Abstract
Join procedures are cost intensive tasks even for in-memory databases. As today’s systems introduce more and more parallelism, intra-operator parallelization moves into focus. This chapter discusses possible schemes to parallelize a hash-join algorithm, as described in Chap. 19.
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References
C. Kim, T. Kaldewey, V.W. Lee, E. Sedlar, A.D. Nguyen, N. Satish, J. Chhugani, A. Di Blas, P. Dubey, Sort vs. Hash revisited: fast join implementation on modern multi-core CPUs, in VLDB, 2009
S. Manegold, P. Boncz, M. Kersten, Optimizing main-memory join on modern hardware. IEEE Trans. Knowl. Data Eng. 19, 412–426 (2008)
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Self Test Questions
Self Test Questions
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1.
Parallelizing Hash-Join Phases
What is the disadvantage when the probing phase of a join algorithm is parallelized and the hashing phase is performed sequentially?
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(a)
Sequentially performing the hashing phase introduces inconsistencies in the produced hash values
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(b)
The algorithm still has a large sequential part that limits its potential to scale
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(c)
The sequential hashing phase will run slower due to the large resource utilization of the parallel probing phase
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(d)
The table has to be split into smaller parts, so that every core, which performs the probing, can finish.
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(a)
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© 2013 Springer-Verlag Berlin Heidelberg
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Plattner, H. (2013). Parallel Join. In: A Course in In-Memory Data Management. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36524-9_23
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DOI: https://doi.org/10.1007/978-3-642-36524-9_23
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