=Paper=
{{Paper
|id=None
|storemode=property
|title=Efficient Query Processing on Modern Hardware
|pdfUrl=https://ceur-ws.org/Vol-733/keynote_neumann.pdf
|volume=Vol-733
|dblpUrl=https://dblp.org/rec/conf/gvd/Neumann11
}}
==Efficient Query Processing on Modern Hardware==
<pdf width="1500px">https://ceur-ws.org/Vol-733/keynote_neumann.pdf</pdf>
<pre>
       Efficient Query Processing on
              Modern Hardware
                             Thomas Neumann
               Lehrstuhl für Informatik III: Datenbanksysteme
                            Fakultät für Informatik
                     Technische Universität München


                                  ABSTRACT

Most database systems translate a given query into an expression in a (physical)
algebra, and then start evaluating this algebraic expression to produce the query
result. The traditional way to execute these algebraic plans is the iterator model:
Every physical algebraic operator conceptually produces a tuple stream from its
input, and allows for iterating over this tuple stream. This is a very nice and simple
interface, and allows for easy combination of arbitrary operators,but it clearly comes
from a time when query processing was dominated by I/O and CPU consumption
was less important: The iterator interface causes thousands of expensive function
calls, degrades the branch prediction of modern CPUs, and ofter results in poor
code locality and complex book-keeping.
On modern hardware query processing can be improved considerably by processing
tuples in a data centric, and not an operator centric, way. Data is processed such that
it can be kept in CPU registers as long as possible. Operator boundaries are blurred
to achieve this goal. In combination with an code compilation framework this
results in query code that rivals the speed of hand-written code. When using these
techniques in the HyPer DBMS, TPC-H Query 1 for example can single-threaded
aggregated the scale factor 1GB data set in about 68ms on commodity hardware.




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</pre>