.

[[docs-update-by-query-task-api]]
===== Running update by query asynchronously

If the request contains `wait_for_completion=false`, {es}
performs some preflight checks, launches the request, and returns a
<<tasks,`task`>> you can use to cancel or get the status of the task. 
{es} creates a record of this task as a document at `.tasks/task/${taskId}`. 
When you are done with a task, you should delete the task document so 
{es} can reclaim the space.

===== Waiting for active shards

`wait_for_active_shards` controls how many copies of a shard must be active
before proceeding with the request. See <<index-wait-for-active-shards>>
for details. `timeout` controls how long each write request waits for unavailable
shards to become available. Both work exactly the way they work in the
<<docs-bulk,Bulk API>>. Update by query uses scrolled searches, so you can also
specify the `scroll` parameter to control how long it keeps the search context 
alive, for example `?scroll=10m`. The default is 5 minutes.

===== Throttling update requests

To control the rate at which update by query issues batches of update operations,
you can set `requests_per_second` to any positive decimal number. This pads each
batch with a wait time to throttle the rate. Set `requests_per_second` to `-1` 
to disable throttling.

Throttling uses a wait time between batches so that the internal scroll requests 
can be given a timeout that takes the request padding into account. 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 `requests_per_second` is set to `500`:

[source,txt]
--------------------------------------------------
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 
cause {es} to create many requests and wait before starting the next set. 
This is "bursty" instead of "smooth". 

[[docs-update-by-query-slice]]
===== Slicing

Update by query supports <<sliced-scroll, sliced scroll>> to parallelize the
update process. This can improve efficiency and provide a
convenient way to break the request down into smaller parts.

Setting `slices` to `auto` chooses a reasonable number for most indices. 
If you're slicing manually or otherwise tuning automatic slicing, keep in mind 
that:

* 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 (for example,
500), choose a lower number as too many `slices` hurts performance. Setting
`slices` higher than the number of shards generally does not improve efficiency
and adds overhead.

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

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

[[docs-update-by-query-api-path-params]]
==== {api-path-parms-title}

`<index>`::
(Optional, string) A comma-separated list of index names to search. Use `_all`
or omit to search all indices.

[[docs-update-by-query-api-query-params]]
==== {api-query-parms-title}

include::{docdir}/rest-api/common-parms.asciidoc[tag=allow-no-indices]

include::{docdir}/rest-api/common-parms.asciidoc[tag=analyzer]

include::{docdir}/rest-api/common-parms.asciidoc[tag=analyze_wildcard]
  
`conflicts`::
  (Optional, string) What to do if delete by query hits version conflicts: 
  `abort` or `proceed`. Defaults to `abort`.

include::{docdir}/rest-api/common-parms.asciidoc[tag=default_operator]

include::{docdir}/rest-api/common-parms.asciidoc[tag=df]
  
include::{docdir}/rest-api/common-parms.asciidoc[tag=expand-wildcards]
+
Defaults to `open`.

include::{docdir}/rest-api/common-parms.asciidoc[tag=from]

include::{docdir}/rest-api/common-parms.asciidoc[tag=index-ignore-unavailable]
  
include::{docdir}/rest-api/common-parms.asciidoc[tag=lenient]
  
include::{docdir}/rest-api/common-parms.asciidoc[tag=max_docs]

include::{docdir}/rest-api/common-parms.asciidoc[tag=pipeline]

include::{docdir}/rest-api/common-parms.asciidoc[tag=preference]

include::{docdir}/rest-api/common-parms.asciidoc[tag=search-q]

include::{docdir}/rest-api/common-parms.asciidoc[tag=request_cache]

include::{docdir}/rest-api/common-parms.asciidoc[tag=refresh]

include::{docdir}/rest-api/common-parms.asciidoc[tag=requests_per_second]

include::{docdir}/rest-api/common-parms.asciidoc[tag=routing]

include::{docdir}/rest-api/common-parms.asciidoc[tag=scroll]

include::{docdir}/rest-api/common-parms.asciidoc[tag=scroll_size]

include::{docdir}/rest-api/common-parms.asciidoc[tag=search_type]

include::{docdir}/rest-api/common-parms.asciidoc[tag=search_timeout]
  
include::{docdir}/rest-api/common-parms.asciidoc[tag=slices]
  
