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Metrics
Table metrics Self-optimizing metrics Amoro provides both table-level and platform-level metrics to help users understand the runtime status of the current table. Table metric... -
Collections
_.at(collection [, index1, index2, …]) Arguments Returns Example _.contains(collection, target [, fromIndex=0]) Aliases Arguments Returns Example _.countBy(collection [, c... -
Object
_.assign(object, [sources]) Since Arguments Returns Example _.assignIn(object, [sources]) Since Aliases Arguments Returns Example _.assignInWith(object, sources, [cust... -
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 ... -
Fork Operator
Overview of the ForkOperator Using the ForkOperator Basics of Usage Per-Fork Configuration Failure Semantics Performance Tuning Comparison with PartitionedDataWriter Writing... -
Overview
Redisson is the Java Client and Real-Time Data Platform for Redis or Valkey . Providing the most convenient and easiest way to work with Redis or Valkey. Redisson objects provide ... -
Logic
and isEmpty not or cond ifElse allPass anyPass defaultTo both complement either propSatisfies unless when pathSatisfies until xor isNotEmpty and a → b → a | b... -
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... -
Mixed-Hive
Mixed-Hive format is a format that has better compatibility with Hive than Mixed-Iceberg format. Mixed-Hive format uses a Hive table as the BaseStore and an Iceberg table as the C... -
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 ...
