MBA Learns to Code created SPARK-22538:
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Summary: SQLTransformer.transform(inputDataFrame) uncaches
inputDataFrame
Key: SPARK-22538
URL: https://issues.apache.org/jira/browse/SPARK-22538
Project: Spark
Issue Type: Bug
Components: ML, PySpark, SQL, Web UI
Affects Versions: 2.2.0
Reporter: MBA Learns to Code
When running the below code on PySpark v2.2.0, the cached input DataFrame `df`
disappears from SparkUI after `SQLTransformer.transform(...)` is called on it.
I don't yet know whether this is only a SparkUI bug, or whether the input
DataFrame `df` is indeed unpersisted from memory. If the latter is true, this
can be a serious bug because any new computation using `new_df` would have to
re-do all the work leading up to `df`.
{code:python}
from __future__ import print_function
import pandas
import pyspark
from pyspark.ml.feature import SQLTransformer
spark = pyspark.sql.SparkSession.builder.getOrCreate()
df = spark.createDataFrame(pandas.DataFrame(dict(x=[-1, 0, 1])))
# after below step, SparkUI Storage shows 1 cached RDD
df.cache(); df.count()
# after below step, cached RDD disappears from SparkUI Storage
new_df = SQLTransformer(statement='SELECT * FROM __THIS__').transform(df)
{code}
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