include::{docdir}/rest-api/common-parms.asciidoc[tag=sort]

include::{docdir}/rest-api/common-parms.asciidoc[tag=source]

include::{docdir}/rest-api/common-parms.asciidoc[tag=source_excludes]

include::{docdir}/rest-api/common-parms.asciidoc[tag=source_includes]

include::{docdir}/rest-api/common-parms.asciidoc[tag=stats]
  
include::{docdir}/rest-api/common-parms.asciidoc[tag=terminate_after]

include::{docdir}/rest-api/common-parms.asciidoc[tag=timeout]

include::{docdir}/rest-api/common-parms.asciidoc[tag=version]

include::{docdir}/rest-api/common-parms.asciidoc[tag=wait_for_active_shards]

[[docs-update-by-query-api-request-body]]
==== {api-request-body-title}

`query`::
  (Optional, <<query-dsl,query object>>) Specifies the documents to update 
  using the  <<query-dsl,Query DSL>>.
  

[[docs-update-by-query-api-response-body]]
==== Response body

`took`::
The number of milliseconds from start to end of the whole operation.

`timed_out`::
This flag is set to `true` if any of the requests executed during the
update by query execution has timed out.

`total`::
The number of documents that were successfully processed.

`updated`::
The number of documents that were successfully updated.

`deleted`::
The number of documents that were successfully deleted.

`batches`::
The number of scroll responses pulled back by the update by query.

`version_conflicts`::
The number of version conflicts that the update by query hit.

`noops`::
The number of documents that were ignored because the script used for
the update by query returned a `noop` value for `ctx.op`.

`retries`::
The number of retries attempted by update by query. `bulk` is the number of bulk
actions retried, and `search` is the number of search actions retried.

`throttled_millis`::
Number of milliseconds the request slept to conform to `requests_per_second`.

`requests_per_second`::
The number of requests per second effectively executed during the update by query.

`throttled_until_millis`::
This field should always be equal to zero in an `_update_by_query` response. It only
has meaning when using the <<docs-update-by-query-task-api, Task API>>, where it
indicates the next time (in milliseconds since epoch) a throttled request will be
executed again in order to conform to `requests_per_second`.

`failures`::
Array of failures if there were any unrecoverable errors during the process. If
this is non-empty then the request aborted because of those failures.
Update by query is implemented using batches. Any failure causes the entire
process to abort, but all failures in the current batch are collected into the
array. You can use the `conflicts` option to prevent reindex from aborting on
version conflicts.

[[docs-update-by-query-api-example]]
==== {api-examples-title}

The simplest usage of `_update_by_query` just performs an update on every
document in the index without changing the source. This is useful to
<<picking-up-a-new-property,pick up a new property>> or some other online
mapping change.

To update selected documents, specify a query in the request body:

[source,console]
--------------------------------------------------
POST twitter/_update_by_query?conflicts=proceed
{
  "query": { <1>
    "term": {
      "user": "kimchy"
    }
  }
}
--------------------------------------------------
// TEST[setup:twitter]

<1> The query must be passed as a value to the `query` key, in the same
way as the <<search-search,Search API>>. You can also use the `q`
parameter in the same way as the search API.

Update documents in multiple indices:

[source,console]
--------------------------------------------------
POST twitter,blog/_update_by_query
--------------------------------------------------
// TEST[s/^/PUT twitter\nPUT blog\n/]

Limit the update by query operation to shards that a particular routing value:

[source,console]
--------------------------------------------------
POST twitter/_update_by_query?routing=1
--------------------------------------------------
// TEST[setup:twitter]

By default update by query uses scroll batches of 1000. 
You can change the batch size with the `scroll_size` parameter:

[source,console]
--------------------------------------------------
POST twitter/_update_by_query?scroll_size=100
--------------------------------------------------
// TEST[setup:twitter]

[[docs-update-by-query-api-source]]
===== Update the document source

Update by query supports scripts to update the document source. 
For example, the following request increments the likes field for all of kimchy’s tweets:

[source,console]
--------------------------------------------------
POST twitter/_update_by_query
{
  "script": {
    "source": "ctx._source.likes++",
    "lang": "painless"
  },
  "query": {
    "term": {
      "user": "kimchy"
    }
  }
}
--------------------------------------------------
// TEST[setup:twitter]

Note that `conflicts=proceed` is not specified in this example. In this case, a
version conflict should halt the process so you can handle the failure.

