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https://github.com/apache/incubator-hudi

Upserts, Deletes And Incremental Processing on Big Data.
https://github.com/apache/incubator-hudi

apacheflink apachehudi apachespark bigdata data-integration datalake hudi incremental-processing stream-processing

Last synced: 2 months ago
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Upserts, Deletes And Incremental Processing on Big Data.

Host: GitHub
URL: https://github.com/apache/incubator-hudi
Owner: apache
License: apache-2.0
Created: 2016-12-14T15:53:41.000Z (almost 8 years ago)
Default Branch: master
Last Pushed: 2024-06-07T12:50:14.000Z (5 months ago)
Last Synced: 2024-06-07T14:13:21.038Z (5 months ago)
Topics: apacheflink, apachehudi, apachespark, bigdata, data-integration, datalake, hudi, incremental-processing, stream-processing
Language: Java
Homepage: https://hudi.apache.org/
Size: 1.12 GB
Stars: 5,146
Watchers: 1,172
Forks: 2,370
Open Issues: 940
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

        

# 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).



[![Build](https://github.com/apache/hudi/actions/workflows/bot.yml/badge.svg)](https://github.com/apache/hudi/actions/workflows/bot.yml)

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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](https://parquet.apache.org/) + [Avro](https://avro.apache.org/docs/current/mr.html)).

 * **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](https://parquet.apache.org/)).

Learn more about Hudi at [https://hudi.apache.org](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-3.5.0-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

```

### 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

3.5.0. 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

```

#### 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 1.18. 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

```

## 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](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](https://hudi.apache.org/contribute/how-to-contribute) to learn more about how to contribute.

For code contributions, please refer to the [developer setup](https://hudi.apache.org/contribute/developer-setup).