TPC-DS is the new decision support benchmark that models several generally applicable aspects of a decision support system,
including queries and data maintenance. Although the underlying business model of TPC-DS is a retail product supplier,
the database schema, data population, queries, data maintenance model and implementation rules have been designed to be
broadly representative of modern decision support systems.
This benchmark illustrates decision support systems that:
- Examine large volumes of data
- Give answers to real-world business questions
- Execute queries of various operational requirements and complexities (e.g., ad-hoc, reporting, iterative OLAP, data mining)
- Are characterized by high CPU and IO load
- Are periodically synchronized with source OLTP databases through database maintenance functions
TPC-DS Version 2 is the next major release of TPC's decision support benchmark.
It includes changes that enables Hadoop based systems to execute the benchmark.
The major changes in Version 2 are in the area of ACID (Atomicity, Consistency,
Isolation and Durability), data maintenance and metric calculation.
Instead of requiring ACID TPC-DS Version 2 requires a much relaxed version of
Durability, which is referred to as Data Accessibility. Data maintenance has
been reduced to the fact tables, i.e. sales, returns and inventory tables.
TPC-DS Version 2 does not require updates, only inserts and deletes. Also, the
execution rules of data maintenance has been modified to separate the execution
of queries from that of data maintenance. The metric in Version 2 has been
changed from being an arithmetic mean of load, single user, multi user and data
maintenance to a geometric mean of the same components.
The most recent draft of Version 2 of TPC-DS is now available for review.
To leave comments, please do so here and use TPC-DS-2.0 in the project pulldown menu.