Elasticsearch
Full-text search, analytics, and log management powered by Elasticsearch — create, query, search with DSL, aggregate, and manage indices from any BizFirst workflow.
Resources & Operations (10 total)
document 6 Operations
| Operation | Description |
|---|---|
document/create | Index a new document in Elasticsearch. Accepts a JSON object of fields. Supports bulk indexing mode for high-throughput batch writes and auto-generated document IDs. |
document/get | Retrieve a single document by its _id. Returns the document's _source fields plus metadata including _id, _index, and _version. |
document/getMany | Retrieve multiple documents using an optional Elasticsearch query DSL filter. Supports pagination via Limit and ReturnAll. |
document/search | Execute a full Elasticsearch search with complete query DSL support including query, sort, aggs, and more. Returns hits, total count, execution time, and aggregation results. |
document/update | Partially update a document's fields by ID. Supports upsert mode — creates the document if it does not exist. Only specified fields are modified; unspecified fields are preserved. |
document/delete | Permanently delete a document by its _id from a specified index. |
index 4 Operations
| Operation | Description |
|---|---|
index/create | Create a new Elasticsearch index with optional field mappings and settings (number of shards, replicas, analyzers, etc.). |
index/get | Retrieve the full details of an index including its mappings, settings, aliases, and current statistics. |
index/getMany | List all indices in the cluster with their names, health status, document count, and storage size. |
index/delete | Permanently delete an index and all its documents. This operation is irreversible. |
Key Use Cases
- Full-text search: Power product search, document retrieval, and knowledge base queries with relevance scoring, field boosting, and fuzziness. Pass complex multi-field queries directly using Elasticsearch DSL.
- Log management: Bulk-index application logs, error events, and audit trails into time-series indices. Query and aggregate logs in real time across workflows triggered by monitoring alerts.
- Analytics & aggregations: Run bucket, metric, and pipeline aggregations to compute order totals, category breakdowns, user activity summaries, and more — directly from workflow data.
- Product catalogue: Maintain searchable product, content, or article catalogues. Update documents in real time as inventory or metadata changes in upstream systems.
- Data pipeline enrichment: Use Elasticsearch as a lookup and enrichment layer — search related records, retrieve reference data, and join results with data from other nodes before passing to downstream services.
Authentication
Host, Username, Password, IgnoreSSL, ConnectTimeout, and RequestTimeout. These are defined once in the node's connection settings and apply to every operation. For self-signed certificates in development clusters, set IgnoreSSL to true. Do not use IgnoreSSL in production environments.
Elasticsearch Query DSL
The document/search and document/getMany operations accept raw Elasticsearch Query DSL JSON. This means you can use the full power of Elasticsearch queries including match, term, range, bool (must/should/must_not/filter), nested, geo_distance, and any other query type supported by your Elasticsearch version. The query JSON is passed directly to the Elasticsearch API with no transformation.
In This Guide
Configuration
Complete property reference for all 10 operations across document and index resources, including authentication and query DSL guidance.
Input & Output
Document object schema, search response format with hits/total/took, aggregation result structure, and output ports.
Examples
Five real-world examples: index a product catalogue, full-text search, order analytics aggregation, bulk log indexing, and partial update with upsert.