Edits to text in Update By Query API doc (#39078)
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@ -39,9 +39,9 @@ That will return something like this:
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// TESTRESPONSE[s/"took" : 147/"took" : "$body.took"/]
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`_update_by_query` gets a snapshot of the index when it starts and indexes what
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it finds using `internal` versioning. That means that you'll get a version
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it finds using `internal` versioning. That means you'll get a version
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conflict if the document changes between the time when the snapshot was taken
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and when the index request is processed. When the versions match the document
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and when the index request is processed. When the versions match, the document
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is updated and the version number is incremented.
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NOTE: Since `internal` versioning does not support the value 0 as a valid
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@ -55,10 +55,10 @@ aborted. While the first failure causes the abort, all failures that are
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returned by the failing bulk request are returned in the `failures` element; therefore
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it's possible for there to be quite a few failed entities.
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If you want to simply count version conflicts not cause the `_update_by_query`
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to abort you can set `conflicts=proceed` on the url or `"conflicts": "proceed"`
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If you want to simply count version conflicts, and not cause the `_update_by_query`
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to abort, you can set `conflicts=proceed` on the url or `"conflicts": "proceed"`
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in the request body. The first example does this because it is just trying to
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pick up an online mapping change and a version conflict simply means that the
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pick up an online mapping change, and a version conflict simply means that the
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conflicting document was updated between the start of the `_update_by_query`
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and the time when it attempted to update the document. This is fine because
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that update will have picked up the online mapping update.
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@ -92,7 +92,7 @@ POST twitter/_update_by_query?conflicts=proceed
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<1> The query must be passed as a value to the `query` key, in the same
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way as the <<search-search,Search API>>. You can also use the `q`
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parameter in the same way as the search api.
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parameter in the same way as the search API.
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So far we've only been updating documents without changing their source. That
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is genuinely useful for things like
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@ -121,7 +121,7 @@ POST twitter/_update_by_query
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Just as in <<docs-update,Update API>> you can set `ctx.op` to change the
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operation that is executed:
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[horizontal]
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`noop`::
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Set `ctx.op = "noop"` if your script decides that it doesn't have to make any
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@ -199,12 +199,12 @@ POST twitter/_update_by_query?pipeline=set-foo
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=== URL Parameters
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In addition to the standard parameters like `pretty`, the Update By Query API
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also supports `refresh`, `wait_for_completion`, `wait_for_active_shards`, `timeout`
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also supports `refresh`, `wait_for_completion`, `wait_for_active_shards`, `timeout`,
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and `scroll`.
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Sending the `refresh` will update all shards in the index being updated when
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the request completes. This is different than the Update API's `refresh`
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parameter which causes just the shard that received the new data to be indexed.
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parameter, which causes just the shard that received the new data to be indexed.
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Also unlike the Update API it does not support `wait_for`.
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If the request contains `wait_for_completion=false` then Elasticsearch will
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@ -219,12 +219,12 @@ Elasticsearch can reclaim the space it uses.
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before proceeding with the request. See <<index-wait-for-active-shards,here>>
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for details. `timeout` controls how long each write request waits for unavailable
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shards to become available. Both work exactly how they work in the
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<<docs-bulk,Bulk API>>. As `_update_by_query` uses scroll search, you can also specify
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<<docs-bulk,Bulk API>>. Because `_update_by_query` uses scroll search, you can also specify
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the `scroll` parameter to control how long it keeps the "search context" alive,
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eg `?scroll=10m`, by default it's 5 minutes.
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e.g. `?scroll=10m`. By default it's 5 minutes.
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`requests_per_second` can be set to any positive decimal number (`1.4`, `6`,
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`1000`, etc) and throttles rate at which `_update_by_query` issues batches of
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`1000`, etc.) and throttles the rate at which `_update_by_query` issues batches of
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index operations by padding each batch with a wait time. The throttling can be
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disabled by setting `requests_per_second` to `-1`.
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@ -240,7 +240,7 @@ target_time = 1000 / 500 per second = 2 seconds
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wait_time = target_time - write_time = 2 seconds - .5 seconds = 1.5 seconds
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--------------------------------------------------
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Since the batch is issued as a single `_bulk` request large batch sizes will
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Since the batch is issued as a single `_bulk` request, large batch sizes will
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cause Elasticsearch to create many requests and then wait for a while before
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starting the next set. This is "bursty" instead of "smooth". The default is `-1`.
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@ -283,6 +283,7 @@ The JSON response looks like this:
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--------------------------------------------------
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// TESTRESPONSE[s/"took" : 147/"took" : "$body.took"/]
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[horizontal]
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`took`::
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The number of milliseconds from start to end of the whole operation.
