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Creating your first interoperable table
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... -
config
Intro to config file Example Config file structure hocon multi-line support json env source transform sink Other Config variable substitution What’s More Intro to co... -
Self-Optimizing
Introduction Self-optimizing mechanism Self-optimizing scheduling policy Quota Balanced Introduction Lakehouse is characterized by its openness and loose coupling, with data... -
1. Overview
Redisson is the Redis Java client and Real-Time Data Platform. It provides more convenient and easiest way to work with Redis. Redisson objects provides a separation of concern, wh... -
Debezium Format
Format Options How To Use Kafka Uses example Changelog-Data-Capture Format: Serialization Schema Format: Deserialization Schema Debezium is a set of distributed services to ca... -
StarRocks
Support These Engines Key Features Description Sink Options save_mode_create_template table [string] schema_save_mode[Enum] data_save_mode[Enum] custom_sql[String] Data Ty... -
3. Trouble Shooting
Common Issues java.lang.UnsupportedClassVersionError .. Unsupported major.minor version 52.0 org.apache.spark.SparkException: When running with master ‘yarn’ either HADOOP_CONF_DI... -
Mixed-Iceberg
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... -
Clickhouse
Support Those Engines Key Features Description Supported DataSource Info Data Type Mapping Sink Options How to Create a Clickhouse Data Synchronization Jobs Tips Clickhouse... -
Introduction
User experience Reliability and performance Open standard Apache Iceberg is an open table format for huge analytic datasets. Iceberg adds tables to compute engines including S...
