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).
- 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
- Optimize data lake layout with clustering
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 (>=3.3.1)
# Checkout code and build
git clone https://github.com/apache/hudi.git && cd hudi
mvn clean package -DskipTests
# Start command
spark-3.5.0-bin-hadoop3/bin/spark-shell \
--jars `ls packaging/hudi-spark-bundle/target/hudi-spark3.5-bundle_2.12-*.*.*-SNAPSHOT.jar` \
--conf 'spark.serializer=org.apache.spark.serializer.KryoSerializer' \
--conf 'spark.sql.extensions=org.apache.spark.sql.hudi.HoodieSparkSessionExtension' \
--conf 'spark.sql.catalog.spark_catalog=org.apache.spark.sql.hudi.catalog.HoodieCatalog' \
--conf 'spark.kryo.registrator=org.apache.spark.HoodieSparkKryoRegistrar'
To build for integration tests that include hudi-integ-test-bundle, use -Dintegration-tests.
To build the Javadoc for all Java and Scala classes:
# Javadoc generated under target/site/apidocs
mvn clean javadoc:aggregate -Pjavadocs
The default Spark 2.x version supported is 2.4.4. The default Spark 3.x version, corresponding to spark3 profile is
3.5.0. The default Scala version is 2.12. Scala 2.13 is supported for Spark 3.5 and above.
Refer to the table below for building with different Spark and Scala versions.
| Maven build options | Expected Spark bundle jar name | Notes |
|---|---|---|
| (empty) | hudi-spark3.5-bundle_2.12 | For Spark 3.5.x and Scala 2.12 (default options) |
-Dspark2.4 -Dscala-2.11 |
hudi-spark2.4-bundle_2.11 | For Spark 2.4.4 and Scala 2.11 |
-Dspark3.3 |
hudi-spark3.3-bundle_2.12 | For Spark 3.3.x and Scala 2.12 |
-Dspark3.4 |
hudi-spark3.4-bundle_2.12 | For Spark 3.4.x and Scala 2.12 |
-Dspark3.5 -Dscala-2.12 |
hudi-spark3.5-bundle_2.12 | For Spark 3.5.x and Scala 2.12 (same as default) |
-Dspark3.5 -Dscala-2.13 |
hudi-spark3.5-bundle_2.13 | For Spark 3.5.x and Scala 2.13 |
-Dspark2 -Dscala-2.11 |
hudi-spark-bundle_2.11 (legacy bundle name) | For Spark 2.4.4 and Scala 2.11 |
-Dspark2 -Dscala-2.12 |
hudi-spark-bundle_2.12 (legacy bundle name) | For Spark 2.4.4 and Scala 2.12 |
-Dspark3 |
hudi-spark3-bundle_2.12 (legacy bundle name) | For Spark 3.5.x and Scala 2.12 |
Please note that only Spark-related bundles, i.e., hudi-spark-bundle, hudi-utilities-bundle,
hudi-utilities-slim-bundle, can be built using scala-2.13 profile. Hudi Flink bundle cannot be built
using scala-2.13 profile. To build these bundles on Scala 2.13, use the following command:
# Build against Spark 3.5.x and Scala 2.13
mvn clean package -DskipTests -Dspark3.5 -Dscala-2.13 -pl packaging/hudi-spark-bundle,packaging/hudi-utilities-bundle,packaging/hudi-utilities-slim-bundle -am
For example,
# Build against Spark 3.5.x
mvn clean package -DskipTests
# Build against Spark 3.4.x
mvn clean package -DskipTests -Dspark3.4
# Build against Spark 2.4.4 and Scala 2.11
mvn clean package -DskipTests -Dspark2.4 -Dscala-2.11
Starting from versions 0.11, Hudi no longer requires spark-avro to be specified using --packages
The default Flink version supported is 1.18. The default Flink 1.18.x version, corresponding to flink1.18 profile is 1.18.0.
Flink is Scala-free since 1.15.x, there is no need to specify the Scala version for Flink 1.15.x and above versions.
Refer to the table below for building with different Flink and Scala versions.
| Maven build options | Expected Flink bundle jar name | Notes |
|---|---|---|
| (empty) | hudi-flink1.18-bundle | For Flink 1.18 (default options) |
-Dflink1.18 |
hudi-flink1.18-bundle | For Flink 1.18 (same as default) |
-Dflink1.17 |
hudi-flink1.17-bundle | For Flink 1.17 |
-Dflink1.16 |
hudi-flink1.16-bundle | For Flink 1.16 |
-Dflink1.15 |
hudi-flink1.15-bundle | For Flink 1.15 |
-Dflink1.14 |
hudi-flink1.14-bundle | For Flink 1.14 and Scala 2.12 |
-Dflink1.14 -Dscala-2.11 |
hudi-flink1.14-bundle | For Flink 1.14 and Scala 2.11 |
For example,
# Build against Flink 1.15.x
mvn clean package -DskipTests -Dflink1.15
# Build against Flink 1.14.x and Scala 2.11
mvn clean package -DskipTests -Dflink1.14 -Dscala-2.11
Unit tests can be run with maven profile unit-tests.
mvn -Punit-tests test
Functional tests, which are tagged with @Tag("functional"), can be run with maven profile functional-tests.
mvn -Pfunctional-tests test
Integration tests can be run with maven profile integration-tests.
mvn -Pintegration-tests verify
To run tests with spark event logging enabled, define the Spark event log directory. This allows visualizing test DAG and stages using Spark History Server UI.
mvn -Punit-tests test -DSPARK_EVLOG_DIR=/path/for/spark/event/log
Please visit https://hudi.apache.org/docs/quick-start-guide.html to quickly explore Hudi's capabilities using spark-shell.
Please check out our contribution guide to learn more about how to contribute. For code contributions, please refer to the developer setup.