sbin/start-master.sh
sbin/start-slave.sh spark://192.168.0.38:7077
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On Fri, 27 Mar 2020 at 05:59, Wenchen Fan <cloud0...@gmail.com> wrote:
> Your Spark cluster, spark://192.168.0.38:7077, how is it deployed if you
> just include Spark dependency in IntelliJ?
>
> On Fri, Mar 27, 2020 at 1:54 PM Zahid Rahman <zahidr1...@gmail.com> wrote:
>
>> I have configured in IntelliJ as external jars
>> spark-3.0.0-preview2-bin-hadoop2.7/jar
>>
>> not pulling anything from maven.
>>
>> Backbutton.co.uk
>> ¯\_(ツ)_/¯
>> ♡۶Java♡۶RMI ♡۶
>> Make Use Method {MUM}
>> makeuse.org
>> <http://www.backbutton.co.uk>
>>
>>
>> On Fri, 27 Mar 2020 at 05:45, Wenchen Fan <cloud0...@gmail.com> wrote:
>>
>>> Which Spark/Scala version do you use?
>>>
>>> On Fri, Mar 27, 2020 at 1:24 PM Zahid Rahman <zahidr1...@gmail.com>
>>> wrote:
>>>
>>>>
>>>> with the following sparksession configuration
>>>>
>>>> val spark = SparkSession.builder().master("local[*]").appName("Spark
>>>> Session take").getOrCreate();
>>>>
>>>> this line works
>>>>
>>>> flights.filter(flight_row => flight_row.ORIGIN_COUNTRY_NAME !=
>>>> "Canada").map(flight_row => flight_row).take(5)
>>>>
>>>>
>>>> however if change the master url like so, with the ip address then the
>>>> following error is produced by the position of .take(5)
>>>>
>>>> val spark =
>>>> SparkSession.builder().master("spark://192.168.0.38:7077").appName("Spark
>>>> Session take").getOrCreate();
>>>>
>>>>
>>>> 20/03/27 05:15:20 WARN TaskSetManager: Lost task 0.0 in stage 1.0 (TID
>>>> 1, 192.168.0.38, executor 0): java.lang.ClassCastException: cannot assign
>>>> instance of java.lang.invoke.SerializedLambda to field
>>>> org.apache.spark.rdd.MapPartitionsRDD.f of type scala.Function3 in instance
>>>> of org.apache.spark.rdd.MapPartitionsRDD
>>>>
>>>> BUT if I remove take(5) or change the position of take(5) or insert an
>>>> extra take(5) as illustrated in code then it works. I don't see why the
>>>> position of take(5) should cause such an error or be caused by changing the
>>>> master url
>>>>
>>>> flights.take(5).filter(flight_row => flight_row.ORIGIN_COUNTRY_NAME !=
>>>> "Canada").map(flight_row => flight_row).take(5)
>>>>
>>>> flights.take(5)
>>>>
>>>> flights
>>>> .take(5)
>>>> .filter(flight_row => flight_row.ORIGIN_COUNTRY_NAME != "Canada")
>>>> .map(fr => flight(fr.DEST_COUNTRY_NAME, fr.ORIGIN_COUNTRY_NAME,fr.count
>>>> + 5))
>>>> flights.show(5)
>>>>
>>>>
>>>> complete code if you wish to replicate it.
>>>>
>>>> import org.apache.spark.sql.SparkSession
>>>>
>>>> object sessiontest {
>>>>
>>>> // define specific data type class then manipulate it using the filter
>>>> and map functions
>>>> // this is also known as an Encoder
>>>> case class flight (DEST_COUNTRY_NAME: String,
>>>> ORIGIN_COUNTRY_NAME:String,
>>>> count: BigInt)
>>>>
>>>>
>>>> def main(args:Array[String]): Unit ={
>>>>
>>>> val spark =
>>>> SparkSession.builder().master("spark://192.168.0.38:7077").appName("Spark
>>>> Session take").getOrCreate();
>>>>
>>>> import spark.implicits._
>>>> val flightDf =
>>>> spark.read.parquet("/data/flight-data/parquet/2010-summary.parquet/")
>>>> val flights = flightDf.as[flight]
>>>>
>>>> flights.take(5).filter(flight_row => flight_row.ORIGIN_COUNTRY_NAME !=
>>>> "Canada").map(flight_row => flight_row).take(5)
>>>>
>>>> flights.take(5)
>>>>
>>>> flights
>>>> .take(5)
>>>> .filter(flight_row => flight_row.ORIGIN_COUNTRY_NAME != "Canada")
>>>> .map(fr => flight(fr.DEST_COUNTRY_NAME,
>>>> fr.ORIGIN_COUNTRY_NAME,fr.count + 5))
>>>> flights.show(5)
>>>>
>>>> } // main
>>>> }
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> Backbutton.co.uk
>>>> ¯\_(ツ)_/¯
>>>> ♡۶Java♡۶RMI ♡۶
>>>> Make Use Method {MUM}
>>>> makeuse.org
>>>> <http://www.backbutton.co.uk>
>>>>
>>>
