Amazon EMR
Amazon EMR is a cloud big data platform for running large-scale distributed data processing jobs, interactive SQL queries, and machine learning applications using open-source analytics frameworks such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto.
Amazon EMR publishes 1 API on the APIs.io network: Clusters API. Tagged areas include Amazon Web Services, Analytics, Apache Spark, Big Data, and Data Processing.
The Amazon EMR catalog on APIs.io includes 1 JSON-LD context and 2 Spectral governance rulesets.
Amazon EMR’s developer surface includes developer portal, documentation, engineering blog, developer console, signup flow, support, FAQ, and 25 more developer resources.
Kin Score
APIs 1
Individual APIs this provider publishes, each with its own machine-readable definition.
Amazon EMR Clusters API
Operations for creating, managing, and terminating EMR clusters
Postman Collections 1
Ready-to-run Postman collections for exercising this provider's APIs.
Amazon EMR API
POSTMANOpen Collections 1
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
Amazon EMR API
OPEN COLLECTIONArazzo Workflows 6
Multi-step API workflows described with the Arazzo specification.
Amazon EMR Launch a Cluster With Processing Steps
Create a cluster and queue processing steps to run as soon as it starts.
ARAZZOAmazon EMR Launch a Hadoop and Hive Cluster
Create an EMR cluster with the Hadoop and Hive applications installed.
ARAZZOAmazon EMR Launch an HBase Cluster
Create an EMR cluster with the Apache HBase application installed.
ARAZZOAmazon EMR Launch a Presto Query Cluster
Create an EMR cluster with the Presto application for interactive SQL.
ARAZZOAmazon EMR Launch a Spark Cluster
Create and start a new EMR cluster pre-configured to run Apache Spark.
ARAZZOAmazon EMR Run a Spark ETL Job
Launch a Spark cluster and queue an ETL processing step in one call.
ARAZZOPricing Plans 1
Published pricing tiers and plan structures.
Rate Limits 1
Documented rate limits and quota policies.
Amazon Emr Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals for API financial operations.
Amazon Emr Finops
FINOPSFeatures 5
Notable capabilities this provider offers.
Apache Spark Support
Run Apache Spark jobs for large-scale data processing and machine learning
Auto Scaling
Automatically adjust cluster size based on workload demand
Spot Instance Integration
Use EC2 Spot instances to reduce costs up to 90%
EMR Serverless
Run analytics without provisioning or managing clusters
Studio Notebooks
Develop and debug jobs using EMR Studio Jupyter notebooks
Semantic Vocabularies 1
JSON-LD contexts and semantic vocabularies used across these APIs.
Amazon Emr Context
JSON-LDSpectral Rules 2
Spectral governance rulesets for linting and validating these APIs.
Amazon EMR API Rules
SPECTRALAmazon EMR API Rules
SPECTRALJSON Schema 1
Standalone JSON Schema definitions for this provider's data models.
Amazon EMR Cluster
JSON SCHEMAJSON Structure 1
JSON Structure definitions describing this provider's data shapes.
Amazon Emr Structure
JSON STRUCTUREExamples 1
Example request and response payloads for these APIs.
Amazon Emr Example
EXAMPLESecurity Posture 3
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Agentic Access 1
Recommended x-agentic-access execution contracts for AI agents.
Use Cases 4
What developers build with this provider.
ETL Data Processing
Extract, transform, and load large datasets across data lakes and warehouses
Machine Learning
Train machine learning models on large datasets using Spark MLlib
Log Analytics
Process and analyze application logs at petabyte scale
Financial Risk Analysis
Run Monte Carlo simulations and risk models on large datasets
Integrations 4
Pre-built integrations with other platforms and tools.
Amazon S3
Use S3 as data lake storage for EMR clusters
AWS Glue
Integrate with Glue Data Catalog for metadata management
Amazon Athena
Query data processed by EMR using Athena SQL
Amazon SageMaker
Hand off processed data to SageMaker for model training
Resources
Get Started 5
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 8
Pagination, idempotency, versioning, errors, and events
Scroll for all 8
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 5
Authentication, authorization, and security posture
Learn 1
Tutorials, courses, talks, and written guidance
Operate 5
Status, limits, changes, and where to get help
Commercial 2
Pricing, plans, and the legal terms of use
Company 1
The organization behind the API
Other 1
Properties that don't map to a standard resource type