collect

Returns all the records in the DataFrame as a list of Row.

Syntax

collect()

Returns

list: A list of Row objects, each representing a row in the DataFrame.

Notes

This method should only be used if the resulting list is expected to be small, as all the data is loaded into the driver's memory.

Examples

df = spark.createDataFrame([(14, "Tom"), (23, "Alice"), (16, "Bob")], ["age", "name"])
df.collect()
# [Row(age=14, name='Tom'), Row(age=23, name='Alice'), Row(age=16, name='Bob')]

df.filter(df.age > 15).collect()
# [Row(age=23, name='Alice'), Row(age=16, name='Bob')]

df.select("name").collect()
# [Row(name='Tom'), Row(name='Alice'), Row(name='Bob')]

from pyspark.sql.functions import upper
df.select(upper(df.name)).collect()
# [Row(upper(name)='TOM'), Row(upper(name)='ALICE'), Row(upper(name)='BOB')]

rows = df.collect()
[row["name"] for row in rows]
# ['Tom', 'Alice', 'Bob']

[row.asDict() for row in rows]
# [{'age': 14, 'name': 'Tom'}, {'age': 23, 'name': 'Alice'}, {'age': 16, 'name': 'Bob'}]