After careful consideration, we have decided to discontinue Amazon Kinesis Data Analytics for SQL applications:

1. From **September 1, 2025**, we won't provide any bug fixes for Amazon Kinesis Data Analytics for SQL applications because we will have limited support for it, given the upcoming discontinuation.

2. From **October 15, 2025**, you will not be able to create new Kinesis Data Analytics for SQL applications.

3. We will delete your applications starting **January 27, 2026**. You will not be able to start or operate your Amazon Kinesis Data Analytics for SQL applications. Support will no longer be available for Amazon Kinesis Data Analytics for SQL from that time. For more information, see [Amazon Kinesis Data Analytics for SQL Applications discontinuation](discontinuation.md).

# Step 1: Prepare the Data
<a name="app-anomaly-with-ex-prepare"></a>

Before you create an Amazon Kinesis Data Analytics application for this [example](app-anomaly-detection-with-explanation.md), you create a Kinesis data stream to use as the streaming source for your application. You also run Python code to write simulated blood pressure data to the stream. 

**Topics**
+ [Step 1.1: Create a Kinesis Data Stream](#app-anomaly-create-two-streams)
+ [Step 1.2: Write Sample Records to the Input Stream](#app-anomaly-write-sample-records-inputstream)

## Step 1.1: Create a Kinesis Data Stream
<a name="app-anomaly-create-two-streams"></a>

In this section, you create a Kinesis data stream named `ExampleInputStream`. You can create this data stream using the AWS Management Console or the AWS CLI.
+ To use the console:

  1. Sign in to the AWS Management Console and open the Kinesis console at [https://console.aws.amazon.com/kinesis](https://console.aws.amazon.com/kinesis).

  1. Choose **Data Streams** in the navigation pane. Then choose **Create Kinesis stream**.

  1. For the name, type **ExampleInputStream**. For the number of shards, type **1**.
+ Alternatively, to use the AWS CLI to create the data stream, run the following command:

  ```
  $ aws kinesis create-stream --stream-name ExampleInputStream --shard-count 1
  ```

## Step 1.2: Write Sample Records to the Input Stream
<a name="app-anomaly-write-sample-records-inputstream"></a>

In this step, you run Python code to continuously generate sample records and write them to the data stream that you created. 

1. Install Python and pip.

   For information about installing Python, see [Python](https://www.python.org/). 

   You can install dependencies using pip. For information about installing pip, see [Installation](https://pip.pypa.io/en/stable/installing/) in the pip documentation.

1. Run the following Python code. You can change the Region to the one you want to use for this example. The `put-record` command in the code writes the JSON records to the stream.

   ```
    
   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"))
   ```

**Next Step**  
[Step 2: Create an Analytics Application](app-anom-with-exp-create-app.md)