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@ -319,8 +320,8 @@ the update by query returned a `noop` value for `ctx.op`.
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`retries`::
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The number of retries attempted by update-by-query. `bulk` is the number of bulk
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actions retried and `search` is the number of search actions retried.
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The number of retries attempted by update by query. `bulk` is the number of bulk
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actions retried, and `search` is the number of search actions retried.
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`throttled_millis`::
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@ -341,8 +342,8 @@ executed again in order to conform to `requests_per_second`.
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Array of failures if there were any unrecoverable errors during the process. If
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this is non-empty then the request aborted because of those failures.
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Update-by-query is implemented using batches and any failure causes the entire
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process to abort but all failures in the current batch are collected into the
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Update by query is implemented using batches. Any failure causes the entire
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process to abort, but all failures in the current batch are collected into the
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array. You can use the `conflicts` option to prevent reindex from aborting on
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version conflicts.
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@ -352,7 +353,7 @@ version conflicts.
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[[docs-update-by-query-task-api]]
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=== Works with the Task API
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You can fetch the status of all running update-by-query requests with the
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You can fetch the status of all running update by query requests with the
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<<tasks,Task API>>:
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[source,js]
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@ -406,7 +407,7 @@ The responses looks like:
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--------------------------------------------------
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// TESTRESPONSE
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<1> this object contains the actual status. It is just like the response json
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<1> This object contains the actual status. It is just like the response JSON
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with the important addition of the `total` field. `total` is the total number
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of operations that the reindex expects to perform. You can estimate the
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progress by adding the `updated`, `created`, and `deleted` fields. The request
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@ -424,7 +425,7 @@ GET /_tasks/r1A2WoRbTwKZ516z6NEs5A:36619
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The advantage of this API is that it integrates with `wait_for_completion=false`
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to transparently return the status of completed tasks. If the task is completed
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and `wait_for_completion=false` was set on it them it'll come back with a
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and `wait_for_completion=false` was set on it, then it'll come back with a
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`results` or an `error` field. The cost of this feature is the document that
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`wait_for_completion=false` creates at `.tasks/task/${taskId}`. It is up to
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you to delete that document.
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@ -434,7 +435,7 @@ you to delete that document.
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[[docs-update-by-query-cancel-task-api]]
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=== Works with the Cancel Task API
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Any Update By Query can be canceled using the <<tasks,Task Cancel API>>:
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Any update by query can be cancelled using the <<tasks,Task Cancel API>>:
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[source,js]
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--------------------------------------------------
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@ -464,25 +465,25 @@ POST _update_by_query/r1A2WoRbTwKZ516z6NEs5A:36619/_rethrottle?requests_per_seco
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The task ID can be found using the <<tasks, tasks API>>.
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Just like when setting it on the `_update_by_query` API `requests_per_second`
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Just like when setting it on the `_update_by_query` API, `requests_per_second`
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can be either `-1` to disable throttling or any decimal number
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like `1.7` or `12` to throttle to that level. Rethrottling that speeds up the
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query takes effect immediately but rethrotting that slows down the query will
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take effect on after completing the current batch. This prevents scroll
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query takes effect immediately, but rethrotting that slows down the query will
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take effect after completing the current batch. This prevents scroll
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timeouts.
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[float]
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[[docs-update-by-query-slice]]
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=== Slicing
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Update-by-query supports <<sliced-scroll>> to parallelize the updating process.
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Update by query supports <<sliced-scroll>> to parallelize the updating process.
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This parallelization can improve efficiency and provide a convenient way to
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break the request down into smaller parts.
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[float]
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[[docs-update-by-query-manual-slice]]
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==== Manual slicing
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Slice an update-by-query manually by providing a slice id and total number of
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Slice an update by query manually by providing a slice id and total number of
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slices to each request:
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[source,js]
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@ -540,7 +541,7 @@ Which results in a sensible `total` like this one:
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[[docs-update-by-query-automatic-slice]]
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==== Automatic slicing
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You can also let update-by-query automatically parallelize using
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You can also let update by query automatically parallelize using
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<<sliced-scroll>> to slice on `_id`. Use `slices` to specify the number of
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slices to use:
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@ -605,8 +606,8 @@ be larger than others. Expect larger slices to have a more even distribution.
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are distributed proportionally to each sub-request. Combine that with the point
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above about distribution being uneven and you should conclude that the using
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`size` with `slices` might not result in exactly `size` documents being
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`_update_by_query`ed.
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* Each sub-requests gets a slightly different snapshot of the source index
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updated.
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* Each sub-request gets a slightly different snapshot of the source index
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though these are all taken at approximately the same time.
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[float]
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