Hash Join Performance - Computer and Information Science - Lecture Slides, Slides of Applications of Computer Sciences

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Improving Hash Join Performance

through Prefetching

1

Outline

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• Overview
• Proposed Techniques
• Experimental setup
• Performance evaluation
• Conclusion

Hash Join Performance

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• Suffer from CPU Cache Stalls - Most of execution time is wasted on data cache misses
  • 82% for partition, 73% for join
  • Because of random access patterns in memory

Solution: Cache Prefetching

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• Cache prefetching has been successfully

applied to several types of applications.

• exploit cache prefetching to improve hash

join performance.

Overcoming These Challenges

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• Evaluate two new prefetching

techniques:

Group prefetching

• try to hide cache miss latency across a group tuples

Software-pipelined prefetching

• avoid these intermittent stalls

Group Prefetching

• Hide cache miss latency across a group tuples.
• Then combine the processing of a group of tuples into a

single loop body and rearrange the probe operations into stages

• Process the tuples for a stage and then move to the next

stage

• Add prefetch instructions to the algorithm.
• issue prefetch instructions in one code stage for the

memory references in the next code stage.

Group vs. Software-Pipelined Prefetching

Hiding latency:

• Software-pipelined pref is always able to hide all latencies

Book-keeping overhead:

• Software-pipelined pref has more overhead

Code complexity:

• Group prefetching is easier to implement
• Natural group boundary provides a place to do necessary processing left (e.g. for read-write conflicts)
• A natural place to send outputs to the parent operator if pipelined operator is needed

Experimental Setup

- Use a simple schema for both the build and

probe relations

- Every tuple contains a 4 byte join attribute

and a fixed length payload

- Perform join without selections and

projections.

- Assume the join phase uses 50MB memory to

join a pair of build and probe partition

Performance Evaluation cont..

User-Mode CPU Cache Performance

• Join Phase Performance

This technique achieved 3.02-4.04X speedups over original hash join

Performance Evaluation cont..

Join Performance varying Memory Latency

-prefecthing techniques are effective even when the processor/memory speed gap increases dramatically

Conclusion

• Even though prefetching is a promising technique for

improving CPU cache performance, applying it to the

hash join algorithm is not straightforward

(due to the dependencies within the processing of a single tuple and the randomness of Hashing)

• Experimental results demonstrated that hash join

performance can be improved by using group

prefetching and software-pipelined prefetching

techniques.

• Several practicle issues when used on DBMS that

targets multiple architectures