OpenSearch::Client::Manual::Modules
Most of the methods available in OpenSearch::Client are accessed through different namespaces. Each of these namespaces is served by a specific module.
You can lookup which modulename->methodname corresponds to each path in the OpenSearch API documentation in OpenSearch::Client::Manual::Paths
Namespaces
asynchronous_search
Searching large volumes of data can take a long time, especially if you're searching across warm nodes or multiple remote clusters. Asynchronous search in OpenSearch lets you send search requests that run in the background. You can monitor the progress of these searches and get back partial results as they become available. After the search finishes, you can save the results to examine at a later time.'
Module : OpenSearch::Client::Core::3_0::Direct::AsyncSearch
cat
You can get essential statistics about your cluster in an easy-to-understand, tabular format using the compact and aligned text (CAT) API. The CAT API is a human-readable interface that returns plain text instead of traditional JSON. Using the CAT API, you can answer questions like which node is the elected cluster manager, what state the cluster is in, how many documents are in each index, and so on.
Module : OpenSearch::Client::Core::3_0::Direct::Cat
cluster
The cluster APIs allow you to manage your cluster. You can use them to check cluster health, modify settings, retrieve statistics, and more.
Module : OpenSearch::Client::Core::3_0::Direct::Cluster
dangling_indices
After a node joins a cluster, dangling indexes occur if any shards exist in the node's local directory that do not already exist in the cluster. Dangling indexes can be listed, deleted, or imported.
Module : OpenSearch::Client::Core::3_0::Direct::DanglingIndices
flow_framework
You can automate complex OpenSearch setup and preprocessing tasks by providing templates for common use cases. For example, automating machine learning (ML) setup tasks streamlines the use of OpenSearch ML offerings.
Module : OpenSearch::Client::Core::3_0::Direct::FlowFramework
geospatial
The ip2geo processor adds information about the geographical location of an IPv4 or IPv6 address. The ip2geo processor uses IP geolocation (GeoIP) data from an external endpoint and therefore requires an additional component, datasource, that defines from where to download GeoIP data and how frequently to update the data.
Module : OpenSearch::Client::Core::3_0::Direct::GeoSpatial
indices
The index API operations let you interact with indexes in your cluster. Using these operations, you can create, delete, close, and complete other index-related operations.
Module : OpenSearch::Client::Core::3_0::Direct::Indices
ingest
Ingest APIs are a valuable tool for loading data into a system. Ingest APIs work together with ingest pipelines and ingest processors to process or transform data from a variety of sources and in a variety of formats.
Module : OpenSearch::Client::Core::3_0::Direct::Ingest
ingestion
Pull-based ingestion enables OpenSearch to ingest data from streaming sources such as Apache Kafka or Amazon Kinesis. Unlike traditional ingestion methods where clients actively push data to OpenSearch through REST APIs, pull-based ingestion allows OpenSearch to control the data flow by retrieving data directly from streaming sources. This approach provides native backpressure handling, helping prevent server overload during traffic spikes. Pull-based ingestion guarantees at-least-once ingestion semantics and uses external versioning to ensure data consistency.
Module : OpenSearch::Client::Core::3_0::Direct::Ingestion
insights
To monitor and analyze the search queries within your OpenSearch cluster, you can obtain query insights.
Module : OpenSearch::Client::Core::3_0::Direct::Insights
ism
Use the index state management operations to programmatically work with policies and managed indexes.
Module : OpenSearch::Client::Core::3_0::Direct::ISM
knn
In OpenSearch, vector search functionality is provided by the k-NN plugin and Neural Search plugin. The k-NN plugin provides basic k-NN functionality, while the Neural Search plugin provides automatic embedding generation at indexing and search time.
Module : OpenSearch::Client::Core::3_0::Direct::KNN
list
The List API retrieves statistics about indexes and shards in a paginated format. This streamlines the task of processing responses that include many indexes.
Module : OpenSearch::Client::Core::3_0::Direct::List
ltr
The Learning to Rank plugin for OpenSearch enables you to use machine learning (ML) and behavioral data to fine-tune the relevance of documents. It uses models from the XGBoost and RankLib libraries. These models rescore the search results, considering query-dependent features such as click-through data or field matches, which can further improve relevance.
Module : OpenSearch::Client::Core::3_0::Direct::LTR
ml
OpenSearch supports ML models that you can use to enhance search relevance through semantic understanding. You can either deploy models directly within your OpenSearch cluster or connect to models hosted on external platforms. These models can transform text into vector embeddings, enabling semantic search capabilities, or provide advanced features like text generation and question answering.
Module : OpenSearch::Client::Core::3_0::Direct::ML
neural
The Neural Search plugin provides several APIs for monitoring semantic and hybrid search features.
Module : OpenSearch::Client::Core::3_0::Direct::Neural
nodes
The Nodes API makes it possible to retrieve information about individual nodes in your cluster.
Module : OpenSearch::Client::Core::3_0::Direct::Nodes
notifications
The Notifications plugin provides a central location for all of your notifications from OpenSearch plugins. Using the plugin, you can configure which communication service you want to use and see relevant statistics and troubleshooting information. Currently, the Alerting and ISM plugins have integrated with the Notifications plugin.
