Spark DataFrame "Limit" function takes too much time to display result

Question

import pyspark
from pyspark.sql import SparkSession
from pyspark.conf import SparkConf
import findspark
from pyspark.sql.functions import countDistinct
spark = SparkSession.builder \
.master("local[*]") \
.appName("usres mobile related information analysis") \
.config("spark.submit.deployMode", "client") \
.config("spark.executor.memory","3g") \
.config("spark.driver.maxResultSize", "1g") \
.config("spark.executor.pyspark.memory","3g") \
.enableHiveSupport() \
.getOrCreate()

handset_info = ora_tmp.select('some_value','some_value','some_value','some_value','some_value','some_value','some_value')

I configure the spark with 3gb execution memory and 3gb execution pyspark memory. My Database has more than 70 Million row. Show I call the

 handset_info.show()

method it is showing the top 20 row in between 2-5 second. But when i try to run the following code

mobile_info_df = handset_info.limit(30)
mobile_info_df.show()

to show the top 30 rows the it takes too much time (3-4 hour). Is it logical to take that much time. Is there any problem in my configuration. Configuration of my laptop is:

• Core i7 (4 core) laptop with 8gb ram

Answer 1

The reason is the way limit and the show is implemented under the hood. Show just reads the first 20 (first n) rows, which limit reads the whole data before showing it. Refer this answer on StackOverflow - link