I\'m using python on Spark and would like to get a csv into a dataframe.
The documentation for Spark SQL strangely does not provide explanations for CSV as a source.
Following Spark 2.0, it is recommended to use a Spark Session:
from pyspark.sql import SparkSession
from pyspark.sql import Row
# Create a SparkSession
spark = SparkSession \
.builder \
.appName("basic example") \
.config("spark.some.config.option", "some-value") \
.getOrCreate()
def mapper(line):
fields = line.split(',')
return Row(ID=int(fields[0]), field1=str(fields[1].encode("utf-8")), field2=int(fields[2]), field3=int(fields[3]))
lines = spark.sparkContext.textFile("file.csv")
df = lines.map(mapper)
# Infer the schema, and register the DataFrame as a table.
schemaDf = spark.createDataFrame(df).cache()
schemaDf.createOrReplaceTempView("tablename")