Which statement describes Delta Lake optimized writes?
A.
A shuffle occurs prior to writing to try to group data together resulting in fewer files instead of each executor writing multiple files based on directory partitions.
B.
Optimized writes logical partitions instead of directory partitions partition boundaries are only represented in metadata fewer small files are written.
C.
An asynchronous job runs after the write completes to detect if files could be further compacted; yes, an OPTIMIZE job is executed toward a default of 1 GB.
D.
Before a job cluster terminates, OPTIMIZE is executed on all tables modified during the most recent job.
Delta Lake optimized writes involve a shuffle operation before writing out data to the Delta table. The shuffle operation groups data by partition keys, which can lead to a reduction in the number of output files and potentially larger files, instead of multiple smaller files. This approach can significantly reduce the total number of files in the table, improve read performance by reducing the metadata overhead, and optimize the table storage layout, especially for workloads with many small files.
References:
Databricks documentation on Delta Lake performance tuning: https://docs.databricks.com/delta/optimizations/auto-optimize.html
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