This configuration is set by default in Databricks Runtime 7.0. Databricks Runtime 6.3 introduced the ability to set the SQL configuration true on your cluster to ensure that the previous run stops. When running Structured Streaming production jobs on High Concurrency mode clusters, restarts of a job would occasionally fail, because the previously running job wasn’t terminated properly. This behavior can be overridden by setting Spark configuration .transparent true. Matplolib figures are now rendered with transparent=False, so that user-specified backgrounds are not lost. They are always displayed inline by default. The %matplotlib inline magic command is no longer required to display Matplolib objects inline in notebook cells. The main benefit of COPY is that lower privileged users can write data to Azure Synapse without needing strict CONTROL permissions on Azure Synapse. For details, see COPY INTO (Delta Lake on Azure Databricks).Īzure Synapse (formerly SQL Data Warehouse) connector supports the COPY statement. The command keeps track of previously loaded files and you safely re-run it in case of failures. The new COPY INTO command provides a familiar declarative interface to load data in SQL. If there are failures during loads, you have to handle them effectively. To load data into Delta Lake today you have to use Apache Spark DataFrame APIs. Released as a Public Preview in Databricks Runtime 6.4, the COPY INTO SQL command lets you load data into Delta Lake with idempotent retries. On Databricks Runtime 7.0 you no longer need to request a custom Databricks Runtime image in order to use Auto Loader.ĬOPY INTO (Public Preview), which lets you load data into Delta Lake with idempotent retries, has been improved in Databricks Runtime 7.0 Auto Loader is also more convenient and effective than file-notification-based structured streaming, which requires that you manually configure file-notification services on the cloud and doesn’t let you backfill existing files. This is an improvement over file-based structured streaming, which identifies new files by repeatedly listing the cloud directory and tracking the files that have been seen, and can be very inefficient as the directory grows. The change list between Scala 2.12 and 2.11 is in the Scala 2.12.0 release notes.Īuto Loader (Public Preview), released in Databricks Runtime 6.4, has been improved in Databricks Runtime 7.0Īuto Loader gives you a more efficient way to process new data files incrementally as they arrive on a cloud blob store during ETL. New featuresĭatabricks Runtime 7.0 includes the following new features:ĭatabricks Runtime 7.0 upgrades Scala from 2.11.12 to 2.12.10. The following release notes provide information about Databricks Runtime 7.0, powered by Apache Spark 3.0.
Databricks released this image in June 2020.
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