Module : OpenSearch::Client::Core::3_0::Direct::Notifications
observability
OpenSearch provides observability capabilities for monitoring applications, infrastructure, and AI agents.
Module : OpenSearch::Client::Core::3_0::Direct::Observability
ppl
Use the SQL and PPL API to send queries to the SQL plugin. Use the _sql endpoint to send queries in SQL, and the _ppl endpoint to send queries in PPL. For both of these, you can also use the _explain endpoint to translate your query into OpenSearch domain-specific language (DSL) or to troubleshoot errors.
Module : OpenSearch::Client::Core::3_0::Direct::PPL
query
Configure metric analytics datasources
Module : OpenSearch::Client::Core::3_0::Direct::Query
remote_store
Remote-backed storage offers OpenSearch users a new way to protect against data loss by automatically creating backups of all index transactions and sending them to remote storage.
Module : OpenSearch::Client::Core::3_0::Direct::RemoteStore
replication
Use these replication operations to programmatically manage cross-cluster replication.
Module : OpenSearch::Client::Core::3_0::Direct::Replication
rollups
Time series data increases storage costs, strains cluster health, and slows down aggregations over time. Index rollup lets you periodically reduce data granularity by rolling up old data into summarized indexes.
Module : OpenSearch::Client::Core::3_0::Direct::Rollups
search_pipeline
You can use search pipelines to build new or reuse existing result rerankers, query rewriters, and other components that operate on queries or results. Search pipelines make it easier for you to process search queries and search results within OpenSearch. Moving some of your application functionality into an OpenSearch search pipeline reduces the overall complexity of your application. As part of a search pipeline, you specify a list of search processors that perform modular tasks. You can then easily add or reorder these processors to customize search results for your application.
Module : OpenSearch::Client::Core::3_0::Direct::SearchPipeline
search_relevance
In search applications, tuning relevance is a constant, iterative exercise intended to provide the right search results to your end users. The tooling in Search Relevance Workbench helps search relevance engineers and business users create the best search experience possible for application users. It does this without hiding internal information, enabling engineers to experiment and investigate details as necessary.
Module : OpenSearch::Client::Core::3_0::Direct::SearchRelevance
security
Manage access control and authentication tokens.
Module : OpenSearch::Client::Core::3_0::Direct::Security
security_analytics
Security Analytics includes a number of APIs to help administrators maintain and update an implementation. The APIs often mimic the same controls available for setting up Security Analytics in OpenSearch Dashboards, and they provide another option for administering the plugin.
Module : OpenSearch::Client::Core::3_0::Direct::SecurityAnalytics
sm
Use the Snapshot Management (SM) API to automate taking snapshots.
Module : OpenSearch::Client::Core::3_0::Direct::SnapshotManagement
snapshot
The snapshot APIs allow you to manage snapshots and snapshot repositories.
Module : OpenSearch::Client::Core::3_0::Direct::Snapshot
sql
Use the SQL and PPL API to send queries to the SQL plugin. Use the _sql endpoint to send queries in SQL, and the _ppl endpoint to send queries in PPL. For both of these, you can also use the _explain endpoint to translate your query into OpenSearch domain-specific language (DSL) or to troubleshoot errors.
Module : OpenSearch::Client::Core::3_0::Direct::SQL
tasks
A task is any operation that you run in a cluster. For example, searching your data collection of books for a title or author name is a task. When you run OpenSearch, a task is automatically created to monitor your cluster's health and performance. For more information about all of the tasks currently executing in your cluster, you can use the tasks API operation.
Module : OpenSearch::Client::Core::3_0::Direct::Tasks
transforms
Whereas index rollup jobs let you reduce data granularity by rolling up old data into condensed indexes, transform jobs let you create a different, summarized view of your data centered around certain fields, so you can visualize or analyze the data in different ways.
Module : OpenSearch::Client::Core::3_0::Direct::Transforms
ubi
User Behavior Insights (UBI) is a schema for capturing user search behavior. Search behavior consists of the queries that the user submits, the results that are presented to them, and the actions they take on those results. The UBI schema links all user interactions (events) to the search result they were performed on. That is, it not only captures the chronological sequence of events but also captures the causal links between events. Analysis of this behavior is used for improving the quality of search results.
Module : OpenSearch::Client::Core::3_0::Direct::UBI
wlm
Workload management allows you to group search traffic and isolate network resources, preventing the overuse of network resources by specific requests.
Module : OpenSearch::Client::Core::3_0::Direct::WLM
MANUAL
Documentation index OpenSearch::Client::Manual
HISTORY
This distribution is derived from Search::Elasticsearch version 7.714. All subsequent changes are unique to this distribution.
AUTHOR
Mark Dootson <mdootson@cpan.org> ( current maintainer )
CREDITS
OpenSearch::Client is based on Search::Elasticsearch version 7.714 by Enrico Zimuel <enrico.zimuel@elastic.co>.
COPYRIGHT AND LICENSE
Copyright (C) 2026 by Mark Dootson ( this distribution )
Copyright (C) 2021 by Elasticsearch BV ( original distribution )
This is free software, licensed under:
The Apache License, Version 2.0, January 2004