Comprehensive Guide to Time Series Data Aggregation in Java

Welcome to our comprehensive guide on time series data aggregation in Java, with a focus on in-memory processing. Time series data, such as daily stock prices, are invaluable in various industries for trend analysis, forecasting, and decision-making. In this post, we delve into the intricacies of efficiently handling time series data within Java applications, emphasizing in-memory aggregation techniques.

Throughout this journey, we’ll use the dynamic world of daily stock data as our prime example. We will create an application to generate random stock prices for some units and publish the results to an endpoint every second.

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Generating Stock Data and Publishing to HTTP Endpoint

Basic Model Class

We’ll start by creating a basic model class with three properties: timestamp, name, and price.

@AllArgsConstructor
@Data
public class Stock {
    private long timestamp;
    private String name;
    private double price;

    public String toString() {
        return "{\"timestamp\": " + timestamp + ", \"name\": \"" + name + "\", \"price\": " + price + "}";
    }
}

Publishing Data