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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2017/11/17 04:45:00 UTC
[jira] [Assigned] (SPARK-22538)
SQLTransformer.transform(inputDataFrame) uncaches inputDataFrame
[ https://issues.apache.org/jira/browse/SPARK-22538?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-22538:
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Assignee: (was: Apache Spark)
> 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 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}
> 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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