Serverless APIs

Streaming Data with AWS Kinesis and Lambda

Maksim Pecherskiy

Data Engineer

Last lesson

Giving access to data

Simple API

Add a trigger

Test your new API

Our first API

API parameters

Sample request

https://.../speederReporterApi?date=20200620

Sample event

{
  "queryStringParameters": {
    "date": "20200620"
  },
  "isBase64Encoded": false
}

Lambda handler

import json, boto3
import awswrangler as wr
import pandas as pd

session = boto3.Session(aws_access_key_id = AWS_KEY, 
                        aws_secret_access_key = AWS_SECRET, 
                        region_name="us-east-1")

Lambda handler

def lambda_handler(event, context):
    filter_date = event['queryStringParameters']['date']

    df = wr.s3.read_csv(
        f"s3://sd-vehicle-data/speeders_daily/{filter_date}.csv", 
        boto3_session=session, 
        delimiter=" ")

Respond with data

def lambda_handler(event, context):
    ...
    return {
        'statusCode': 200,
        'headers': {
            "content-type" : "application/json"
        },
        'body': df.to_json()
    }

Live response

https://.../default/speederReporterApi?date=20200621

[
  {
      "record_id":"939ed1d1-1740-420c-8906-445278573c7f",
      "timestamp":"4:25:06.000",
      "vin":"4FTEX4944AK844294",
      "lon":106.9447146,
      "lat":-6.3385652,
      "speed":25
  },
  {
      "record_id":"f29a5b3d-d0fa-43c0-9e1a-e2a5cdb8be7a",
      ...
  },

  ...
]

Trigger another Lambda

def trigger_recalc():
  lambda_client = boto3.client("s3", 
                            aws_access_key_id = AWS_KEY, 
                            aws_secret_access_key = AWS_SECRET, 
                            region_name = 'us-east-1')

def lambda_handler(event, context):
  ...

speederAggregator ARN

Invoke

def trigger_recalc():
  ...
  lambda_client.invoke(
    FunctionName='arn:aws:lambda:us-east-1:458913182630:function:speederAggregator',
    InvocationType='Event', # (or RequestResponse)
  )

Review

Let's practice!

Streaming Data with AWS Kinesis and Lambda