for Python (Boto3) を使用した Managed Service SDK for Apache Flink の例

class KinesisAnalyticsApplicationV2:
    """Encapsulates Kinesis Data Analytics application functions."""

    def __init__(self, analytics_client):
        """
        :param analytics_client: A Boto3 Kinesis Data Analytics v2 client.
        """
        self.analytics_client = analytics_client
        self.name = None
        self.arn = None
        self.version_id = None
        self.create_timestamp = None


    def add_input(self, input_prefix, stream_arn, input_schema):
        """
        Adds an input stream to the application. The input stream data is mapped
        to an in-application stream that can be processed by your code running in
        Kinesis Data Analytics.

        :param input_prefix: The prefix prepended to in-application input stream names.
        :param stream_arn: The ARN of the input stream.
        :param input_schema: A schema that maps the data in the input stream to the
                             runtime environment. This can be automatically generated
                             by using `discover_input_schema` or you can create it
                             yourself.
        :return: Metadata about the newly added input.
        """
        try:
            response = self.analytics_client.add_application_input(
                ApplicationName=self.name,
                CurrentApplicationVersionId=self.version_id,
                Input={
                    "NamePrefix": input_prefix,
                    "KinesisStreamsInput": {"ResourceARN": stream_arn},
                    "InputSchema": input_schema,
                },
            )
            self.version_id = response["ApplicationVersionId"]
            logger.info("Add input stream %s to application %s.", stream_arn, self.name)
        except ClientError:
            logger.exception(
                "Couldn't add input stream %s to application %s.", stream_arn, self.name
            )
            raise
        else:
            return response

class KinesisAnalyticsApplicationV2:
    """Encapsulates Kinesis Data Analytics application functions."""

    def __init__(self, analytics_client):
        """
        :param analytics_client: A Boto3 Kinesis Data Analytics v2 client.
        """
        self.analytics_client = analytics_client
        self.name = None
        self.arn = None
        self.version_id = None
        self.create_timestamp = None


    def add_output(self, in_app_stream_name, output_arn):
        """
        Adds an output stream to the application. Kinesis Data Analytics maps data
        from the specified in-application stream to the output stream.

        :param in_app_stream_name: The name of the in-application stream to map
                                   to the output stream.
        :param output_arn: The ARN of the output stream.
        :return: A list of metadata about the output resources currently assigned
                 to the application.
        """
        try:
            response = self.analytics_client.add_application_output(
                ApplicationName=self.name,
                CurrentApplicationVersionId=self.version_id,
                Output={
                    "Name": in_app_stream_name,
                    "KinesisStreamsOutput": {"ResourceARN": output_arn},
                    "DestinationSchema": {"RecordFormatType": "JSON"},
                },
            )
            outputs = response["OutputDescriptions"]
            self.version_id = response["ApplicationVersionId"]
            logging.info(
                "Added output %s to %s, which now has %s outputs.",
                output_arn,
                self.name,
                len(outputs),
            )
        except ClientError:
            logger.exception("Couldn't add output %s to %s.", output_arn, self.name)
            raise
        else:
            return outputs

class KinesisAnalyticsApplicationV2:
    """Encapsulates Kinesis Data Analytics application functions."""

    def __init__(self, analytics_client):
        """
        :param analytics_client: A Boto3 Kinesis Data Analytics v2 client.
        """
        self.analytics_client = analytics_client
        self.name = None
        self.arn = None
        self.version_id = None
        self.create_timestamp = None


    def create(self, app_name, role_arn, env="SQL-1_0"):
        """
        Creates a Kinesis Data Analytics application.

        :param app_name: The name of the application.
        :param role_arn: The ARN of a role that can be assumed by Kinesis Data
                         Analytics and grants needed permissions.
        :param env: The runtime environment of the application, such as SQL. Code
                    uploaded to the application runs in this environment.
        :return: Metadata about the newly created application.
        """
        try:
            response = self.analytics_client.create_application(
                ApplicationName=app_name,
                RuntimeEnvironment=env,
                ServiceExecutionRole=role_arn,
            )
            details = response["ApplicationDetail"]
            self._update_details(details)
            logger.info("Application %s created.", app_name)
        except ClientError:
            logger.exception("Couldn't create application %s.", app_name)
            raise
        else:
            return details

class KinesisAnalyticsApplicationV2:
    """Encapsulates Kinesis Data Analytics application functions."""

    def __init__(self, analytics_client):
        """
        :param analytics_client: A Boto3 Kinesis Data Analytics v2 client.
        """
        self.analytics_client = analytics_client
        self.name = None
        self.arn = None
        self.version_id = None
        self.create_timestamp = None


    def delete(self):
        """
        Deletes an application.
        """
        try:
            self.analytics_client.delete_application(
                ApplicationName=self.name, CreateTimestamp=self.create_timestamp
            )
            logger.info("Deleted application %s.", self.name)
        except ClientError:
            logger.exception("Couldn't delete application %s.", self.name)
            raise

class KinesisAnalyticsApplicationV2:
    """Encapsulates Kinesis Data Analytics application functions."""

    def __init__(self, analytics_client):
        """
        :param analytics_client: A Boto3 Kinesis Data Analytics v2 client.
        """
        self.analytics_client = analytics_client
        self.name = None
        self.arn = None
        self.version_id = None
        self.create_timestamp = None


    def describe(self, name):
        """
        Gets metadata about an application.

