datablogs: Postgresql
Showing posts with label Postgresql. Show all posts
Showing posts with label Postgresql. Show all posts

Tuesday, November 14, 2023

PostgreSQL Table Partition on AWS RDS

If we grow bigger in the business , seamlessly our customer and transaction data also increases . In the meantime performance needs to consider as well 

So in this case of bigger tables indexes will not help us to achieve good performance on peak times . Alternatively we have partitioning to split the tables data into multiple pieces on all the relational database environments 

Like wise we are going to do range partition on sample table in PostgreSQL Database , In PostgreSQL three types of partition methods are available , 


Below are the important concern in the PostgreSQL Partition ,

  • Possible to attach regular table into partitioned one 
  • Not Possible to transform regular table to partitioned one   

So based on the above formula , we have tried to transform regular table into partitioned one for your reference 

Any one can use this example and perform partitioning in AWS PostgreSQL RDS easily 

Click GitHub Link for Code : AWS-PostgreSQL-RDS-Table-Partition

Step 1 : Create base datablogspaycheck table and insert some sample records 

DROP TABLE IF EXISTS datablogspaycheck CASCADE;

DROP SEQUENCE IF EXISTS public.paycheck_id_seq;

CREATE SEQUENCE public.paycheck_id_seq

    START WITH 1

    INCREMENT BY 1

    NO MINVALUE

    NO MAXVALUE

    CACHE 1;

create table datablogspaycheck

(

    payment_id int NOT NULL DEFAULT nextval('public.paycheck_id_seq'::regclass), 

    created timestamptz NOT NULL,

    updated  timestamptz NOT NULL DEFAULT now(),

    amount float,

    status varchar DEFAULT 'new'

);

CREATE INDEX idx_paycheck ON datablogspaycheck (created);

INSERT INTO datablogspaycheck (created) VALUES (

generate_series(timestamp '2023-01-01'

               , now()

               , interval  '5 minutes') ); 

Step 2 : Rename base table with new name

ALTER TABLE datablogspaycheck RENAME TO datablogspaycheck_basetable;

Step 3 : Create Partitioned table 

create table datablogspaycheck

(

    payment_id int NOT NULL DEFAULT nextval('public.paycheck_id_seq'::regclass), 

    created timestamptz NOT NULL,

    updated  timestamptz NOT NULL DEFAULT now(),

    amount float,

    status varchar DEFAULT 'new'

)PARTITION BY RANGE (created);

Step 4 : Create Separate Partition for each create date 

CREATE TABLE datablogspaycheck_202303 PARTITION OF datablogspaycheck

    FOR VALUES FROM ('2023-01-01') TO ('2023-03-01');

   

CREATE TABLE datablogspaycheck_20230304 PARTITION OF datablogspaycheck

    FOR VALUES FROM ('2023-03-01') TO ('2023-04-01');

    

CREATE TABLE datablogspaycheck_202304 PARTITION OF datablogspaycheck

    FOR VALUES FROM ('2023-04-01') TO ('2023-05-01');

    

CREATE TABLE datablogspaycheck_202311 PARTITION OF datablogspaycheck

    FOR VALUES FROM ('2023-05-01') TO ('2023-11-01');

   

CREATE TABLE datablogspaycheck_2024 PARTITION OF datablogspaycheck

    FOR VALUES FROM ('2023-11-01') TO ('2024-01-01');

Step 5 : Migrate the all records

insert into datablogspaycheck (payment_id,created,updated,amount,status) select payment_id,created,updated,amount,status from datablogspaycheck_basetable;

Step 6 : Validate each partition 

select * from datablogspaycheck_202303 order by 2 desc

select * from datablogspaycheck_20230304 order by 2 desc

select * from datablogspaycheck_202311 order by 2 desc

Its done , Easily migrated normal table data into partitioned table 

Thanks for Reading !!!



Sunday, June 25, 2023

Deep dive into Babelfish Compass

        Wow !!! If suppose on the migration projects we need to more stuffs and things to convert when coming to procedures , functions and other database objects 

But AWS is providing good things to migrate with easy steps , Ha Ha ... Don't overthink still you need to do 40% code migration works 

In this part Babelfish Compass is giving various options to support migration the codes from SQL Server to PostgreSQL with bebelfish feature enabled PaaS servers 

Below are easy steps on the Script Conversations

Prerequisites 
  • Install a 64-bit Java Runtime Environment (JRE) version 8 or higher

1.Download Compass Tool in Below 

https://github.com/babelfish-for-postgresql/babelfish_compass/releases/tag/v.2023-03-a

Needs to download .zip file to work with Babelfish Compatibility 


2.Unzip and Place the files in separate folder 


3.Be Ready with you SQL Database Generated Scripts file and Copy it in Same Folder 

Database name has been highlighted in below , 


4.Next , we can start running report with Babelfish Compass 

C:\Users\Admin\Downloads\BabelfishCompass_v.2023-03-a\BabelfishCompass>BabelfishCompass.bat reportfinal datablogsdbprod.sql


5.Finally Reports are generated in Documents Directory 


6.We can review the reports in any format , for me its easy with in HTML browser 

Just double click the HTML document , So like below we will get supported and unsupported features details in depth . 

We can directly go and debug the code . Also bebelfish compass is having plenty of methods to rewrite the code , we will check it in next blog 


Happy Coding !!!