xushiyan commented on code in PR #10624: URL: https://github.com/apache/hudi/pull/10624#discussion_r1478861210
########## website/docs/hudi_stack.md: ########## @@ -0,0 +1,99 @@ +--- +title: Apache Hudi Stack +summary: "Explains about the various layers of software components that make up Hudi" +toc: true +toc_min_heading_level: 2 +toc_max_heading_level: 4 +last_modified_at: +--- + +Apache Hudi is a Transactional Data Lakehouse Platform built around a database kernel. It brings core warehouse and database functionality directly to a data lake thereby providing a table-level abstraction over open file formats like Apache Parquet/ORC (more recently known as the lakehouse architecture) and enabling transactional capabilities such as updates/deletes. Hudi also incorporates essential table services that are tightly integrated with the database kernel. These services can be executed automatically across both ingested and derived data to manage various aspects such as table bookkeeping, metadata, and storage layout. This integration along with various platform-specific services extends Hudi's role from being just a 'table format' to a comprehensive and robust data lakehouse platform. + +In this section, we will explore the Hudi stack and deconstruct the layers of software components that constitute Hudi. The features marked with an asterisk (*) represent work in progress, and the dotted boxes indicate planned future work. These components collectively aim to fulfill the [vision](https://github.com/apache/hudi/blob/master/rfc/rfc-69/rfc-69.md) for the project. + + +_Figure: Apache Hudi Architectural stack_ + +# Lake Storage +The storage layer is where the data files (such as Parquet) are stored. Hudi interacts with the storage layer through the [Hadoop FileSystem API](https://hadoop.apache.org/docs/stable/api/org/apache/hadoop/fs/FileSystem.html), enabling compatibility with various systems including HDFS for fast appends, and various cloud stores such as Amazon S3, Google Cloud Storage (GCS), and Azure Blob Storage. Additionally, Hudi offers its own storage APIs that can rely on Hadoop-independent file system implementation to simplify the integration of various file systems. Hudi adds a custom wrapper filesystem that lays out the foundation for improved storage optimizations. + +# File Formats + +_Figure: File format structure in Hudi_ + +File formats hold the raw data and are physically stored on the lake storage. Hudi operates on a 'base file and log file' structure. The base files are compacted and optimized for reads and are augmented with log files for efficient append. Future updates aim to integrate diverse formats like unstructured data (e.g., JSON, images), and compatibility with different storage layers in event-streaming, OLAP engines, and warehouses. Hudi's layout scheme encodes all changes to a log file as a sequence of blocks (data, delete, rollback). By making data available in open file formats (such as Parquet), Hudi enables users to bring any compute engine for specific workloads. Review Comment: ```suggestion File formats hold the raw data and are physically stored on the lake storage. Hudi operates on logical structures of File Groups and File Slices, which consist of Base File and Log Files. Base Files are compacted and optimized for reads and are augmented with Log Files for efficient append. Future updates aim to integrate diverse formats like unstructured data (e.g., images), and compatibility with different storage layers in event-streaming, OLAP engines, and warehouses. Hudi's layout scheme encodes all changes to a Log File as a sequence of blocks (data, delete, rollback). By making data available in open file formats (such as Parquet), Hudi enables users to bring any compute engine for specific workloads. ``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: commits-unsubscr...@hudi.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
