Showing posts with the label greenplum

Featured Post

Best Practices for Handling Duplicate Elements in Python Lists

Here are three awesome ways that you can use to remove duplicates in a list. These are helpful in resolving your data analytics solutions.  01. Using a Set Convert the list into a set , which automatically removes duplicates due to its unique element nature, and then convert the set back to a list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = list(set(original_list)) 02. Using a Loop Iterate through the original list and append elements to a new list only if they haven't been added before. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] for item in original_list:     if item not in unique_list:         unique_list.append(item) 03. Using List Comprehension Create a new list using a list comprehension that includes only the elements not already present in the new list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] [unique_list.append(item) for item in original_list if item not in unique_list] All three methods will result in uni

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