Best practices for Reltio data sharing with Databricks - essentials
Learn about recommended practices for using streaming tables in Reltio data sharing with Databricks - essentials so that you can query the supported tables and avoid unsupported downstream usage.
Recommended practices
Use data shares for analytics and data engineering workloads
Use data shares for downstream systems such as BI, reporting, and ML pipelines.
Query supported streaming tables
Use the following streaming tables to query data.
entity_<entity_type>relation_<relation_type>interaction_<interaction_type>linksmatchesmerges
These streaming tables use the hierarchical All Values schema, which includes all values available for each attribute.
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Data synchronization is triggered every four hours. The time required for updates to become available in the shared tables depends on the volume of data to be processed and the processing duration.
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The data share supports a cumulative maximum of 490 entity, relationship, and interaction types. If your business configuration contains more than 490 types, you must apply filtering to limit the data share to a maximum of 490 types.Contact Reltio Support to learn more about configuring the filter.
Practices to avoid
Avoid querying landing tables
Do not use the following streaming tables to query data.
entities_<entity_type>_landingtablerelations_<relation_type>_landingtableinteractions_<interaction_type>_landingtablelinks_landingtablematches_landingtablemerges_landingtable
Avoid using data shares for non-analytics downstream systems
Do not use data shares to build downstream systems for non-analytics use cases.