Package co.elastic.clients.elasticsearch.core

Class UpdateByQueryRequest

java.lang.Object
co.elastic.clients.elasticsearch._types.RequestBase
co.elastic.clients.elasticsearch.core.UpdateByQueryRequest
All Implemented Interfaces:
JsonpSerializable
@JsonpDeserializable public class UpdateByQueryRequest extends RequestBase implements JsonpSerializable
Update documents. Updates documents that match the specified query. If no query is specified, performs an update on every document in the data stream or index without modifying the source, which is useful for picking up mapping changes.

If the Elasticsearch security features are enabled, you must have the following index privileges for the target data stream, index, or alias:

  • read
  • index or write

You can specify the query criteria in the request URI or the request body using the same syntax as the search API.

When you submit an update by query request, Elasticsearch gets a snapshot of the data stream or 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 that if you opt to count version conflicts, the operation could attempt to update more documents from the source than max_docs until it has successfully updated max_docs documents or it has gone through every document in the source query.

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, Elasticsearch 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 to the update API's refresh parameter, which causes only the shard that received the request to be refreshed. Unlike the update API, it does not support wait_for.

Running update by query asynchronously

If the request contains wait_for_completion=false, Elasticsearch performs some preflight checks, launches the request, and returns a task you can use to cancel or get the status of the task. Elasticsearch creates a record of this task as a document at .tasks/task/${taskId}.

Waiting for active shards

wait_for_active_shards controls how many copies of a shard must be active before proceeding with the request. See 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 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 turn off 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: 

 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 Elasticsearch to create many requests and wait before starting the next set. This is "bursty" instead of "smooth".

Slicing

Update by query supports 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 data streams and indices. This setting will use one slice per shard, up to a certain limit. If there are multiple source data streams or indices, it will choose the number of slices based on the index or backing index with the smallest number of shards.

Adding slices to _update_by_query just automates the manual process of creating sub-requests, which means it has some quirks:

  • You can see these requests in the 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 data stream or index though these are all taken at approximately the same time.

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 or backing 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. Refer to the linked documentation for examples of how to update documents using the _update_by_query API:

See Also:

  • Field Details

  • Method Details

    • of

      public static UpdateByQueryRequest of(Function<UpdateByQueryRequest.Builder,ObjectBuilder<UpdateByQueryRequest>> fn)

    • allowNoIndices

      @Nullable public final Boolean allowNoIndices()
      If false, the request returns an error if any wildcard expression, index alias, or _all value targets only missing or closed indices. This behavior applies even if the request targets other open indices. For example, a request targeting foo*,bar* returns an error if an index starts with foo but no index starts with bar.

      API name: allow_no_indices

    • analyzeWildcard

      @Nullable public final Boolean analyzeWildcard()
      If true, wildcard and prefix queries are analyzed. This parameter can be used only when the q query string parameter is specified.

      API name: analyze_wildcard

    • analyzer

      @Nullable public final String analyzer()
      The analyzer to use for the query string. This parameter can be used only when the q query string parameter is specified.

      API name: analyzer

    • conflicts

      @Nullable public final Conflicts conflicts()
      The preferred behavior when update by query hits version conflicts: abort or proceed.

      API name: conflicts

    • defaultOperator

      @Nullable public final Operator defaultOperator()
      The default operator for query string query: and or or. This parameter can be used only when the q query string parameter is specified.

      API name: default_operator

    • df

      @Nullable public final String df()
      The field to use as default where no field prefix is given in the query string. This parameter can be used only when the q query string parameter is specified.

      API name: df

    • expandWildcards

      public final List<ExpandWildcard> expandWildcards()
      The type of index that wildcard patterns can match. If the request can target data streams, this argument determines whether wildcard expressions match hidden data streams. It supports comma-separated values, such as open,hidden.

      API name: expand_wildcards

    • from

      @Nullable public final Long from()
      Skips the specified number of documents.

      API name: from

    • ignoreUnavailable

      @Nullable public final Boolean ignoreUnavailable()
      If false, the request returns an error if it targets a missing or closed index.

      API name: ignore_unavailable

    • index

      public final List<String> index()
      Required - A comma-separated list of data streams, indices, and aliases to search. It supports wildcards (*). To search all data streams or indices, omit this parameter or use * or _all.

      API name: index

    • lenient

      @Nullable public final Boolean lenient()
      If true, format-based query failures (such as providing text to a numeric field) in the query string will be ignored. This parameter can be used only when the q query string parameter is specified.

      API name: lenient

    • maxDocs

      @Nullable public final Long maxDocs()
      The maximum number of documents to update.