        :param name: The name of the application to look up.
        :return: Metadata about the application.
        """
        try:
            response = self.analytics_client.describe_application(ApplicationName=name)
            details = response["ApplicationDetail"]
            self._update_details(details)
            logger.info("Got metadata for application %s.", name)
        except ClientError:
            logger.exception("Couldn't get metadata for application %s.", name)
            raise
        else:
            return details

class KinesisAnalyticsApplicationV2:
    """Encapsulates Kinesis Data Analytics application functions."""

    def __init__(self, analytics_client):
        """
        :param analytics_client: A Boto3 Kinesis Data Analytics v2 client.
        """
        self.analytics_client = analytics_client
        self.name = None
        self.arn = None
        self.version_id = None
        self.create_timestamp = None


    def describe_snapshot(self, application_name, snapshot_name):
        """
        Gets metadata about a previously saved application snapshot.

        :param application_name: The name of the application.
        :param snapshot_name: The name of the snapshot.
        :return: Metadata about the snapshot.
        """
        try:
            response = self.analytics_client.describe_application_snapshot(
                ApplicationName=application_name, SnapshotName=snapshot_name
            )
            snapshot = response["SnapshotDetails"]
            logger.info(
                "Got metadata for snapshot %s of application %s.",
                snapshot_name,
                application_name,
            )
        except ClientError:
            logger.exception(
                "Couldn't get metadata for snapshot %s of application %s.",
                snapshot_name,
                application_name,
            )
            raise
        else:
            return snapshot

class KinesisAnalyticsApplicationV2:
    """Encapsulates Kinesis Data Analytics application functions."""

    def __init__(self, analytics_client):
        """
        :param analytics_client: A Boto3 Kinesis Data Analytics v2 client.
        """
        self.analytics_client = analytics_client
        self.name = None
        self.arn = None
        self.version_id = None
        self.create_timestamp = None


    def discover_input_schema(self, stream_arn, role_arn):
        """
        Discovers a schema that maps data in a stream to a format that is usable by
        an application's runtime environment. The stream must be active and have
        enough data moving through it for the service to sample. The returned schema
        can be used when you add the stream as an input to the application or you can
        write your own schema.

        :param stream_arn: The ARN of the stream to map.
        :param role_arn: A role that lets Kinesis Data Analytics read from the stream.
        :return: The discovered schema of the data in the input stream.
        """
        try:
            response = self.analytics_client.discover_input_schema(
                ResourceARN=stream_arn,
                ServiceExecutionRole=role_arn,
                InputStartingPositionConfiguration={"InputStartingPosition": "NOW"},
            )
            schema = response["InputSchema"]
            logger.info("Discovered input schema for stream %s.", stream_arn)
        except ClientError:
            logger.exception(
                "Couldn't discover input schema for stream %s.", stream_arn
            )
            raise
        else:
            return schema

class KinesisAnalyticsApplicationV2:
    """Encapsulates Kinesis Data Analytics application functions."""

    def __init__(self, analytics_client):
        """
        :param analytics_client: A Boto3 Kinesis Data Analytics v2 client.
        """
        self.analytics_client = analytics_client
        self.name = None
        self.arn = None
        self.version_id = None
        self.create_timestamp = None


    def start(self, input_id):
        """
        Starts an application. After the application is running, it reads from the
        specified input stream and runs the application code on the incoming data.

