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SQL Query: 3 Methods for Calculating Cumulative SUM

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

Here's to Know Data lake Vs Database

In a data lake, data stored internally in a repository. You can call it a blob. The data in the lake a no-format data, but you need a schema for the database. 

Data lake Repository


  • In the database, the Schema definition you need before you store data on it.
  • It should follow Codd's rules.
  • Here data is completely formatted.
  • The data stores here in Tables, so you need SQL language to read the records.
  • Poor performance in terms of scalability.

Data lake

  • It doesn't have any format - it's just a dump.
  • You can send this dump to the Hadoop repository for data analysis.
  • This repository can be incremental. You can build a database.
  • The data lake is a dump of data with no format. It needs a pre-format before it sends for analytics.
  • Data security and encryption: You need these before you send data to Hadoop.
  • In real-time, you need to pre-process data.
  • This data you need to send to the data warehouse to get insights.


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