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Why you should benchmark your database using stored procedures

HammerDB

HammerDB uses stored procedures to achieve maximum throughput when benchmarking your database. HammerDB has always used stored procedures as a design decision because the original benchmark was implemented as close as possible to the example workload in the TPC-C specification that uses stored procedures.

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The Speed of Time

Brendan Gregg

A Cassandra database cluster had switched to Ubuntu and noticed write latency increased by over 30%. The broken Java stacks turned out to be beneficial: They helped group together the os::javaTimeMillis() calls which otherwise might have have been scattered on top of different Java code paths, appearing as thin stacks everywhere.

Speed 126
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An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems

The Morning Paper

An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems Gan et al., A typical architecture diagram for one of these services looks like this: Suitably armed with a set of benchmark microservices applications, the investigation can begin! ASPLOS’19.

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SLOG: serializable, low-latency, geo-replicated transactions

The Morning Paper

SLOG: serializable, low-latency, geo-replicated transactions Ren et al., Strict serializability reduces application code complexity and bugs, since it behaves like a system that is running on a single machine processing transactions sequentially. That’s where SLOG (Serializable LOw-latency, Geo-replicated transactions) comes in.

Latency 70
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The Speed of Time

Brendan Gregg

A Cassandra database cluster had switched to Ubuntu and noticed write latency increased by over 30%. The broken Java stacks turned out to be beneficial: They helped group together the os::javaTimeMillis() calls which otherwise might have have been scattered on top of different Java code paths, appearing as thin stacks everywhere.

Speed 52
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The Speed of Time

Brendan Gregg

A Cassandra database cluster had switched to Ubuntu and noticed write latency increased by over 30%. The broken Java stacks turned out to be beneficial: They helped group together the os::javaTimeMillis() calls which otherwise might have have been scattered on top of different Java code paths, appearing as thin stacks everywhere.

Speed 40
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A Management Maturity Model for Performance

Alex Russell

This is a complex topic, but to borrow from a recent post , web performance expands access to information and services by reducing latency and variance across interactions in a session, with a particular focus on the tail of the distribution (P75+). Consistent performance matters just as much as low average latency. Who owns this code?