1. read files

# define schema
from pyspark.sql.types import StructType,StructField
from pyspark.sql.types import DoubleType,StringType,IntegerType

schema = StructType([ 
      StructField('x1' = StringType()),
      StructField('x2' = DoubleType())
])

# read csv
sel_col = ['x1']
xs = spark.read.schema(schema)\
     .option('header','false')\
     .csv(path.format(s3_buckect),sep = '\\t')\
     .select(*sel_col)

2. add columns

from pyspark.sql.window import window as W
from pyspark.sql import functions as F

# add columns
df = df.withColumn('new_col',F.monotonically_increasing_id())\
       .withColumn('row_number',F.row_number().over(windowSpec))

# rename columns
df = df.withColumnRenamed('X1','newname')

# sort/drop
df.sort('x1').drop('x1')

3. join tables

dfx = df1.join(df2, df1.col1 == df2.col2, how ='inner')