I need to migrate my Database in Amazon Redshift to MySQL DB. What are the steps I need to follow? The DB has around 200 tables

Question

ChatGPT · Answer

Migrating a database from Amazon Redshift to MySQL involves several steps. Here’s a structured approach to guide you through the process:
Step 1: Assess Your Data
1. Understand Your Schema: Analyze the schema of your Redshift database. Identify the tables, their relationships, data types, and any constraints or indexes.
2. Check Compatibility: MySQL and Redshift have different data types and features. Make a list of how data types map between the two systems (e.g., [code]VARCHAR[/code], [code]INTEGER[/code], etc.).
Step 2: Prepare the Environment
1. Set Up MySQL: Ensure that you have a MySQL instance ready for the migration, either on-premises or in the cloud.
2. Create Databases and Tables: Based on your assessment, create the corresponding databases and tables in MySQL. You may need to adjust data types and structures.
Step 3: Export Data from Redshift
1. Use UNLOAD Command: You can use the [code]UNLOAD[/code] command to export data from Redshift to Amazon S3 in a format like CSV or Parquet. For example:
   [code]sql
   UNLOAD ('SELECT * FROM your_table')
   TO 's3://your-bucket/your_table_'
   IAM_ROLE 'your-iam-role'
   FORMAT AS CSV
   ALLOWOVERWRITE[/code]
2. Export All Tables: Repeat the [code]UNLOAD[/code] command for all 200 tables, ensuring you have a consistent naming convention for the files.
Step 4: Transfer Data to MySQL
1. Download from S3: Download the exported files from your S3 bucket to your local machine or a suitable server with MySQL access.
2. Prepare Data for Import: If needed, clean or transform the data files to match MySQL’s requirements (e.g., handling NULL values, date formats).
Step 5: Import Data into MySQL
1. Use LOAD DATA INFILE: You can use the [code]LOAD DATA INFILE[/code] command to import data into MySQL. For example:
   [code]sql
   LOAD DATA INFILE '/path/to/your_table.csv'
   INTO TABLE your_table
   FIELDS TERMINATED BY ','
   LINES TERMINATED BY '
'
   IGNORE 1 ROWS;  -- if there's a header[/code]
2. Repeat for All Tables: Execute the import process for each of the 200 tables.
Step 6: Validate and Test
1. Data Validation: After migration, run queries to compare row counts and data integrity between Redshift and MySQL.
2. Test Application Compatibility: If there are applications that rely on the database, perform thorough testing to ensure they work correctly with the new MySQL database.
Step 7: Optimize MySQL
1. Indexing: Create indexes on MySQL tables as needed to improve query performance.
2. Configuration: Tune MySQL settings based on your workload and performance requirements.
Step 8: Plan for Cutover
1. Schedule Downtime: If necessary, schedule a downtime window for final data synchronization.
2. Final Sync: If there have been changes in Redshift since the initial export, perform a final sync for any updated data.
Additional Considerations
 * Automation: You may consider scripts or tools to automate parts of the migration process, especially if you need to do this for many tables.
 * Backup: Always ensure you have backups of your data before starting the migration process.
By following these steps, you should be able to successfully migrate your database from Amazon Redshift to MySQL.

Olek Buzu · Answer

Your data integration approach depends on where is you MySQL endpoint.

1. Your target MySQL is outside of AWS
In this case you can use Python, psql.exe, and mysql.exe client software to copy data over from Redshift table to MySQL table.

I took similar approach for Oracle to MySQL [ https://github.com/alexbuz/Oracle-to-MySQL-DataMigrator/blob/master/README.txt ] data load.

1. Your target MySQL is hosted on EC2 instance.
For faster loads it’s better to use AWS DataPipeline [ https://aws.amazon.com/documentation/data-pipeline/ ]. If you choose to go for approach outlined in #1 use EBS or local instance SSD disk for temporary file storage.

1. Your target MySQL is Amazon RDS.
For scale-able loads use AWS DataPipeline [ https://aws.amazon.com/documentation/data-pipeline/ ]. For ad-hoc repeatable data loads you can use integration strategy outlined in #1. Python script can be configured to pipe binary data from psql.exe to mysql.exe without creating temporary data file.