As with the <<docs-update,Update API>>, you can set `ctx.op` to change the
operation that is performed:

[horizontal]
`noop`::
Set `ctx.op = "noop"` if your script decides that it doesn't have to make any changes. 
The update by query operation skips updating the document and increments the  `noop` counter.

`delete`::
Set `ctx.op = "delete"` if your script decides that the document should be deleted. 
The update by query operation deletes the document and increments the  `deleted` counter.

Update by query only supports `update`, `noop`, and `delete`.
Setting `ctx.op` to anything else is an error. Setting any other field in `ctx` is an error.
This API only enables you to modify the source of matching documents, you cannot move them. 

[[docs-update-by-query-api-ingest-pipeline]]
===== Update documents using an ingest pipeline

Update by query can use the <<ingest>> feature by specifying a `pipeline`:

[source,console]
--------------------------------------------------
PUT _ingest/pipeline/set-foo
{
  "description" : "sets foo",
  "processors" : [ {
      "set" : {
        "field": "foo",
        "value": "bar"
      }
  } ]
}
POST twitter/_update_by_query?pipeline=set-foo
--------------------------------------------------
// TEST[setup:twitter]


[float]
[[docs-update-by-query-fetch-tasks]]
===== Get the status of update by query operations

You can fetch the status of all running update by query requests with the
<<tasks,Task API>>:

[source,console]
--------------------------------------------------
GET _tasks?detailed=true&actions=*byquery
--------------------------------------------------
// TEST[skip:No tasks to retrieve]

The responses looks like:

[source,console-result]
--------------------------------------------------
{
  "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/update/byquery",
          "status" : {    <1>
            "total" : 6154,
            "updated" : 3500,
            "created" : 0,
            "deleted" : 0,
            "batches" : 4,
            "version_conflicts" : 0,
            "noops" : 0,
            "retries": {
              "bulk": 0,
              "search": 0
            },
            "throttled_millis": 0
          },
          "description" : ""
        }
      }
    }
  }
}
--------------------------------------------------

<1> This object contains the actual status. It is just like the response JSON
with the important addition of the `total` field. `total` is the total number
of operations that the reindex expects to perform. You can estimate the
progress by adding the `updated`, `created`, and `deleted` fields. The request
will finish when their sum is equal to the `total` field.

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

[source,console]
--------------------------------------------------
GET /_tasks/r1A2WoRbTwKZ516z6NEs5A:36619
--------------------------------------------------
// TEST[catch:missing]

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 on it, then it'll come back with 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.


[float]
[[docs-update-by-query-cancel-task-api]]
===== Cancel an update by query operation

Any update by query can be cancelled using the <<tasks,Task Cancel API>>:

[source,console]
--------------------------------------------------
POST _tasks/r1A2WoRbTwKZ516z6NEs5A:36619/_cancel
--------------------------------------------------

The task ID can be found using the <<tasks,tasks API>>.

Cancellation should happen quickly but might take a few seconds. The task status 
API above will continue to list the update by query task until this task checks 
that it has been cancelled and terminates itself.


[float]
[[docs-update-by-query-rethrottle]]
===== Change throttling for a request

The value of `requests_per_second` can be changed on a running update by query
using the `_rethrottle` API:

[source,console]
--------------------------------------------------
POST _update_by_query/r1A2WoRbTwKZ516z6NEs5A:36619/_rethrottle?requests_per_second=-1
--------------------------------------------------

The task ID can be found using the <<tasks, tasks API>>.

Just like when setting it on the `_update_by_query` 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 after completing the current batch. This prevents scroll
timeouts.

[float]
[[docs-update-by-query-manual-slice]]
===== Slice manually
Slice an update by query manually by providing a slice id and total number of
slices to each request:

[source,console]
----------------------------------------------------------------
POST twitter/_update_by_query
{
  "slice": {
    "id": 0,
    "max": 2
  },
  "script": {
    "source": "ctx._source['extra'] = 'test'"
  }
}
POST twitter/_update_by_query
{
  "slice": {
    "id": 1,
    "max": 2
  },
  "script": {
    "source": "ctx._source['extra'] = 'test'"
  }
}
----------------------------------------------------------------
// TEST[setup:big_twitter]

Which you can verify works with:

