Maximize migration success with unique validation features of LeapLogic - LeapLogic
Blog
05 Apr 2024

Maximize migration success with unique validation features of LeapLogic

Revolutionize Hadoop modernization with LeapLogic’s intelligent automation capabilities

Transitioning from Hadoop to cloud-native solutions is pivotal for enterprises because it speeds up time to market, reduces costs and latency, provides granular security, and improves user experience. Dynamic scaling and instance types in the cloud also provide better fault tolerance, availability, and cost management. Moreover, embracing cloud-native solutions enables innovation with new data products and deeper analytics, empowering intelligent decision-making.

LeapLogic, Impetus’ automated cloud migration accelerator, ensures seamless Hadoop modernization with up to 95% automation, minimizing risk and business disruptions. From initial assessment to code migration and operational readiness, LeapLogic ensures a highly automated transformation, saving time and effort.

Why is validating transformed code crucial in modernization?

Migrating Hadoop queries, code, or scripts to their target equivalents is only half the battle. Any error in the transformed code can derail the entire migration and lead to spiraling costs and time. Therefore, validating the workloads at unit and integration levels to ensure optimal performance in the target environment is crucial.

The validation process for Hadoop migration is complex due to the heterogeneous nature of data, diverse formats, intricate business logic, and the imperative to maintain data integrity and accuracy. The sheer volume of data in Hadoop environments amplifies the challenges, making validation resource-intensive and susceptible to errors.

LeapLogic addresses these challenges by streamlining validation through automated tools, reducing time consumption, and ensuring performance optimization and cross-platform compatibility.

Highlighted features of the LeapLogic validation tool include:

Comprehensive and selective data validation: LeapLogic enables organizations to perform detailed cell-by-cell value validation of their entire dataset and selective validation based on specified filtering criteria.

Validation with or without primary keys: Unlike many validation tools, LeapLogic can conduct validation even in the absence of primary keys, utilizing column-level validation to pinpoint value differences.

Record count validation: The tool compares the number of records in the source and target datasets, identifying any discrepancies to maintain data integrity.

Aggregation validation: LeapLogic conducts aggregation validation on both source and target datasets, providing insights into data uniqueness and cardinality.

Data type validation: The tool detects inconsistencies in data types and offers configurable options to handle encountered errors.

Duplicates validation: LeapLogic flags duplicate records within source and target tables while continuing the validation process.

Validation of encrypted data: Ensures integrity of encrypted data, maintaining security and privacy throughout the validation process.

Compatibility with various file formats: Supports diverse data sources and structures, including CSV, Fixed Width, AVRO, ORC, and Parquet.

Exclusion of columns from validation: This option allows users to omit specific columns from the validation process if they are irrelevant to the objectives.

Validation by column position/name: Offers flexibility in validation methods, allowing validation by either column name or position within the dataset.

Validation based on percentage variance: This unique feature enables validation based on a percentage variance threshold for numerical columns, ensuring target data falls within an acceptable range.

LeapLogic is an end-to-end modernization tool, encompassing the four steps of assessment, transformation, validation, and operationalization.

 

Step 1
Assessment

Complete analysis of workloads, code profiling, and dependencies with actionable recommendations

Step 2
Transformation

End-to-end transformation, including core business logic to target-native equivalents

Step 3
Validation

Validation for pipelines, data, and row and cell-level queries

Step 4
Operationalization

Target-specific executable packaging with optimal price-performance ratio

Within this framework, validation plays a pivotal role in ensuring the successful migration of Hadoop to cloud-native stacks. These validation features provide comprehensive checks throughout the migration process, minimizing errors and disruptions. By leveraging LeapLogic’s validation capabilities, organizations can confidently embrace modernization while safeguarding data integrity and reliability.

Charan Kumar Murthy
Author
Charan Kumar Murthy
Technical Project Manager