Apache Hudi (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).

https://hudi.apache.org/

• 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 supports three types of queries:

• Snapshot Query - Provides snapshot queries on real-time data, using a combination of columnar & row-based storage (e.g Parquet + Avro).
• Incremental Query - Provides a change stream with records inserted or updated after a point in time.
• Read Optimized Query - Provides excellent snapshot query performance via purely columnar storage (e.g. Parquet).

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/hudi.git && cd hudi
mvn clean package -DskipTests -DskipITs

# Start command
spark-2.4.4-bin-hadoop2.7/bin/spark-shell \
  --jars `ls packaging/hudi-spark-bundle/target/hudi-spark-bundle_2.11-*.*.*-SNAPSHOT.jar` \
  --conf 'spark.serializer=org.apache.spark.serializer.KryoSerializer'

To build the Javadoc for all Java and Scala classes:

# Javadoc generated under target/site/apidocs
mvn clean javadoc:aggregate -Pjavadocs

The default Scala version supported is 2.11. To build for Scala 2.12 version, build using scala-2.12 profile

mvn clean package -DskipTests -DskipITs -Dscala-2.12

The default hudi-jar bundles spark-avro module. To build without spark-avro module, build using spark-shade-unbundle-avro profile

# Checkout code and build
git clone https://github.com/apache/hudi.git && cd hudi
mvn clean package -DskipTests -DskipITs -Pspark-shade-unbundle-avro

# Start command
spark-2.4.4-bin-hadoop2.7/bin/spark-shell \
  --packages org.apache.spark:spark-avro_2.11:2.4.4 \
  --jars `ls packaging/hudi-spark-bundle/target/hudi-spark-bundle_2.11-*.*.*-SNAPSHOT.jar` \
  --conf 'spark.serializer=org.apache.spark.serializer.KryoSerializer'

Please visit https://hudi.apache.org/docs/quick-start-guide.html to quickly explore Hudi's capabilities using spark-shell.