        :param input_id: The ID of the input to read.
        """
        try:
            self.analytics_client.start_application(
                ApplicationName=self.name,
                RunConfiguration={
                    "SqlRunConfigurations": [
                        {
                            "InputId": input_id,
                            "InputStartingPositionConfiguration": {
                                "InputStartingPosition": "NOW"
                            },
                        }
                    ]
                },
            )
            logger.info("Started application %s.", self.name)
        except ClientError:
            logger.exception("Couldn't start application %s.", self.name)
            raise

class KinesisAnalyticsApplicationV2:
    """Encapsulates Kinesis Data Analytics application functions."""

    def __init__(self, analytics_client):
        """
        :param analytics_client: A Boto3 Kinesis Data Analytics v2 client.
        """
        self.analytics_client = analytics_client
        self.name = None
        self.arn = None
        self.version_id = None
        self.create_timestamp = None


    def stop(self):
        """
        Stops an application. This stops the application from processing data but
        does not delete any resources.
        """
        try:
            self.analytics_client.stop_application(ApplicationName=self.name)
            logger.info("Stopping application %s.", self.name)
        except ClientError:
            logger.exception("Couldn't stop application %s.", self.name)
            raise

この例は、既存のアプリケーションで実行されるコードを更新します。

class KinesisAnalyticsApplicationV2:
    """Encapsulates Kinesis Data Analytics application functions."""

    def __init__(self, analytics_client):
        """
        :param analytics_client: A Boto3 Kinesis Data Analytics v2 client.
        """
        self.analytics_client = analytics_client
        self.name = None
        self.arn = None
        self.version_id = None
        self.create_timestamp = None


    def update_code(self, code):
        """
        Updates the code that runs in the application. The code must run in the
        runtime environment of the application, such as SQL. Application code
        typically reads data from in-application streams and transforms it in some way.

        :param code: The code to upload. This completely replaces any existing code
                     in the application.
        :return: Metadata about the application.
        """
        try:
            response = self.analytics_client.update_application(
                ApplicationName=self.name,
                CurrentApplicationVersionId=self.version_id,
                ApplicationConfigurationUpdate={
                    "ApplicationCodeConfigurationUpdate": {
                        "CodeContentTypeUpdate": "PLAINTEXT",
                        "CodeContentUpdate": {"TextContentUpdate": code},
                    }
                },
            )
            details = response["ApplicationDetail"]
            self.version_id = details["ApplicationVersionId"]
            logger.info("Update code for application %s.", self.name)
        except ClientError:
            logger.exception("Couldn't update code for application %s.", self.name)
            raise
        else:
            return details

import json
import boto3

STREAM_NAME = "ExampleInputStream"


def get_data():
    return {"REFERRER": "http://www.amazon.com"}


def generate(stream_name, kinesis_client):
    while True:
        data = get_data()
        print(data)
        kinesis_client.put_record(
            StreamName=stream_name, Data=json.dumps(data), PartitionKey="partitionkey"
        )


if __name__ == "__main__":
    generate(STREAM_NAME, boto3.client("kinesis"))

from enum import Enum
import json
import random
import boto3

STREAM_NAME = "ExampleInputStream"


class PressureType(Enum):
    low = "LOW"
    normal = "NORMAL"
    high = "HIGH"


def get_blood_pressure(pressure_type):
    pressure = {"BloodPressureLevel": pressure_type.value}
    if pressure_type == PressureType.low:
        pressure["Systolic"] = random.randint(50, 80)
        pressure["Diastolic"] = random.randint(30, 50)
    elif pressure_type == PressureType.normal:
        pressure["Systolic"] = random.randint(90, 120)
        pressure["Diastolic"] = random.randint(60, 80)
    elif pressure_type == PressureType.high:
        pressure["Systolic"] = random.randint(130, 200)
        pressure["Diastolic"] = random.randint(90, 150)
    else:
        raise TypeError
    return pressure


def generate(stream_name, kinesis_client):
    while True:
        rnd = random.random()
        pressure_type = (
            PressureType.low
            if rnd < 0.005
            else PressureType.high
            if rnd > 0.995
            else PressureType.normal
        )
        blood_pressure = get_blood_pressure(pressure_type)
        print(blood_pressure)
        kinesis_client.put_record(
            StreamName=stream_name,
            Data=json.dumps(blood_pressure),
            PartitionKey="partitionkey",
        )


if __name__ == "__main__":
    generate(STREAM_NAME, boto3.client("kinesis"))

import json
import boto3

STREAM_NAME = "ExampleInputStream"


def get_data():
    return {"Col_A": "a", "Col_B": "b", "Col_C": "c", "Col_E_Unstructured": "x,y,z"}


def generate(stream_name, kinesis_client):
    while True:
        data = get_data()
        print(data)
        kinesis_client.put_record(
            StreamName=stream_name, Data=json.dumps(data), PartitionKey="partitionkey"
        )


if __name__ == "__main__":
    generate(STREAM_NAME, boto3.client("kinesis"))

from enum import Enum
import json
import random
import boto3

STREAM_NAME = "ExampleInputStream"


class RateType(Enum):
    normal = "NORMAL"
    high = "HIGH"


def get_heart_rate(rate_type):
    if rate_type == RateType.normal:
        rate = random.randint(60, 100)
    elif rate_type == RateType.high:
        rate = random.randint(150, 200)
    else:
        raise TypeError
    return {"heartRate": rate, "rateType": rate_type.value}


def generate(stream_name, kinesis_client, output=True):
    while True:
        rnd = random.random()
        rate_type = RateType.high if rnd < 0.01 else RateType.normal
        heart_rate = get_heart_rate(rate_type)
        if output:
            print(heart_rate)
        kinesis_client.put_record(
            StreamName=stream_name,
            Data=json.dumps(heart_rate),
            PartitionKey="partitionkey",
        )


if __name__ == "__main__":
    generate(STREAM_NAME, boto3.client("kinesis"))