You can take the same approach i did for MySQL-to-Redshift-Migration [ https://github.com/alexbuz/MySQL_To_Redshift_Loader/blob/master/README.md ]

Surendar S · Answer

From Redshift to MySQL,

1.Unload the Redshift tables to Amazon S3 as CSV files.
2.Copy or move those unloaded files into EC2 instance local server.
3.From local server CSV files to Load into MySQL tables using LOAD command in MySQL

Better you can create a ETL job to perform the all above operations.

Kautuk Pandey · Answer

Well, I dont think that's a very nice problem to have. 
Redshift is an MPP columnar database, while MySQL is a traditional row-store RDBMS. There are a lot of thing which are implemented differently in these two database systems. For instance, your tables in Redshift must be having distribution styles, compression schemes etc. You will not find any equivalent things in MySQL. 
Redshift has a concept of schema within the same database( just like Microsoft SQL Server), while MySQL follows a more Oracle-like methodology where you can have different schema within the same instance (and not within the same database). So, if you have your tables in Redshift with different schema withing the same database, you will have to rethink how you want to implement those tables in MySQL.

Solutions:
If you just have to do it, I would suggest to use Aginity workbench and extract the scripts for DDLs and DMLs for your Redshift tables, then apply the changes which are incompatible with MySQL manually.

Another approach can to be use Unload command to push data into CSV files and then move them to MySQL. But unload command might give multiple files for each table based on the amount of data in the table, so you might face some problems in importing them back into MySQL.

Jacob Martin · Answer

You can migrate your database from Amazon Redshift to MySQL DB (without a CSV step) with the help of Skyvia [ https://skyvia.com/connectors/redshift ].

Wrd Zou · Answer

My SQL is system used to creaate databases in local that can be linked to website using php langusge but when this database is becaming big or the administrator want the database can be accessed in every moment onligne like put in a cloud system management like Amazon Redshift which is a fully managed with zero administration enverement.

This next few steps can resume the transfer, strating by creating count in amazon redshift. Then the next steps in ordre:

1. Export MySQL data, using an export query, and split them into multiple files.
2. Upload the load files to Amazon S3.
3. Run a COPY command (possibly in multiple iterations) to load the table.
4. Verify that the data was loaded correctly.
There are others methods of transfer MySQL database to amazon redshift likeusing treasue data as midill system, Change Data Capture with Binlog, and others but reach one must be verified befor using it.

Amit Singh Rathore · Answer

Unlike AWS RDS, Data Migration Service does not support Redshift as data source. It can only be used as target. So if you are trying to move data out of Redshift you have two option.

#1. Connect sql server installed in ec2 to AWS redshift. You need to install Amazon Redshift ODBC Driver. Once installed you have to create a DSN.

Install and Configure the Amazon Redshift ODBC Driver on Microsoft Windows Operating Systems [ http://docs.aws.amazon.com/redshift/latest/mgmt/install-odbc-driver-windows.html ]

#2. Go via S3. You will use the unload command to get the data out of Redshift and dump it into S3 bucket.

UNLOAD ('select * from my_table')
 TO 's3://bucket_name/path/my_filename'
 WITH CREDENTIALS
 'aws_access_key_id=%3Cmy_access_key%3E;
 aws_secret_access_key=%3Cmy_secret_key%3E'
 MANIFEST
 GZIP
 ALLOWOVERWRITE
 ESCAPE
 NULL AS '\N'

After dumping the file into S3 you can move it to your database on ec2 instance. For that you need to have PostgreSql ODBC driver. Once you have this driver you can use SSIS to load data from S3 into Sql server.

Praveen · Answer

To move data from MySQL/SQLite to Redshift:

1. Export data and prepare it for Redshift.
2. Create tables in Redshift to match the data structure.
3. Use Redshift's COPY command to load the prepared data into the tables.
4. Verify the data has been loaded correctly.
It's important to secure the data transfer and protect sensitive information.

