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Study mode:
on
1
intro
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preamble
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about me
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outline
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yql: distributed sql database engine
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massive data handling
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yql architecture overview
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example
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execution plan
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bechmark-driven approach
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tpc-h benchmark
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data generation
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continuous integration ci
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run distributed engine in one process
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run distributed engine in multi-process configuration
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unixbench's style measures
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tpc--h 100: target values
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hardware
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linus performance tools
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more linux performance tools
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slow join
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perf top
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stackcount
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memory allocator
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results
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user code isolation
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execution plan
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executions pipeline with unix pipe
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slow results
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linux ipc performance
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pipe performance
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results: dq @pipe+ pipe
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what's next?
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thanks you
Description:
Explore the optimization techniques for enhancing a distributed SQL database engine in this conference talk from Conf42 DevOps 2024. Dive into YQL architecture, massive data handling, and benchmark-driven approaches using TPC-H. Learn about continuous integration strategies, running distributed engines in single and multi-process configurations, and performance measurement techniques. Discover Linux performance tools for investigating bottlenecks, including slow joins and memory allocation issues. Examine containerization challenges, user code isolation, and execution pipeline optimizations using Unix pipes. Gain insights into Linux IPC performance and future directions for distributed database optimization.

Enhancing a Distributed SQL Database Engine - Performance Optimization Techniques

Conf42
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