tag | ac39652968c043780bfd40350f76dd14f4133696 | |
---|---|---|
tagger | Udit Mehrotra <udit.mehrotra90@gmail.com> | Sun Aug 15 14:19:22 2021 -0700 |
object | b02ec689b3270bc72ed67739d4520fb14e1f3aae |
0.9.0
commit | b02ec689b3270bc72ed67739d4520fb14e1f3aae | [log] [tgz] |
---|---|---|
author | Udit Mehrotra <udit.mehrotra90@gmail.com> | Sun Aug 15 14:04:03 2021 -0700 |
committer | GitHub <noreply@github.com> | Sun Aug 15 17:04:03 2021 -0400 |
tree | 94740dda57b22239411e92ab2f7400f4a14eaff4 | |
parent | 8d82d19ee4da8910c7101b24ab976ac7cf54e732 [diff] |
[Hot Fix]Add apache license to spark_command.txt.template (#3479)
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).
Hudi supports three types of queries:
Learn more about Hudi at https://hudi.apache.org
Prerequisites for building Apache Hudi:
# Checkout code and build git clone https://github.com/apache/hudi.git && cd hudi mvn clean package -DskipTests # 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 -Dscala-2.12
The default Spark version supported is 2.4.4. To build for Spark 3.0.0 version, build using spark3
profile
mvn clean package -DskipTests -Dspark3
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 -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'
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
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.