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 ...
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...
This section describes the information and materials you should get ready to install a cluster using Ambari. Ambari provides an end-to-end management and monitoring solution for y...
Introduction Dataset Config Management Requirement Data Model Versioning Client library Config Store Current Dataset Config Management Implementation Data model Client appli...
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...
Object holder Java implementation of Redis or Valkey based RBucket object is a holder for any type of object. Size is limited to 512Mb. Code example: RBucket < AnyObject > buc...
Flink Queries Iceberg support streaming and batch read With Apache Flink ‘s DataStream API and Table API. Reading with SQL Iceberg support both streaming and batch read in Flink...