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Discover how to efficiently calculate the total amount of consecutive sales transactions in Java using a window size of 3. Learn the implementation step-by-step!
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Java Counting in a Period of a Window Size: How to Sum Elements in Groups

Calculating the sum of elements in a list can be a common requirement in data analysis tasks. If you are working with transaction data, for example, you might want to calculate the total of certain transactions over a specific period or window size. In this article, we will explore how to implement this in Java, with a specific focus on summing the amounts over a window size of 3 for a series of transactions.

The Problem Set-Up

Let's say you have a data structure named SaleTxn, which represents a sales transaction with the following fields:

id: Unique identifier of the transaction.

txnDate: The date of the transaction.

amount: The amount of money for that transaction.

For illustration, consider the following mock data representing six transactions:

idtxnDateamount12018-10-1010022018-10-1120032018-10-1210042018-10-1310052018-10-1420062018-10-15200Your goal is to compute the total of the transaction amounts for every consecutive 3 transactions, resembling the following expected output:

From 2018-10-10 to 2018-10-12: Total: 100 + 200 + 100 = 400

From 2018-10-13 to 2018-10-14: Total: 100 + 200 + 200 = 500

Step-by-Step Solution

To implement this in Java, we can utilize the power of the Java Stream API for easy collection manipulation. Here's how you can accomplish this.

Step 1: Create the SaleTxn Class

The first step is to define your SaleTxn class:

[[See Video to Reveal this Text or Code Snippet]]

Step 2: Instantiate Your Transaction List

Next, you'll want to create a list of SaleTxn objects:

[[See Video to Reveal this Text or Code Snippet]]

Step 3: Filter and Partition the List

Here, you can filter your list if necessary and then partition it into sublists of size 3. For this, you can use the Google Guava library which simplifies partitioning:

[[See Video to Reveal this Text or Code Snippet]]

Step 4: Output the Results

The resulting list will give you the total amounts for each three consecutive transactions. If we run the code above, the output will be:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

In conclusion, utilizing Java Streams along with the Guava library allows for efficient manipulation of lists to meet your data processing needs. By partitioning your data into manageable chunks, summing them up, and retrieving the results can be done seamlessly. This method is not just limited to summing but can be adapted for various forms of data analysis and aggregation.

Now you are equipped to implement similar counting algorithms in your Java projects, helping you extract meaningful insights from your transaction data!