While using Databricks Runtime, if you want CONVERT to overwrite the existing metadata in the Delta Lake transaction log, set the SQL configuration .metadataCheck.enabled to false. Keep in mind, it is possible to use Apache Iceberg when using Databricks which can help to prevent migration friction if you leave the platform in the future. If the underlying directory has already been converted to Delta Lake and its metadata is different from the catalog metadata, a convertMetastoreMetadataMismatchException is thrown. Outside the Databricks platform, several platforms give Apache Iceberg first-class support, making it a compelling option when Databricks is not part of your architecture. To query or write to these external tables again, you must run CONVERT on them as well.ĬONVERT populates the catalog information, such as schema and table properties, to the Delta Lake transaction log. spark.sql('CREATE OR REPLACE TABLE USING ICEBERG AS (SELECT FROM people LIMIT 0)') In order to add only the Parquet files corresponding to the latest version of the delta. In this case, if you run CONVERT on one of the external tables, then you will not be able to access the other external tables because their underlying directory has been converted from Parquet to Delta Lake. It is possible that multiple external tables share the same underlying Parquet directory. SAN FRANCISCO J Databricks, the Data and AI company, today announced the latest contribution to award-winning Linux Foundation open source project Delta Lake, with the release of Delta Lake 3.0. After the table is converted, make sure all writes go through Delta Lake. New release unifies lakehouse storage formats and reinforces Delta Lake as the best choice for building an open lakehouse. You should avoid updating or appending data files during the conversion process. INSERT OVERWRITE DIRECTORY with Hive formatĪny file not tracked by Delta Lake is invisible and can be deleted when you run VACUUM. Databricks on Wednesday unveiled Delta Lake 3.0, the latest version of the open source storage format used by many of the vendors customers.REFRESH FOREIGN (CATALOG, SCHEMA, or TABLE).Federated queries (Lakehouse Federation).Privileges and securable objects in the Hive metastore.In Databricks Runtime 13.1 and above, you can work with truncated columns of types string, long, or int. ![]() Privileges and securable objects in Unity Catalog The following are limitations for converting Iceberg tables with partitions defined on truncated columns: In Databricks Runtime 13.0 and below, the only truncated column type supported is string.
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