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A telecommunications company has petabytes of call detail records (CDRs) stored in an on-premises Hadoop Distributed File System (HDFS). They need to migrate this data to Azure and perform complex analytical queries using Spark and other big data tools. The solution must support a hierarchical file system, be highly scalable, and cost-effective for long-term storage and analytics. Which Azure data storage solution is best suited for this migration?

  1. AAzure Blob Storage (Archive Tier)
  2. BAzure Database for PostgreSQL
  3. CAzure Data Lake Storage Gen2
  4. DAzure SQL Database
Show answer & explanation

Correct answer: C. Azure Data Lake Storage Gen2

Azure Data Lake Storage Gen2 is designed for big data analytics, offering petabyte-scale storage, a hierarchical file system, and native integration with Spark and other big data tools. It provides a cost-effective solution for storing and analyzing large volumes of unstructured and semi-structured data like CDRs, making it ideal for migrating from HDFS.

Why the other options are wrong

  • A. Azure Blob Storage (Archive Tier) is for very long-term, rarely accessed data and does not offer the hierarchical file system or direct integration with big data analytics engines required.
  • B. Azure Database for PostgreSQL is a relational database and is not designed for petabyte-scale semi-structured data analytics with big data tools.
  • D. Azure SQL Database is a relational database and is not suitable for storing petabytes of semi-structured CDRs from HDFS or for integration with big data analytics tools like Spark.

Azure Data Lake Storage Gen2 (HDFS Integration)

ADLS Gen2 provides a hierarchical namespace that allows it to present object storage as a file system, making it fully compatible with Hadoop Distributed File System (HDFS) semantics and tools like Apache Spark and Hadoop.

  • Leverages Azure Blob Storage's scale and cost
  • Enables POSIX-compliant file system operations
  • Optimized for analytical workloads

Memory trick: ADLS Gen2: HDFS's best 'Gen'etic match in the cloud.

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