Compared with Iceberg format, Mixed-Iceberg format provides more features: Stronger primary key constraints that also apply to Spark OLAP performance that is production-ready fo...
System requirements Download the distribution Source code compilation Configuration Configure the service address Configure system database Configure high availability Config...
Create a table Using a Hive catalog Using a Hadoop catalog Branching and Tagging Creating branches and tags Committing to branches Reading from branches and tags Replacing an...
Preparation when using Flink SQL Client Flink’s Python API Adding catalogs. Catalog Configuration Hive catalog Creating a table Writing Branch Writes Reading Type conversi...
Pre-requisites Steps Initialize a pyspark shell Create dataset Running sync Conclusion Next steps Using OneTable to sync your source tables in different target format invo...
Feature support Enabling Iceberg support in Hive Hive 4.0.0-beta-1 Hive 4.0.0-alpha-2 Hive 4.0.0-alpha-1 Hive 2.3.x, Hive 3.1.x Loading runtime jar Enabling support Hadoop con...