elasticsearch-file-ingest
elastic/agent-skills
Stream large data files (CSV/JSON/Parquet/Arrow) into Elasticsearch with custom transforms and high throughput.
What is elasticsearch-file-ingest?
Ingests and transforms data files into Elasticsearch using stream-based processing to handle large datasets efficiently. Use this skill when loading files or batch importing data into Elasticsearch indices.
- Stream-based ingestion supporting NDJSON, CSV, Parquet, and Arrow IPC formats
- Process 50k+ documents per second on standard hardware
- Apply custom JavaScript transforms to enrich, filter, or split documents during ingestion
- Ingest multiple files matching a pattern (e.g., logs/*.json)
- Infer mappings and ingest pipelines automatically from file samples
- Split single source documents into multiple target documents
How to install elasticsearch-file-ingest
npx skills add https://github.com/elastic/agent-skills --skill elasticsearch-file-ingest- Elasticsearch 8.x or 9.x (local or remote)
- Node.js 22 or later
- Environment variables configured for Elasticsearch connection (ELASTICSEARCH_CLOUD_ID/API_KEY or ELASTICSEARCH_URL with credentials)
How to use elasticsearch-file-ingest
- 1.Run `npm install` in the skill directory to install dependencies
- 2.Set up Elasticsearch connection via environment variables (ELASTICSEARCH_CLOUD_ID + ELASTICSEARCH_API_KEY, or ELASTICSEARCH_URL + credentials)
- 3.Run `node scripts/ingest.js test` to verify the connection
- 4.Run `node scripts/ingest.js ingest --file <path> --target <index>` to ingest a file, or pipe data via stdin with `--stdin`
- 5.Optionally add `--transform <file.js>` to apply custom transformations, `--infer-mappings` to auto-detect schema, or `--mappings <file.json>` for custom mappings
Use cases
- Bulk import CSV or JSON files into Elasticsearch indices
- Stream large Parquet datasets without memory overhead
- Transform and enrich data during ingestion with custom JavaScript logic
- Batch process multiple log files matching a glob pattern
- Automatically infer index mappings from file samples before ingestion
- Data engineers loading files into Elasticsearch
- DevOps teams performing batch data imports
- Developers building ETL pipelines with custom transformations
- Teams migrating data from CSV/JSON/Parquet sources to Elasticsearch
elasticsearch-file-ingest FAQ
NDJSON, CSV, Parquet, and Arrow IPC. Use `--source-format` to specify the format (default is NDJSON).
Yes, use `--transform <file.js>` with a JavaScript function that modifies, filters (return null), or splits (return array) documents.
Use `--file <path> --source-format csv` or `--infer-mappings` (which auto-detects CSV and creates mappings/pipeline). Do not combine `--infer-mappings` with `--source-format csv`.
Yes, use wildcards in the file path, e.g., `--file logs/*.json`.
Use `--infer-mappings` to send a sample to Elasticsearch's `_text_structure/find_structure` endpoint, which returns both mappings and an ingest pipeline.
Full instructions (SKILL.md)
Source of truth, from elastic/agent-skills.
name: elasticsearch-file-ingest description: > Ingest and transform data files (CSV/JSON/Parquet/Arrow IPC) into Elasticsearch with stream processing and custom transforms. Use when loading files or batch importing data — not for reindexing, general ingest pipeline design, or bulk API patterns. metadata: author: elastic version: 0.2.0
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
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