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With Databricks Runtime 14.0 and above, shared clusters now use Spark Connect with the Spark Driver from the Python REPL by default. Internal Spark APIs are no longer accessible from user code.
Lakehouse Federation is now available on single-user clusters using Databricks Runtime 13.1 and above. Only the connection owner can run queries on federated catalogs.
Workflows
To prevent runs of Databricks jobs from being skipped because of concurrency limits, you can enable queueing on the job. When it’s enabled if a concurrency limit is reached, the job is placed in a queue until capacity is available. For more informationhttps://docs.databricks.com/en/workflows/jobs/create-run-jobs.html#job-queueing
Databricks asset bundles is now public preview. It enables end to end analytics and ML projects to be expressed as a collection of sources. This makes it simpler to apply Data engineering best practices. For more informationhttps://docs.databricks.com/en/dev-tools/bundles/index.html
Row-level concurrency reduces conflicts between concurrent write operations by detecting changes at the row-level and automatically resolving competing changes in concurrent writes that update or delete different rows in the same data file. For more informationhttps://docs.databricks.com/en/optimizations/isolation-level.html#row-level-concurrency
Partner connect
You can use Partner connect to connect your databricks workspace to Snowplow.