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apache / hudi / 48f89aeb1c732d1ba1a99832b908d99558ac7c9c
commit48f89aeb1c732d1ba1a99832b908d99558ac7c9c[log] [tgz]
authorSivabalan Narayanan <n.siva.b@gmail.com>Wed Sep 06 13:56:21 2023 -0400
committerGitHub <noreply@github.com>Wed Sep 06 10:56:21 2023 -0700
tree861fb10c1f46ca93c2dd5f80f825f0e090bc1a95
parenteab00d570fdc986d865b511cc0402069b4b9ce2b [diff]
[HUDI-6397][HUDI-6759] Fixing misc bugs w/ metadata table (#9546)

1. This commit allows users to disable metadata using write configs cleanly.
2. Valid instants consideration while reading from MDT is solid now. We are going to treat any special instant time (that has additional suffix compared to DT's commit time) as valid.

Especially with MDT partition initialization, the suffix is dynamic, and so we can't really find exact match. So, might have to go with total instant time length and treat all special instant times as valid ones.

In the LogRecordReader, we will first ignore any uncommitted instants. And then if it's completed in MDT timeline, we check w/ the instantRange. So it should be fine to return true for any special instant times.
7 files changed
tree: 861fb10c1f46ca93c2dd5f80f825f0e090bc1a95
  1. .github/
  2. .idea/
  3. conf/
  4. dependencies/
  5. docker/
  6. hudi-aws/
  7. hudi-cli/
  8. hudi-client/
  9. hudi-common/
  10. hudi-examples/
  11. hudi-flink-datasource/
  12. hudi-gcp/
  13. hudi-hadoop-mr/
  14. hudi-integ-test/
  15. hudi-kafka-connect/
  16. hudi-platform-service/
  17. hudi-spark-datasource/
  18. hudi-sync/
  19. hudi-tests-common/
  20. hudi-timeline-service/
  21. hudi-utilities/
  22. packaging/
  23. release/
  24. rfc/
  25. scripts/
  26. style/
  27. .asf.yaml
  28. .codecov.yml
  29. .gitignore
  30. azure-pipelines-20230430.yml
  31. doap_HUDI.rdf
  32. LICENSE
  33. NOTICE
  34. pom.xml
  35. README.md
README.md

Apache Hudi

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/

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Features

  • 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

Building Apache Hudi from source

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-3.2.3-bin-hadoop3.2/bin/spark-shell \
  --jars `ls packaging/hudi-spark-bundle/target/hudi-spark3.2-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

Build with different Spark versions

The default Spark 2.x version supported is 2.4.4. The default Spark 3.x version, corresponding to spark3 profile is 3.4.0. The default Scala version is 2.12. Refer to the table below for building with different Spark and Scala versions.

Maven build optionsExpected Spark bundle jar nameNotes
(empty)hudi-spark3.2-bundle_2.12For Spark 3.2.x and Scala 2.12 (default options)
-Dspark2.4 -Dscala-2.11hudi-spark2.4-bundle_2.11For Spark 2.4.4 and Scala 2.11
-Dspark3.0hudi-spark3.0-bundle_2.12For Spark 3.0.x and Scala 2.12
-Dspark3.1hudi-spark3.1-bundle_2.12For Spark 3.1.x and Scala 2.12
-Dspark3.2hudi-spark3.2-bundle_2.12For Spark 3.2.x and Scala 2.12 (same as default)
-Dspark3.3hudi-spark3.3-bundle_2.12For Spark 3.3.x and Scala 2.12
-Dspark3.4hudi-spark3.4-bundle_2.12For Spark 3.4.x and Scala 2.12
-Dspark2 -Dscala-2.11hudi-spark-bundle_2.11 (legacy bundle name)For Spark 2.4.4 and Scala 2.11
-Dspark2 -Dscala-2.12hudi-spark-bundle_2.12 (legacy bundle name)For Spark 2.4.4 and Scala 2.12
-Dspark3hudi-spark3-bundle_2.12 (legacy bundle name)For Spark 3.4.x and Scala 2.12

For example,

# Build against Spark 3.2.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

What about “spark-avro” module?

Starting from versions 0.11, Hudi no longer requires spark-avro to be specified using --packages

Build with different Flink versions

The default Flink version supported is 1.17. The default Flink 1.17.x version, corresponding to flink1.17 profile is 1.17.0. 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 optionsExpected Flink bundle jar nameNotes
(empty)hudi-flink1.17-bundleFor Flink 1.17 (default options)
-Dflink1.17hudi-flink1.17-bundleFor Flink 1.17 (same as default)
-Dflink1.16hudi-flink1.16-bundleFor Flink 1.16
-Dflink1.15hudi-flink1.15-bundleFor Flink 1.15
-Dflink1.14hudi-flink1.14-bundleFor Flink 1.14 and Scala 2.12
-Dflink1.14 -Dscala-2.11hudi-flink1.14-bundleFor Flink 1.14 and Scala 2.11
-Dflink1.13hudi-flink1.13-bundleFor Flink 1.13 and Scala 2.12
-Dflink1.13 -Dscala-2.11hudi-flink1.13-bundleFor Flink 1.13 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

# Build against Flink 1.13.x and Scala 2.12
mvn clean package -DskipTests -Dflink1.13

Running Tests

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

Quickstart

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

Contributing

Please check out our contribution guide to learn more about how to contribute. For code contributions, please refer to the developer setup.