Step 1: Prepare the Data - Amazon Kinesis Data Analytics for SQL Applications Developer Guide
Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China (PDF).

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

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

2. 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.

Step 1: Prepare the Data

In this section, you create a Kinesis data stream, and then populate order and trade records on the stream. This is your streaming source for the application that you create in the next step.

Step 1.1: Create a Streaming Source

You can create a Kinesis data stream using the console or the Amazon CLI. The example assumes OrdersAndTradesStream as the stream name.

  • Using the console – Sign in to the Amazon Web Services Management Console and open the Kinesis console at https://console.amazonaws.cn/kinesis. Choose Data Streams, and then create a stream with one shard. For more information, see Create a Stream in the Amazon Kinesis Data Streams Developer Guide.

  • Using the Amazon CLI – Use the following Kinesis create-stream Amazon CLI command to create the stream:

    $ aws kinesis create-stream \ --stream-name OrdersAndTradesStream \ --shard-count 1 \ --region us-east-1 \ --profile adminuser

Step 1.2: Populate the Streaming Source

Run the following Python script to populate sample records on the OrdersAndTradesStream. If you created the stream with a different name, update the Python code appropriately.

  1. Install Python and pip.

    For information about installing Python, see the Python website.

    You can install dependencies using pip. For information about installing pip, see Installation on the pip website.

  2. Run the following Python code. The put-record command in the code writes the JSON records to the stream.

    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"))

Next Step

Step 2: Create the Application