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Hive
Hive Iceberg supports reading and writing Iceberg tables through Hive by using a StorageHandler . Feature support The following features matrix illustrates the support for diff... -
Z-Ordering Support
Introduction Supported table format Supported column data type How to use Optimize history data Syntax Examples Optimize incremental data To improve query speed, Kyuubi su... -
Customize Services
Credentials Databases Directories Accounts All Configurations Next Step More Information The Customize Services step presents you with a set of tabs that let you review and... -
Procedures
Spark Procedures To use Iceberg in Spark, first configure Spark catalogs . Stored procedures are only available when using Iceberg SQL extensions in Spark 3. Usage Procedures c... -
AWS Datasync
DataSync 节点 综述 创建任务 任务样例 独有参数 环境配置 DataSync 节点 综述 AWS DataSync 是一种在线数据传输服务，可简化、自动化和加速本地存储系统和 AWS Storage 服务之间，以及不同 AWS Storage 服务之间的数据移动。 DataSync 支持的组件: Network File ... -
Architecture
Gobblin Architecture Overview Gobblin Job Flow Gobblin Constructs Source and Extractor Converter Quality Checker Fork Operator Data Writer Data Publisher Gobblin Task Flow... -
Creating your first interoperable table
Creating your first interoperable table Using Apache XTable™ (Incubating) to sync your source tables in different target format involves running sync on your current dataset usi... -
File Sizing
Auto-sizing during writes File sizing for Copy-On-Write (COW) and Merge-On-Read (MOR) tables More details about file sizing for Merge-On-Read(MOR) tables Configs Auto-Sizing Wi... -
Using Logstore
Real-Time data in LogStore Overview Prerequisites for using LogStore Double write LogStore and FileStore Due to the limitations of traditional offline data warehouse architect... -
Iceberg
Iceberg format refers to Apache Iceberg table, which is an open table format for large analytical datasets designed to provide scalable, efficient, and secure data storage and qu...