[source,console]
----------------------------------------------------------------
GET _refresh
POST twitter/_search?size=0&q=extra:test&filter_path=hits.total
----------------------------------------------------------------
// TEST[continued]

Which results in a sensible `total` like this one:

[source,console-result]
----------------------------------------------------------------
{
  "hits": {
    "total": {
        "value": 120,
        "relation": "eq"
    }
  }
}
----------------------------------------------------------------

[float]
[[docs-update-by-query-automatic-slice]]
===== Use automatic slicing

You can also let update by query automatically parallelize using
<<sliced-scroll>> to slice on `_id`. Use `slices` to specify the number of
slices to use:

[source,console]
----------------------------------------------------------------
POST twitter/_update_by_query?refresh&slices=5
{
  "script": {
    "source": "ctx._source['extra'] = 'test'"
  }
}
----------------------------------------------------------------
// TEST[setup:big_twitter]

Which you also can verify works with:

[source,console]
----------------------------------------------------------------
POST twitter/_search?size=0&q=extra:test&filter_path=hits.total
----------------------------------------------------------------
// TEST[continued]

Which results in a sensible `total` like this one:

[source,console-result]
----------------------------------------------------------------
{
  "hits": {
    "total": {
        "value": 120,
        "relation": "eq"
    }
  }
}
----------------------------------------------------------------

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 `_update_by_query` just automates the manual process used in
the section above, creating sub-requests which means it has some quirks:

* You can see these requests in the
<<docs-update-by-query-task-api,Tasks APIs>>. These sub-requests are "child"
tasks of the task for the request with `slices`.
* Fetching the status of the task for the request with `slices` only contains
the status of completed slices.
* These sub-requests are individually addressable for things like cancellation
and rethrottling.
* Rethrottling the request with `slices` will rethrottle the unfinished
sub-request proportionally.
* Canceling the request with `slices` will cancel each sub-request.
* Due to the nature of `slices` each sub-request won't get a perfectly even
portion of the documents. All documents will be addressed, but some slices may
be larger than others. Expect larger slices to have a more even distribution.
* Parameters like `requests_per_second` and `max_docs` on a request with
`slices` are distributed proportionally to each sub-request. Combine that with
the point above about distribution being uneven and you should conclude that
using `max_docs` with `slices` might not result in exactly `max_docs` documents
being updated.
* Each sub-request gets a slightly different snapshot of the source index
though these are all taken at approximately the same time.

[float]
[[picking-up-a-new-property]]
===== Pick up a new property

Say you created an index without dynamic mapping, filled it with data, and then
added a mapping value to pick up more fields from the data:

[source,console]
--------------------------------------------------
PUT test
{
  "mappings": {
    "dynamic": false,   <1>
    "properties": {
      "text": {"type": "text"}
    }
  }
}

POST test/_doc?refresh
{
  "text": "words words",
  "flag": "bar"
}
POST test/_doc?refresh
{
  "text": "words words",
  "flag": "foo"
}
PUT test/_mapping   <2>
{
  "properties": {
    "text": {"type": "text"},
    "flag": {"type": "text", "analyzer": "keyword"}
  }
}
--------------------------------------------------

<1> This means that new fields won't be indexed, just stored in `_source`.

<2> This updates the mapping to add the new `flag` field. To pick up the new
field you have to reindex all documents with it.

Searching for the data won't find anything:

[source,console]
--------------------------------------------------
POST test/_search?filter_path=hits.total
{
  "query": {
    "match": {
      "flag": "foo"
    }
  }
}
--------------------------------------------------
// TEST[continued]

[source,console-result]
--------------------------------------------------
{
  "hits" : {
    "total": {
        "value": 0,
        "relation": "eq"
    }
  }
}
--------------------------------------------------

But you can issue an `_update_by_query` request to pick up the new mapping:

[source,console]
--------------------------------------------------
POST test/_update_by_query?refresh&conflicts=proceed
POST test/_search?filter_path=hits.total
{
  "query": {
    "match": {
      "flag": "foo"
    }
  }
}
--------------------------------------------------
// TEST[continued]

[source,console-result]
--------------------------------------------------
{
  "hits" : {
    "total": {
        "value": 1,
        "relation": "eq"
    }
  }
}
--------------------------------------------------

You can do the exact same thing when adding a field to a multifield.