Thanks a lot Khalid for replying.
I have one question though. The approach tou showed needs an understanding
on python side before hand about the data type of columns of dataframe. Can
we implement a generic approach where this info is not required and we just
have the java dataframe as input on python side?
Also one more question, in my use case I will sending a dataframe from java
to python and then on python side there will be some transformation done on
the dataframe(including using python udfs) but no actions will be performed
here and then will send it back to java where actions will be performed. So
also wanted to ask if this is feasible and if yes do we need to send some
special jars to executors so that it can execute udfs on the dataframe.
On Wed, 31 Mar 2021 at 3:37 AM, Khalid Mammadov <khalidmammad...@gmail.com>
wrote:
> Hi Aditya,
>
>
> I think you original question was as how to convert a DataFrame from Spark
> session created on Java/Scala to a DataFrame on a Spark session created
> from Python(PySpark).
>
> So, as I have answered on your SO question:
>
>
> There is a missing call to *entry_point* before calling getDf() in your
> code
>
> So, try this :
>
> app = gateway.entry_point
> j_df = app.getDf()
>
> Additionally, I have create working copy using Python and Scala (hope you
> dont mind) below that shows how on Scala side py4j gateway is started with
> Spark session and a sample DataFrame and on Python side I have accessed
> that DataFrame and converted to Python List[Tuple] before converting back
> to a DataFrame for a Spark session on Python side:
>
> *Python:*
>
> from py4j.java_gateway import JavaGatewayfrom pyspark.sql import
> SparkSessionfrom pyspark.sql.types import StructType, IntegerType, StructField
> if __name__ == '__main__':
> gateway = JavaGateway()
>
> spark_app = gateway.entry_point
> df = spark_app.df()
>
> # Note "apply" method here comes from Scala's companion object to access
> elements of an array
> df_to_list_tuple = [(int(i.apply(0)), int(i.apply(1))) for i in df]
>
> spark = (SparkSession
> .builder
> .appName("My PySpark App")
> .getOrCreate())
>
> schema = StructType([
> StructField("a", IntegerType(), True),
> StructField("b", IntegerType(), True)])
>
> df = spark.createDataFrame(df_to_list_tuple, schema)
>
> df.show()
>
>
> *Scala:*
>
> import java.nio.file.{Path, Paths}
> import org.apache.spark.sql.SparkSessionimport py4j.GatewayServer
> object SparkApp {
> val myFile: Path = Paths.get(System.getProperty("user.home") +
> "/dev/sample_data/games.csv")
> val spark = SparkSession.builder()
> .master("local[*]")
> .appName("My app")
> .getOrCreate()
>
> val df = spark
> .read
> .option("header", "True")
> .csv(myFile.toString)
> .collect()
>
> }
> object Py4JServerApp extends App {
>
>
> val server = new GatewayServer(SparkApp)
> server.start()
>
> print("Started and running...")
> }
>
>
>
>
>
> Regards,
> Khalid
>
>
> On 30/03/2021 07:57, Aditya Singh wrote:
>
> Hi Sean,
>
> Thanks a lot for replying and apologies for the late reply(I somehow
> missed this mail before) but I am under the impression that passing the
> py4j.java_gateway.JavaGateway object lets the pyspark access the spark
> context created on the java side.
> My use case is exactly what you mentioned in the last email. I want to
> access the same spark session across java and pyspark. So how can we share
> the spark context and in turn spark session, across java and pyspark.
>
> Regards,
> Aditya
>
> On Fri, 26 Mar 2021 at 6:49 PM, Sean Owen <sro...@gmail.com> wrote:
>
>> The problem is that both of these are not sharing a SparkContext as far
>> as I can see, so there is no way to share the object across them, let alone
>> languages.
>>
>> You can of course write the data from Java, read it from Python.
>>
>> In some hosted Spark products, you can access the same session from two
>> languages and register the DataFrame as a temp view in Java, then access it
>> in Pyspark.
>>
>>
>> On Fri, Mar 26, 2021 at 8:14 AM Aditya Singh <aditya.singh9...@gmail.com>
>> wrote:
>>
>>> Hi All,
>>>
>>> I am a newbie to spark and trying to pass a java dataframe to pyspark.
>>> Foloowing link has details about what I am trying to do:-
>>>
>>>
>>> https://stackoverflow.com/questions/66797382/creating-pysparks-spark-context-py4j-java-gateway-object
>>>
>>> Can someone please help me with this?
>>>
>>> Thanks,
>>>
>>
