jayaaiyappan

LambdaSamIntroFn:
    Type: 'AWS::Serverless::Function'
    Properties:
      FunctionName: sam_intro_fn
      Handler: publishtosns.lambda_handler
      Runtime: python3.9
      CodeUri: .
      Description: ''
      MemorySize: 128
      Timeout: 3

jayaaiyappan

import boto3
import urllib.parse

s3 = boto3.client('s3')
sns = boto3.client('sns')

def lambda_handler(event, context):
    source_bucket = event['Records'][0]['s3']['bucket']['name']
    object_key = urllib.parse.unquote_plus(event['Records'][0]['s3']['object']['key'])

jayaaiyappan

LambdaRole:
    Type: 'AWS::IAM::Role'
    Properties:
      AssumeRolePolicyDocument:
        Version: "2012-10-17"
        Statement:
          - Effect: Allow
            Principal:
              Service:
                - lambda.amazonaws.com

jayaaiyappan

AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Description: An AWS Serverless Specification template for aws_sam_intro project
Resources:
  SrcBucket:
    Type: AWS::S3::Bucket
    Properties:
      BucketName: sam-intro-bck
      PublicAccessBlockConfiguration:
        BlockPublicAcls: true

jayaaiyappan

AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Description: An AWS Serverless Specification template for aws_sam_intro project
Resources:
  SrcBucket:
    Type: AWS::S3::Bucket
    Properties:
      BucketName: sam-intro-bck
      PublicAccessBlockConfiguration:
        BlockPublicAcls: true

jayaaiyappan

import org.apache.log4j.{Level, Logger}
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.expressions.Window
import org.apache.spark.sql.functions.{row_number, rank}


object Practice {
    def main(args: Array[String]): Unit = {
      Logger.getLogger("org").setLevel(Level.OFF)

jayaaiyappan

import org.apache.log4j.{Level, Logger}
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.expressions.Window
import org.apache.spark.sql.functions.{row_number, rank}


object Practice {
    def main(args: Array[String]): Unit = {
      Logger.getLogger("org").setLevel(Level.OFF)

jayaaiyappan

import org.apache.log4j.{Level, Logger}
import org.apache.spark.sql.SparkSession

object Practice {
    def main(args: Array[String]): Unit = {
      Logger.getLogger("org").setLevel(Level.OFF)
      val spark = SparkSession.builder().master("local").appName("practice").getOrCreate()

      var datadf = spark.read.csv("C:\\testdata\\sample.txt")
      System.out.println("Initial Data:")

jayaaiyappan

import org.apache.log4j.{Level, Logger}
import org.apache.spark.sql.SparkSession

object Practice {
    def main(args: Array[String]): Unit = {
      Logger.getLogger("org").setLevel(Level.OFF)
      val spark = SparkSession.builder().master("local").appName("practice").getOrCreate()

      var data = spark.sparkContext.textFile("C:\\testdata\\sample.txt")
      System.out.println("Initial Data:")

jayaaiyappan

import org.apache.log4j.{Level, Logger}
import org.apache.spark.sql.SparkSession

object Practice {
    def main(args: Array[String]): Unit = {
      Logger.getLogger("org").setLevel(Level.OFF)
      val spark = SparkSession.builder().master("local").appName("practice").getOrCreate()

      val data = spark.sparkContext.textFile("C:\\testdata\\sample.txt")
      System.out.println("Initial Data:")