A data engineer has realized that the data files associated with a Delta table are incredibly small. They want to compact the small files to form…

The keyword that can be used to compact the small files associated with a Delta table

is OPTIMIZE. The OPTIMIZE command performs file compaction on a Delta table by rewriting a set of

small files into a set of larger files1. This can improve the performance of queries that scan the table

by reducing the number of files that need to be read and the amount of metadata that needs to be

processed1. The OPTIMIZE command can also optionally sort the data within each file by a given set

of columns, which can further improve the query performance by enabling data skipping and

predicate pushdown1. The OPTIMIZE command can be applied to the whole table or to a specific

partition of the table1.

The other keywords are not suitable for compacting the small files associated with a Delta

table. REDUCE is a keyword used in the SQL syntax for aggregating data using a user-defined

function2. COMPACTION is not a valid keyword in SQL or Python. REPARTITION is a keyword used in

the Python syntax for changing the number of partitions of a DataFrame or an RDD3. VACUUM is a

keyword used to remove files that are no longer referenced by a Delta table and are older than a

retention threshold4.

Reference:

1: OPTIMIZE | Databricks on AWS

2: REDUCE | Databricks on AWS

3: repartition | Databricks on AWS

4: VACUUM | Databricks on AWS