Featured Post

SQL Query: 3 Methods for Calculating Cumulative SUM

Image
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

Greenplum Database basics in the age of Hadoop (1 of 2)

The Greenplum Database constructs on the basis of open origin database PostgreSQL. It firstly purposes like a information storage and uses a shared-nothing architecture|shared-nothing, astronomically collateral (computing)|massively collateral handling (MPP) design.

How Greenplum works...
In this design, information is partitioned athwart numerous section servers, and every one section controls and commands a clearly different part of the altogether data; there is no disk-level parting nor information argument amid sections.
Greenplum Database’s collateral request optimizer changes every one request into a material implementation design.
Greenplum’s optimizer utilizes a cost-based set of rules to appraise prospective implementation designs, bears a worldwide view of implementation athwart the computer array, and circumstances in the charges of moving information amid knots.

The ensuing request designs hold customary relational database transactions like well like collateral motion transactions that report as and how information ought to be moved amid knots throughout request implementation. Commodity Gigabit Ethernet and 10-gigabit Ethernet technics is applied aimed at the transference amid knots.

The design part of Greenplum...
During implementation of every one node within the design, numerous relational transactions are treated by Pipeline (computing)|pipelining: the capacity to start a assignment beforehand its forerunner assignment has finished, to rise effectual alikeness. For instance, when a table audit is seizing place, lines picked may be pipelined in to a connect procedure. 30+High+Paying+IT+Jobs
  • Internally, the Greenplum configuration uses record delivering and segment-level replication and delivers converted to be operated by largely automatic equipment a procedure by which a system automatically transfers control to a duplicate system when it detects a fault or failure. At the storage layer, RAID methods may disguise flat circular plate disappointments.
  • At the configuration layer, Greenplum copies section and principal information to different knots to establish that the mislaying of a engine must not influence the altogether database obtainability.

Comments

Popular posts from this blog

How to Fix datetime Import Error in Python Quickly

Explained Ideal Structure of Python Class

How to Check Kafka Available Brokers