flatmap python

1array = [[1, 2], [3, 4]]
2
3flatArray = [element for element in innerArray for innerArray in array]
4# [1, 2, 3, 4]
5

1
2rdd2=rdd.flatMap(lambda x: x.split(" "))
3for element in rdd2.collect():
4    print(element)
5

1
2from pyspark.sql import SparkSession
3spark = SparkSession.builder.appName('SparkByExamples.com').getOrCreate()
4
5data = ["Project Gutenberg’s",
6        "Alice’s Adventures in Wonderland",
7        "Project Gutenberg’s",
8        "Adventures in Wonderland",
9        "Project Gutenberg’s"]
10rdd=spark.sparkContext.parallelize(data)
11for element in rdd.collect():
12    print(element)
13
14#Flatmap    
15rdd2=rdd.flatMap(lambda x: x.split(" "))
16for element in rdd2.collect():
17    print(element)
18

1
2import pyspark
3from pyspark.sql import SparkSession
4spark = SparkSession.builder.appName('pyspark-by-examples').getOrCreate()
5
6arrayData = [
7        ('James',['Java','Scala'],{'hair':'black','eye':'brown'}),
8        ('Michael',['Spark','Java',None],{'hair':'brown','eye':None}),
9        ('Robert',['CSharp',''],{'hair':'red','eye':''}),
10        ('Washington',None,None),
11        ('Jefferson',['1','2'],{})
12df = spark.createDataFrame(data=arrayData, schema = ['name','knownLanguages','properties'])
13
14from pyspark.sql.functions import explode
15df2 = df.select(df.name,explode(df.knownLanguages))
16df2.printSchema()
17df2.show()
18

1
2data = ["Project Gutenberg’s",
3        "Alice’s Adventures in Wonderland",
4        "Project Gutenberg’s",
5        "Adventures in Wonderland",
6        "Project Gutenberg’s"]
7rdd=spark.sparkContext.parallelize(data)
8for element in rdd.collect():
9    print(element)
10