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1. Terminologies
Terminologies Kyuubi JDBC Apache Hive Apache Thrift Server ServerSpace Engine EngineSpace Apache Spark Multi Tenancy High Availability / Load Balance Apache Zookeeper Apa... -
Introduction
Architecture Supported table formats Supported engines Iceberg format Paimon format Mixed format User cases Self-managed streaming Lakehouse Stream-and-batch-fused data pipe... -
Self-Optimizing
Introduction Self-optimizing mechanism Self-optimizing scheduling policy Quota Balanced Introduction Lakehouse is characterized by its openness and loose coupling, with data... -
Table Watermark
Table freshness Table watermark Table freshness Data freshness represents timeliness, and in many discussions, freshness is considered one of the important indicators of data q... -
SQL DDL
Spark SQL Create table Create non-partitioned table Create partitioned table Create table with record keys and ordering fields Create table from an external location Create Ta... -
SQL Queries
Spark SQL Snapshot Query Time Travel Query Change Data Capture Incremental Query Flink SQL Snapshot Query Options Streaming Query Options Incremental Query Options Catal... -
Use Cases
A Streaming Data Lake Near Real-Time Ingestion Incremental Processing Pipelines Unified Batch and Streaming Cloud-Native Tables Schema Management ACID Transactions Efficient ... -
Apache Hudi Stack
Lake Storage File Formats Transactional Database Layer Table Format Indexes Table Services Clustering Compaction Cleaning Indexing Concurrency Control Lake Cache* Metase... -
Metadata Table
Metadata Table Supporting Multi-Modal Index in Hudi Metadata table indices Enable Hudi Metadata Table and Multi-Modal Index in write side Use metadata indices for query side im... -
Design & Concepts
How does Hudi ensure atomicity? Does Hudi extend the Hive table layout? What concurrency control approaches does Hudi adopt? Hudi’s commits are based on transaction start time i...