Numpy and other library dependencies for Spark application on Kubernetes












1















I am running pyspark application, v2.4.0, on Kubernetes, my spark application depends on numpy and tensorflow modules, please suggest the way to add these dependencies to Spark executors.



I have checked the documentation, we can include the remote dependencies using --py-files, --jars etc. but nothing mentioned about library dependencies.










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    1















    I am running pyspark application, v2.4.0, on Kubernetes, my spark application depends on numpy and tensorflow modules, please suggest the way to add these dependencies to Spark executors.



    I have checked the documentation, we can include the remote dependencies using --py-files, --jars etc. but nothing mentioned about library dependencies.










    share|improve this question

























      1












      1








      1


      1






      I am running pyspark application, v2.4.0, on Kubernetes, my spark application depends on numpy and tensorflow modules, please suggest the way to add these dependencies to Spark executors.



      I have checked the documentation, we can include the remote dependencies using --py-files, --jars etc. but nothing mentioned about library dependencies.










      share|improve this question














      I am running pyspark application, v2.4.0, on Kubernetes, my spark application depends on numpy and tensorflow modules, please suggest the way to add these dependencies to Spark executors.



      I have checked the documentation, we can include the remote dependencies using --py-files, --jars etc. but nothing mentioned about library dependencies.







      apache-spark kubernetes






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      share|improve this question











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      share|improve this question










      asked Nov 13 '18 at 9:48









      Lakshman BattiniLakshman Battini

      1,107315




      1,107315
























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          Found the way to add the library dependencies to Spark applications on K8S, thought of sharing it here.



          Mention the required dependencies installation commands in Dockerfile and rebuild the spark image, when we submit the spark job, new container will be instantiated with the dependencies as well.



          Dokerfile (/{spark_folder_path}/resource-managers/kubernetes/docker/src/main/dockerfiles/spark/bindings/python/Dockerfile) contents:



          RUN apk add --no-cache python && 
          apk add --no-cache python3 &&
          python -m ensurepip &&
          python3 -m ensurepip &&
          # We remove ensurepip since it adds no functionality since pip is
          # installed on the image and it just takes up 1.6MB on the image
          rm -r /usr/lib/python*/ensurepip &&
          pip install --upgrade pip setuptools &&
          # You may install with python3 packages by using pip3.6
          pip install numpy &&
          # Removed the .cache to save space
          rm -r /root/.cache





          share|improve this answer























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            Found the way to add the library dependencies to Spark applications on K8S, thought of sharing it here.



            Mention the required dependencies installation commands in Dockerfile and rebuild the spark image, when we submit the spark job, new container will be instantiated with the dependencies as well.



            Dokerfile (/{spark_folder_path}/resource-managers/kubernetes/docker/src/main/dockerfiles/spark/bindings/python/Dockerfile) contents:



            RUN apk add --no-cache python && 
            apk add --no-cache python3 &&
            python -m ensurepip &&
            python3 -m ensurepip &&
            # We remove ensurepip since it adds no functionality since pip is
            # installed on the image and it just takes up 1.6MB on the image
            rm -r /usr/lib/python*/ensurepip &&
            pip install --upgrade pip setuptools &&
            # You may install with python3 packages by using pip3.6
            pip install numpy &&
            # Removed the .cache to save space
            rm -r /root/.cache





            share|improve this answer




























              0














              Found the way to add the library dependencies to Spark applications on K8S, thought of sharing it here.



              Mention the required dependencies installation commands in Dockerfile and rebuild the spark image, when we submit the spark job, new container will be instantiated with the dependencies as well.



              Dokerfile (/{spark_folder_path}/resource-managers/kubernetes/docker/src/main/dockerfiles/spark/bindings/python/Dockerfile) contents:



              RUN apk add --no-cache python && 
              apk add --no-cache python3 &&
              python -m ensurepip &&
              python3 -m ensurepip &&
              # We remove ensurepip since it adds no functionality since pip is
              # installed on the image and it just takes up 1.6MB on the image
              rm -r /usr/lib/python*/ensurepip &&
              pip install --upgrade pip setuptools &&
              # You may install with python3 packages by using pip3.6
              pip install numpy &&
              # Removed the .cache to save space
              rm -r /root/.cache





              share|improve this answer


























                0












                0








                0







                Found the way to add the library dependencies to Spark applications on K8S, thought of sharing it here.



                Mention the required dependencies installation commands in Dockerfile and rebuild the spark image, when we submit the spark job, new container will be instantiated with the dependencies as well.



                Dokerfile (/{spark_folder_path}/resource-managers/kubernetes/docker/src/main/dockerfiles/spark/bindings/python/Dockerfile) contents:



                RUN apk add --no-cache python && 
                apk add --no-cache python3 &&
                python -m ensurepip &&
                python3 -m ensurepip &&
                # We remove ensurepip since it adds no functionality since pip is
                # installed on the image and it just takes up 1.6MB on the image
                rm -r /usr/lib/python*/ensurepip &&
                pip install --upgrade pip setuptools &&
                # You may install with python3 packages by using pip3.6
                pip install numpy &&
                # Removed the .cache to save space
                rm -r /root/.cache





                share|improve this answer













                Found the way to add the library dependencies to Spark applications on K8S, thought of sharing it here.



                Mention the required dependencies installation commands in Dockerfile and rebuild the spark image, when we submit the spark job, new container will be instantiated with the dependencies as well.



                Dokerfile (/{spark_folder_path}/resource-managers/kubernetes/docker/src/main/dockerfiles/spark/bindings/python/Dockerfile) contents:



                RUN apk add --no-cache python && 
                apk add --no-cache python3 &&
                python -m ensurepip &&
                python3 -m ensurepip &&
                # We remove ensurepip since it adds no functionality since pip is
                # installed on the image and it just takes up 1.6MB on the image
                rm -r /usr/lib/python*/ensurepip &&
                pip install --upgrade pip setuptools &&
                # You may install with python3 packages by using pip3.6
                pip install numpy &&
                # Removed the .cache to save space
                rm -r /root/.cache






                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Nov 17 '18 at 10:19









                Lakshman BattiniLakshman Battini

                1,107315




                1,107315






























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