elasticsearch-file-ingest▌
elastic/agent-skills · updated Apr 8, 2026
Stream-based ingestion and transformation of large data files (NDJSON, CSV, Parquet, Arrow IPC) into Elasticsearch.
Elasticsearch File Ingest
Stream-based ingestion and transformation of large data files (NDJSON, CSV, Parquet, Arrow IPC) into Elasticsearch.
Features & Use Cases
- Stream-based: Handle large files without running out of memory
- High throughput: 50k+ documents/second on commodity hardware
- Formats: NDJSON, CSV, Parquet, Arrow IPC
- Transformations: Apply custom JavaScript transforms during ingestion (enrich, split, filter)
- Batch processing: Ingest multiple files matching a pattern (e.g.,
logs/*.json) - Document splitting: Transform one source document into multiple targets
Prerequisites
- Elasticsearch 8.x or 9.x accessible (local or remote)
- Node.js 22+ installed
Setup
This skill is self-contained. The scripts/ folder and package.json live in this skill's directory. Run all commands
from this directory. Use absolute paths when referencing data files located elsewhere.
Before first use, install dependencies:
npm install
Environment Configuration
Elasticsearch connection is configured by users exclusively via environment variables. Never pass credentials as command-line arguments. If the test fails, output the setup options below to the user, then stop. Do not proceed with ingestion until a successful connection test.
Option 1: Elastic Cloud (recommended for production)
export ELASTICSEARCH_CLOUD_ID="<your-cloud-id>"
export ELASTICSEARCH_API_KEY="<your-api-key>"
Option 2: Direct URL with API Key
export ELASTICSEARCH_URL="https://elasticsearch:9200"
export ELASTICSEARCH_API_KEY="<your-api-key>"
Option 3: Basic Authentication
export ELASTICSEARCH_URL="https://elasticsearch:9200"
export ELASTICSEARCH_USERNAME="<your-username>"
export ELASTICSEARCH_PASSWORD="<your-password>"
Option 4: Local Development
For local development and testing, see Run Elasticsearch locally to spin up Elasticsearch and Kibana. After setup, export the connection variables (URL and API key or credentials) as shown in Option 2 or Option 3 above.
Optional: Skip TLS verification (development only)
export ELASTICSEARCH_INSECURE="true"
Test Connection
Verify the Elasticsearch connection before ingesting data:
node scripts/ingest.js test
Always run this first. If the test fails, resolve the connection issue before proceeding.
Examples
Ingest a JSON file
node scripts/ingest.js ingest --file /absolute/path/to/data.json --target my-index
Stream NDJSON/CSV via stdin
# NDJSON
cat /absolute/path/to/data.ndjson | node scripts/ingest.js ingest --stdin --target my-index
# CSV
cat /absolute/path/to/data.csv | node scripts/ingest.js ingest --stdin --source-format csv --target my-index
Ingest CSV directly
node scripts/ingest.js ingest --file /absolute/path/to/users.csv --source-format csv --target users
Ingest Parquet directly
node scripts/ingest.js ingest --file /absolute/path/to/users.parquet --source-format parquet --target users
Ingest Arrow IPC directly
node scripts/ingest.js ingest --file /absolute/path/to/users.arrow --source-format arrow --target users
Ingest CSV with parser options
# csv-options.json
# {
# "columns": true,
# "delimiter": ";",
# "trim": true
# }
node scripts/ingest.js ingest --file /absolute/path/to/users.csv --source-format csv --csv-options csv-options.json --target users
Infer mappings/pipeline from CSV
When using --infer-mappings, do not combine it with --source-format csv. Inference sends a raw sample to
Elasticsearch's _text_structure/find_structure endpoint, which returns both mappings and an ingest pipeline with a CSV
processor. If --source-format csv is also set, CSV is parsed client-side and server-side, resulting in an empty
index. Let --infer-mappings handle everything:
node scripts/ingest.js ingest --file /absolute/path/to/users.csv --infer-mappings --target users
Infer mappings with options
# infer-options.json
# {
# "sampleBytes": 200000,
# "lines_to_sample": 2000
# }
node scripts/ingest.js ingest --file /absolute/path/to/users.csv --infer-mappings --infer-mappings-options infer-options.json --target users
Ingest with custom mappings
node scripts/ingest.js ingest --file /absolute/path/to/data.json --target my-index --mappings mappings.json
Ingest with transformation
node scripts/ingest.js ingest --file /absolute/path/to/data.json --target my-index --transform transform.js
Command Reference
Required Options
--target <index> # Target index name
Source Options (choose one)
--file <path> # Source file (supports wildcards, e.g., logs/*.json)
--stdin # Read NDJSON/CSV from stdin
Index Configuration
--mappings <file.json> # Mappings file
--infer-mappings # Infer mappings/pipeline from file/stream (do NOT combine with --source-format)
--infer-mappings-options <file> # Options for inference (JSON file)
--delete-index # Delete target index if exists
--pipeline <name> # Ingest pipeline name
Processing
--transform <file.js> # Transform function (export as default or module.exports)
--source-format <fmt> # Source format: ndjson|csv|parquet|arrow (default: ndjson)
--csv-options <file> # CSV parser options (JSON file)
