An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
Operations such as optimize return a DataFrame with the operation's metrics; however, vacuum() returns an empty DataFrame.
Steps to reproduce
from delta import DeltaTable
from pyspark.sql import SparkSession
spark = SparkSession.builder.getOrCreate()
my_table = DeltaTable.forName(spark, "my_schema.my_table")
df = my_table.vacuum()
assert df.isEmpty()
Environment information
Delta Lake version: 3.2.0
Spark version: 3.5.2
Scala version:
Willingness to contribute
The Delta Lake Community encourages bug fix contributions. Would you or another member of your organization be willing to contribute a fix for this bug to the Delta Lake code base?
[x] Yes. I can contribute a fix for this bug independently.
Bug
Which Delta project/connector is this regarding?
Describe the problem
Operations such as optimize return a
DataFramewith the operation's metrics; however, vacuum() returns an empty DataFrame.Steps to reproduce
Environment information
Willingness to contribute
The Delta Lake Community encourages bug fix contributions. Would you or another member of your organization be willing to contribute a fix for this bug to the Delta Lake code base?