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"),
    )

import json
import boto3

STREAM_NAME = "ExampleInputStream"


def get_data():
    return {
        "LOGENTRY": "203.0.113.24 - - [25/Mar/2018:15:25:37 -0700] "
        '"GET /index.php HTTP/1.1" 200 125 "-" '
        '"Mozilla/5.0 [en] Gecko/20100101 Firefox/52.0"'
    }


def generate(stream_name, kinesis_client):
    while True:
        data = get_data()
        print(data)
        kinesis_client.put_record(
            StreamName=stream_name, Data=json.dumps(data), PartitionKey="partitionkey"
        )


if __name__ == "__main__":
    generate(STREAM_NAME, boto3.client("kinesis"))

import datetime
import json
import random
import time
import boto3

STREAM_NAME = "ExampleInputStream"


def get_data():
    event_time = datetime.datetime.utcnow() - datetime.timedelta(seconds=10)
    return {
        "EVENT_TIME": event_time.isoformat(),
        "TICKER": random.choice(["AAPL", "AMZN", "MSFT", "INTC", "TBV"]),
    }


def generate(stream_name, kinesis_client):
    while True:
        data = get_data()
        # Send six records, ten seconds apart, with the same event time and ticker
        for _ in range(6):
            print(data)
            kinesis_client.put_record(
                StreamName=stream_name,
                Data=json.dumps(data),
                PartitionKey="partitionkey",
            )
            time.sleep(10)


if __name__ == "__main__":
    generate(STREAM_NAME, boto3.client("kinesis"))

import datetime
import json
import random
import boto3

STREAM_NAME = "ExampleInputStream"


def get_data():
    return {
        "EVENT_TIME": datetime.datetime.now().isoformat(),
        "TICKER": random.choice(["AAPL", "AMZN", "MSFT", "INTC", "TBV"]),
        "PRICE": round(random.random() * 100, 2),
    }


def generate(stream_name, kinesis_client):
    while True:
        data = get_data()
        print(data)
        kinesis_client.put_record(
            StreamName=stream_name, Data=json.dumps(data), PartitionKey="partitionkey"
        )


if __name__ == "__main__":
    generate(STREAM_NAME, boto3.client("kinesis"))

import json
import random
import boto3

STREAM_NAME = "OrdersAndTradesStream"
PARTITION_KEY = "partition_key"


def get_order(order_id, ticker):
    return {
        "RecordType": "Order",
        "Oid": order_id,
        "Oticker": ticker,
        "Oprice": random.randint(500, 10000),
        "Otype": "Sell",
    }


def get_trade(order_id, trade_id, ticker):
    return {
        "RecordType": "Trade",
        "Tid": trade_id,
        "Toid": order_id,
        "Tticker": ticker,
        "Tprice": random.randint(0, 3000),
    }


def generate(stream_name, kinesis_client):
    order_id = 1
    while True:
        ticker = random.choice(["AAAA", "BBBB", "CCCC"])
        order = get_order(order_id, ticker)
        print(order)
        kinesis_client.put_record(
            StreamName=stream_name, Data=json.dumps(order), PartitionKey=PARTITION_KEY
        )
        for trade_id in range(1, random.randint(0, 6)):
            trade = get_trade(order_id, trade_id, ticker)
            print(trade)
            kinesis_client.put_record(
                StreamName=stream_name,
                Data=json.dumps(trade),
                PartitionKey=PARTITION_KEY,
            )
        order_id += 1


if __name__ == "__main__":
    generate(STREAM_NAME, boto3.client("kinesis"))

import json
import boto3

STREAM_NAME = "ExampleInputStream"


def get_data():
    return {
        "log": "192.168.254.30 - John [24/May/2004:22:01:02 -0700] "
        '"GET /icons/apache_pb.gif HTTP/1.1" 304 0'
    }


def generate(stream_name, kinesis_client):
    while True:
        data = get_data()
        print(data)
        kinesis_client.put_record(
            StreamName=stream_name, Data=json.dumps(data), PartitionKey="partitionkey"
        )


if __name__ == "__main__":
    generate(STREAM_NAME, boto3.client("kinesis"))