Data Migration is a critical activity for organizations to be analytics-ready. Having an approach or framework that accelerates the process, optimises for performance is a useful tool for data engineers.
In this blog, we will explore a dynamic framework for data migration in Talend that can empower businesses to tackle complex data migration challenges with ease.
Let’s delve into the details of this framework and understand how it can handle diverse scenarios, including selective column migration, table combination, logic application, and handling flat files without metadata information.
The Context Files:
The foundation of a flexible data migration framework lies in the context files, which store crucial connection details and paths required for data migration.
• context.txt
This file holds the source and target connection details, as well as the S3 paths for the migration process.
• sales_context.txt
The sales_context.txt file plays a significant role in controlling the migration process. It enables you to specify the tables you want to migrate and offers control over the data extraction period. By mentioning the start and end dates, you can extract data within a specific timeframe. For master tables, no dates need to be mentioned, as they are not bound by any specific period. Additionally, for incremental loads, dates are controlled using incremental_audit tables, simplifying the process even further.
Sample of the context file content:
• master_context.txt
This context file is designed for master tables, providing the flexibility to balance data loads effectively. Depending on your data load requirements, you can create as many context files as needed.
Business=master table_id=’1028′,’1029′
Audit Tables:
To ensure transparency and monitor the data migration process, the Flexible Data Migration Framework employs two essential audit tables:
• Table_List
Each table is assigned a unique ID, which allows for precise control of job execution. Additionally, HL_Query and IL_Query enable the inclusion of SQL queries to apply transformations, filters, or exclude specific columns from the source during the migration process.
• Audit Table
This table captures vital job statistics, providing valuable insights into the migration process’s progress and success.
Talend Job Design: Database to Flat File
In this section, we will explore the first pipeline of the Flexible Data Migration Framework, transferring data from a source database to a flat file stored in S3. The process is achieved through four Talend jobs:
• S3_extraction_parent
• S3_extraction_child1
• S3_master_extraction_child1
• S3_extraction_child2
S3_extraction_parent
The S3_extraction_parent job acts as an orchestrator for the tables’ migration. By customizing this parent job according to your specific requirements, you can efficiently manage the data transfer process.
As mentioned in the context section of this document, you can segregate tables into different context files based on load balancing, incremental load scheduling, or any other specific needs.
By utilizing context variables, you can control which tables to run. Each tRunjob will execute based on the chosen context, ensuring a streamlined and efficient migration process. For example, selecting the “master” context would trigger the execution of subjobs associated with master tables, while other subjobs would remain inactive.
S3_extraction_child1
The purpose of S3_extraction_child1 is to iterate through the list of tables and pass them to S3_extraction_child2 for further processing. The tMap_1 component also plays a key role in framing SQL queries for history loads, incremental loads, master tables, or transaction tables, ensuring the appropriate data extraction for each scenario. The queries are assigned to a context and then passed to the S3_extraction_child2 job.
S3_extraction_child2
The core of the magic happens within S3_extraction_child2, where each subjob fulfills a specific role in the migration process.
The record count check subjob ensures that a table contains data before extracting it, avoiding the creation of empty files in the process.
The subjob iterates through the table list using the framed query and, with the help of dynamic schema, writes the output to a CSV file, which is then moved to S3 for storage.
Talend Job Design: Flat File to Database
In this section, we will explore the second pipeline of the Flexible Data Migration Framework, focusing on data migration from flat files stored in S3 to a target database. To achieve this, we use three key Talend jobs:
• S3_to_postgres_parent
• S3_to_postgres_child1
• S3_to_postgres_child2
As mentioned earlier in the Pre-requisites section, the Source to Target Mapping (STM) document provides essential schema metadata information for the target tables, as flat files do not contain column metadata. This extracted schema is then stored as context using tJavaRow_2, streamlining the migration process.
The S3 file check subjob, as mentioned in the Audit Table section, ensures that the S3 files are ready to be processed, preventing duplicate file processing and ensuring efficient execution.
The final subjob, File to DB migration, extracts data from the flat files and writes it to the target database. The magic lies in the dynamic framing of INSERT, UPDATE, and DELETE SQL queries using Java code in the tJavaRow_1 component. These queries are then passed as context to the Postgres target database, facilitating a smooth and automated migration process.
The Flexible Data Migration Framework is a powerful tool that enables seamless data migration from diverse sources to various targets, all while accommodating any necessary transformations. This efficient framework empowers businesses to undertake complex data migration tasks without extensive development efforts. With the ability to handle selective column migration, table combinations, logic application, and flat files without metadata information, the Flexible Data Migration Framework stands as a robust solution for organizations seeking a reliable and flexible data migration solution.
In conclusion, the Flexible Data Migration Framework offers an optimal balance between ease of use and powerful functionality, ensuring that data migration is no longer a daunting task. With this framework at your disposal, your organization can confidently embrace data-driven decision-making and stay ahead in today’s competitive landscape.
Data-driven organizations can rely on such frameworks to continuously evolve, innovate and stay relevant in today’s marketplace. Contact us or write to info@gain-insights.com to explore a hands-on session or a discussion.
