Pyspark Split DataFrame berdasarkan baris
from pyspark.sql.window import Window
from pyspark.sql.functions import monotonically_increasing_id, ntile
values = [(str(i),) for i in range(100)]
df = spark.createDataFrame(values, ('value',))
def split_by_row_index(df, num_partitions=4):
# Let's assume you don't have a row_id column that has the row order
t = df.withColumn('_row_id', monotonically_increasing_id())
# Using ntile() because monotonically_increasing_id is discontinuous across partitions
t = t.withColumn('_partition', ntile(num_partitions).over(Window.orderBy(t._row_id)))
return [t.filter(t._partition == i+1).drop('_row_id', '_partition') for i in range(partitions)]
[i.collect() for i in split_by_row_index(df)]
Glorious Gnu