Big Data
A collection of 6 issues
Introduction to Apache Spark: A Powerful Solution for Big Data Processing and Analytics
Hadoop and Teradata Data Warehousing: A Comparison and Integration Perspective
Hadoop is a buzzword in the world of big data, but its actual value can be concealed by the hype. This article compares Teradata and Hadoop Data Warehousing, highlighting the advantages of leveraging Hadoop's scalability and preprocessing capabilities to improve Teradata's performance. However, the
Real-World Map-Reduce Implementations: Design and Fault Tolerance
Here is an illustration depicting the design of real-world map-reduce implementations, such as Hadoop:
The input files reside in a distributed file system, such as HDFS for Hadoop, or GFS as Google calls it.
Worker processes handle mapper or reducer tasks.
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A Brief History of Parallel Database Architectures and Their Limitations
Discover the history of parallel database architectures - from shared memory to shared disk and shared-nothing. Learn about the advantages and limitations of each architecture and how fault tolerance is handled. Explore the shift towards big data and the trend of "Hadoop over SQL."
Understanding the Relationship Between RDBMS and Hadoop: A Map Reduce Example
Discover how Map Reduce is becoming a key feature of most database vendors' RDBMS. Follow an example of SQL aggregation statement joined with two tables.