Void

(summaries of and key takeaways from two papers I read last month)

Paper: SLIK: Scalable Low-Latency Indexes for a Key-Value Store

• Building a low latency, consistent, and scalable secondary index for a NoSQL distributed store is hard.
• Partitioning your secondary index independently of your data (i.e. not co-locating your secondary index with the data) is key for high performance.
• SLIK returns consistent data without the need for transactions at write time by using what they term an “ordered write approach”. The SLIK client library shields applications from consistency checking by primary key hashes at read time.
• I’ve used rule-based programming languages like Prolog before, but I did not know that rule-based programming can be used for non-AI related tasks like concurrent, pipelined RPC requests like SLIK does in its client API implementation.
• SLIK reuses its underlying system’s (i.e. RAMCloud‘s) storage system to store a representation of the secondary indexes SLIK builds for fast recovery in the face of failure.
• Measure n times (where n >= 2) cut once: SLIK keeps its design simple by not implementing a garbage collection mechanism to handle invalid secondary index entries. The paper explains how the space saving gained by a garbage collector in their system are negligible.
• By performing expensive operations like index creation in the background without locking the entire table SLIK ensures that performance never suffers.

Paper:  Caching Doesn’t Improve Mobile Web Performance (Much)

• Measure n times (where n >= 2) cut once: a 10% increase in cache hit rate in Flywheel only lead to a 1-2% reduction in mobile page load times. This is because of the inherent limitations in web page design and cell phone device hardware (as revealed and evaluated in this paper). A systematic evaluation of the problem (i.e. quantifying the gains of caching in mobile web performance) might have saved engineering effort in improving cache hit rate.
• I was surprised that page load time was used as an evaluation criteria for cache performance, when above-the-fold load time seems like a more appropriate metric. As revealed in section 3.3 of the paper, this is because above-the-fold load time is harder to measure.
• The load time for the critical path of a web page determines its overall page load time, and if the elements along the path are not cacheable, then more caching will have zero benefit to page load time. As proved in the experiments detailed in the paper, the amount of data on the critical path that can be cached is much smaller than the amount of overall data that can be cached for most mobile web pages.
• The bottleneck for mobile web performance is the slow CPUs on mobile devices. Since the computational complexity involved with rendering the page is so high, caching does not give us the page load time reductions we expect on mobile devices.