Olek Buzu · Answer

Best in my opinion is to use Python/MySQL client(mysql.exe)/psycopg2 [ https://pypi.python.org/pypi/psycopg2 ]/

Her’s how I see it using Python:

1. Open extract pipe to MySLQ using mysql.exe
2. Read from pipe, compress and upload to Amazon S3 .
3. Using COPY command load from S3 to Amazon Redshift.
I’ve compiled all load steps into one Python script - MySQL-To-Redshift-Loader [ https://github.com/alexbuz/MySQL_To_Redshift_Loader ].

It extracts using `mysql.exe`, loads to S3 using multi-part upload and executes COPY command using psycopg2 [ https://pypi.python.org/pypi/psycopg2 ]

Here’s the example  [ https://github.com/alexbuz/MySQL_To_Redshift_Loader/blob/master/sources/include/extractor.py ]of how to extract data from MySQL using Python and mysql.exe:

[code]def extract(env):
	
	in_qry=open(opt.mysql_query_file, "r").read().strip().strip(';')
	db_client_dbshell=r'%s\mysql.exe' % MYSQL_CLIENT_HOME.strip('"')
	loadConf=[ db_client_dbshell ,'-u', opt.mysql_user,'-p%s' % opt.mysql_pwd,'-D',opt.mysql_db_name, '-h', opt.mysql_db_server]
	
	limit=''
	if opt.mysql_lame_duck%3E0:
		limit='LIMIT %d' % opt.mysql_lame_duck
	out_file='c:/tmp/orders.csv'
	if os.path.isfile(out_file):
		os.remove(out_file)

q="""
%s %s
INTO OUTFILE '%s'
FIELDS TERMINATED BY '%s'
ENCLOSED BY '%s'
LINES TERMINATED BY '
';
	""" % (in_qry, limit, out_file, opt.mysql_col_delim,opt.mysql_quote)
	p1 = Popen(['echo', q], stdout=PIPE,stderr=PIPE,env=env)
	
	p2 = Popen(loadConf, stdin=p1.stdout, stdout=PIPE,stderr=PIPE)

output=' '
	status=0
	if 1:
		while output:
			output = p2.stdout.readline()
			print output
	if 1:
		err=' '
		while err:
			err = p2.stderr.readline()
			print err
	p1.wait()
	p2.wait()
[/code]Here’s an example  [ https://github.com/alexbuz/MySQL_To_Redshift_Loader/blob/master/sources/include/loader.py ]of how to load data to Redshift form S3 using COPY command:

[code]def load(location):
	start_time = time.time()
	fn='http://s3://%s' % location
	conn_string = REDSHIFT_CONNECT_STRING.strip().strip('"')	
	con = psycopg2.connect(conn_string);
	cur = con.cursor();	
	quote=''
	if opt.red_quote:
		quote='quote \'%s\'' % opt.red_quote
	ignoreheader =''
	if opt.red_ignoreheader:
		ignoreheader='IGNOREHEADER %s' % opt.red_ignoreheader
	timeformat=''
	if opt.red_timeformat:
		#timeformat=" dateformat 'auto' "
		timeformat=" TIMEFORMAT '%s'" % opt.red_timeformat.strip().strip("'")
	sql="""
COPY %s FROM '%s' 
	CREDENTIALS 'aws_access_key_id=%s;aws_secret_access_key=%s' 
	DELIMITER '%s' 
	FORMAT CSV %s 
	GZIP 
	%s 
	%s; 
	COMMIT;
""" % (opt.red_to_table, fn, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY,opt.red_col_delim,quote, timeformat, ignoreheader)
	cur.execute(sql)	
	con.close()
[/code]

Mayank Pandey · Answer

1. Unload the data from Redshift to CSV files in S3 (UNLOAD - Amazon Redshift [ http://docs.aws.amazon.com/redshift/latest/dg/r_UNLOAD.html ])
2. Use these files to import data in SQL Server.

Philipp Berner · Answer

Airbnb (product) [ https://www.quora.com/topic/Airbnb-product ] posted on the engineering blog a while ago an article on how they migrated their MySql database to Amazon RDS [ https://www.quora.com/topic/Amazon-RDS ]. You'll find it here: http://nerds.airbnb.com/mysql-in-the-cloud-at-airbnb

Shivam Gulati · Answer

If you are looking into RDS MySQL, the native replication would work best since this is a homogeneous migration.

