Langkah 1 Buat Aliran Input dan Output

Instal Python dan pip.

Untuk informasi tentang menginstal Python, lihat situs web Python.

Anda dapat menginstal dependensi menggunakan pip. Untuk informasi tentang menginstal pip, lihat Penginstalan di situs web pip.

Jalankan kode Phyton berikut. Kode ini melakukan hal berikut:

 
import json
from pprint import pprint
import random
import time
import boto3

STREAM_NAME = "ExampleInputStream"


def get_hotspot(field, spot_size):
    hotspot = {
        "left": field["left"] + random.random() * (field["width"] - spot_size),
        "width": spot_size,
        "top": field["top"] + random.random() * (field["height"] - spot_size),
        "height": spot_size,
    }
    return hotspot


def get_record(field, hotspot, hotspot_weight):
    rectangle = hotspot if random.random() < hotspot_weight else field
    point = {
        "x": rectangle["left"] + random.random() * rectangle["width"],
        "y": rectangle["top"] + random.random() * rectangle["height"],
        "is_hot": "Y" if rectangle is hotspot else "N",
    }
    return {"Data": json.dumps(point), "PartitionKey": "partition_key"}


def generate(
    stream_name, field, hotspot_size, hotspot_weight, batch_size, kinesis_client
):
    """
    Generates points used as input to a hotspot detection algorithm.
    With probability hotspot_weight (20%), a point is drawn from the hotspot;
    otherwise, it is drawn from the base field. The location of the hotspot
    changes for every 1000 points generated.
    """
    points_generated = 0
    hotspot = None
    while True:
        if points_generated % 1000 == 0:
            hotspot = get_hotspot(field, hotspot_size)
        records = [
            get_record(field, hotspot, hotspot_weight) for _ in range(batch_size)
        ]
        points_generated += len(records)
        pprint(records)
        kinesis_client.put_records(StreamName=stream_name, Records=records)

        time.sleep(0.1)


if __name__ == "__main__":
    generate(
        stream_name=STREAM_NAME,
        field={"left": 0, "width": 10, "top": 0, "height": 10},
        hotspot_size=1,
        hotspot_weight=0.2,
        batch_size=10,
        kinesis_client=boto3.client("kinesis"),
    )