SparkSession is not a replacement for a SparkContext but an equivalent of the SQLContext. Just use it use the same way as you used to use SQLContext:

spark.createDataFrame(...)

and if you ever have to access SparkContext use sparkContext attribute:

spark.sparkContext

so if you need SQLContext for backwards compatibility you can:

SQLContext(sparkContext=spark.sparkContext, sparkSession=spark)

getOrCreate is a method on SparkSession.Builder. You need to invoke it by adding the parentheses after:

spark = SparkSession.builder.master("local").appName("Search").config(conf=SparkConf()).getOrCreate()

See for more information: https://spark.apache.org/docs/2.0.1/api/java/org/apache/spark/sql/SparkSession.html

In general, the 'function' object has no attribute error is very common when you are accidentally referencing a function rather than invoking it.

There is no need to use both SparkContext and SparkSession to initialize Spark. Since SparkSession is the newer, recommended way, use that:

spark = SparkSession\
  .builder\
  .config("spark.executor.memory"，"1g")\
  .config("spark.cores.max"，"2")\
  .appName("name")\
  .getOrCreate()

createDataFrame can then be accessed by:

prueba_2 = spark.createDataFrame(...)

If you have to use the underlying SparkContext, you can simply do spark.sparkContext.

You can try this way:

from pyspark.sql import SparkSession

spark = SparkSession.builder \
    .appName('so')\
    .getOrCreate()

sc = spark.sparkContext

map = {'a': 3, 'b': 44}
data = sc.parallelize([(k, v) for k, v in map.items()]).toDF(['A', 'B'])

data.show()

# +---+---+
# |  A|  B|
# +---+---+
# |  a|  3|
# |  b| 44|
# +---+---+

SparkContext doesn't have, SQLContext has:

from pyspark.sql import SQLContext

sqlContext = SQLContext(sc)
sqlContext.createDataFrame(pandas_df)