1. Copy dump with mysqldump
2. Setup replication
3. Stop and switch over to RDS when complete
You can also look at AWS Database Migration Service [ https://aws.amazon.com/dms/ ]

Tony Dorie · Answer

Pros: The single most significant pro is that you don't have to have a database admin. Amazon handles all of the nitty gritty details of patching, set-up and configuration. Having replication and automated back-up features ready at the click of a button is also very nice to have.

Cons: Depending on your needs, you may not be able to justify the additional costs. I also don't think you can add your own MySQL extensions. You also have to get used to the idea that someone else is responsible for the availability of your data.

To me it comes down to a question of what you need and how much your time is worth. If you don't need more advanced features like replication and automated backups, then rolling your own DB instance on a EC2 server should suffice.  If you do need those features, then the question to ask is whether you don't mind spending time configuring and maintaining your own database servers.

Jurg van Vliet · Answer

In our experience the performance of an RDS instance depends highly on a properly designed schema. For our RDS deploys with poorly designed schemas RDS is unforgiving.

We figure that this mainly has to do with disk access. For the RDS instances with a well designed schema performance of even a small instance is pretty good.

There are some additional drawbacks over 'rolling your own'. The most important is that it is quite a pain to work with parameter groups, in the AWS console. If want to add stored procedures, for example, you need to change variables.

The most important (and painful) lesson for us was that all the promises RDS vanish when you have MyISAM tables. Backups are just not available. This is obscurely documented, and confusing when you just read FAQ. But, if you have a fully InnoDB database all these features are invaluable.

Rudraksha Singh · Answer

Migrating H2 data to MySQL using the command line

1. Stop the MySQL service.
2. Edit the my. ini configuration file.
3. Start the MySQL service.
4. Open the MySQL Command Line Client and run the following commands to create the database schema and users: CREATE SCHEMA %3Cschema%3E; ...
5. Stop the Policy Manager service.
6. Run the following command to start the migration:

Kautuk Pandey · Answer

Well, to get a better answer you need to add details like where is your DW currently? Do you just want to move the DW as it is or you want to redesign your DW etc.

In general, you will have to setup an AWS account, create a Redshift cluster and use some ETL framework to populate your DW. There are some SaaS vendors also who are now providing migration solutions from MySQL/PostgreSQL/ Oracle to Redshift.
Pardon for the generic answer but the question is too generic for a specific answer.

Justin Swanhart · Answer

Use MySQL SELECT INTO OUTFILE to extract data to flat files.

Place your flat files on S3, then use the redshift COPY command to load from S3.  You can also use the AWS data pipeline to load data, but I find COPY to be fast and straightforward.

Jacko Ang · Answer

Step 1: Launch the RDS Instances in a VPC by Using the CloudFormation Template.

Step 2: Install the SQL Tools and AWS Schema Conversion Tool on Your Local Computer.

Step 3: Test Connectivity to the Oracle DB Instance and Create the Sample Schema.

Step 4: Test the Connectivity to the Aurora MySQL DB Instance.

Ronald Bradford · Answer

RDS is an impractical use for OLTP applications. The primary reason is RDS will only guarantee data up to 5 minutes ago. You have to start with at minimum a Multi-AZ deployment for basic needs. Then you still get no guarantee about timeframes, and you have zero access to monitoring your DB. With an EC2 instance you immediately get greater flexibility, however you need to know more for ideal management.

Unless you can re-create your data a single server RDS server is not a practical solution. Even then you can't add RDS into a MySQL replication topology.

Russell Christopher · Answer

Use the AWS Schema Conversion Tool (What Is the AWS Schema Conversion Tool? [ https://docs.aws.amazon.com/SchemaConversionTool/latest/userguide/Welcome.html ]) to covert your Oracle schema to one that is Redshift-compatible.

Then, use the AWS Database Migration Service (AWS Database Migration Service [ https://aws.amazon.com/dms/ ]) to stream data from your On Prem Oracle to Redshift.