Apache Hudi (Incubating) (pronounced Hoodie) stands for Hadoop Upserts Deletes and Incrementals.
Hudi manages the storage of large analytical datasets on DFS (Cloud stores, HDFS or any Hadoop FileSystem compatible storage).
- Upsert support with fast, pluggable indexing
- Atomically publish data with rollback support
- Snapshot isolation between writer & queries
- Savepoints for data recovery
- Manages file sizes, layout using statistics
- Async compaction of row & columnar data
- Timeline metadata to track lineage
Hudi provides the ability to query via three types of views:
- Read Optimized View - Provides excellent snapshot query performance via purely columnar storage (e.g. Parquet).
- Incremental View - Provides a change stream with records inserted or updated after a point in time.
- Real-time View - Provides snapshot queries on real-time data, using a combination of columnar & row-based storage (e.g Parquet + Avro).
Learn more about Hudi at https://hudi.apache.org
Prerequisites for building Apache Hudi:
- Unix-like system (like Linux, Mac OS X)
- Java 8 (Java 9 or 10 may work)
- Git
- Maven
# Checkout code and build
git clone https://github.com/apache/incubator-hudi.git && cd incubator-hudi
mvn clean package -DskipTests -DskipITs
Please visit https://hudi.apache.org/quickstart.html to quickly explore Hudi's capabilities using spark-shell.