The following queries show an example of how to calculate the completion_days as the difference between eco_date and orginated_date. To calculate the difference between the subfields of the date, Amazon Redshift has the function datediff. In the following example queries, we calculate the number of completion_days by calculating the difference between originated_date and eco_date. When the application needs to calculate the difference between the subfields of dates for Greenplum, it uses the function date_part, which allows you to retrieve subfields such as year, month, week, and day. In this section, we discuss calculating the difference between date_part for Greenplum and datediff for Amazon Redshift. Select * from temp1 where DeptName IN ('10-F','20-F','30-F') Working with date functions The function doesn’t add the separator at the end of the string. The STRING_AGG() function is an aggregate function that concatenates a list of strings and places a separator between them. Select JSON_EXTRACT_ARRAY_ELEMENT_TEXT('',ns.n-1) When the element of array is in the form of array itself, use the JSON_EXTRACT_ARRAY_ELEMENT_TEXT() function and JSON_ARRAY_LENGTH: ,split_part(MobilePhone|| '&' || HomePhone, '&', ns.n::int) as PhoneNumber ,split_part('Mobile,Home',',',ns.n::int) as PhoneType Select row_number() over(order by 1) as n from pg_tables In Greenplum, the UNNEST function is used to expand an array to a set of rows: Some of Amazon Redshift functions used to unnest arrays are split_part, json_extract_path_text, json_array_length, and json_extract_array_element_text. You can use UNNEST() for basic array, multiple arrays, and multiple arrays with different lengths. It is introduced to improve the database performance of thousands or records for inserts, updates, and deletes. UNNEST() is PostgreSQL’s system function for semi-structured data, expanding an array, or a combination of arrays to a set of rows. Select 'Mary' as FirstName, 'Jane' as LastName , Select 'Bob' as FirstName, 'Haris' as LastName , Select 'John' as FirstName, 'Smith' as LastName ,Īrray as PhoneNumbers It can be used to extract the n th element from an array in PostgreSQL or Greenplum. This function returns the upper bound of an array. JSON_EXTACT_ARRAY_ELEMENT_TEXT and JSON_ARRAY_LENGTH.This post outlines the most common array functions: Developers need to extensively convert those functions manually. The AWS SCT doesn’t convert array functions while migrating from Greenplum or PostgreSQL to Amazon Redshift. Please note that for this post, we use Greenplum 4.3 and Amazon Redshift PostgreSQL 8.2. The posts focuses on how to handle the following while migrating from Greenplum to Amazon Redshift: To address this type of situation, manual conversion of the code is required. But there are some situations where code conversion teams encounter errors and warnings for views, procedures, and functions while creating them in Amazon Redshift. It is focused on the migration of procedures, functions, and views.ĪWS Database Migration Service (AWS DMS) and the AWS Schema Conversion Tool (AWS SCT) can migrate most of the objects in a heterogeneous database migration from Greenplum to Amazon Redshift. This post covers the key functions and considerations while performing code conversion from Greenplum to Amazon Redshift. Benefits of other AWS services such as Amazon Simple Storage Service (Amazon S3), Amazon CloudWatch, Amazon EMR, Amazon SageMaker, and moreĮven though both Greenplum and Amazon Redshift use the open-source PostgreSQL database engine, migration still requires a lot of planning and manual intervention.The opportunity to modernize the data lake and data warehouse environment.Many customers have found migration to Amazon Redshift from Greenplum an attractive option instead of managing on-premises Greenplum for the following reasons: Greenplum is based on the PostgreSQL database engine. Greenplum is an open-source, massively parallel database used for analytics, mostly for on-premises infrastructure. Amazon Redshift is used by tens of thousands of businesses around the globe for modernizing their data analytics platform. Post Syndicated from Jagrit Shrestha original Īmazon Redshift is a fully managed service for data lakes, data analytics, and data warehouses for startups, medium enterprises, and large enterprises.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |