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SQL Query: 3 Methods for Calculating Cumulative SUM

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SQL provides various constructs for calculating cumulative sums, offering flexibility and efficiency in data analysis. In this article, we explore three distinct SQL queries that facilitate the computation of cumulative sums. Each query leverages different SQL constructs to achieve the desired outcome, catering to diverse analytical needs and preferences. Using Window Functions (e.g., PostgreSQL, SQL Server, Oracle) SELECT id, value, SUM(value) OVER (ORDER BY id) AS cumulative_sum  FROM your_table; This query uses the SUM() window function with the OVER clause to calculate the cumulative sum of the value column ordered by the id column. Using Subqueries (e.g., MySQL, SQLite): SELECT t1.id, t1.value, SUM(t2.value) AS cumulative_sum FROM your_table t1 JOIN your_table t2 ON t1.id >= t2.id GROUP BY t1.id, t1.value ORDER BY t1.id; This query uses a self-join to calculate the cumulative sum. It joins the table with itself, matching rows where the id in the first table is greater than or

Hadoop 2x vs 3x top differences

In many interviews, the first question for Hadoop developers is what are the differences between Hadoop 2 and 3. You already know that Hadoop upgraded from version 1.

Hadoop features


The below list is useful to know the differences. I have given Hadoop details in the form of questions and answers so that beginners can understand.

Hadoop 2.x Vs 3.x


hadoop v2 vs 3
The major change in hadoop 3 is no storage overhead. So, you may be curious about how Hadoop 3 is managing storage.

My plan is for you is first to go through the list of differences and check the references section, to learn more about Hadoop storage management.

References

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