      API name: max_docs

    • pipeline

      @Nullable public final String pipeline()
      The ID of the pipeline to use to preprocess incoming documents. If the index has a default ingest pipeline specified, then setting the value to _none disables the default ingest pipeline for this request. If a final pipeline is configured it will always run, regardless of the value of this parameter.

      API name: pipeline

    • preference

      @Nullable public final String preference()
      The node or shard the operation should be performed on. It is random by default.

      API name: preference

    • q

      @Nullable public final String q()
      A query in the Lucene query string syntax.

      API name: q

    • query

      @Nullable public final Query query()
      The documents to update using the Query DSL.

      API name: query

    • refresh

      @Nullable public final Boolean refresh()
      If true, Elasticsearch refreshes affected shards to make the operation visible to search after the request completes. This is different than the update API's refresh parameter, which causes just the shard that received the request to be refreshed.

      API name: refresh

    • requestCache

      @Nullable public final Boolean requestCache()
      If true, the request cache is used for this request. It defaults to the index-level setting.

      API name: request_cache

    • requestsPerSecond

      @Nullable public final Float requestsPerSecond()
      The throttle for this request in sub-requests per second.

      API name: requests_per_second

    • routing

      @Nullable public final String routing()
      A custom value used to route operations to a specific shard.

      API name: routing

    • script

      @Nullable public final Script script()
      The script to run to update the document source or metadata when updating.

      API name: script

    • scroll

      @Nullable public final Time scroll()
      The period to retain the search context for scrolling.

      API name: scroll

    • scrollSize

      @Nullable public final Long scrollSize()
      The size of the scroll request that powers the operation.

      API name: scroll_size

    • searchTimeout

      @Nullable public final Time searchTimeout()
      An explicit timeout for each search request. By default, there is no timeout.

      API name: search_timeout

    • searchType

      @Nullable public final SearchType searchType()
      The type of the search operation. Available options include query_then_fetch and dfs_query_then_fetch.

      API name: search_type

    • slice

      @Nullable public final SlicedScroll slice()
      Slice the request manually using the provided slice ID and total number of slices.

      API name: slice

    • slices

      @Nullable public final Slices slices()
      The number of slices this task should be divided into.

      API name: slices

    • sort

      public final List<String> sort()
      A comma-separated list of <field>:<direction> pairs.

      API name: sort

    • stats

      public final List<String> stats()
      The specific tag of the request for logging and statistical purposes.

      API name: stats

    • terminateAfter

      @Nullable public final Long terminateAfter()
      The maximum number of documents to collect for each shard. If a query reaches this limit, Elasticsearch terminates the query early. Elasticsearch collects documents before sorting.

      IMPORTANT: Use with caution. Elasticsearch applies this parameter to each shard handling the request. When possible, let Elasticsearch perform early termination automatically. Avoid specifying this parameter for requests that target data streams with backing indices across multiple data tiers.

      API name: terminate_after

    • timeout

      @Nullable public final Time timeout()
      The period each update request waits for the following operations: dynamic mapping updates, waiting for active shards. By default, it is one minute. This guarantees Elasticsearch waits for at least the timeout before failing. The actual wait time could be longer, particularly when multiple waits occur.

      API name: timeout

    • version

      @Nullable public final Boolean version()
      If true, returns the document version as part of a hit.

      API name: version

    • versionType

      @Nullable public final Boolean versionType()
      Should the document increment the version number (internal) on hit or not (reindex)

      API name: version_type

    • waitForActiveShards

      @Nullable public final WaitForActiveShards waitForActiveShards()
      The number of shard copies that must be active before proceeding with the operation. Set to all or any positive integer up to the total number of shards in the index (number_of_replicas+1). The timeout parameter controls how long each write request waits for unavailable shards to become available. Both work exactly the way they work in the bulk API.

      API name: wait_for_active_shards

    • waitForCompletion

      @Nullable public final Boolean waitForCompletion()
      If true, the request blocks until the operation is complete. If false, Elasticsearch performs some preflight checks, launches the request, and returns a task ID that you can use to cancel or get the status of the task. Elasticsearch creates a record of this task as a document at .tasks/task/${taskId}.

      API name: wait_for_completion

    • serialize

      public void serialize(jakarta.json.stream.JsonGenerator generator, JsonpMapper mapper)
      Serialize this object to JSON.
      Specified by:
      serialize in interface JsonpSerializable

    • serializeInternal

      protected void serializeInternal(jakarta.json.stream.JsonGenerator generator, JsonpMapper mapper)

    • setupUpdateByQueryRequestDeserializer

      protected static void setupUpdateByQueryRequestDeserializer(ObjectDeserializer<UpdateByQueryRequest.Builder> op)