Big Data Testing Solutions

XenonStack, being automated Big Data Testing Solution Company helps you check organized and unstructured informational indexes, patterns, approaches and innate procedures living at various layers in your big data platforms, for example, 'Apache Sqoop', 'Apache Nifi' at Data Ingestion Layer, 'Spark', 'Mapreduce', 'Apache Pig' at Data Processing Layer and 'HBase', 'Hive', 'Cassandra' at Data Storage Layer.


Big Data Testing Strategies

  • Big Data Migration Testing
    • Data Migration Test Strategy
    • Source to Target (NoSQL DB/Hive/HDFS) Field Validation
    • Data Accuracy Validation Post Migration
    • Multi-Source Data Integration Validation
  • Security Testing
    • Security Test Assessment
    • Role Based Security Testing
    • Default Permission Configuration Check
    • Data Node and Name Node direct access validation
  • Performance Testing
    • Performance Test Strategy
    • Performance Monitoring Scripts Creation
    • Performance Monitoring and Identifying Bottlenecks
  • Big Data Sources Extraction Testing
    • Data Processing/ETL Test Strategy
    • Data Extraction Validation
    • MapReduce Jobs Validation
    • Spark Jobs Validation
    • Hive Queries/Pig Jobs Validation
    • Data Storage in Hadoop Distribution File
    • System (HDFS) and NoSQL Database
    • DB Validation
  • Big Data Ecosystem Testing
    • Referential Integrity Tests
    • Constraints Check
    • Metadata Analysis
    • Statistical Analysis
    • Data Duplication Check
    • Data Accuracy/Consistency Check
  • Data Analytics & Data Visualization Testing
    • Report Objects Validation
    • Reports Validation
    • Dashboards Validation
    • Mobile Reports Validation
    • Visualization Validation

Testing Methods & Tools for Pre-Hadoop Processing

Big Data systems typically processes a mix of structured data, unstructured data, and semi-structured data. Data sources can include a local file system, HDFS, Hive Tables, Streaming Sources, and Relational or other databases.

  • Typical Testing includes -
    • Data Type Validation,
    • Range and Constraint Validation,
    • Code and Cross-Reference Validation,
    • Count of Rows Validation in ETL Data Process,
    • Structured Validation
  • Tools for Validation Pre-Hadoop Processing
    • Apache Flume,
    • Apache Nifi,
    • Apache Sqoop,
    • Apache Spark,
    • Apache Pig,
    • Logstash,
    • Collected,
    • Streamsets

Testing Methods & Tools for Hadoop MapReduce Processes

Hadoop MapReduce is a software framework for easily writing applications that processes vast amounts of data in-parallel or large clusters.

  • Methods & Testing Tools for Hadoop MapReduce Processes
    • MRUnit - Unit Testing for MR Jobs,
    • Local Job Runner Testing - Running MR Jobs on a single machine in a single JVM,
    • Pseudo-Distributed Testing - Running MR Jobs on a single machine using Hadoop,
    • Full Integration Testing - Running MR Jobs on a QA Cluster

Testing Methods & Tools for Data Extract and EDW Loading

Data Warehouses play a vital role in Big Data. Companies rely on Data Warehouses for collecting information on their business operations, markets, and client behavior to identify patterns, and collect the results to identify more business opportunities and operational improvements.

  • Typical Testing Methods -
    • The data in the data sources is validated directly in the Data Warehouse,
    • The data is validated from the data sources through each step of the extract, including the final load in the Data Warehouse
  • Testing Tools for Data Extract and EDW Loading
    • SQL Server Integration Services (SSIS),
    • Informatica PowerCenter,
    • OpenText Integration Centre,
    • Cognos Data Manager

Testing Methods & Tools for Big Data Analytics

Big Data Analytics refers to the process of collecting, organizing, and analyzing large sets of data to discover patterns and reporting useful information. Specific areas within analytics include Predictive Analytics, Enterprise Decision Management, Retail Analytics, Predictive Science, Credit Risk Analysis, and Fraud Analytics.

  • Testing Methods for Big Data Analytics
    • Validating the Dashboard Report Model,
    • Checking the Source Record Count and Target Record Count,
    • Authentication Testing,
    • Data Level Security,
    • Bursting the Reports,
    • Buzz Matrix Validation,
    • User Acceptance Criteria,
    • Time Series Functions Validations,
    • End-to-End Testing
  • Tools for Big Data Analytics
    • Apache Falcon - Falcon simplifies the development and management of data processing pipelines with a higher level of abstraction taking the complex coding out of data processing applications by providing out-of-the-box data management services.

Testing Methods & Tools for Performance Testing and Failover Testing

Identify response time, maximum online user data capacity size, and maximum processing capacity with Performance Testing. Failover Testing validates the recovery process and ensures data processing continues correctly when switched to other data nodes.

  • Testing Techniques for Performance and Failover Testing
    • Static/Default Installation,
    • Backup/Restore,
    • Data Replication,
    • Rolling Installation
  • Testing Tools for Performance Testing and Failover Testing
    • SandStorm,
    • JMeter,
    • Nagios,
    • Zabbix,
    • Ganglia,
    • JMX Utilities,
    • AppDynamics,
    • Jespen

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