Spark DataFrame Limit Function Takes Too Much Time to Show












1












$begingroup$


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










share|improve this question









$endgroup$

















    1












    $begingroup$


    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










    share|improve this question









    $endgroup$















      1












      1








      1





      $begingroup$


      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










      share|improve this question









      $endgroup$




      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







      bigdata apache-spark pyspark






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked 14 hours ago









      Taimur IslamTaimur Islam

      167211




      167211






















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