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.
APIs
Amazon EMR API
API for creating and managing Amazon EMR clusters, steps, instance groups, and running distributed big data processing workloads.
Capabilities
Amazon EMR Management
Unified capability for managing Amazon EMR resources. Combines Amazon EMR APIs for Data Engineer workflows in Big Data Processing.
Run with NaftikoFeatures
Run Apache Spark jobs for large-scale data processing and machine learning
Automatically adjust cluster size based on workload demand
Use EC2 Spot instances to reduce costs up to 90%
Run analytics without provisioning or managing clusters
Develop and debug jobs using EMR Studio Jupyter notebooks
Use Cases
Extract, transform, and load large datasets across data lakes and warehouses
Train machine learning models on large datasets using Spark MLlib
Process and analyze application logs at petabyte scale
Run Monte Carlo simulations and risk models on large datasets
Integrations
Use S3 as data lake storage for EMR clusters
Integrate with Glue Data Catalog for metadata management
Query data processed by EMR using Athena SQL
Hand off processed data to SageMaker for model training