lab88_diagram

In this lab a DynamoDB table will be created and some item put in. Then S3 bucket will be created as destination for files generated by a Lambda function.

Lab Details

  1. Services covered
  2. Lab description
  3. Lab date
  4. Prerequisites
  5. Lab steps
  6. Lab files
  7. Acknowledgements

Services Covered

  • dynamodb¬†DynamoDB
  • lambda¬†Lambda

Lab description

In this lab a DynamoDB table will be created and some item put in. Then S3 bucket will be created as destination for files generated by a Lambda function. That function will scan the table, and for every item in the table it’ll read it and then eventually save it to a text file into the bucket. Lambda will be triggered whenever a new item or a change to an item occurs.

  • Create a Lambda Function
  • Create S3 bucket
  • Create DynamoDB Table
  • Create Trigger for table

Lab date

04-10-2021


Prerequisites

  • AWS account

Lab steps

  1. Create DynamoDB Table. Create a Partition key called id of type string. Add couple of items to the table, with additional attributes.
  2. Create a S3 Bucket for the incoming files. Note buckets name.
  3. Create a Lambda Function with Python as runtime. [Code]() will scan the table and save all items as a text file to the S3 bucket. Fill the buckets and table names with your values.
    import boto3
    import json
    from botocore.exceptions import ClientError
    def lambda_handler(event, context):
       data = []
       TableName = "whizlabs_dynamodb_table"
       try:
           s3 = boto3.resource('s3', region_name='us-east-1')
           ddbclient = boto3.client('dynamodb', region_name='us-east-1')
           response = ddbclient.list_tables()
           mytables = response['TableNames']
    
           if TableName in mytables:
               allitems = ddbclient.scan(TableName= TableName)
               for item in allitems['Items']:
                   item_list = {}
                   allKeys = item.keys()
                   for k in allKeys:
                       value = list(item[k].values())[0]
                       item_list[k] = str(value)
                   data.append(item_list)
               data = json.dumps(data)
               responses3 = s3.Object('whizlabs.38916.94360902', 'data.txt').put(Body=data)
               print("Completed Upload to S3")
           print("Lambda run completed")
           return {
                   'statusCode': 200,
                   'body': json.dumps("success")
                   }
       except ClientError as e:
               print("Detailed error: ",e)
               return {
                       'statusCode': 500,
                       'body': json.dumps("error")
                       }
       except Exception as e:
               print("Detailed error: ",e)
               return {
                       'statusCode': 500,
                       'body': json.dumps("error")
                       }
  4. Add Trigger to the DynamoDB Table. Choose your table, under Trigger section choose Create trigger and from drop-down menu Choose Existing Lambda Function. Use the function created earlier, BatchSize set to 1 and EnableTrigger checked in.

  5. Add new Items to the table to trigger the Lambda Function. This should produce a data.txt file to the S3 bucket.

    Lab files


Acknowledgements

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