user1982118 user1982118 - 2 months ago 28
Python Question

Explode in PySpark

I would like to transform from a DataFrame that contains lists of words into a DataFrame with each word in its own row.

How do I do explode on a column in a DataFrame?

Here is an example with some of my attempts where you can uncomment each code line and get the error listed in the following comment. I use PySpark in Python 2.7 with Spark 1.6.1.

from pyspark.sql.functions import split, explode
DF = sqlContext.createDataFrame([('cat \n\n elephant rat \n rat cat', )], ['word'])
print 'Dataset:'
DF.show()
print '\n\n Trying to do explode: \n'
DFsplit_explode = (
DF
.select(split(DF['word'], ' '))
# .select(explode(DF['word'])) # AnalysisException: u"cannot resolve 'explode(word)' due to data type mismatch: input to function explode should be array or map type, not StringType;"
# .map(explode) # AttributeError: 'PipelinedRDD' object has no attribute 'show'
# .explode() # AttributeError: 'DataFrame' object has no attribute 'explode'
).show()

# Trying without split
print '\n\n Only explode: \n'

DFsplit_explode = (
DF
.select(explode(DF['word'])) # AnalysisException: u"cannot resolve 'explode(word)' due to data type mismatch: input to function explode should be array or map type, not StringType;"
).show()


Please advice

Answer

explode and split are SQL functions. Both operate on SQL Column. split takes a Java regular expression as a second argument. If you want to separate data on arbitrary whitespace you'll need something like this:

df = sqlContext.createDataFrame(
    [('cat \n\n elephant rat \n rat cat', )], ['word']
)

df.select(explode(split(col("word"), "\s+")).alias("word")).show()

## +--------+
## |    word|
## +--------+
## |     cat|
## |elephant|
## |     rat|
## |     rat|
## |     cat|
## +--------+
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