How to create dataframe from list in Spark SQL?
here is how -
from pyspark.sql.types import *
cSchema = StructType([StructField("WordList", ArrayType(StringType()))])
# notice extra square brackets around each element of list
test_list = [['Hello', 'world']], [['I', 'am', 'fine']]
df = spark.createDataFrame(test_list,schema=cSchema)
You should use list of Row objects([Row]) to create data frame.
from pyspark.sql import Row
spark.createDataFrame(list(map(lambda x: Row(words=x), test_list)))
i had to work with multiple columns and types - the example below has one string column and one integer column. A slight adjustment to Pushkr's code (above) gives:
from pyspark.sql.types import *
cSchema = StructType([StructField("Words", StringType())\
,StructField("total", IntegerType())])
test_list = [['Hello', 1], ['I am fine', 3]]
df = spark.createDataFrame(test_list,schema=cSchema)
output:
df.show()
+---------+-----+
| Words|total|
+---------+-----+
| Hello| 1|
|I am fine| 3|
+---------+-----+