What Is Apache Hudi?
Apache Hudi (Hadoop Upserts Deletes and Incremental) is an open-source data management framework used to simplify incremental data processing and data pipeline development. It provides transactional capabilities on top of data lakes, effectively enabling users to manage data stored in distributed file systems like HDFS or cloud storage.
History
Apache Hudi was originally developed by Uber in 2016 to manage its ever-growing volume of data and data processing workloads. It was later contributed to open-source and became a part of the Apache Software Foundation in 2020.
Functionality and Features
Apache Hudi's core features include:
- Upsert and Delete Support: Enables modification of stored datasets.
- Atomic Publish: Ensures data integrity while publishing data.
- Snapshot and Incremental Queries: Provides efficient data querying capabilities.
- Savepoints: Allows rollback to a previous point in time data snapshot.
Architecture
Apache Hudi adopts a MVCC (Multi Version Concurrency Control) model to manage and store data, comprised of components like the Timeline Server, Cleaner, Compacter, and Clustering.
Benefits and Use Cases
Apache Hudi allows for simpler data pipeline development, efficient data processing, and data management. Key use cases include:
- Change Data Capture (CDC)
- Audit Trails
- Real-time data analytics
Challenges and Limitations
Despite its many benefits, Apache Hudi may present challenges in complex query performance and may require substantial resource allocation for large data workloads.
Integration with Data Lakehouse
In a data lakehouse environment, Apache Hudi serves as a critical component that brings together the advantages of data warehouses and data lakes, offering transactional support, data versioning, and efficient querying.
Security Aspects
Apache Hudi supports Kerberos authentication. Additionally, it complies with the underlying file system's security measures (like HDFS or cloud storage).
Performance
Apache Hudi offers efficient pipeline performance, though it may vary depending on the specific workload, the available resources, and the configuration settings.
FAQs
What is Apache Hudi? - Apache Hudi is an open-source data management framework used for incremental data processing and pipeline development.
Who developed Apache Hudi? - Apache Hudi was originally developed by Uber in 2016 and then became a part of Apache Software Foundation in 2020.
What are the core features of Apache Hudi? - Apache Hudi's core features include upsert and delete support, atomic publish, snapshot and incremental queries, and savepoints.
What are some use cases for Apache Hudi? - Some use cases of Apache Hudi include change data capture (CDC), audit trails, and real-time data analytics.
How does Apache Hudi integrate with a data lakehouse? - In a data lakehouse setup, Apache Hudi enables features that combine the advantages of both data lakes and data warehouses, like transactional support, data versioning, and efficient querying.
Glossary
Data Lakehouse: A data architecture that combines the elements of data lakes and data warehouses.
Change Data Capture (CDC): A process that captures changes in data so that other software can respond to those changes.
Upsert: A DBMS operation that either inserts a row into a database or updates it if it already exists.
Query: A request for data or information from a database.
Kerberos: A network authentication protocol designed to provide strong authentication for client/server applications.