--skip-header # Skip first line (e.g., CSV header)
Performance
--buffer-size <kb> # Buffer size in KB (default: 5120)
--total-docs <n> # Total docs for progress bar (file/stream)
--stall-warn-seconds <n> # Stall warning threshold (default: 30)
--progress-mode <mode> # Progress output: auto|line|newline (default: auto)
--debug-events # Log pause/resume/stall events
--quiet # Disable progress bars
Transform Functions
Transform functions let you modify documents during ingestion. Create a JavaScript file that exports a transform function:
Basic Transform (transform.js)
// ES modules (default)
export default function transform(doc) {
return {
...doc,
full_name: `${doc.first_name} ${doc.last_name}`,
timestamp: new Date().toISOString(),
};
}
// Or CommonJS
module.exports = function transform(doc) {
return {
...doc,
full_name: `${doc.first_name} ${doc.last_name}`,
};
};
Skip Documents
Return null or undefined to skip a document:
export default function transform(doc) {
// Skip invalid documents
if (!doc.email || !doc.email.includes("@")) {
return null;
}
return doc;
}
Split Documents
Return an array to create multiple target documents from one source:
export default function transform(doc) {
// Split a tweet into multiple hashtag documents
const hashtags = doc.text.match(/#\w+/g) || [];
return hashtags.map((tag) => ({
hashtag: tag,
tweet_id: doc.id,
created_at: doc.created_at,
}));
}
Mappings
Custom Mappings (mappings.json)
{
"properties": {
"@timestamp": { "type": "date" },
"message": { "type": "text" },
"user": {
"properties": {
"name": { "type": "keyword" },
"email": { "type": "keyword" }
}
}
}
}
node scripts/ingest.js ingest --file /absolute/path/to/data.json --target my-index --mappings mappings.json
Boundaries
- Never echo, print, log, or otherwise reveal the values of credential environment variables
(
$ELASTICSEARCH_API_KEY,$ELASTICSEARCH_PASSWORD,$ELASTICSEARCH_CLOUD_ID, etc.). Do not run shell commands whose output would expose secret values (e.g.,echo $ELASTICSEARCH_API_KEY,env | grep KEY,printenv). Exporting these variables and running scripts that read them internally is expected and safe — the restriction is on surfacing secret values in command output. The only way to verify connectivity isnode scripts/ingest.js test. If the test fails, ask the user to check their environment configuration — do not attempt to diagnose credentials yourself. - Never run destructive commands (such as using the
--delete-indexflag or deleting existing indices and data) without explicit user confirmation.
Guidelines
- Test first: Always run
node scripts/ingest.js testbefore ingesting data. If the connection fails, ask the user to verify their environment configuration and re-test. Do not attempt ingestion until the test passes. - Never combine
--infer-mappingswith--source-format. Inference creates a server-side ingest pipeline that handles parsing (e.g., CSV processor). Using--source-format csvparses client-side as well, causing double-parsing and an empty index. Use--infer-mappingsalone for automatic detection, or--source-formatwith explicit--mappingsfor manual control. - Use
--source-format csvwith--mappingswhen you want client-side CSV parsing with known field types. - Use
--infer-mappingsalone when you want Elasticsearch to detect the format, infer field types, and create an ingest pipeline automatically.
When NOT to Use
Consider alternatives for:
- Reindexing or index migration: Use the
elasticsearch-reindexskill for copying, migrating, or transforming existing Elasticsearch indices - Real-time ingestion: Use Filebeat or Elastic Agent
- Enterprise pipelines: Use Logstash
- Built-in transforms: Use Elasticsearch Transforms
Additional Resources
- Common Patterns - Detailed examples for CSV loading, batch ingestion, enrichment, and more
- Troubleshooting - Solutions for common issues
References
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★64 reviews- ★★★★★Soo Farah· Dec 20, 2024
elasticsearch-file-ingest reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Omar Agarwal· Dec 8, 2024
Keeps context tight: elasticsearch-file-ingest is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Lucas Jain· Dec 8, 2024
Registry listing for elasticsearch-file-ingest matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Pratham Ware· Dec 4, 2024
elasticsearch-file-ingest is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Camila Okafor· Nov 27, 2024
I recommend elasticsearch-file-ingest for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Lucas Smith· Nov 27, 2024
elasticsearch-file-ingest reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Omar White· Nov 11, 2024
Registry listing for elasticsearch-file-ingest matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Luis Desai· Oct 18, 2024
elasticsearch-file-ingest reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Isabella Gonzalez· Oct 18, 2024
I recommend elasticsearch-file-ingest for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Omar Abbas· Oct 2, 2024
Keeps context tight: elasticsearch-file-ingest is the kind of skill you can hand to a new teammate without a long onboarding doc.
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