# How take a random row from a PySpark DataFrame?

How can I get a random row from a PySpark DataFrame? I only see the method sample() which takes a fraction as parameter. Setting this fraction to 1/numberOfRows leads to random results, where sometimes I won't get any row.

On RRD there is a method takeSample() that takes as a parameter the number of elements you want the sample to contain. I understand that this might be slow, as you have to count each partition, but is there a way to get something like this on a DataFrame?

## Answers

You can simply call takeSample on a RDD:

df = sqlContext.createDataFrame( [(1, "a"), (2, "b"), (3, "c"), (4, "d")], ("k", "v")) df.rdd.takeSample(False, 1, seed=0) ## [Row(k=3, v='c')]

If you don't want to collect you can simply take a higher fraction and limit:

df.sample(False, 0.1, seed=0).limit(1)