python - Filter by whether column value equals a list in Spark

Question

I'm trying to filter a Spark dataframe based on whether the values in a column equal a list. I would like to do something like this:

filtered_df = df.where(df.a == ['list','of' , 'stuff'])

Where filtered_df only contains rows where the value of filtered_df.a is ['list','of' , 'stuff'] and the type of a is array (nullable = true).

Answer 1

Update:

With current versions you can use an array of literals:

from pyspark.sql.functions import array, lit

df.where(df.a == array(*[lit(x) for x in ['list','of' , 'stuff']]))

Original answer:

Well, a little bit hacky way to do it, which doesn't require a Python batch job, is something like this:

from pyspark.sql.functions import col, lit, size
from functools import reduce
from operator import and_

def array_equal(c, an_array):
    same_size = size(c) == len(an_array)  # Check if the same size
    # Check if all items equal
    same_items = reduce(
        and_, 
        (c.getItem(i) == an_array[i] for i in range(len(an_array)))
    )
    return and_(same_size, same_items)

Quick test:

df = sc.parallelize([
    (1, ['list','of' , 'stuff']),
    (2, ['foo', 'bar']),
    (3, ['foobar']),
    (4, ['list','of' , 'stuff', 'and', 'foo']),
    (5, ['a', 'list','of' , 'stuff']),
]).toDF(['id', 'a'])

df.where(array_equal(col('a'), ['list','of' , 'stuff'])).show()
## +---+-----------------+
## | id|                a|
## +---+-----------------+
## |  1|[list, of, stuff]|
## +---+-----------------+