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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

Here is Hadoop MapReduce DataFlow Tutorial

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Here are the six stages of MapReduce. The MapReduce is critical for your data processing needs. Traditionally, the whole file needs to read once then divided manually, but it is not convenient. With that respect, Hadoop provides the facility to read files (ignoring their size) line-for-line by using offset and key-value. MapReduce dataflow Quick Tutorial 1. Dataflow Diagram 2. MapReduce Stages MapReduce receives input and processes it. Here are the six stages of processing . It is helpful for your interviews and project. MapReduce Stage-1 Take the file as input for processing purposes. Any file will consist of a group of lines. These lines containing key-value pairs of data. The whole file can be read out with this method. MapReduce Stage-2 In the next step, the file will be in "splitting" mode. This mode will divide the file into key, value pair of data. This time key will be offset and data will be a valuable part of the program. Each line will be read individually so there