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Ed Lee commented on SPARK-20617: -------------------------------- Thank you for the clarification. So conversely: {code:java} spark.sql("select null NOT in ('a')") {code} evaluates to null. And when the filter is applied with null == False this is false and therefore the filter wouldn't return those rows. I see now that Pandas doesn't follow SQL standards test_df.query("col1 not in (['a'])") > pyspark.sql filtering fails when using ~isin when there are nulls in column > --------------------------------------------------------------------------- > > Key: SPARK-20617 > URL: https://issues.apache.org/jira/browse/SPARK-20617 > Project: Spark > Issue Type: Bug > Components: PySpark, SQL > Affects Versions: 2.2.0 > Environment: Ubuntu Xenial 16.04, Python 3.5 > Reporter: Ed Lee > Priority: Major > > Hello encountered a filtering bug using 'isin' in pyspark sql on version > 2.2.0, Ubuntu 16.04. > Enclosed below an example to replicate: > from pyspark.sql import SparkSession > from pyspark.sql import functions as sf > import pandas as pd > spark = SparkSession.builder.master("local").appName("Word > Count").getOrCreate() > test_df = pd.DataFrame({"col1": [None, None, "a", "b", "c"], > "col2": range(5) > }) > test_sdf = spark.createDataFrame(test_df) > test_sdf.show() > |col1|col2| > |null| 0| > |null| 1| > | a| 2| > | b| 3| > | c| 4| > # Below shows when filtering col1 NOT in list ['a'] the col1 rows with null > are missing: > test_sdf.filter(sf.col("col1").isin(["a"]) == False).show() > Or: > test_sdf.filter(~sf.col("col1").isin(["a"])).show() > *Expecting*: > |col1|col2| > |null| 0| > |null| 1| > | b| 3| > | c| 4| > *Got*: > |col1|col2| > | b| 3| > | c| 4| > My workarounds: > 1. null is considered 'in', so add OR isNull conditon: > test_sdf.filter((sf.col("col1").isin(["a"])== False) | ( > sf.col("col1").isNull())).show() > To get: > |col1|col2|isin| > |null| 0|null| > |null| 1|null| > | c| 4|null| > | b| 3|null| > 2. Use left join and filter > join_df = pd.DataFrame({"col1": ["a"], > "isin": 1 > }) > join_sdf = spark.createDataFrame(join_df) > test_sdf.join(join_sdf, on="col1", how="left") \ > .filter(sf.col("isin").isNull()) \ > .show() > To get: > |col1|col2|isin| > |null| 0|null| > |null| 1|null| > | c| 4|null| > | b| 3|null| > Thank you -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org