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Microsoft Azure
Disclaimer Supported Storage System Verified Combination of Spark and storage system HDInsight Spark2.4 on Azure Data Lake Storage Gen 2 Databricks Spark2.4 on Azure Data Lake S... -
任务类型
Appendix Shell SubProcess Dynamic Dependent Stored Procedure SQL Spark MapReduce Python Flink HTTP DataX Sqoop Pigeon Conditions Switch SeaTunnel Amazon EMR Apac... -
Console
Support Connector Version Support Those Engines Description Key Features Options Task Example Simple: Multiple Sources Simple: Console Sample Data Console sink connector... -
Configuration
Spark Configuration Catalogs Spark adds an API to plug in table catalogs that are used to load, create, and manage Iceberg tables. Spark catalogs are configured by setting Spark ... -
Engine UI
Engine Management Details This engine UI is able to help you understand status of the engine behind Kyuubi servers. Engine Management Details The Engine UI offers an Engine Man... -
Java API
Iceberg Java API Tables The main purpose of the Iceberg API is to manage table metadata, like schema, partition spec, metadata, and data files that store table data. Table metad... -
Debugging Kyuubi
Debugging Server Debugging Engine Flink Engine Trino Engine Hive Engine Debugging Apps Spark Engine Flink Engine You can use the Java Debug Wire Protocol to debug Kyuubi ... -
Hive Dialect Support
Features Usage Hive Dialect plugin aims to provide Hive Dialect support to Spark’s JDBC source. It will auto registered to Spark and applied to JDBC sources with url prefix of j... -
Branching and Tagging
Branching and Tagging Overview Iceberg table metadata maintains a snapshot log, which represents the changes applied to a table. Snapshots are fundamental in Iceberg as they are ... -
Structured Streaming
Spark Structured Streaming Iceberg uses Apache Spark’s DataSourceV2 API for data source and catalog implementations. Spark DSv2 is an evolving API with different levels of support...
